repo_id
stringlengths 15
132
| file_path
stringlengths 34
176
| content
stringlengths 2
3.52M
| __index_level_0__
int64 0
0
|
|---|---|---|---|
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_tools_json_ignored.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.017'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.180'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.081'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.120'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Wed, 29 Nov 2023 09:03:57 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/webClassification3.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '379'
content-md5:
- lI/pz9jzTQ7Td3RHPL7y7w==
content-type:
- application/octet-stream
last-modified:
- Mon, 06 Nov 2023 08:30:18 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Mon, 06 Nov 2023 08:30:18 GMT
x-ms-meta-name:
- 94331215-cf7f-452a-9f1a-1d276bc9b0e4
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 3f163752-edb0-4afc-a6f5-b0a670bd7c24
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Wed, 29 Nov 2023 09:03:58 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/webClassification3.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.123'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.124'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Wed, 29 Nov 2023 09:04:02 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/flow_with_dict_input/flow.dag.yaml
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '390'
content-md5:
- rvNrgMFl6rXC96Bo0HAgiQ==
content-type:
- application/octet-stream
last-modified:
- Wed, 29 Nov 2023 09:02:57 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Wed, 29 Nov 2023 09:02:56 GMT
x-ms-meta-name:
- fea20834-dda6-4ae9-a2bf-b8c08cd7e883
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Wed, 29 Nov 2023 09:04:03 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/flow_with_dict_input/flow.dag.yaml
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_request_id_when_making_http_requests.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.017'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.716'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.105'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.140'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 30 Nov 2023 08:11:19 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '49'
content-md5:
- quXiEreYvPinSj0HsaNa/g==
content-type:
- application/octet-stream
last-modified:
- Wed, 08 Nov 2023 04:26:09 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Wed, 08 Nov 2023 04:26:09 GMT
x-ms-meta-name:
- c4092674-5e53-4c17-b78d-75353ae0edb6
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 579021dc-8ac8-4c73-8110-4642bd00c69b
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 30 Nov 2023 08:11:21 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.103'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.107'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 30 Nov 2023 08:11:25 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '245'
content-md5:
- F+JA0a3CxcLYZ0ANRdlZbA==
content-type:
- application/octet-stream
last-modified:
- Wed, 29 Nov 2023 02:51:35 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Thu, 17 Aug 2023 10:30:09 GMT
x-ms-meta-name:
- 56efdd28-6297-4baa-aad3-be46f4b768a2
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 30 Nov 2023 08:11:26 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.070'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.104'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 30 Nov 2023 08:11:35 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '49'
content-md5:
- quXiEreYvPinSj0HsaNa/g==
content-type:
- application/octet-stream
last-modified:
- Wed, 08 Nov 2023 04:26:09 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Wed, 08 Nov 2023 04:26:09 GMT
x-ms-meta-name:
- c4092674-5e53-4c17-b78d-75353ae0edb6
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 579021dc-8ac8-4c73-8110-4642bd00c69b
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 30 Nov 2023 08:11:36 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.073'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.092'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 30 Nov 2023 08:11:40 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '245'
content-md5:
- F+JA0a3CxcLYZ0ANRdlZbA==
content-type:
- application/octet-stream
last-modified:
- Wed, 29 Nov 2023 02:51:35 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Thu, 17 Aug 2023 10:30:09 GMT
x-ms-meta-name:
- 56efdd28-6297-4baa-aad3-be46f4b768a2
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 30 Nov 2023 08:11:42 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_eager_flow_download.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.031'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.066'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.075'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.125'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 25 Jan 2024 09:16:18 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/simple_eager_flow_data.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '25'
content-md5:
- zt1zN1V/HR5p7N0Sh5396w==
content-type:
- application/octet-stream
last-modified:
- Tue, 23 Jan 2024 06:27:00 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Tue, 23 Jan 2024 06:26:59 GMT
x-ms-meta-name:
- 1e376ce4-7c3b-4683-82ad-412f5cd23626
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 7e65351c-7e4b-4a4d-90f8-304eacdc36bc
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 25 Jan 2024 09:16:21 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/simple_eager_flow_data.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.108'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.088'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 25 Jan 2024 09:16:25 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/simple_with_req/entry.py
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '331'
content-md5:
- bf0G3F/eNgZO8UPfGebSUQ==
content-type:
- application/octet-stream
last-modified:
- Thu, 25 Jan 2024 08:57:55 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Thu, 25 Jan 2024 08:57:54 GMT
x-ms-meta-name:
- c42d946f-2978-4455-8a89-b768c66a9277
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 25 Jan 2024 09:16:28 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/simple_with_req/entry.py
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/simple_with_req/flow.dag.yaml",
"runId": "name", "runDisplayName": "name", "runExperimentName": "", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/simple_eager_flow_data.jsonl"},
"inputsMapping": {}, "connections": {}, "environmentVariables": {}, "runtimeName":
"fake-runtime-name", "sessionId": "000000000000000000000000000000000000000000000000",
"sessionSetupMode": "SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '791'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '6.330'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/e62bc4d5a164939b21d42dd420469da7/simple_eager_flow_data.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "automatic",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "1ac134f8-0696-4ce1-ba89-cd4d9748e886",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '1028'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.273'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/e62bc4d5a164939b21d42dd420469da7/simple_eager_flow_data.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "automatic",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "1ac134f8-0696-4ce1-ba89-cd4d9748e886",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '1028'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.372'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/e62bc4d5a164939b21d42dd420469da7/simple_eager_flow_data.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "automatic",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "1ac134f8-0696-4ce1-ba89-cd4d9748e886",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '1028'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.420'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/e62bc4d5a164939b21d42dd420469da7/simple_eager_flow_data.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "automatic",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "1ac134f8-0696-4ce1-ba89-cd4d9748e886",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '1028'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.469'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/e62bc4d5a164939b21d42dd420469da7/simple_eager_flow_data.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "automatic",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "1ac134f8-0696-4ce1-ba89-cd4d9748e886",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '1028'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.173'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/e62bc4d5a164939b21d42dd420469da7/simple_eager_flow_data.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "automatic",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "1ac134f8-0696-4ce1-ba89-cd4d9748e886",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '1028'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.214'
status:
code: 200
message: OK
- request:
body: '{}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '2'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/metric/v2.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/runs/name/lastvalues
response:
body:
string: '{"value": [{"dataContainerId": "dcid.name", "name": "__pf__.lines.completed",
"columns": {"__pf__.lines.completed": "Double"}, "properties": {"uxMetricType":
"azureml.v1.scalar", "dataLocation": null}, "namespace": null, "standardSchemaId":
null, "value": [{"metricId": "acecc185-aa1e-4e95-b342-d391d260bc46", "createdUtc":
"2024-01-25T09:17:00.198+00:00", "step": 0, "data": {"__pf__.lines.completed":
1.0}}]}, {"dataContainerId": "dcid.name", "name": "__pf__.lines.failed", "columns":
{"__pf__.lines.failed": "Double"}, "properties": {"uxMetricType": "azureml.v1.scalar",
"dataLocation": null}, "namespace": null, "standardSchemaId": null, "value":
[{"metricId": "aeeb8ed5-aca3-475d-a76d-a58ecc12ad99", "createdUtc": "2024-01-25T09:17:00.563+00:00",
"step": 0, "data": {"__pf__.lines.failed": 0.0}}]}]}'
headers:
connection:
- keep-alive
content-length:
- '1240'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.066'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/e62bc4d5a164939b21d42dd420469da7/simple_eager_flow_data.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "automatic",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "1ac134f8-0696-4ce1-ba89-cd4d9748e886",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '1028'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.292'
status:
code: 200
message: OK
- request:
body: '{"value": "azureml://locations/eastus/workspaces/00000/data/azureml_name_output_data_debug_info/versions/1"}'
headers:
accept:
- '*/*'
accept-encoding:
- gzip, deflate
connection:
- keep-alive
content-length:
- '171'
content-type:
- application/json
host:
- eastus.api.azureml.ms
user-agent:
- python-httpx/0.26.0
method: POST
uri: https://eastus.api.azureml.ms/data/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/dataversion/getByAssetId
response:
content: '{"dataVersion": {"assetId": "azureml://locations/eastus/workspaces/00000/data/azureml_name_output_data_debug_info/versions/1",
"dataContainerName": "azureml_name_output_data_debug_info", "dataType": "UriFolder",
"dataUri": "azureml://subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/workspaces/00000/datastores/workspaceblobstore/paths/promptflow/PromptFlowArtifacts/name/",
"versionId": "1", "mutableProps": {"dataExpiryTime": null, "description": null,
"tags": null, "isArchived": false, "stage": "Logged", "autoDeleteSetting": null},
"referencedDataUris": null, "properties": null, "initialAssetId": "azureml://locations/eastus/workspaces/00000/data/azureml_name_output_data_debug_info/versions/1",
"isRegistered": false, "runId": "name", "originAssetId": null}, "entityMetadata":
{"etag": "\"87008635-0000-0100-0000-65b2270d0000\"", "createdTime": "2024-01-25T09:17:01.3632335+00:00",
"modifiedTime": "2024-01-25T09:17:01.3970754+00:00", "createdBy": {"userObjectId":
"00000000-0000-0000-0000-000000000000", "userPuId": "100320005227D154", "userIdp":
null, "userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "Han Wang",
"upn": "[email protected]"}, "modifiedBy": null}, "legacyDatasetId": "c78cba45-2c03-4f27-8f6d-7a0f7fcaa3fc",
"isV2": true, "legacyDatasetType": null, "legacyDataflowType": null, "legacyDataflow":
null, "legacySavedDatasetId": null, "putAssetLROResponseDto": null}'
headers:
connection:
- keep-alive
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.064'
http_version: HTTP/1.1
status_code: 200
- request:
body: '{"snapshotOrAssetId": "1ac134f8-0696-4ce1-ba89-cd4d9748e886"}'
headers:
accept:
- '*/*'
accept-encoding:
- gzip, deflate
connection:
- keep-alive
content-length:
- '61'
content-type:
- application/json
host:
- eastus.api.azureml.ms
user-agent:
- python-httpx/0.26.0
method: POST
uri: https://eastus.api.azureml.ms/content/v2.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/snapshots/sas
response:
content: '{"name": "", "hash": null, "type": "Directory", "timestamp": "0001-01-01T00:00:00+00:00",
"sasUrl": null, "absoluteUrl": null, "sizeBytes": 0, "sizeSet": false, "children":
{"entry.py": {"name": "entry.py", "hash": "6DFD06DC5FDE36064EF143DF19E6D251",
"type": "File", "timestamp": "0001-01-01T00:00:00+00:00", "sasUrl": "https://promptfloweast4063704120.blob.core.windows.net/azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/runs/name/entry.py?sv=2019-07-07&sr=b&sig=uNX4%2F%2BOW1NSRGOeyt5nunbdGqVOmeV84SX9FrinPAaU%3D&st=2024-01-25T09%3A08%3A38Z&se=2024-01-25T17%3A18%3A38Z&sp=r&rscd=filename%3Dentry.py",
"absoluteUrl": "https://promptfloweast4063704120.blob.core.windows.net/azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/runs/name/entry.py",
"sizeBytes": 331, "sizeSet": true, "children": {}}, "flow.dag.yaml": {"name":
"flow.dag.yaml", "hash": "E9583EF05B4434346632808F5714E8B0", "type": "File",
"timestamp": "0001-01-01T00:00:00+00:00", "sasUrl": "https://promptfloweast4063704120.blob.core.windows.net/azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/runs/name/flow.dag.yaml?sv=2019-07-07&sr=b&sig=3plGLhXfe%2Fudi%2Fm0Z7%2FSz7Cte1sDfk8cDwBsYGfvMrQ%3D&st=2024-01-25T09%3A08%3A38Z&se=2024-01-25T17%3A18%3A38Z&sp=r&rscd=filename%3Dflow.dag.yaml",
"absoluteUrl": "https://promptfloweast4063704120.blob.core.windows.net/azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/runs/name/flow.dag.yaml",
"sizeBytes": 93, "sizeSet": true, "children": {}}, "requirements.txt": {"name":
"requirements.txt", "hash": "93AEF5DCE3D6FE02C4425D72C0E1DABD", "type": "File",
"timestamp": "0001-01-01T00:00:00+00:00", "sasUrl": "https://promptfloweast4063704120.blob.core.windows.net/azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/runs/name/requirements.txt?sv=2019-07-07&sr=b&sig=KJrkxjj4vFvaXoSEzbexwXAJIkisbxTIgI8M1l0%2FWlY%3D&st=2024-01-25T09%3A08%3A38Z&se=2024-01-25T17%3A18%3A38Z&sp=r&rscd=filename%3Drequirements.txt",
"absoluteUrl": "https://promptfloweast4063704120.blob.core.windows.net/azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/runs/name/requirements.txt",
"sizeBytes": 109, "sizeSet": true, "children": {}}}}'
headers:
connection:
- keep-alive
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.142'
http_version: HTTP/1.1
status_code: 200
- request:
body: null
headers:
Accept:
- application/xml
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 25 Jan 2024 09:18:43 GMT
x-ms-range:
- bytes=0-33554431
x-ms-version:
- '2023-11-03'
method: GET
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/runs/name/requirements.txt
response:
body:
string: "--extra-index-url https://azuremlsdktestpypi.azureedge.net/test-promptflow/\r\npromptflow[azure]==0.0.116642424"
headers:
accept-ranges:
- bytes
content-length:
- '109'
content-range:
- bytes 0-108/109
content-type:
- application/octet-stream
last-modified:
- Thu, 25 Jan 2024 09:16:44 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-content-md5:
- k6713OPW/gLEQl1ywOHavQ==
x-ms-blob-type:
- BlockBlob
x-ms-copy-completion-time:
- Thu, 25 Jan 2024 09:16:44 GMT
x-ms-copy-id:
- bcd3c079-6acb-4b8d-9af6-b23b87ffca84
x-ms-copy-progress:
- 109/109
x-ms-copy-source:
- https://promptfloweast4063704120.blob.core.windows.net/azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/LocalUpload/79819672296a1785a95c65c8c0e75b0d/simple_with_req/requirements.txt
x-ms-copy-status:
- success
x-ms-creation-time:
- Thu, 25 Jan 2024 09:16:44 GMT
x-ms-version:
- '2023-11-03'
status:
code: 206
message: Partial Content
- request:
body: null
headers:
Accept:
- application/xml
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 25 Jan 2024 09:18:42 GMT
x-ms-range:
- bytes=0-33554431
x-ms-version:
- '2023-11-03'
method: GET
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/runs/name/entry.py
response:
body:
string: "# ---------------------------------------------------------\r\n# Copyright
(c) Microsoft Corporation. All rights reserved.\r\n# ---------------------------------------------------------\r\n\r\ndef
my_flow(input_val) -> str:\r\n \"\"\"Simple flow with yaml.\"\"\"\r\n print(f\"Hello
world! {input_val}\")\r\n return f\"Hello world! {input_val}\"\r\n"
headers:
accept-ranges:
- bytes
content-length:
- '331'
content-range:
- bytes 0-330/331
content-type:
- application/octet-stream
last-modified:
- Thu, 25 Jan 2024 09:16:44 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-content-md5:
- bf0G3F/eNgZO8UPfGebSUQ==
x-ms-blob-type:
- BlockBlob
x-ms-copy-completion-time:
- Thu, 25 Jan 2024 09:16:44 GMT
x-ms-copy-id:
- 5b6fc216-f239-42fa-a163-c92db62cb949
x-ms-copy-progress:
- 331/331
x-ms-copy-source:
- https://promptfloweast4063704120.blob.core.windows.net/azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/LocalUpload/79819672296a1785a95c65c8c0e75b0d/simple_with_req/entry.py
x-ms-copy-status:
- success
x-ms-creation-time:
- Thu, 25 Jan 2024 09:16:44 GMT
x-ms-meta-name:
- c42d946f-2978-4455-8a89-b768c66a9277
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 206
message: Partial Content
- request:
body: null
headers:
Accept:
- application/xml
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 25 Jan 2024 09:18:38 GMT
x-ms-version:
- '2023-11-03'
method: GET
uri: https://fake_account_name.blob.core.windows.net/fake-container-name?comp=list&prefix=promptflow%2FPromptFlowArtifacts%2Fname%2F&restype=container
response:
body:
string: "\uFEFF<?xml version=\"1.0\" encoding=\"utf-8\"?><EnumerationResults
ServiceEndpoint=\"https://promptfloweast4063704120.blob.core.windows.net/\"
ContainerName=\"azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5\"><Prefix>promptflow/PromptFlowArtifacts/name/</Prefix><Blobs><Blob><Name>promptflow/PromptFlowArtifacts/name/flow_artifacts/000000000_000000024.jsonl</Name><Properties><Creation-Time>Thu,
25 Jan 2024 09:16:58 GMT</Creation-Time><Last-Modified>Thu, 25 Jan 2024 09:16:58
GMT</Last-Modified><Etag>0x8DC1D8661A992B8</Etag><Content-Length>1132</Content-Length><Content-Type>application/octet-stream</Content-Type><Content-Encoding
/><Content-Language /><Content-CRC64 /><Content-MD5 /><Cache-Control /><Content-Disposition
/><BlobType>AppendBlob</BlobType><LeaseStatus>unlocked</LeaseStatus><LeaseState>available</LeaseState><ServerEncrypted>true</ServerEncrypted></Properties><OrMetadata
/></Blob><Blob><Name>promptflow/PromptFlowArtifacts/name/flow_outputs/output.jsonl</Name><Properties><Creation-Time>Thu,
25 Jan 2024 09:17:01 GMT</Creation-Time><Last-Modified>Thu, 25 Jan 2024 09:17:01
GMT</Last-Modified><Etag>0x8DC1D8663B60064</Etag><Content-Length>52</Content-Length><Content-Type>application/octet-stream</Content-Type><Content-Encoding
/><Content-Language /><Content-CRC64 /><Content-MD5>e7CC/hOg8uoJ3TK2HaKeZA==</Content-MD5><Cache-Control
/><Content-Disposition /><BlobType>BlockBlob</BlobType><AccessTier>Hot</AccessTier><AccessTierInferred>true</AccessTierInferred><LeaseStatus>unlocked</LeaseStatus><LeaseState>available</LeaseState><ServerEncrypted>true</ServerEncrypted></Properties><OrMetadata
/></Blob><Blob><Name>promptflow/PromptFlowArtifacts/name/instance_results.jsonl</Name><Properties><Creation-Time>Thu,
25 Jan 2024 09:16:58 GMT</Creation-Time><Last-Modified>Thu, 25 Jan 2024 09:16:58
GMT</Last-Modified><Etag>0x8DC1D8661AE6F40</Etag><Content-Length>105</Content-Length><Content-Type>application/octet-stream</Content-Type><Content-Encoding
/><Content-Language /><Content-CRC64 /><Content-MD5 /><Cache-Control /><Content-Disposition
/><BlobType>AppendBlob</BlobType><LeaseStatus>unlocked</LeaseStatus><LeaseState>available</LeaseState><ServerEncrypted>true</ServerEncrypted></Properties><OrMetadata
/></Blob><Blob><Name>promptflow/PromptFlowArtifacts/name/meta.json</Name><Properties><Creation-Time>Thu,
25 Jan 2024 09:16:52 GMT</Creation-Time><Last-Modified>Thu, 25 Jan 2024 09:16:52
GMT</Last-Modified><Etag>0x8DC1D865E80BFF2</Etag><Content-Length>18</Content-Length><Content-Type>application/octet-stream</Content-Type><Content-Encoding
/><Content-Language /><Content-CRC64 /><Content-MD5>/u1NXUpgXMFDmZEw835qnw==</Content-MD5><Cache-Control
/><Content-Disposition /><BlobType>BlockBlob</BlobType><AccessTier>Hot</AccessTier><AccessTierInferred>true</AccessTierInferred><LeaseStatus>unlocked</LeaseStatus><LeaseState>available</LeaseState><ServerEncrypted>true</ServerEncrypted></Properties><OrMetadata
/></Blob></Blobs><NextMarker /></EnumerationResults>"
headers:
content-type:
- application/xml
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 25 Jan 2024 09:18:44 GMT
x-ms-range:
- bytes=0-33554431
x-ms-version:
- '2023-11-03'
method: GET
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/promptflow/PromptFlowArtifacts/name/flow_artifacts/000000000_000000024.jsonl
response:
body:
string: '{"line_number": 0, "run_info": {"run_id": "name_0", "status": "Completed",
"error": null, "inputs": {"input_val": "input1"}, "output": {"output": "Hello
world! input1"}, "metrics": null, "request": null, "parent_run_id": "name",
"root_run_id": "name", "source_run_id": null, "flow_id": "default_flow_id",
"start_time": "2024-01-25T09:16:58.053129Z", "end_time": "2024-01-25T09:16:58.055292Z",
"index": 0, "api_calls": [{"name": "my_flow", "type": "Function", "inputs":
{"input_val": "input1"}, "output": "Hello world! input1", "start_time": 1706174218.053984,
"end_time": 1706174218.054859, "error": null, "children": [], "node_name":
null, "parent_id": "", "id": "27b021bc-89d3-43f8-b3ac-a9eed2a84949"}], "variant_id":
"", "name": "", "description": "", "tags": null, "system_metrics": {"duration":
0.002163}, "result": {"output": "Hello world! input1"}, "upload_metrics":
false}, "start_time": "2024-01-25T09:16:58.053129", "end_time": "2024-01-25T09:16:58.055292",
"name": "", "description": "", "status": "Completed", "tags": null}
'
headers:
accept-ranges:
- bytes
content-length:
- '1132'
content-range:
- bytes 0-1131/1132
content-type:
- application/octet-stream
last-modified:
- Thu, 25 Jan 2024 09:16:58 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-committed-block-count:
- '1'
x-ms-blob-type:
- AppendBlob
x-ms-creation-time:
- Thu, 25 Jan 2024 09:16:58 GMT
x-ms-version:
- '2023-11-03'
status:
code: 206
message: Partial Content
- request:
body: null
headers:
Accept:
- application/xml
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 25 Jan 2024 09:18:44 GMT
x-ms-range:
- bytes=0-33554431
x-ms-version:
- '2023-11-03'
method: GET
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/promptflow/PromptFlowArtifacts/name/flow_outputs/output.jsonl
response:
body:
string: '{"line_number": 0, "output": "Hello world! input1"}
'
headers:
accept-ranges:
- bytes
content-length:
- '52'
content-range:
- bytes 0-51/52
content-type:
- application/octet-stream
last-modified:
- Thu, 25 Jan 2024 09:17:01 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-content-md5:
- e7CC/hOg8uoJ3TK2HaKeZA==
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Thu, 25 Jan 2024 09:17:01 GMT
x-ms-version:
- '2023-11-03'
status:
code: 206
message: Partial Content
- request:
body: null
headers:
Accept:
- application/xml
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 25 Jan 2024 09:18:44 GMT
x-ms-range:
- bytes=0-33554431
x-ms-version:
- '2023-11-03'
method: GET
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/promptflow/PromptFlowArtifacts/name/instance_results.jsonl
response:
body:
string: '{"line_number": 0, "status": "Completed", "inputs.input_val": "input1",
"output": "Hello world! input1"}
'
headers:
accept-ranges:
- bytes
content-length:
- '105'
content-range:
- bytes 0-104/105
content-type:
- application/octet-stream
last-modified:
- Thu, 25 Jan 2024 09:16:58 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-committed-block-count:
- '1'
x-ms-blob-type:
- AppendBlob
x-ms-creation-time:
- Thu, 25 Jan 2024 09:16:58 GMT
x-ms-version:
- '2023-11-03'
status:
code: 206
message: Partial Content
- request:
body: null
headers:
Accept:
- application/xml
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 25 Jan 2024 09:18:42 GMT
x-ms-range:
- bytes=0-33554431
x-ms-version:
- '2023-11-03'
method: GET
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/runs/name/flow.dag.yaml
response:
body:
string: "path: ./entry.py\r\nentry: my_flow\r\nenvironment:\r\n python_requirements_txt:
requirements.txt"
headers:
accept-ranges:
- bytes
content-length:
- '93'
content-range:
- bytes 0-92/93
content-type:
- application/octet-stream
last-modified:
- Thu, 25 Jan 2024 09:16:44 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-content-md5:
- 6Vg+8FtENDRmMoCPVxTosA==
x-ms-blob-type:
- BlockBlob
x-ms-copy-completion-time:
- Thu, 25 Jan 2024 09:16:44 GMT
x-ms-copy-id:
- f4653407-3dac-4827-a65f-e1cf4b99a458
x-ms-copy-progress:
- 93/93
x-ms-copy-source:
- https://promptfloweast4063704120.blob.core.windows.net/azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/LocalUpload/79819672296a1785a95c65c8c0e75b0d/simple_with_req/flow.dag.yaml
x-ms-copy-status:
- success
x-ms-creation-time:
- Thu, 25 Jan 2024 09:16:44 GMT
x-ms-version:
- '2023-11-03'
status:
code: 206
message: Partial Content
- request:
body: null
headers:
Accept:
- application/xml
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Thu, 25 Jan 2024 09:18:44 GMT
x-ms-range:
- bytes=0-33554431
x-ms-version:
- '2023-11-03'
method: GET
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/promptflow/PromptFlowArtifacts/name/meta.json
response:
body:
string: '{"batch_size": 25}'
headers:
accept-ranges:
- bytes
content-length:
- '18'
content-range:
- bytes 0-17/18
content-type:
- application/octet-stream
last-modified:
- Thu, 25 Jan 2024 09:16:52 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-content-md5:
- /u1NXUpgXMFDmZEw835qnw==
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Thu, 25 Jan 2024 09:16:52 GMT
x-ms-version:
- '2023-11-03'
status:
code: 206
message: Partial Content
- request:
body: '{"runId": "name", "selectRunMetadata": true, "selectRunDefinition": true,
"selectJobSpecification": true}'
headers:
accept:
- '*/*'
accept-encoding:
- gzip, deflate
connection:
- keep-alive
content-length:
- '137'
content-type:
- application/json
host:
- eastus.api.azureml.ms
user-agent:
- python-httpx/0.26.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
content: '{"runMetadata": {"runNumber": 1706174203, "rootRunId": "name", "createdUtc":
"2024-01-25T09:16:43.8144219+00:00", "createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": "100320005227D154", "userIdp": null, "userAltSecId": null, "userIss":
"https://sts.windows.net/00000000-0000-0000-0000-000000000000/", "userTenantId":
"00000000-0000-0000-0000-000000000000", "userName": "Han Wang", "upn": null},
"userId": "00000000-0000-0000-0000-000000000000", "token": null, "tokenExpiryTimeUtc":
null, "error": null, "warnings": null, "revision": 6, "statusRevision": 3, "runUuid":
"7da6a191-0945-4e9f-bfc6-a1fc7c72b72c", "parentRunUuid": null, "rootRunUuid":
"7da6a191-0945-4e9f-bfc6-a1fc7c72b72c", "lastStartTimeUtc": null, "currentComputeTime":
null, "computeDuration": "00:00:08.3698759", "effectiveStartTimeUtc": null,
"lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000", "userPuId":
"100320005227D154", "userIdp": null, "userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "Han Wang",
"upn": "[email protected]"}, "lastModifiedUtc": "2024-01-25T09:17:00.9260346+00:00",
"duration": "00:00:08.3698759", "cancelationReason": null, "currentAttemptId":
1, "runId": "name", "parentRunId": null, "experimentId": "64465848-e4a8-42a2-a617-d7f0fcda6f32",
"status": "Completed", "startTimeUtc": "2024-01-25T09:16:53.6662445+00:00",
"endTimeUtc": "2024-01-25T09:17:02.0361204+00:00", "scheduleId": null, "displayName":
"name", "name": null, "dataContainerId": "dcid.name", "description": null, "hidden":
false, "runType": "azureml.promptflow.FlowRun", "runTypeV2": {"orchestrator":
null, "traits": [], "attribution": "PromptFlow", "computeType": null}, "properties":
{"azureml.promptflow.runtime_name": "automatic", "azureml.promptflow.runtime_version":
"20240116.v1", "azureml.promptflow.definition_file_name": "flow.dag.yaml", "azureml.promptflow.flow_lineage_id":
"63d67b0b61e34b0527b5f3c46dfc953854138b2ffebc68175580285dc2d95663", "azureml.promptflow.flow_definition_datastore_name":
"workspaceblobstore", "azureml.promptflow.flow_definition_blob_path": "LocalUpload/79819672296a1785a95c65c8c0e75b0d/simple_with_req/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/e62bc4d5a164939b21d42dd420469da7/simple_eager_flow_data.jsonl",
"_azureml.evaluation_run": "promptflow.BatchRun", "azureml.promptflow.session_id":
"b905697d9d04e1b8c87c12d30eb37326380d5cfeb7d0500e", "azureml.promptflow.snapshot_id":
"1ac134f8-0696-4ce1-ba89-cd4d9748e886", "azureml.promptflow.run_mode": "Eager",
"azureml.promptflow.total_tokens": "0", "_azureml.evaluate_artifacts": "[{\"path\":
\"instance_results.jsonl\", \"type\": \"table\"}]"}, "parameters": {}, "actionUris":
{}, "scriptName": null, "target": null, "uniqueChildRunComputeTargets": [],
"tags": {}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName": null,
"createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": {"debug_info": {"assetId":
"azureml://locations/eastus/workspaces/00000/data/azureml_name_output_data_debug_info/versions/1",
"type": "UriFolder"}, "flow_outputs": {"assetId": "azureml://locations/eastus/workspaces/00000/data/azureml_name_output_data_flow_outputs/versions/1",
"type": "UriFolder"}}}, "runDefinition": null, "jobSpecification": null, "systemSettings":
null}'
headers:
connection:
- keep-alive
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.050'
http_version: HTTP/1.1
status_code: 200
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name/logContent
response:
body:
string: '"2024-01-25 09:16:46 +0000 50 promptflow-runtime INFO [name]
Receiving v2 bulk run request d3077030-8829-4e75-84e2-23ffb7fe5647: {\"flow_id\":
\"name\", \"flow_run_id\": \"name\", \"flow_source\": {\"flow_source_type\":
1, \"flow_source_info\": {\"snapshot_id\": \"1ac134f8-0696-4ce1-ba89-cd4d9748e886\"},
\"flow_dag_file\": \"flow.dag.yaml\"}, \"log_path\": \"https://promptfloweast4063704120.blob.core.windows.net/azureml/ExperimentRun/dcid.name/logs/azureml/executionlogs.txt?sv=2019-07-07&sr=b&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-25T08%3A48%3A12Z&ske=2024-01-26T16%3A58%3A12Z&sks=b&skv=2019-07-07&st=2024-01-25T09%3A06%3A45Z&se=2024-01-25T17%3A16%3A45Z&sp=rcw\",
\"app_insights_instrumentation_key\": \"InstrumentationKey=**data_scrubbed**;IngestionEndpoint=https://eastus-6.in.applicationinsights.azure.com/;LiveEndpoint=https://eastus.livediagnostics.monitor.azure.com/\",
\"data_inputs\": {\"data\": \"azureml://datastores/workspaceblobstore/paths/LocalUpload/e62bc4d5a164939b21d42dd420469da7/simple_eager_flow_data.jsonl\"},
\"azure_storage_setting\": {\"azure_storage_mode\": 1, \"storage_account_name\":
\"promptfloweast4063704120\", \"blob_container_name\": \"azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5\",
\"flow_artifacts_root_path\": \"promptflow/PromptFlowArtifacts/name\", \"blob_container_sas_token\":
\"?sv=2019-07-07&sr=c&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-25T09%3A16%3A45Z&ske=2024-02-01T09%3A16%3A45Z&sks=b&skv=2019-07-07&se=2024-02-01T09%3A16%3A45Z&sp=racwl\",
\"output_datastore_name\": \"workspaceblobstore\"}}\n2024-01-25 09:16:46 +0000 50
promptflow-runtime INFO Runtime version: 20240116.v1. PromptFlow version:
1.4.0rc3\n2024-01-25 09:16:46 +0000 50 promptflow-runtime INFO Updating
name to Status.Preparing...\n2024-01-25 09:16:47 +0000 50 promptflow-runtime
INFO Downloading snapshot to /mnt/host/service/app/37305/requests/name\n2024-01-25
09:16:47 +0000 50 promptflow-runtime INFO Get snapshot sas url for
1ac134f8-0696-4ce1-ba89-cd4d9748e886.\n2024-01-25 09:16:47 +0000 50 promptflow-runtime
INFO Snapshot 1ac134f8-0696-4ce1-ba89-cd4d9748e886 contains 3 files.\n2024-01-25
09:16:47 +0000 50 promptflow-runtime INFO Download snapshot 1ac134f8-0696-4ce1-ba89-cd4d9748e886
completed.\n2024-01-25 09:16:47 +0000 50 promptflow-runtime INFO Successfully
download snapshot to /mnt/host/service/app/37305/requests/name\n2024-01-25
09:16:47 +0000 50 promptflow-runtime INFO About to execute a python
flow.\n2024-01-25 09:16:47 +0000 50 promptflow-runtime INFO Use spawn
method to start child process.\n2024-01-25 09:16:47 +0000 50 promptflow-runtime
INFO Starting to check process 526 status for run name\n2024-01-25 09:16:47
+0000 50 promptflow-runtime INFO Start checking run status for run
name\n2024-01-25 09:16:51 +0000 526 promptflow-runtime INFO [50--526]
Start processing flowV2......\n2024-01-25 09:16:51 +0000 526 promptflow-runtime
INFO Runtime version: 20240116.v1. PromptFlow version: 0.0.116642424\n2024-01-25
09:16:51 +0000 526 promptflow-runtime INFO Setting mlflow tracking
uri...\n2024-01-25 09:16:51 +0000 526 promptflow-runtime INFO Validating
''AzureML Data Scientist'' user authentication...\n2024-01-25 09:16:52 +0000 526
promptflow-runtime INFO Successfully validated ''AzureML Data Scientist''
user authentication.\n2024-01-25 09:16:52 +0000 526 promptflow-runtime
INFO Using AzureMLRunStorageV2\n2024-01-25 09:16:52 +0000 526 promptflow-runtime
INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-25
09:16:52 +0000 526 promptflow-runtime INFO Initialized blob service
client for AzureMLRunTracker.\n2024-01-25 09:16:52 +0000 526 promptflow-runtime
INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-25
09:16:53 +0000 526 promptflow-runtime INFO Resolve data from url finished
in 0.5306580369999665 seconds\n2024-01-25 09:16:53 +0000 526 promptflow-runtime
INFO Starting the aml run ''name''...\n2024-01-25 09:16:53 +0000 526
execution WARNING Starting run without column mapping may lead to
unexpected results. Please consult the following documentation for more information:
https://aka.ms/pf/column-mapping\n2024-01-25 09:16:53 +0000 526 execution.bulk INFO Set
process count to 1 by taking the minimum value among the factors of {''default_worker_count'':
4, ''row_count'': 1}.\n2024-01-25 09:16:57 +0000 526 execution.bulk INFO Process
name(ForkProcess-2:2:1)-Process id(596)-Line number(0) start execution.\n2024-01-25
09:16:58 +0000 526 execution.bulk INFO Process name(ForkProcess-2:2:1)-Process
id(596)-Line number(0) completed.\n2024-01-25 09:16:58 +0000 526 execution.bulk INFO Finished
1 / 1 lines.\n2024-01-25 09:16:58 +0000 526 execution.bulk INFO Average
execution time for completed lines: 5.0 seconds. Estimated time for incomplete
lines: 0.0 seconds.\n2024-01-25 09:17:00 +0000 526 promptflow-runtime
INFO Post processing batch result...\n2024-01-25 09:17:00 +0000 526
execution.bulk INFO Upload status summary metrics for run name finished
in 0.6790808640000705 seconds\n2024-01-25 09:17:00 +0000 526 promptflow-runtime
INFO Successfully write run properties {\"azureml.promptflow.total_tokens\":
0, \"_azureml.evaluate_artifacts\": \"[{\\\"path\\\": \\\"instance_results.jsonl\\\",
\\\"type\\\": \\\"table\\\"}]\"} with run id ''name''\n2024-01-25 09:17:00
+0000 526 execution.bulk INFO Upload RH properties for run name
finished in 0.06737575900001502 seconds\n2024-01-25 09:17:00 +0000 526
promptflow-runtime INFO Creating unregistered output Asset for Run name...\n2024-01-25
09:17:01 +0000 526 promptflow-runtime INFO Created debug_info Asset:
azureml://locations/eastus/workspaces/00000/data/azureml_name_output_data_debug_info/versions/1\n2024-01-25
09:17:01 +0000 526 promptflow-runtime INFO Creating unregistered output
Asset for Run name...\n2024-01-25 09:17:01 +0000 526 promptflow-runtime
INFO Created flow_outputs output Asset: azureml://locations/eastus/workspaces/00000/data/azureml_name_output_data_flow_outputs/versions/1\n2024-01-25
09:17:01 +0000 526 promptflow-runtime INFO Creating Artifact for Run
name...\n2024-01-25 09:17:01 +0000 526 promptflow-runtime INFO Created
instance_results.jsonl Artifact.\n2024-01-25 09:17:01 +0000 526 promptflow-runtime
INFO Patching name...\n2024-01-25 09:17:01 +0000 526 promptflow-runtime
INFO Ending the aml run ''name'' with status ''Completed''...\n2024-01-25
09:17:53 +0000 50 promptflow-runtime INFO Process 526 finished\n2024-01-25
09:17:53 +0000 50 promptflow-runtime INFO [50] Child process finished!\n2024-01-25
09:17:54 +0000 50 promptflow-runtime INFO [name] End processing bulk
run\n2024-01-25 09:17:54 +0000 50 promptflow-runtime INFO Cleanup
working dir /mnt/host/service/app/37305/requests/name for bulk run\n"'
headers:
connection:
- keep-alive
content-length:
- '8401'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '1.347'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_run_with_connection_overwrite.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.019'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.099'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.087'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.136'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:22:35 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/webClassification1.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '127'
content-md5:
- i/8q1x5YKzHv3Fd/R8lYUQ==
content-type:
- application/octet-stream
last-modified:
- Fri, 28 Jul 2023 12:34:52 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Fri, 28 Jul 2023 12:34:52 GMT
x-ms-meta-name:
- 13fa99dd-c98e-4f2a-a704-4295d4ed6f68
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 0367c5c6-9f53-4a75-8623-7e53699f0d0b
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:22:36 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/webClassification1.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.083'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.107'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:22:40 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/web_classification/classify_with_llm.jinja2
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '853'
content-md5:
- ylTeNqjvuOvtzEZJ/X5n3A==
content-type:
- application/octet-stream
last-modified:
- Fri, 12 Jan 2024 08:13:57 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Fri, 12 Jan 2024 08:13:56 GMT
x-ms-meta-name:
- 950201e8-c52c-4b15-ada1-5e58de9b2f4d
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:22:41 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/web_classification/classify_with_llm.jinja2
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/web_classification/flow.dag.yaml",
"runId": "name", "runDisplayName": "name", "runExperimentName": "", "nodeVariant":
"${summarize_text_content.variant_0}", "batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/webClassification1.jsonl"},
"inputsMapping": {"url": "${data.url}"}, "connections": {"classify_with_llm":
{"connection": "azure_open_ai", "model": "gpt-3.5-turbo"}}, "environmentVariables":
{}, "runtimeName": "fake-runtime-name", "sessionId": "000000000000000000000000000000000000000000000000",
"sessionSetupMode": "SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '951'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '6.277'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "fetch_text_content_from_url", "type":
"python", "source": {"type": "code", "path": "fetch_text_content_from_url.py"},
"inputs": {"fetch_url": "${inputs.url}"}, "tool": "fetch_text_content_from_url.py",
"reduce": false}, {"name": "prepare_examples", "type": "python", "source":
{"type": "code", "path": "prepare_examples.py"}, "inputs": {}, "tool": "prepare_examples.py",
"reduce": false}, {"name": "classify_with_llm", "type": "llm", "source": {"type":
"code", "path": "classify_with_llm.jinja2"}, "inputs": {"deployment_name":
"gpt-35-turbo", "suffix": "", "max_tokens": "128", "temperature": "0.1", "top_p":
"1.0", "logprobs": "", "echo": "False", "stop": "", "presence_penalty": "0",
"frequency_penalty": "0", "best_of": "1", "logit_bias": "", "url": "${inputs.url}",
"examples": "${prepare_examples.output}", "text_content": "${summarize_text_content.output}",
"model": "gpt-3.5-turbo"}, "tool": "classify_with_llm.jinja2", "reduce": false,
"api": "chat", "provider": "AzureOpenAI", "connection": "azure_open_ai", "module":
"promptflow.tools.aoai"}, {"name": "convert_to_dict", "type": "python", "source":
{"type": "code", "path": "convert_to_dict.py"}, "inputs": {"input_str": "${classify_with_llm.output}"},
"tool": "convert_to_dict.py", "reduce": false}, {"name": "summarize_text_content",
"type": "llm", "source": {"type": "code", "path": "summarize_text_content.jinja2"},
"inputs": {"deployment_name": "gpt-35-turbo", "suffix": "", "max_tokens":
"128", "temperature": "0.2", "top_p": "1.0", "logprobs": "", "echo": "False",
"stop": "", "presence_penalty": "0", "frequency_penalty": "0", "best_of":
"1", "logit_bias": "", "text": "${fetch_text_content_from_url.output}"}, "tool":
"summarize_text_content.jinja2", "reduce": false, "api": "chat", "provider":
"AzureOpenAI", "connection": "azure_open_ai_connection", "module": "promptflow.tools.aoai"}],
"tools": [{"name": "Content Safety (Text Analyze)", "type": "python", "inputs":
{"connection": {"type": ["AzureContentSafetyConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "hate_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "self_harm_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "sexual_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "text": {"type":
["string"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "violence_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"}},
"description": "Use Azure Content Safety to detect harmful content.", "module":
"promptflow.tools.azure_content_safety", "function": "analyze_text", "is_builtin":
true, "package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "classify_with_llm.jinja2", "type":
"prompt", "inputs": {"examples": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "text_content":
{"type": ["string"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "url": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "classify_with_llm.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}, {"name":
"convert_to_dict.py", "type": "python", "inputs": {"input_str": {"type": ["string"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"}},
"source": "convert_to_dict.py", "function": "convert_to_dict", "is_builtin":
false, "enable_kwargs": false, "tool_state": "stable"}, {"name": "fetch_text_content_from_url.py",
"type": "python", "inputs": {"fetch_url": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "fetch_text_content_from_url.py",
"function": "fetch_text_content_from_url", "is_builtin": false, "enable_kwargs":
false, "tool_state": "stable"}, {"name": "prepare_examples.py", "type": "python",
"source": "prepare_examples.py", "function": "prepare_examples", "is_builtin":
false, "enable_kwargs": false, "tool_state": "stable"}, {"name": "summarize_text_content.jinja2",
"type": "prompt", "inputs": {"text": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "summarize_text_content.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}, {"name":
"summarize_text_content__variant_1.jinja2", "type": "prompt", "inputs": {"text":
{"type": ["string"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "source": "summarize_text_content__variant_1.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"url": {"type": "string", "default": "https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h",
"is_chat_input": false}}, "outputs": {"category": {"type": "string", "reference":
"${convert_to_dict.output.category}", "evaluation_only": false, "is_chat_output":
false}, "evidence": {"type": "string", "reference": "${convert_to_dict.output.evidence}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name", "flowRunId":
"name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/107bd3498e44deb2dccc53d2208d32b2/webClassification1.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"url": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "a356b061-8870-40da-9061-3920ac5171cf",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '16252'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.355'
status:
code: 200
message: OK
- request:
body: '{"runId": "name", "selectRunMetadata": true, "selectRunDefinition": true,
"selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705047766, "rootRunId": "name", "createdUtc":
"2024-01-12T08:22:46.9110681+00:00", "createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": null, "warnings": null, "revision": 3,
"statusRevision": 1, "runUuid": "6d870fe2-b2a7-4273-97c9-1f054cd88ab3", "parentRunUuid":
null, "rootRunUuid": "6d870fe2-b2a7-4273-97c9-1f054cd88ab3", "lastStartTimeUtc":
null, "currentComputeTime": "00:00:00", "computeDuration": null, "effectiveStartTimeUtc":
null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:22:50.8542458+00:00", "duration":
null, "cancelationReason": null, "currentAttemptId": 1, "runId": "name", "parentRunId":
null, "experimentId": "d30efbeb-f81d-4cfa-b5cc-a0570a049009", "status": "Preparing",
"startTimeUtc": null, "endTimeUtc": null, "scheduleId": null, "displayName":
"name", "name": null, "dataContainerId": "dcid.name", "description": null,
"hidden": false, "runType": "azureml.promptflow.FlowRun", "runTypeV2": {"orchestrator":
null, "traits": [], "attribution": "PromptFlow", "computeType": "AmlcDsi"},
"properties": {"azureml.promptflow.runtime_name": "test-runtime-ci", "azureml.promptflow.runtime_version":
"20231204.v4", "azureml.promptflow.definition_file_name": "flow.dag.yaml",
"azureml.promptflow.session_id": "4dd8f4d5f44dfeb817d3438cf84bd739215d87afd9458597",
"azureml.promptflow.flow_lineage_id": "af1a6951de9be2ce13d3b58b23dbd8b6a0cd8fd4918ad9cb22b28fb8395fbcb0",
"azureml.promptflow.node_variant": "${summarize_text_content.variant_0}",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/a1fa6ef1ead7ff3ce76b36250f6f5461/web_classification/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/107bd3498e44deb2dccc53d2208d32b2/webClassification1.jsonl",
"azureml.promptflow.inputs_mapping": "{\"url\":\"${data.url}\"}", "_azureml.evaluation_run":
"promptflow.BatchRun", "azureml.promptflow.snapshot_id": "a356b061-8870-40da-9061-3920ac5171cf"},
"parameters": {}, "actionUris": {}, "scriptName": null, "target": null, "uniqueChildRunComputeTargets":
[], "tags": {}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": null}, "runDefinition":
null, "jobSpecification": null, "systemSettings": null}'
headers:
connection:
- keep-alive
content-length:
- '4011'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.056'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_azure_cli_perf_TestAzureCliPerf_test_pfazure_run_update.yaml | interactions:
- request:
body: '{"displayName": "test_run", "description": "test_description", "tags":
{"key1": "value1"}}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '90'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: PATCH
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/runs/test_run/modify
response:
body:
string: '{"runNumber": 1705290707, "rootRunId": "test_run", "createdUtc": "2024-01-15T03:51:47.7832069+00:00",
"createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000", "userPuId":
"10032001A114F500", "userIdp": null, "userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "Chenyang
Zhang", "upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token":
null, "tokenExpiryTimeUtc": null, "error": null, "warnings": null, "revision":
7, "statusRevision": 3, "runUuid": "115295b6-152f-44b3-a79f-2188901c76fd",
"parentRunUuid": null, "rootRunUuid": "115295b6-152f-44b3-a79f-2188901c76fd",
"lastStartTimeUtc": null, "currentComputeTime": null, "computeDuration": "00:00:03.3854385",
"effectiveStartTimeUtc": null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": "10032001A114F500", "userIdp": null, "userAltSecId": null, "userIss":
"https://sts.windows.net/00000000-0000-0000-0000-000000000000/", "userTenantId":
"00000000-0000-0000-0000-000000000000", "userName": "Chenyang Zhang", "upn":
"[email protected]"}, "lastModifiedUtc": "2024-01-15T04:04:54.041594+00:00",
"duration": "00:00:03.3854385", "cancelationReason": null, "currentAttemptId":
1, "runId": "test_run", "parentRunId": null, "experimentId": "00000000-0000-0000-0000-000000000000",
"status": "Completed", "startTimeUtc": "2024-01-15T03:51:57.3800585+00:00",
"endTimeUtc": "2024-01-15T03:52:00.765497+00:00", "scheduleId": null, "displayName":
"test_run", "name": null, "dataContainerId": "dcid.test_run", "description":
"test_description", "hidden": false, "runType": "azureml.promptflow.FlowRun",
"runTypeV2": {"orchestrator": null, "traits": [], "attribution": "PromptFlow",
"computeType": null}, "properties": {"azureml.promptflow.runtime_name": "automatic",
"azureml.promptflow.runtime_version": "20240111.v2", "azureml.promptflow.definition_file_name":
"flow.dag.yaml", "azureml.promptflow.session_id": "96c35660d759b526cb14cf69bbb56fcaa90c05a778b147b4",
"azureml.promptflow.flow_lineage_id": "fcb01d4faf8f2137f9d142cc1f3f22ecdf3d485e1435c4c971ff0ee09077f1b5",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/52675845d616ad8b41db77e9ba9e9d4a/print_input_flow/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/80d5ca5a93c8c6ea7c2fcdf1cd4b9d07/print_input_flow.jsonl",
"_azureml.evaluation_run": "promptflow.BatchRun", "azureml.promptflow.snapshot_id":
"a18c2edd-59e6-4b07-a264-b0a97a213218", "azureml.promptflow.total_tokens":
"0", "_azureml.evaluate_artifacts": "[{\"path\": \"instance_results.jsonl\",
\"type\": \"table\"}]"}, "parameters": {}, "actionUris": {}, "scriptName":
null, "target": null, "uniqueChildRunComputeTargets": [], "tags": {"key1":
"value1"}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": null}'
headers:
connection:
- keep-alive
content-length:
- '3592'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.142'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.9.17 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/test_run
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_input", "type": "python",
"source": {"type": "code", "path": "print_input.py"}, "inputs": {"text": "${inputs.text}"},
"tool": "print_input.py", "reduce": false}], "tools": [{"name": "Azure OpenAI
GPT-4 Turbo with Vision", "type": "custom_llm", "inputs": {"connection": {"type":
["AzureOpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "frequency_penalty":
{"type": ["double"], "default": 0, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "max_tokens": {"type": ["int"], "default":
512, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Azure OpenAI GPT-4 Turbo
with Vision to leverage AOAI vision ability.", "module": "promptflow.tools.aoai_gpt4v",
"class_name": "AzureOpenAI", "function": "chat", "icon": {"dark": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAA2ElEQVR4nJXSzW3CQBAF4DUSTjk+Al1AD0ikESslpBIEheRALhEpgAYSWV8OGUublf/yLuP3PPNmdndS+gdwXZrYDmh7fGE/W+wXbaYd8IYm4rxJPnZ0boI3wZcdJxs/n+AwV7DFK7aFyfQdYIMLPvES8YJNf5yp4jMeeEYdWh38gXOR35YGHe5xabvQdsHv6PLi8qV6gycc8YH3iMfQu6Lh4ASr+F5Hh3XwVWnQYzUkVlX1nccplAb1SN6Y/sfgmlK64VS8wimldIv/0yj2QLkHizG0iWP4AVAfQ34DVQONAAAAAElFTkSuQmCC",
"light": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAx0lEQVR4nJWSwQ2CQBBFX0jAcjgqXUgPJNiIsQQrIVCIFy8GC6ABDcGDX7Mus9n1Xz7zZ+fPsLPwH4bUg0dD2wMPcbR48Uxq4AKU4iSTDwZ1LhWXipN/B3V0J6hjBTvgLHZNonewBXrgDpzEvXSIjN0BE3AACmmF4kl5F6tNzcCoLpW0SvGovFvsb4oZ2AANcAOu4ka6axCcINN3rg654sww+CYsPD0OwjcozFNh/Qcd78tqVbCIW+n+Fky472Bh/Q6SYb1EEy8tDzd+9IsVPAAAAABJRU5ErkJggg=="},
"is_builtin": true, "package": "promptflow-tools", "package_version": "1.0.3",
"default_prompt": "# system:\nAs an AI assistant, your task involves interpreting
images and responding to questions about the image.\nRemember to provide accurate
answers based on the information present in the image.\n\n# user:\nCan you
tell me what the image depicts?\n\n", "enable_kwargs":
false, "tool_state": "preview"}, {"name": "Content Safety (Text Analyze)",
"type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"1.0.3", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": true, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "1.0.3", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Model LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "default": "", "dynamic_list": {"func_path": "promptflow.tools.open_model_llm.list_deployment_names",
"func_kwargs": [{"name": "endpoint", "optional": true, "reference": "${inputs.endpoint}",
"type": ["string"]}]}, "allow_manual_entry": true, "is_multi_select": false,
"input_type": "default"}, "endpoint_name": {"type": ["string"], "dynamic_list":
{"func_path": "promptflow.tools.open_model_llm.list_endpoint_names"}, "allow_manual_entry":
true, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an open model from the Azure Model catalog, deployed to
an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_model_llm", "class_name": "OpenModelLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "1.0.3",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": 512, "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "icon": {"dark": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAA2ElEQVR4nJXSzW3CQBAF4DUSTjk+Al1AD0ikESslpBIEheRALhEpgAYSWV8OGUublf/yLuP3PPNmdndS+gdwXZrYDmh7fGE/W+wXbaYd8IYm4rxJPnZ0boI3wZcdJxs/n+AwV7DFK7aFyfQdYIMLPvES8YJNf5yp4jMeeEYdWh38gXOR35YGHe5xabvQdsHv6PLi8qV6gycc8YH3iMfQu6Lh4ASr+F5Hh3XwVWnQYzUkVlX1nccplAb1SN6Y/sfgmlK64VS8wimldIv/0yj2QLkHizG0iWP4AVAfQ34DVQONAAAAAElFTkSuQmCC",
"light": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAx0lEQVR4nJWSwQ2CQBBFX0jAcjgqXUgPJNiIsQQrIVCIFy8GC6ABDcGDX7Mus9n1Xz7zZ+fPsLPwH4bUg0dD2wMPcbR48Uxq4AKU4iSTDwZ1LhWXipN/B3V0J6hjBTvgLHZNonewBXrgDpzEvXSIjN0BE3AACmmF4kl5F6tNzcCoLpW0SvGovFvsb4oZ2AANcAOu4ka6axCcINN3rg654sww+CYsPD0OwjcozFNh/Qcd78tqVbCIW+n+Fky472Bh/Q6SYb1EEy8tDzd+9IsVPAAAAABJRU5ErkJggg=="},
"is_builtin": true, "package": "promptflow-tools", "package_version": "1.0.3",
"default_prompt": "# system:\nAs an AI assistant, your task involves interpreting
images and responding to questions about the image.\nRemember to provide accurate
answers based on the information present in the image.\n\n# user:\nCan you
tell me what the image depicts?\n\n", "enable_kwargs":
false, "tool_state": "preview"}, {"name": "Serp API", "type": "python", "inputs":
{"connection": {"type": ["SerpConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "engine": {"type": ["string"], "default":
"google", "enum": ["google", "bing"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "location": {"type": ["string"], "default":
"", "allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"num": {"type": ["int"], "default": "10", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "safe": {"type":
["string"], "default": "off", "enum": ["active", "off"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "description":
"Use Serp API to obtain search results from a specific search engine.", "module":
"promptflow.tools.serpapi", "class_name": "SerpAPI", "function": "search",
"is_builtin": true, "package": "promptflow-tools", "package_version": "1.0.3",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Index Lookup",
"type": "python", "inputs": {"acs_content_field": {"type": ["string"], "enabled_by":
"index_type", "enabled_by_value": ["Azure AI Search"], "dynamic_list": {"func_path":
"promptflow_vectordb.tool.common_index_lookup_utils.list_acs_index_fields",
"func_kwargs": [{"name": "acs_connection", "optional": false, "reference":
"${inputs.acs_index_connection}", "type": ["CognitiveSearchConnection"]},
{"name": "acs_index_name", "optional": false, "reference": "${inputs.acs_index_name}",
"type": ["string"]}, {"default": "Edm.String", "name": "field_data_type",
"optional": false, "type": ["string"]}]}, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "uionly_hidden"}, "acs_embedding_field": {"type": ["string"],
"enabled_by": "index_type", "enabled_by_value": ["Azure AI Search"], "dynamic_list":
{"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_acs_index_fields",
"func_kwargs": [{"name": "acs_connection", "optional": false, "reference":
"${inputs.acs_index_connection}", "type": ["CognitiveSearchConnection"]},
{"name": "acs_index_name", "optional": false, "reference": "${inputs.acs_index_name}",
"type": ["string"]}, {"default": "Collection(Edm.Single)", "name": "field_data_type",
"optional": false, "type": ["string"]}]}, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "uionly_hidden"}, "acs_index_connection": {"type": ["CognitiveSearchConnection"],
"enabled_by": "index_type", "enabled_by_value": ["Azure AI Search"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "uionly_hidden"}, "acs_index_name":
{"type": ["string"], "enabled_by": "index_type", "enabled_by_value": ["Azure
AI Search"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_acs_indices",
"func_kwargs": [{"name": "acs_connection", "optional": false, "reference":
"${inputs.acs_index_connection}", "type": ["CognitiveSearchConnection"]}]},
"allow_manual_entry": false, "is_multi_select": false, "input_type": "uionly_hidden"},
"acs_metadata_field": {"type": ["string"], "enabled_by": "index_type", "enabled_by_value":
["Azure AI Search"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_acs_index_fields",
"func_kwargs": [{"name": "acs_connection", "optional": false, "reference":
"${inputs.acs_index_connection}", "type": ["CognitiveSearchConnection"]},
{"name": "acs_index_name", "optional": false, "reference": "${inputs.acs_index_name}",
"type": ["string"]}, {"default": "Edm.String", "name": "field_data_type",
"optional": false, "type": ["string"]}]}, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "uionly_hidden"}, "aoai_embedding_connection": {"type":
["AzureOpenAIConnection"], "enabled_by": "embedding_type", "enabled_by_value":
["Azure OpenAI"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"uionly_hidden"}, "embedding_deployment": {"type": ["string"], "enabled_by":
"embedding_type", "enabled_by_value": ["Azure OpenAI"], "dynamic_list": {"func_path":
"promptflow_vectordb.tool.common_index_lookup_utils.list_aoai_embedding_deployments",
"func_kwargs": [{"name": "aoai_connection", "optional": false, "reference":
"${inputs.aoai_embedding_connection}", "type": ["AzurOpenAIConnection"]}]},
"allow_manual_entry": false, "is_multi_select": false, "input_type": "uionly_hidden"},
"embedding_model": {"type": ["string"], "enabled_by": "embedding_type", "enabled_by_value":
["OpenAI", "Hugging Face"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_embedding_models",
"func_kwargs": [{"name": "embedding_type", "optional": false, "reference":
"${inputs.embedding_type}", "type": ["string"]}]}, "allow_manual_entry": false,
"is_multi_select": false, "input_type": "uionly_hidden"}, "embedding_type":
{"type": ["string"], "enabled_by": "index_type", "enabled_by_value": ["Azure
AI Search", "FAISS", "Pinecone"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_available_embedding_types",
"func_kwargs": [{"name": "index_type", "optional": false, "reference": "${inputs.index_type}",
"type": ["string"]}]}, "allow_manual_entry": false, "is_multi_select": false,
"input_type": "uionly_hidden"}, "faiss_index_path": {"type": ["string"], "enabled_by":
"index_type", "enabled_by_value": ["FAISS"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "uionly_hidden"}, "index_type": {"type":
["string"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_available_index_types"},
"allow_manual_entry": false, "is_multi_select": false, "input_type": "uionly_hidden"},
"mlindex_asset_id": {"type": ["string"], "enabled_by": "index_type", "enabled_by_value":
["Registered Index"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_registered_mlindices"},
"allow_manual_entry": false, "is_multi_select": false, "input_type": "uionly_hidden"},
"mlindex_content": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "generated_by": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.forward_mapping",
"func_kwargs": [{"name": "index_type", "reference": "${inputs.index_type}",
"type": ["string"]}, {"name": "mlindex_asset_id", "optional": true, "reference":
"${inputs.mlindex_asset_id}", "type": ["string"]}, {"name": "mlindex_path",
"optional": true, "reference": "${inputs.mlindex_path}", "type": ["string"]},
{"name": "acs_index_connection", "optional": true, "reference": "${inputs.acs_index_connection}",
"type": ["CognitiveSearchConnection"]}, {"name": "acs_index_name", "optional":
true, "reference": "${inputs.acs_index_name}", "type": ["string"]}, {"name":
"acs_content_field", "optional": true, "reference": "${inputs.acs_content_field}",
"type": ["string"]}, {"name": "acs_embedding_field", "optional": true, "reference":
"${inputs.acs_embedding_field}", "type": ["string"]}, {"name": "acs_metadata_field",
"optional": true, "reference": "${inputs.acs_metadata_field}", "type": ["string"]},
{"name": "semantic_configuration", "optional": true, "reference": "${inputs.semantic_configuration}",
"type": ["string"]}, {"name": "faiss_index_path", "optional": true, "reference":
"${inputs.faiss_index_path}", "type": ["string"]}, {"name": "pinecone_index_connection",
"optional": true, "reference": "${inputs.pinecone_index_connection}", "type":
["string"]}, {"name": "pinecone_index_name", "optional": true, "reference":
"${inputs.pinecone_index_name}", "type": ["string"]}, {"name": "pinecone_content_field",
"optional": true, "reference": "${inputs.pinecone_content_field}", "type":
["string"]}, {"name": "pinecone_metadata_field", "optional": true, "reference":
"${inputs.pinecone_metadata_field}", "type": ["string"]}, {"name": "embedding_type",
"optional": true, "reference": "${inputs.embedding_type}", "type": ["string"]},
{"name": "aoai_embedding_connection", "optional": true, "reference": "${inputs.aoai_embedding_connection}",
"type": ["AzureOpenAIConnection"]}, {"name": "oai_embedding_connection", "optional":
true, "reference": "${inputs.oai_embedding_connection}", "type": ["string"]},
{"name": "embedding_model", "optional": true, "reference": "${inputs.embedding_model}",
"type": ["string"]}, {"name": "embedding_deployment", "optional": true, "reference":
"${inputs.embedding_deployment}", "type": ["string"]}], "reverse_func_path":
"promptflow_vectordb.tool.common_index_lookup_utils.reverse_mapping"}, "input_type":
"default"}, "mlindex_path": {"type": ["string"], "enabled_by": "index_type",
"enabled_by_value": ["MLIndex file from path"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "uionly_hidden"}, "oai_embedding_connection":
{"type": ["OpenAIConnection"], "enabled_by": "embedding_type", "enabled_by_value":
["OpenAI"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"uionly_hidden"}, "pinecone_content_field": {"type": ["string"], "enabled_by":
"index_type", "enabled_by_value": ["Pinecone"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "uionly_hidden"}, "pinecone_index_connection":
{"type": ["PineconeConnection"], "enabled_by": "index_type", "enabled_by_value":
["Pinecone"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_pinecone_connections"},
"allow_manual_entry": false, "is_multi_select": false, "input_type": "uionly_hidden"},
"pinecone_index_name": {"type": ["string"], "enabled_by": "index_type", "enabled_by_value":
["Pinecone"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_pinecone_indices",
"func_kwargs": [{"name": "pinecone_connection_name", "optional": false, "reference":
"${inputs.pinecone_index_connection}", "type": ["string"]}]}, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "uionly_hidden"}, "pinecone_metadata_field":
{"type": ["string"], "enabled_by": "index_type", "enabled_by_value": ["Pinecone"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "uionly_hidden"},
"queries": {"type": ["object"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query_type": {"type": ["string"], "dynamic_list":
{"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_available_query_types",
"func_kwargs": [{"name": "mlindex_content", "optional": false, "reference":
"${inputs.mlindex_content}", "type": ["string"]}]}, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "semantic_configuration":
{"type": ["string"], "enabled_by": "index_type", "enabled_by_value": ["Azure
AI Search"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_acs_index_semantic_configurations",
"func_kwargs": [{"name": "acs_connection", "optional": false, "reference":
"${inputs.acs_index_connection}", "type": ["CognitiveSearchConnection"]},
{"name": "acs_index_name", "optional": false, "reference": "${inputs.acs_index_name}",
"type": ["string"]}]}, "allow_manual_entry": false, "is_multi_select": false,
"input_type": "uionly_hidden"}, "top_k": {"type": ["int"], "default": 3, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "description":
"Search an AzureML Vector Index for relevant results using one or more text
queries.", "module": "promptflow_vectordb.tool.common_index_lookup", "function":
"search", "is_builtin": true, "package": "promptflow-vectordb", "package_version":
"0.0.1", "enable_kwargs": false, "tool_state": "preview"}, {"name": "Faiss
Index Lookup", "type": "python", "inputs": {"path": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "vector": {"type": ["list"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "description":
"Search vector based query from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_input.py", "type": "python",
"inputs": {"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_input.py", "function":
"print_inputs", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"text": {"type": "string", "is_chat_input": false}},
"outputs": {"output_text": {"type": "string", "reference": "${print_input.output}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus2euap/workspaces/00000/flows/test_run/flowRuns/test_run",
"flowRunId": "test_run", "flowRunDisplayName": "test_run", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/80d5ca5a93c8c6ea7c2fcdf1cd4b9d07/print_input_flow.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "automatic",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/test_run/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "a18c2edd-59e6-4b07-a264-b0a97a213218",
"studioPortalEndpoint": "https://ml.azure.com/runs/test_run?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '25970'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.331'
status:
code: 200
message: OK
- request:
body: '{"runId": "test_run", "selectRunMetadata": true, "selectRunDefinition":
true, "selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '109'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705290707, "rootRunId": "test_run",
"createdUtc": "2024-01-15T03:51:47.7832069+00:00", "createdBy": {"userObjectId":
"00000000-0000-0000-0000-000000000000", "userPuId": "10032001A114F500", "userIdp":
null, "userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "Chenyang
Zhang", "upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token":
null, "tokenExpiryTimeUtc": null, "error": null, "warnings": null, "revision":
7, "statusRevision": 3, "runUuid": "115295b6-152f-44b3-a79f-2188901c76fd",
"parentRunUuid": null, "rootRunUuid": "115295b6-152f-44b3-a79f-2188901c76fd",
"lastStartTimeUtc": null, "currentComputeTime": null, "computeDuration": "00:00:03.3854385",
"effectiveStartTimeUtc": null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": "10032001A114F500", "userIdp": null, "userAltSecId": null, "userIss":
"https://sts.windows.net/00000000-0000-0000-0000-000000000000/", "userTenantId":
"00000000-0000-0000-0000-000000000000", "userName": "Chenyang Zhang", "upn":
"[email protected]"}, "lastModifiedUtc": "2024-01-15T04:04:54.041594+00:00",
"duration": "00:00:03.3854385", "cancelationReason": null, "currentAttemptId":
1, "runId": "test_run", "parentRunId": null, "experimentId": "4d67b7d7-dc1c-4699-a53e-318ca24f1f72",
"status": "Completed", "startTimeUtc": "2024-01-15T03:51:57.3800585+00:00",
"endTimeUtc": "2024-01-15T03:52:00.765497+00:00", "scheduleId": null, "displayName":
"test_run", "name": null, "dataContainerId": "dcid.test_run", "description":
"test_description", "hidden": false, "runType": "azureml.promptflow.FlowRun",
"runTypeV2": {"orchestrator": null, "traits": [], "attribution": "PromptFlow",
"computeType": null}, "properties": {"azureml.promptflow.runtime_name": "automatic",
"azureml.promptflow.runtime_version": "20240111.v2", "azureml.promptflow.definition_file_name":
"flow.dag.yaml", "azureml.promptflow.session_id": "96c35660d759b526cb14cf69bbb56fcaa90c05a778b147b4",
"azureml.promptflow.flow_lineage_id": "fcb01d4faf8f2137f9d142cc1f3f22ecdf3d485e1435c4c971ff0ee09077f1b5",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/52675845d616ad8b41db77e9ba9e9d4a/print_input_flow/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/80d5ca5a93c8c6ea7c2fcdf1cd4b9d07/print_input_flow.jsonl",
"_azureml.evaluation_run": "promptflow.BatchRun", "azureml.promptflow.snapshot_id":
"a18c2edd-59e6-4b07-a264-b0a97a213218", "azureml.promptflow.total_tokens":
"0", "_azureml.evaluate_artifacts": "[{\"path\": \"instance_results.jsonl\",
\"type\": \"table\"}]"}, "parameters": {}, "actionUris": {}, "scriptName":
null, "target": null, "uniqueChildRunComputeTargets": [], "tags": {"key1":
"value1"}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": {"debug_info": {"assetId":
"azureml://locations/eastus2euap/workspaces/00000/data/azureml_test_run_output_data_debug_info/versions/1",
"type": "UriFolder"}, "flow_outputs": {"assetId": "azureml://locations/eastus2euap/workspaces/00000/data/azureml_test_run_output_data_flow_outputs/versions/1",
"type": "UriFolder"}}}, "runDefinition": null, "jobSpecification": null, "systemSettings":
null}'
headers:
connection:
- keep-alive
content-length:
- '4332'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.033'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_run_without_dump.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.018'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.098'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.081'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.164'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:47:34 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/webClassification1.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '127'
content-md5:
- i/8q1x5YKzHv3Fd/R8lYUQ==
content-type:
- application/octet-stream
last-modified:
- Fri, 28 Jul 2023 12:34:52 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Fri, 28 Jul 2023 12:34:52 GMT
x-ms-meta-name:
- 13fa99dd-c98e-4f2a-a704-4295d4ed6f68
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 0367c5c6-9f53-4a75-8623-7e53699f0d0b
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:47:35 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/webClassification1.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.075'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.080'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:47:37 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/web_classification/classify_with_llm.jinja2
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '853'
content-md5:
- ylTeNqjvuOvtzEZJ/X5n3A==
content-type:
- application/octet-stream
last-modified:
- Fri, 12 Jan 2024 08:13:57 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Fri, 12 Jan 2024 08:13:56 GMT
x-ms-meta-name:
- 950201e8-c52c-4b15-ada1-5e58de9b2f4d
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:47:38 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/web_classification/classify_with_llm.jinja2
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/web_classification/flow.dag.yaml",
"runId": "name", "runDisplayName": "name", "runExperimentName": "", "nodeVariant":
"${summarize_text_content.variant_0}", "batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/webClassification1.jsonl"},
"inputsMapping": {"url": "${data.url}"}, "connections": {}, "environmentVariables":
{}, "runtimeName": "fake-runtime-name", "sessionId": "000000000000000000000000000000000000000000000000",
"sessionSetupMode": "SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '873'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '12.752'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "fetch_text_content_from_url", "type":
"python", "source": {"type": "code", "path": "fetch_text_content_from_url.py"},
"inputs": {"fetch_url": "${inputs.url}"}, "tool": "fetch_text_content_from_url.py",
"reduce": false}, {"name": "prepare_examples", "type": "python", "source":
{"type": "code", "path": "prepare_examples.py"}, "inputs": {}, "tool": "prepare_examples.py",
"reduce": false}, {"name": "classify_with_llm", "type": "llm", "source": {"type":
"code", "path": "classify_with_llm.jinja2"}, "inputs": {"deployment_name":
"gpt-35-turbo", "suffix": "", "max_tokens": "128", "temperature": "0.1", "top_p":
"1.0", "logprobs": "", "echo": "False", "stop": "", "presence_penalty": "0",
"frequency_penalty": "0", "best_of": "1", "logit_bias": "", "url": "${inputs.url}",
"examples": "${prepare_examples.output}", "text_content": "${summarize_text_content.output}"},
"tool": "classify_with_llm.jinja2", "reduce": false, "api": "chat", "provider":
"AzureOpenAI", "connection": "azure_open_ai_connection", "module": "promptflow.tools.aoai"},
{"name": "convert_to_dict", "type": "python", "source": {"type": "code", "path":
"convert_to_dict.py"}, "inputs": {"input_str": "${classify_with_llm.output}"},
"tool": "convert_to_dict.py", "reduce": false}, {"name": "summarize_text_content",
"type": "llm", "source": {"type": "code", "path": "summarize_text_content.jinja2"},
"inputs": {"deployment_name": "gpt-35-turbo", "suffix": "", "max_tokens":
"128", "temperature": "0.2", "top_p": "1.0", "logprobs": "", "echo": "False",
"stop": "", "presence_penalty": "0", "frequency_penalty": "0", "best_of":
"1", "logit_bias": "", "text": "${fetch_text_content_from_url.output}"}, "tool":
"summarize_text_content.jinja2", "reduce": false, "api": "chat", "provider":
"AzureOpenAI", "connection": "azure_open_ai_connection", "module": "promptflow.tools.aoai"}],
"tools": [{"name": "Content Safety (Text Analyze)", "type": "python", "inputs":
{"connection": {"type": ["AzureContentSafetyConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "hate_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "self_harm_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "sexual_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "text": {"type":
["string"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "violence_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"}},
"description": "Use Azure Content Safety to detect harmful content.", "module":
"promptflow.tools.azure_content_safety", "function": "analyze_text", "is_builtin":
true, "package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "classify_with_llm.jinja2", "type":
"prompt", "inputs": {"examples": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "text_content":
{"type": ["string"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "url": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "classify_with_llm.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}, {"name":
"convert_to_dict.py", "type": "python", "inputs": {"input_str": {"type": ["string"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"}},
"source": "convert_to_dict.py", "function": "convert_to_dict", "is_builtin":
false, "enable_kwargs": false, "tool_state": "stable"}, {"name": "fetch_text_content_from_url.py",
"type": "python", "inputs": {"fetch_url": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "fetch_text_content_from_url.py",
"function": "fetch_text_content_from_url", "is_builtin": false, "enable_kwargs":
false, "tool_state": "stable"}, {"name": "prepare_examples.py", "type": "python",
"source": "prepare_examples.py", "function": "prepare_examples", "is_builtin":
false, "enable_kwargs": false, "tool_state": "stable"}, {"name": "summarize_text_content.jinja2",
"type": "prompt", "inputs": {"text": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "summarize_text_content.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}, {"name":
"summarize_text_content__variant_1.jinja2", "type": "prompt", "inputs": {"text":
{"type": ["string"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "source": "summarize_text_content__variant_1.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"url": {"type": "string", "default": "https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h",
"is_chat_input": false}}, "outputs": {"category": {"type": "string", "reference":
"${convert_to_dict.output.category}", "evaluation_only": false, "is_chat_output":
false}, "evidence": {"type": "string", "reference": "${convert_to_dict.output.evidence}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name", "flowRunId":
"name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/107bd3498e44deb2dccc53d2208d32b2/webClassification1.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"url": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "b235c474-d764-454f-a8da-63b47303ce80",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '16239'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.498'
status:
code: 200
message: OK
- request:
body: '{"runId": "name", "selectRunMetadata": true, "selectRunDefinition": true,
"selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705049270, "rootRunId": "name", "createdUtc":
"2024-01-12T08:47:50.4752183+00:00", "createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": null, "warnings": null, "revision": 3,
"statusRevision": 1, "runUuid": "54649bc5-afa2-485d-8a4b-1a2296754d78", "parentRunUuid":
null, "rootRunUuid": "54649bc5-afa2-485d-8a4b-1a2296754d78", "lastStartTimeUtc":
null, "currentComputeTime": "00:00:00", "computeDuration": null, "effectiveStartTimeUtc":
null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:47:55.0106055+00:00", "duration":
null, "cancelationReason": null, "currentAttemptId": 1, "runId": "name", "parentRunId":
null, "experimentId": "d30efbeb-f81d-4cfa-b5cc-a0570a049009", "status": "Preparing",
"startTimeUtc": null, "endTimeUtc": null, "scheduleId": null, "displayName":
"name", "name": null, "dataContainerId": "dcid.name", "description": null,
"hidden": false, "runType": "azureml.promptflow.FlowRun", "runTypeV2": {"orchestrator":
null, "traits": [], "attribution": "PromptFlow", "computeType": "AmlcDsi"},
"properties": {"azureml.promptflow.runtime_name": "test-runtime-ci", "azureml.promptflow.runtime_version":
"20231204.v4", "azureml.promptflow.definition_file_name": "flow.dag.yaml",
"azureml.promptflow.session_id": "4dd8f4d5f44dfeb817d3438cf84bd739215d87afd9458597",
"azureml.promptflow.flow_lineage_id": "af1a6951de9be2ce13d3b58b23dbd8b6a0cd8fd4918ad9cb22b28fb8395fbcb0",
"azureml.promptflow.node_variant": "${summarize_text_content.variant_0}",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/a1fa6ef1ead7ff3ce76b36250f6f5461/web_classification/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/107bd3498e44deb2dccc53d2208d32b2/webClassification1.jsonl",
"azureml.promptflow.inputs_mapping": "{\"url\":\"${data.url}\"}", "_azureml.evaluation_run":
"promptflow.BatchRun", "azureml.promptflow.snapshot_id": "b235c474-d764-454f-a8da-63b47303ce80"},
"parameters": {}, "actionUris": {}, "scriptName": null, "target": null, "uniqueChildRunComputeTargets":
[], "tags": {}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": null}, "runDefinition":
null, "jobSpecification": null, "systemSettings": null}'
headers:
connection:
- keep-alive
content-length:
- '4011'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.051'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_connection_operations_TestConnectionOperations_test_get_connection.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/api-version=2023-08-01-preview
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.023'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?api-version=2023-04-01-preview&count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.058'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/Connections/azure_open_ai_connection
response:
body:
string: '{"connectionName": "azure_open_ai_connection", "connectionType": "AzureOpenAI",
"configs": {"api_base": "https://fake.openai.azure.com", "api_key": null,
"api_type": "azure", "api_version": "2023-07-01-preview", "resource_id": null},
"owner": {"userName": "[email protected]"}, "createdDate": "2023-08-22T10:15:34.5762053Z",
"lastModifiedDate": "2023-08-22T10:15:34.5762053Z"}'
headers:
connection:
- keep-alive
content-length:
- '366'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.382'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/Connections/custom_connection
response:
body:
string: '{"connectionName": "custom_connection", "connectionType": "Custom",
"owner": {"userName": "[email protected]"}, "createdDate": "2023-06-19T20:56:12.0353964Z",
"lastModifiedDate": "2023-06-19T20:56:12.0353964Z"}'
headers:
connection:
- keep-alive
content-length:
- '204'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '0.367'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_arm_connection_operations_TestArmConnectionOperations_test_get_connection.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/api-version=2023-08-01-preview
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.017'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?api-version=2023-04-01-preview&count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.070'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/connections/azure_open_ai_connection/listsecrets?api-version=2023-04-01-preview
response:
body:
string: '{"tags": null, "location": null, "id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/connections/azure_open_ai_connection",
"name": "azure_open_ai_connection", "type": "Microsoft.MachineLearningServices/workspaces/connections",
"properties": {"authType": "ApiKey", "credentials": {"key": "_"}, "group":
"AzureAI", "category": "AzureOpenAI", "expiryTime": null, "target": "_", "createdByWorkspaceArmId":
null, "isSharedToAll": false, "sharedUserList": [], "metadata": {"azureml.flow.connection_type":
"AzureOpenAI", "azureml.flow.module": "promptflow.connections", "ApiType":
"azure", "ApiVersion": "2023-07-01-preview", "ResourceId": null, "DeploymentApiVersion":
"2023-10-01-preview"}}, "systemData": {"createdAt": "2023-08-22T10:15:34.5762053Z",
"createdBy": "[email protected]", "createdByType": "User", "lastModifiedAt":
"2023-08-22T10:15:34.5762053Z", "lastModifiedBy": "[email protected]",
"lastModifiedByType": "User"}}'
headers:
cache-control:
- no-cache
content-length:
- '1246'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.072'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/connections/custom_connection/listsecrets?api-version=2023-04-01-preview
response:
body:
string: '{"tags": null, "location": null, "id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/connections/custom_connection",
"name": "custom_connection", "type": "Microsoft.MachineLearningServices/workspaces/connections",
"properties": {"authType": "CustomKeys", "credentials": {"keys": {}}, "group":
"AzureAI", "category": "CustomKeys", "expiryTime": null, "target": "_", "createdByWorkspaceArmId":
null, "isSharedToAll": false, "sharedUserList": [], "metadata": {"azureml.flow.connection_type":
"Custom", "azureml.flow.module": "promptflow.connections"}}, "systemData":
{"createdAt": "2023-06-19T20:56:12.0353964Z", "createdBy": "[email protected]",
"createdByType": "User", "lastModifiedAt": "2023-06-19T20:56:12.0353964Z",
"lastModifiedBy": "[email protected]", "lastModifiedByType": "User"}}'
headers:
cache-control:
- no-cache
content-length:
- '1275'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.075'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_run_bulk.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.027'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.214'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.066'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.192'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:39:26 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/webClassification1.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '127'
content-md5:
- i/8q1x5YKzHv3Fd/R8lYUQ==
content-type:
- application/octet-stream
last-modified:
- Fri, 28 Jul 2023 12:34:52 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Fri, 28 Jul 2023 12:34:52 GMT
x-ms-meta-name:
- 13fa99dd-c98e-4f2a-a704-4295d4ed6f68
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 0367c5c6-9f53-4a75-8623-7e53699f0d0b
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:39:27 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/webClassification1.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.093'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.081'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:39:31 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/web_classification/classify_with_llm.jinja2
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '853'
content-md5:
- ylTeNqjvuOvtzEZJ/X5n3A==
content-type:
- application/octet-stream
last-modified:
- Fri, 12 Jan 2024 08:13:57 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Fri, 12 Jan 2024 08:13:56 GMT
x-ms-meta-name:
- 950201e8-c52c-4b15-ada1-5e58de9b2f4d
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:39:32 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/web_classification/classify_with_llm.jinja2
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/web_classification/flow.dag.yaml",
"runId": "name", "runDisplayName": "name", "runExperimentName": "", "nodeVariant":
"${summarize_text_content.variant_0}", "batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/webClassification1.jsonl"},
"inputsMapping": {"url": "${data.url}"}, "connections": {}, "environmentVariables":
{}, "runtimeName": "fake-runtime-name", "sessionId": "000000000000000000000000000000000000000000000000",
"sessionSetupMode": "SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '873'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '6.880'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "fetch_text_content_from_url", "type":
"python", "source": {"type": "code", "path": "fetch_text_content_from_url.py"},
"inputs": {"fetch_url": "${inputs.url}"}, "tool": "fetch_text_content_from_url.py",
"reduce": false}, {"name": "prepare_examples", "type": "python", "source":
{"type": "code", "path": "prepare_examples.py"}, "inputs": {}, "tool": "prepare_examples.py",
"reduce": false}, {"name": "classify_with_llm", "type": "llm", "source": {"type":
"code", "path": "classify_with_llm.jinja2"}, "inputs": {"deployment_name":
"gpt-35-turbo", "suffix": "", "max_tokens": "128", "temperature": "0.1", "top_p":
"1.0", "logprobs": "", "echo": "False", "stop": "", "presence_penalty": "0",
"frequency_penalty": "0", "best_of": "1", "logit_bias": "", "url": "${inputs.url}",
"examples": "${prepare_examples.output}", "text_content": "${summarize_text_content.output}"},
"tool": "classify_with_llm.jinja2", "reduce": false, "api": "chat", "provider":
"AzureOpenAI", "connection": "azure_open_ai_connection", "module": "promptflow.tools.aoai"},
{"name": "convert_to_dict", "type": "python", "source": {"type": "code", "path":
"convert_to_dict.py"}, "inputs": {"input_str": "${classify_with_llm.output}"},
"tool": "convert_to_dict.py", "reduce": false}, {"name": "summarize_text_content",
"type": "llm", "source": {"type": "code", "path": "summarize_text_content.jinja2"},
"inputs": {"deployment_name": "gpt-35-turbo", "suffix": "", "max_tokens":
"128", "temperature": "0.2", "top_p": "1.0", "logprobs": "", "echo": "False",
"stop": "", "presence_penalty": "0", "frequency_penalty": "0", "best_of":
"1", "logit_bias": "", "text": "${fetch_text_content_from_url.output}"}, "tool":
"summarize_text_content.jinja2", "reduce": false, "api": "chat", "provider":
"AzureOpenAI", "connection": "azure_open_ai_connection", "module": "promptflow.tools.aoai"}],
"tools": [{"name": "Content Safety (Text Analyze)", "type": "python", "inputs":
{"connection": {"type": ["AzureContentSafetyConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "hate_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "self_harm_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "sexual_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "text": {"type":
["string"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "violence_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"}},
"description": "Use Azure Content Safety to detect harmful content.", "module":
"promptflow.tools.azure_content_safety", "function": "analyze_text", "is_builtin":
true, "package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAACgElEQVR4nGWSz2vcVRTFP/e9NzOZ1KDGohASslLEH6VLV0ak4l/QpeDCrfQPcNGliODKnVm4EBdBsIjQIlhciKW0ycKFVCSNbYnjdDLtmPnmO/nO9917XcxMkjYX3uLx7nnn3HOuMK2Nix4fP78ZdrYXVkLVWjf3l3B1B+HpcjzGFtmqa6cePz7/x0dnn1n5qhj3iBJPYREIURAJuCtpY8PjReDbrf9WG7H1fuefwQU9qKztTcMJT+PNnEFvjGVDBDlSsH6p/9MLzy6+NxwVqI8RAg4IPmWedMckdLYP6O6UpIaQfvyyXG012+e79/ZfHukoS1ISMT2hGTB1RkUmNgQ5QZ0w+a2VWDq73MbdEWmfnnv6UWe7oNzPaLapl5CwuLTXK9WUGBuCjqekzhP+z52ZXOrKMD3OJg0Hh778aiOuvpnYvp05d6GJO4iAO4QAe/eV36/X5LFRV4Zmn+AdkqlL8Vjp3oVioOz+WTPzzYEgsN+fgPLYyJVheSbPPVl2ikeGZRjtG52/8rHuaV9VOlpP2OtKyVndcRVCSqOhsvxa4vW359i6OuKdD+aP8Q4SYPdOzS/flGjt1JUSaMqZ5nwa1Y8qWb/Ud/eZZkHisYezEM0m+fcelDr8F1SqW2LNK6r1jXQwyLzy1hxvrLXZulry7ocL+FS6G4QIu3fG/Px1gdYeW7LIgXU2P/115TOA5G7e3Rmj2aS/m7l5pThiZzrCcE/d1XHzbln373nw7y6veeoUm5KCNKT/IPPwbiY1hYd/l5MIT65BMFt87sU4v9D7/JMflr44uV6hGh1+L4RCkg6z5iK2tAhNLeLsNGwYA4fDYnC/drvuuFxe86NV/x+Ut27g0FvykgAAAABJRU5ErkJggg==",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "classify_with_llm.jinja2", "type":
"prompt", "inputs": {"examples": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "text_content":
{"type": ["string"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "url": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "classify_with_llm.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}, {"name":
"convert_to_dict.py", "type": "python", "inputs": {"input_str": {"type": ["string"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"}},
"source": "convert_to_dict.py", "function": "convert_to_dict", "is_builtin":
false, "enable_kwargs": false, "tool_state": "stable"}, {"name": "fetch_text_content_from_url.py",
"type": "python", "inputs": {"fetch_url": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "fetch_text_content_from_url.py",
"function": "fetch_text_content_from_url", "is_builtin": false, "enable_kwargs":
false, "tool_state": "stable"}, {"name": "prepare_examples.py", "type": "python",
"source": "prepare_examples.py", "function": "prepare_examples", "is_builtin":
false, "enable_kwargs": false, "tool_state": "stable"}, {"name": "summarize_text_content.jinja2",
"type": "prompt", "inputs": {"text": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "summarize_text_content.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}, {"name":
"summarize_text_content__variant_1.jinja2", "type": "prompt", "inputs": {"text":
{"type": ["string"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "source": "summarize_text_content__variant_1.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"url": {"type": "string", "default": "https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h",
"is_chat_input": false}}, "outputs": {"category": {"type": "string", "reference":
"${convert_to_dict.output.category}", "evaluation_only": false, "is_chat_output":
false}, "evidence": {"type": "string", "reference": "${convert_to_dict.output.evidence}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name", "flowRunId":
"name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/107bd3498e44deb2dccc53d2208d32b2/webClassification1.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"url": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "f8f59233-47fa-48df-a9e1-fc6866b7597e",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '16239'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.210'
status:
code: 200
message: OK
- request:
body: '{"runId": "name", "selectRunMetadata": true, "selectRunDefinition": true,
"selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705048778, "rootRunId": "name", "createdUtc":
"2024-01-12T08:39:38.859607+00:00", "createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": null, "warnings": null, "revision": 3,
"statusRevision": 1, "runUuid": "ead544d1-f5d3-4eb1-b931-ab04cd0e1b39", "parentRunUuid":
null, "rootRunUuid": "ead544d1-f5d3-4eb1-b931-ab04cd0e1b39", "lastStartTimeUtc":
null, "currentComputeTime": "00:00:00", "computeDuration": null, "effectiveStartTimeUtc":
null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:39:43.2026482+00:00", "duration":
null, "cancelationReason": null, "currentAttemptId": 1, "runId": "name", "parentRunId":
null, "experimentId": "d30efbeb-f81d-4cfa-b5cc-a0570a049009", "status": "Preparing",
"startTimeUtc": null, "endTimeUtc": null, "scheduleId": null, "displayName":
"name", "name": null, "dataContainerId": "dcid.name", "description": null,
"hidden": false, "runType": "azureml.promptflow.FlowRun", "runTypeV2": {"orchestrator":
null, "traits": [], "attribution": "PromptFlow", "computeType": "AmlcDsi"},
"properties": {"azureml.promptflow.runtime_name": "test-runtime-ci", "azureml.promptflow.runtime_version":
"20231204.v4", "azureml.promptflow.definition_file_name": "flow.dag.yaml",
"azureml.promptflow.session_id": "4dd8f4d5f44dfeb817d3438cf84bd739215d87afd9458597",
"azureml.promptflow.flow_lineage_id": "af1a6951de9be2ce13d3b58b23dbd8b6a0cd8fd4918ad9cb22b28fb8395fbcb0",
"azureml.promptflow.node_variant": "${summarize_text_content.variant_0}",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/a1fa6ef1ead7ff3ce76b36250f6f5461/web_classification/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/107bd3498e44deb2dccc53d2208d32b2/webClassification1.jsonl",
"azureml.promptflow.inputs_mapping": "{\"url\":\"${data.url}\"}", "_azureml.evaluation_run":
"promptflow.BatchRun", "azureml.promptflow.snapshot_id": "f8f59233-47fa-48df-a9e1-fc6866b7597e"},
"parameters": {}, "actionUris": {}, "scriptName": null, "target": null, "uniqueChildRunComputeTargets":
[], "tags": {}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": null}, "runDefinition":
null, "jobSpecification": null, "systemSettings": null}'
headers:
connection:
- keep-alive
content-length:
- '4010'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.037'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_run_display_name_with_macro.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.020'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.088'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.108'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.101'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:25:13 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '49'
content-md5:
- quXiEreYvPinSj0HsaNa/g==
content-type:
- application/octet-stream
last-modified:
- Wed, 08 Nov 2023 04:26:09 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Wed, 08 Nov 2023 04:26:09 GMT
x-ms-meta-name:
- c4092674-5e53-4c17-b78d-75353ae0edb6
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 579021dc-8ac8-4c73-8110-4642bd00c69b
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:25:14 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.121'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.101'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:25:18 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '245'
content-md5:
- F+JA0a3CxcLYZ0ANRdlZbA==
content-type:
- application/octet-stream
last-modified:
- Wed, 29 Nov 2023 02:51:35 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Thu, 17 Aug 2023 10:30:09 GMT
x-ms-meta-name:
- 56efdd28-6297-4baa-aad3-be46f4b768a2
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:25:19 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/print_env_var/flow.dag.yaml",
"runId": "name", "runDisplayName": "my_display_name_${variant_id}_${timestamp}",
"runExperimentName": "", "batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/env_var_names.jsonl"},
"inputsMapping": {}, "connections": {}, "environmentVariables": {"API_BASE":
"${azure_open_ai_connection.api_base}"}, "runtimeName": "fake-runtime-name",
"sessionId": "000000000000000000000000000000000000000000000000", "sessionSetupMode":
"SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '840'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '7.626'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAACgElEQVR4nGWSz2vcVRTFP/e9NzOZ1KDGohASslLEH6VLV0ak4l/QpeDCrfQPcNGliODKnVm4EBdBsIjQIlhciKW0ycKFVCSNbYnjdDLtmPnmO/nO9917XcxMkjYX3uLx7nnn3HOuMK2Nix4fP78ZdrYXVkLVWjf3l3B1B+HpcjzGFtmqa6cePz7/x0dnn1n5qhj3iBJPYREIURAJuCtpY8PjReDbrf9WG7H1fuefwQU9qKztTcMJT+PNnEFvjGVDBDlSsH6p/9MLzy6+NxwVqI8RAg4IPmWedMckdLYP6O6UpIaQfvyyXG012+e79/ZfHukoS1ISMT2hGTB1RkUmNgQ5QZ0w+a2VWDq73MbdEWmfnnv6UWe7oNzPaLapl5CwuLTXK9WUGBuCjqekzhP+z52ZXOrKMD3OJg0Hh778aiOuvpnYvp05d6GJO4iAO4QAe/eV36/X5LFRV4Zmn+AdkqlL8Vjp3oVioOz+WTPzzYEgsN+fgPLYyJVheSbPPVl2ikeGZRjtG52/8rHuaV9VOlpP2OtKyVndcRVCSqOhsvxa4vW359i6OuKdD+aP8Q4SYPdOzS/flGjt1JUSaMqZ5nwa1Y8qWb/Ud/eZZkHisYezEM0m+fcelDr8F1SqW2LNK6r1jXQwyLzy1hxvrLXZulry7ocL+FS6G4QIu3fG/Px1gdYeW7LIgXU2P/115TOA5G7e3Rmj2aS/m7l5pThiZzrCcE/d1XHzbln373nw7y6veeoUm5KCNKT/IPPwbiY1hYd/l5MIT65BMFt87sU4v9D7/JMflr44uV6hGh1+L4RCkg6z5iK2tAhNLeLsNGwYA4fDYnC/drvuuFxe86NV/x+Ut27g0FvykgAAAABJRU5ErkJggg==",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "my_display_name_variant_0_202401120825",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/c32a61842e439cecc022ebcff5dc0da4/env_var_names.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "7c640c9a-e7b9-4746-b306-8b2711e9d569",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12857'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.400'
status:
code: 200
message: OK
- request:
body: '{"runId": "name", "selectRunMetadata": true, "selectRunDefinition": true,
"selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705047926, "rootRunId": "name", "createdUtc":
"2024-01-12T08:25:26.2141242+00:00", "createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": null, "warnings": null, "revision": 3,
"statusRevision": 1, "runUuid": "98d3a750-0801-45c0-9002-d6c5f419a252", "parentRunUuid":
null, "rootRunUuid": "98d3a750-0801-45c0-9002-d6c5f419a252", "lastStartTimeUtc":
null, "currentComputeTime": "00:00:00", "computeDuration": null, "effectiveStartTimeUtc":
null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:25:30.0060955+00:00", "duration":
null, "cancelationReason": null, "currentAttemptId": 1, "runId": "name", "parentRunId":
null, "experimentId": "6a87c3ae-5a75-4c5d-9eb9-5203b0062282", "status": "Preparing",
"startTimeUtc": null, "endTimeUtc": null, "scheduleId": null, "displayName":
"my_display_name_variant_0_202401120825", "name": null, "dataContainerId":
"dcid.name", "description": null, "hidden": false, "runType": "azureml.promptflow.FlowRun",
"runTypeV2": {"orchestrator": null, "traits": [], "attribution": "PromptFlow",
"computeType": "AmlcDsi"}, "properties": {"azureml.promptflow.runtime_name":
"test-runtime-ci", "azureml.promptflow.runtime_version": "20231204.v4", "azureml.promptflow.definition_file_name":
"flow.dag.yaml", "azureml.promptflow.session_id": "62adccc385dd5d078797bdd0d2e1c55e120f3d5216885b81",
"azureml.promptflow.flow_lineage_id": "f1efdb93dcf9b3c17e246e7bcf0e2c7398d7bc289f8dd2c3d8f808eacc63c31f",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/3360ae705933fb90bcd290241ca0ece9/print_env_var/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/c32a61842e439cecc022ebcff5dc0da4/env_var_names.jsonl",
"_azureml.evaluation_run": "promptflow.BatchRun", "azureml.promptflow.snapshot_id":
"7c640c9a-e7b9-4746-b306-8b2711e9d569"}, "parameters": {}, "actionUris": {},
"scriptName": null, "target": null, "uniqueChildRunComputeTargets": [], "tags":
{}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": null}, "runDefinition":
null, "jobSpecification": null, "systemSettings": null}'
headers:
connection:
- keep-alive
content-length:
- '3851'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.044'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_cli_with_azure_TestCliWithAzure_test_cli_telemetry.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.073'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.089'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:30:17 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '49'
content-md5:
- quXiEreYvPinSj0HsaNa/g==
content-type:
- application/octet-stream
last-modified:
- Wed, 08 Nov 2023 04:26:09 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Wed, 08 Nov 2023 04:26:09 GMT
x-ms-meta-name:
- c4092674-5e53-4c17-b78d-75353ae0edb6
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 579021dc-8ac8-4c73-8110-4642bd00c69b
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:30:19 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.069'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.088'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:30:21 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '245'
content-md5:
- F+JA0a3CxcLYZ0ANRdlZbA==
content-type:
- application/octet-stream
last-modified:
- Wed, 29 Nov 2023 02:51:35 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Thu, 17 Aug 2023 10:30:09 GMT
x-ms-meta-name:
- 56efdd28-6297-4baa-aad3-be46f4b768a2
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:30:22 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '[{"iKey": "8b52b368-4c91-4226-b7f7-be52822f0509", "tags": {"ai.cloud.role":
"pfazure", "ai.device.locale": "en_US", "ai.device.osVersion": "10.0.22631",
"ai.device.type": "Other", "ai.internal.sdkVersion": "py3.10.13:oc0.11.2:ext1.1.9",
"ai.operation.id": "00000000000000000000000000000000", "ai.operation.parentId":
"|00000000000000000000000000000000.0000000000000000."}, "time": "2024-01-12T08:30:14.771082Z",
"name": "Microsoft.ApplicationInsights.Event", "data": {"baseData": {"name":
"pfazure.run.create.start", "properties": {"request_id": "79d30574-8153-43d8-bdec-2d1f3c9e436b",
"first_call": true, "activity_name": "pfazure.run.create", "activity_type":
"PublicApi", "user_agent": "promptflow-sdk/0.0.1 promptflow-cli/0.0.1", "subscription_id":
"96aede12-2f73-41cb-b983-6d11a904839b", "resource_group_name": "promptflow",
"workspace_name": "promptflow-eastus", "level": "INFO", "from_ci": false, "python_version":
"3.10.13", "installation_id": "9d18c597-0a5c-4e8c-8ef5-d7e9c4aa82a3"}, "measurements":
{}, "ver": 2}, "baseType": "EventData"}}]'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '1050'
Content-Type:
- application/json; charset=utf-8
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://dc.services.visualstudio.com/v2.1/track
response:
body:
string: '{"itemsReceived": 1, "itemsAccepted": 0, "errors": [{"index": 0, "statusCode":
307, "message": "Ingestion is allowed only from stamp specific endpoint -
Location: https://eastus-8.in.applicationinsights.azure.com/v2.1/track"}]}'
headers:
cache-control:
- max-age=604800
content-length:
- '217'
content-type:
- application/json; charset=utf-8
location:
- https://eastus-8.in.applicationinsights.azure.com/v2.1/track
server:
- Microsoft-HTTPAPI/2.0
strict-transport-security:
- max-age=31536000
x-content-type-options:
- nosniff
status:
code: 307
message: Temporary Redirect
- request:
body: '[{"iKey": "8b52b368-4c91-4226-b7f7-be52822f0509", "tags": {"ai.cloud.role":
"pfazure", "ai.device.locale": "en_US", "ai.device.osVersion": "10.0.22631",
"ai.device.type": "Other", "ai.internal.sdkVersion": "py3.10.13:oc0.11.2:ext1.1.9",
"ai.operation.id": "00000000000000000000000000000000", "ai.operation.parentId":
"|00000000000000000000000000000000.0000000000000000."}, "time": "2024-01-12T08:30:14.771082Z",
"name": "Microsoft.ApplicationInsights.Event", "data": {"baseData": {"name":
"pfazure.run.create.start", "properties": {"request_id": "79d30574-8153-43d8-bdec-2d1f3c9e436b",
"first_call": true, "activity_name": "pfazure.run.create", "activity_type":
"PublicApi", "user_agent": "promptflow-sdk/0.0.1 promptflow-cli/0.0.1", "subscription_id":
"96aede12-2f73-41cb-b983-6d11a904839b", "resource_group_name": "promptflow",
"workspace_name": "promptflow-eastus", "level": "INFO", "from_ci": false, "python_version":
"3.10.13", "installation_id": "9d18c597-0a5c-4e8c-8ef5-d7e9c4aa82a3"}, "measurements":
{}, "ver": 2}, "baseType": "EventData"}}]'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '1050'
Content-Type:
- application/json; charset=utf-8
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus-8.in.applicationinsights.azure.com/v2.1/track
response:
body:
string: '{"itemsReceived": 1, "itemsAccepted": 1, "errors": []}'
headers:
content-length:
- '49'
content-type:
- application/json; charset=utf-8
server:
- Microsoft-HTTPAPI/2.0
strict-transport-security:
- max-age=31536000
x-content-type-options:
- nosniff
status:
code: 200
message: OK
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/print_env_var/flow.dag.yaml",
"runId": "name", "runDisplayName": "name", "runExperimentName": "", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/env_var_names.jsonl"},
"inputsMapping": {}, "connections": {}, "environmentVariables": {"API_BASE":
"${azure_open_ai_connection.api_base}"}, "runtimeName": "fake-runtime-name",
"sessionId": "000000000000000000000000000000000000000000000000", "sessionSetupMode":
"SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '834'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '6.733'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/c32a61842e439cecc022ebcff5dc0da4/env_var_names.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "457d8581-14b3-4b7c-8e9d-b545a00f572d",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.417'
status:
code: 200
message: OK
- request:
body: '{"runId": "name", "selectRunMetadata": true, "selectRunDefinition": true,
"selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705048228, "rootRunId": "name", "createdUtc":
"2024-01-12T08:30:28.5299765+00:00", "createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": null, "warnings": null, "revision": 3,
"statusRevision": 1, "runUuid": "e233a8cf-f6f9-413a-abb3-57f45e9163ea", "parentRunUuid":
null, "rootRunUuid": "e233a8cf-f6f9-413a-abb3-57f45e9163ea", "lastStartTimeUtc":
null, "currentComputeTime": "00:00:00", "computeDuration": null, "effectiveStartTimeUtc":
null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:30:33.0648112+00:00", "duration":
null, "cancelationReason": null, "currentAttemptId": 1, "runId": "name", "parentRunId":
null, "experimentId": "6a87c3ae-5a75-4c5d-9eb9-5203b0062282", "status": "Preparing",
"startTimeUtc": null, "endTimeUtc": null, "scheduleId": null, "displayName":
"name", "name": null, "dataContainerId": "dcid.name", "description": null,
"hidden": false, "runType": "azureml.promptflow.FlowRun", "runTypeV2": {"orchestrator":
null, "traits": [], "attribution": "PromptFlow", "computeType": "AmlcDsi"},
"properties": {"azureml.promptflow.runtime_name": "test-runtime-ci", "azureml.promptflow.runtime_version":
"20231204.v4", "azureml.promptflow.definition_file_name": "flow.dag.yaml",
"azureml.promptflow.session_id": "62adccc385dd5d078797bdd0d2e1c55e120f3d5216885b81",
"azureml.promptflow.flow_lineage_id": "f1efdb93dcf9b3c17e246e7bcf0e2c7398d7bc289f8dd2c3d8f808eacc63c31f",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/3360ae705933fb90bcd290241ca0ece9/print_env_var/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/c32a61842e439cecc022ebcff5dc0da4/env_var_names.jsonl",
"_azureml.evaluation_run": "promptflow.BatchRun", "azureml.promptflow.snapshot_id":
"457d8581-14b3-4b7c-8e9d-b545a00f572d"}, "parameters": {}, "actionUris": {},
"scriptName": null, "target": null, "uniqueChildRunComputeTargets": [], "tags":
{}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": null}, "runDefinition":
null, "jobSpecification": null, "systemSettings": null}'
headers:
connection:
- keep-alive
content-length:
- '3849'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.051'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_flow_operations_TestFlow_test_list_flows_invalid_cases.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.10.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3548'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.027'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.10.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.093'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_failed_run_to_dict_exclude.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.020'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.189'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.092'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.104'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:02:51 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/webClassification3.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '379'
content-md5:
- lI/pz9jzTQ7Td3RHPL7y7w==
content-type:
- application/octet-stream
last-modified:
- Mon, 06 Nov 2023 08:30:18 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Mon, 06 Nov 2023 08:30:18 GMT
x-ms-meta-name:
- 94331215-cf7f-452a-9f1a-1d276bc9b0e4
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 3f163752-edb0-4afc-a6f5-b0a670bd7c24
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:02:53 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/webClassification3.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.091'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.078'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:02:56 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/partial_fail/data.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '52'
content-md5:
- kHimciLnA7d3/I2LBUeLNA==
content-type:
- application/octet-stream
last-modified:
- Fri, 22 Sep 2023 09:37:31 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Fri, 22 Sep 2023 09:37:30 GMT
x-ms-meta-name:
- aa1844d8-4898-4daa-8100-6140558fc7c9
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:02:57 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/partial_fail/data.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/partial_fail/flow.dag.yaml",
"runId": "failed_run_name", "runDisplayName": "sdk-cli-test-fixture-failed-run",
"runExperimentName": "", "batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/webClassification3.jsonl"},
"inputsMapping": {}, "connections": {}, "environmentVariables": {}, "runtimeName":
"fake-runtime-name", "sessionId": "000000000000000000000000000000000000000000000000",
"sessionSetupMode": "SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '782'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"failed_run_name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '8.331'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/failed_run_name/flowRuns/failed_run_name",
"flowRunId": "failed_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-failed-run",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/failed_run_name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "5132ecba-405b-4fa2-85de-01c959708f2e",
"studioPortalEndpoint": "https://ml.azure.com/runs/failed_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.229'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/failed_run_name/flowRuns/failed_run_name",
"flowRunId": "failed_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-failed-run",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/failed_run_name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "5132ecba-405b-4fa2-85de-01c959708f2e",
"studioPortalEndpoint": "https://ml.azure.com/runs/failed_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.428'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/failed_run_name/flowRuns/failed_run_name",
"flowRunId": "failed_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-failed-run",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/failed_run_name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "5132ecba-405b-4fa2-85de-01c959708f2e",
"studioPortalEndpoint": "https://ml.azure.com/runs/failed_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.381'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/failed_run_name/flowRuns/failed_run_name",
"flowRunId": "failed_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-failed-run",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/failed_run_name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "5132ecba-405b-4fa2-85de-01c959708f2e",
"studioPortalEndpoint": "https://ml.azure.com/runs/failed_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.405'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/failed_run_name/flowRuns/failed_run_name",
"flowRunId": "failed_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-failed-run",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/failed_run_name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "5132ecba-405b-4fa2-85de-01c959708f2e",
"studioPortalEndpoint": "https://ml.azure.com/runs/failed_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.248'
status:
code: 200
message: OK
- request:
body: '{"runId": "failed_run_name", "selectRunMetadata": true, "selectRunDefinition":
true, "selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705046584, "rootRunId": "failed_run_name",
"createdUtc": "2024-01-12T08:03:04.1182041+00:00", "createdBy": {"userObjectId":
"00000000-0000-0000-0000-000000000000", "userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": {"error": {"code": "UserError", "severity":
null, "message": "The input for batch run is incorrect. Couldn''t find these
mapping relations: ${data.key}. Please make sure your input mapping keys and
values match your YAML input section and input data. For more information,
refer to the following documentation: https://aka.ms/pf/column-mapping", "messageFormat":
"The input for batch run is incorrect. Couldn''t find these mapping relations:
{invalid_relations}. Please make sure your input mapping keys and values match
your YAML input section and input data. For more information, refer to the
following documentation: https://aka.ms/pf/column-mapping", "messageParameters":
{"invalid_relations": "${data.key}"}, "referenceCode": "Executor", "detailsUri":
null, "target": null, "details": [], "innerError": {"code": "ValidationError",
"innerError": {"code": "InputMappingError", "innerError": null}}, "debugInfo":
{"type": "InputMappingError", "message": "The input for batch run is incorrect.
Couldn''t find these mapping relations: ${data.key}. Please make sure your
input mapping keys and values match your YAML input section and input data.
For more information, refer to the following documentation: https://aka.ms/pf/column-mapping",
"stackTrace": "Traceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/runtime/runtime.py\",
line 671, in execute_bulk_run_request\n batch_engine.run(\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\",
line 147, in run\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\",
line 132, in run\n batch_inputs = batch_input_processor.process_batch_inputs(input_dirs,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 41, in process_batch_inputs\n return self._validate_and_apply_inputs_mapping(input_dicts,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 91, in _validate_and_apply_inputs_mapping\n resolved_inputs = self._apply_inputs_mapping_for_all_lines(inputs,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 163, in _apply_inputs_mapping_for_all_lines\n result = [apply_inputs_mapping(item,
inputs_mapping) for item in merged_list]\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 163, in <listcomp>\n result = [apply_inputs_mapping(item, inputs_mapping)
for item in merged_list]\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 292, in apply_inputs_mapping\n raise InputMappingError(\n", "innerException":
null, "data": null, "errorResponse": null}, "additionalInfo": null}, "correlation":
null, "environment": null, "location": null, "time": "2024-01-12T08:03:23.917435+00:00",
"componentName": "promptflow-runtime/20231204.v4 Designer/1.0 promptflow-sdk/0.0.1
azsdk-python-azuremachinelearningdesignerserviceclient/unknown Python/3.10.13
(Windows-10-10.0.22631-SP0) promptflow/1.2.0rc1"}, "warnings": null, "revision":
7, "statusRevision": 3, "runUuid": "d70fd62f-58da-4194-9181-8f598c163252",
"parentRunUuid": null, "rootRunUuid": "d70fd62f-58da-4194-9181-8f598c163252",
"lastStartTimeUtc": null, "currentComputeTime": null, "computeDuration": "00:00:01.9157474",
"effectiveStartTimeUtc": null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "18a66f5f-dbdf-4c17-9dd7-1634712a9cbe",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:03:23.3386801+00:00", "duration":
"00:00:01.9157474", "cancelationReason": null, "currentAttemptId": 1, "runId":
"failed_run_name", "parentRunId": null, "experimentId": "1848033e-509f-4c52-92ee-f0a0121fe99e",
"status": "Failed", "startTimeUtc": "2024-01-12T08:03:22.2208565+00:00", "endTimeUtc":
"2024-01-12T08:03:24.1366039+00:00", "scheduleId": null, "displayName": "sdk-cli-test-fixture-failed-run",
"name": null, "dataContainerId": "dcid.failed_run_name", "description": null,
"hidden": false, "runType": "azureml.promptflow.FlowRun", "runTypeV2": {"orchestrator":
null, "traits": [], "attribution": "PromptFlow", "computeType": "AmlcDsi"},
"properties": {"azureml.promptflow.runtime_name": "test-runtime-ci", "azureml.promptflow.runtime_version":
"20231204.v4", "azureml.promptflow.definition_file_name": "flow.dag.yaml",
"azureml.promptflow.session_id": "31858a8dfc61a642bb0ab6df4fc3ac7b3807de4ffead00d1",
"azureml.promptflow.flow_lineage_id": "de293df4f50622090c0225852d59cd663b6b629e38728f7444fa0f12255a0647",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/bc20fa079592a8072922533f187e3184/partial_fail/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl",
"_azureml.evaluation_run": "promptflow.BatchRun", "azureml.promptflow.snapshot_id":
"5132ecba-405b-4fa2-85de-01c959708f2e", "azureml.promptflow.total_tokens":
"0", "_azureml.evaluate_artifacts": "[{\"path\": \"instance_results.jsonl\",
\"type\": \"table\"}]"}, "parameters": {}, "actionUris": {}, "scriptName":
null, "target": null, "uniqueChildRunComputeTargets": [], "tags": {}, "settings":
{}, "services": {}, "inputDatasets": [], "outputDatasets": [], "runDefinition":
null, "jobSpecification": null, "primaryMetricName": null, "createdFrom":
null, "cancelUri": null, "completeUri": null, "diagnosticsUri": null, "computeRequest":
null, "compute": null, "retainForLifetimeOfWorkspace": false, "queueingInfo":
null, "inputs": null, "outputs": {"debug_info": {"assetId": "azureml://locations/eastus/workspaces/00000/data/azureml_failed_run_name_output_data_debug_info/versions/1",
"type": "UriFolder"}}}, "runDefinition": null, "jobSpecification": null, "systemSettings":
null}'
headers:
connection:
- keep-alive
content-length:
- '7988'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.061'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name/logContent
response:
body:
string: '"2024-01-12 08:03:09 +0000 49 promptflow-runtime INFO [failed_run_name]
Receiving v2 bulk run request 4babbe77-fec5-48ec-9949-b3bb23717de0: {\"flow_id\":
\"failed_run_name\", \"flow_run_id\": \"failed_run_name\", \"flow_source\":
{\"flow_source_type\": 1, \"flow_source_info\": {\"snapshot_id\": \"5132ecba-405b-4fa2-85de-01c959708f2e\"},
\"flow_dag_file\": \"flow.dag.yaml\"}, \"log_path\": \"https://promptfloweast4063704120.blob.core.windows.net/azureml/ExperimentRun/dcid.failed_run_name/logs/azureml/executionlogs.txt?sv=2019-07-07&sr=b&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T07%3A53%3A03Z&ske=2024-01-13T16%3A03%3A03Z&sks=b&skv=2019-07-07&st=2024-01-12T07%3A53%3A08Z&se=2024-01-12T16%3A03%3A08Z&sp=rcw\",
\"app_insights_instrumentation_key\": \"InstrumentationKey=**data_scrubbed**;IngestionEndpoint=https://eastus-6.in.applicationinsights.azure.com/;LiveEndpoint=https://eastus.livediagnostics.monitor.azure.com/\",
\"data_inputs\": {\"data\": \"azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl\"},
\"azure_storage_setting\": {\"azure_storage_mode\": 1, \"storage_account_name\":
\"promptfloweast4063704120\", \"blob_container_name\": \"azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5\",
\"flow_artifacts_root_path\": \"promptflow/PromptFlowArtifacts/failed_run_name\",
\"blob_container_sas_token\": \"?sv=2019-07-07&sr=c&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T08%3A03%3A09Z&ske=2024-01-19T08%3A03%3A08Z&sks=b&skv=2019-07-07&se=2024-01-19T08%3A03%3A08Z&sp=racwl\",
\"output_datastore_name\": \"workspaceblobstore\"}}\n2024-01-12 08:03:09 +0000 49
promptflow-runtime INFO Runtime version: 20231204.v4. PromptFlow version:
1.2.0rc1\n2024-01-12 08:03:09 +0000 49 promptflow-runtime INFO Updating
failed_run_name to Status.Preparing...\n2024-01-12 08:03:09 +0000 49
promptflow-runtime INFO Downloading snapshot to /mnt/host/service/app/39649/requests/failed_run_name\n2024-01-12
08:03:09 +0000 49 promptflow-runtime INFO Get snapshot sas url for
5132ecba-405b-4fa2-85de-01c959708f2e...\n2024-01-12 08:03:16 +0000 49
promptflow-runtime INFO Downloading snapshot 5132ecba-405b-4fa2-85de-01c959708f2e
from uri https://promptfloweast4063704120.blob.core.windows.net/snapshotzips/promptflow-eastus:3e123da1-f9a5-4c91-9234-8d9ffbb39ff5:snapshotzip/5132ecba-405b-4fa2-85de-01c959708f2e.zip...\n2024-01-12
08:03:16 +0000 49 promptflow-runtime INFO Downloaded file /mnt/host/service/app/39649/requests/failed_run_name/5132ecba-405b-4fa2-85de-01c959708f2e.zip
with size 701 for snapshot 5132ecba-405b-4fa2-85de-01c959708f2e.\n2024-01-12
08:03:16 +0000 49 promptflow-runtime INFO Download snapshot 5132ecba-405b-4fa2-85de-01c959708f2e
completed.\n2024-01-12 08:03:16 +0000 49 promptflow-runtime INFO Successfully
download snapshot to /mnt/host/service/app/39649/requests/failed_run_name\n2024-01-12
08:03:16 +0000 49 promptflow-runtime INFO About to execute a python
flow.\n2024-01-12 08:03:16 +0000 49 promptflow-runtime INFO Use spawn
method to start child process.\n2024-01-12 08:03:16 +0000 49 promptflow-runtime
INFO Starting to check process 3482 status for run failed_run_name\n2024-01-12
08:03:16 +0000 49 promptflow-runtime INFO Start checking run status
for run failed_run_name\n2024-01-12 08:03:20 +0000 3482 promptflow-runtime
INFO [49--3482] Start processing flowV2......\n2024-01-12 08:03:20 +0000 3482
promptflow-runtime INFO Runtime version: 20231204.v4. PromptFlow version:
1.2.0rc1\n2024-01-12 08:03:20 +0000 3482 promptflow-runtime INFO Setting
mlflow tracking uri...\n2024-01-12 08:03:20 +0000 3482 promptflow-runtime
INFO Validating ''AzureML Data Scientist'' user authentication...\n2024-01-12
08:03:21 +0000 3482 promptflow-runtime INFO Successfully validated
''AzureML Data Scientist'' user authentication.\n2024-01-12 08:03:21 +0000 3482
promptflow-runtime INFO Using AzureMLRunStorageV2\n2024-01-12 08:03:21
+0000 3482 promptflow-runtime INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
08:03:21 +0000 3482 promptflow-runtime INFO Initialized blob service
client for AzureMLRunTracker.\n2024-01-12 08:03:21 +0000 3482 promptflow-runtime
INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
08:03:21 +0000 3482 promptflow-runtime INFO Resolve data from url finished
in 0.5524158906191587 seconds\n2024-01-12 08:03:21 +0000 3482 promptflow-runtime
INFO Starting the aml run ''failed_run_name''...\n2024-01-12 08:03:22
+0000 3482 execution WARNING Starting run without column mapping
may lead to unexpected results. Please consult the following documentation
for more information: https://aka.ms/pf/column-mapping\n2024-01-12 08:03:22
+0000 3482 execution.bulk ERROR Error occurred while executing batch
run. Exception: The input for batch run is incorrect. Couldn''t find these
mapping relations: ${data.key}. Please make sure your input mapping keys and
values match your YAML input section and input data. For more information,
refer to the following documentation: https://aka.ms/pf/column-mapping\n2024-01-12
08:03:22 +0000 3482 promptflow-runtime ERROR Run failed_run_name failed.
Exception: {\n \"message\": \"The input for batch run is incorrect. Couldn''t
find these mapping relations: ${data.key}. Please make sure your input mapping
keys and values match your YAML input section and input data. For more information,
refer to the following documentation: https://aka.ms/pf/column-mapping\",\n \"messageFormat\":
\"The input for batch run is incorrect. Couldn''t find these mapping relations:
{invalid_relations}. Please make sure your input mapping keys and values match
your YAML input section and input data. For more information, refer to the
following documentation: https://aka.ms/pf/column-mapping\",\n \"messageParameters\":
{\n \"invalid_relations\": \"${data.key}\"\n },\n \"referenceCode\":
\"Executor\",\n \"code\": \"UserError\",\n \"innerError\": {\n \"code\":
\"ValidationError\",\n \"innerError\": {\n \"code\": \"InputMappingError\",\n \"innerError\":
null\n }\n },\n \"debugInfo\": {\n \"type\": \"InputMappingError\",\n \"message\":
\"The input for batch run is incorrect. Couldn''t find these mapping relations:
${data.key}. Please make sure your input mapping keys and values match your
YAML input section and input data. For more information, refer to the following
documentation: https://aka.ms/pf/column-mapping\",\n \"stackTrace\": \"Traceback
(most recent call last):\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/runtime/runtime.py\\\",
line 671, in execute_bulk_run_request\\n batch_engine.run(\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\\\",
line 147, in run\\n raise e\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\\\",
line 132, in run\\n batch_inputs = batch_input_processor.process_batch_inputs(input_dirs,
inputs_mapping)\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\\\",
line 41, in process_batch_inputs\\n return self._validate_and_apply_inputs_mapping(input_dicts,
inputs_mapping)\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\\\",
line 91, in _validate_and_apply_inputs_mapping\\n resolved_inputs = self._apply_inputs_mapping_for_all_lines(inputs,
inputs_mapping)\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\\\",
line 163, in _apply_inputs_mapping_for_all_lines\\n result = [apply_inputs_mapping(item,
inputs_mapping) for item in merged_list]\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\\\",
line 163, in <listcomp>\\n result = [apply_inputs_mapping(item, inputs_mapping)
for item in merged_list]\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\\\",
line 292, in apply_inputs_mapping\\n raise InputMappingError(\\n\",\n \"innerException\":
null\n }\n}\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/runtime/runtime.py\",
line 671, in execute_bulk_run_request\n batch_engine.run(\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\",
line 147, in run\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\",
line 132, in run\n batch_inputs = batch_input_processor.process_batch_inputs(input_dirs,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 41, in process_batch_inputs\n return self._validate_and_apply_inputs_mapping(input_dicts,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 91, in _validate_and_apply_inputs_mapping\n resolved_inputs = self._apply_inputs_mapping_for_all_lines(inputs,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 163, in _apply_inputs_mapping_for_all_lines\n result = [apply_inputs_mapping(item,
inputs_mapping) for item in merged_list]\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 163, in <listcomp>\n result = [apply_inputs_mapping(item, inputs_mapping)
for item in merged_list]\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 292, in apply_inputs_mapping\n raise InputMappingError(\npromptflow.batch._errors.InputMappingError:
The input for batch run is incorrect. Couldn''t find these mapping relations:
${data.key}. Please make sure your input mapping keys and values match your
YAML input section and input data. For more information, refer to the following
documentation: https://aka.ms/pf/column-mapping\n2024-01-12 08:03:23 +0000 3482
execution.bulk INFO Upload status summary metrics for run failed_run_name
finished in 0.7668862864375114 seconds\n2024-01-12 08:03:23 +0000 3482
promptflow-runtime INFO Successfully write run properties {\"azureml.promptflow.total_tokens\":
0, \"_azureml.evaluate_artifacts\": \"[{\\\"path\\\": \\\"instance_results.jsonl\\\",
\\\"type\\\": \\\"table\\\"}]\"} with run id ''failed_run_name''\n2024-01-12
08:03:23 +0000 3482 execution.bulk INFO Upload RH properties for
run failed_run_name finished in 0.07698679156601429 seconds\n2024-01-12 08:03:23
+0000 3482 promptflow-runtime INFO Creating unregistered output Asset
for Run failed_run_name...\n2024-01-12 08:03:23 +0000 3482 promptflow-runtime
INFO Created debug_info Asset: azureml://locations/eastus/workspaces/00000/data/azureml_failed_run_name_output_data_debug_info/versions/1\n2024-01-12
08:03:23 +0000 3482 promptflow-runtime INFO Patching failed_run_name...\n2024-01-12
08:03:23 +0000 3482 promptflow-runtime WARNING [failed_run_name] Run failed.
Execution stackTrace: Traceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/runtime/runtime.py\",
line 671, in execute_bulk_run_request\n batch_engine.run(\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\",
line 147, in run\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\",
line 132, in run\n batch_inputs = batch_input_processor.process_batch_inputs(input_dirs,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 41, in process_batch_inputs\n return self._validate_and_apply_inputs_mapping(input_dicts,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 91, in _validate_and_apply_inputs_mapping\n resolved_inputs = self._apply_inputs_mapping_for_all_lines(inputs,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 163, in _apply_inputs_mapping_for_all_lines\n result = [apply_inputs_mapping(item,
inputs_mapping) for item in merged_list]\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 163, in <listcomp>\n result = [apply_inputs_mapping(item, inputs_mapping)
for item in merged_list]\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 292, in apply_inputs_mapping\n raise InputMappingError(\n\n2024-01-12
08:03:24 +0000 3482 promptflow-runtime INFO Ending the aml run ''failed_run_name''
with status ''Failed''...\n2024-01-12 08:03:25 +0000 49 promptflow-runtime
INFO Process 3482 finished\n2024-01-12 08:03:25 +0000 49 promptflow-runtime
INFO [49] Child process finished!\n2024-01-12 08:03:25 +0000 49 promptflow-runtime
INFO [failed_run_name] End processing bulk run\n2024-01-12 08:03:25 +0000 49
promptflow-runtime ERROR Submit flow request failed Code: 400 InnerException
type: InputMappingError Exception type hierarchy: UserError/ValidationError/InputMappingError\n2024-01-12
08:03:25 +0000 49 promptflow-runtime INFO Cleanup working dir /mnt/host/service/app/39649/requests/failed_run_name
for bulk run\n"'
headers:
connection:
- keep-alive
content-length:
- '15117'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.616'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_get_invalid_run_cases.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.020'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.079'
status:
code: 200
message: OK
- request:
body: '{"runId": "non_exist_run", "selectRunMetadata": true, "selectRunDefinition":
true, "selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"error": {"code": "UserError", "severity": null, "message": "Run runId=non_exist_run
was not found", "messageFormat": "Run {runId} was not found", "messageParameters":
{"runId": "runId=non_exist_run"}, "referenceCode": null, "detailsUri": null,
"target": null, "details": [], "innerError": {"code": "NotFoundError", "innerError":
null}, "debugInfo": null, "additionalInfo": null}, "correlation": {"operation":
"4524d4f22ddaa62600fff8c00e9256f6", "request": "6ed7f8ac3ca2136c"}, "environment":
"eastus", "location": "eastus", "time": "2023-11-29T09:03:44.6763704+00:00",
"componentName": "run-history", "statusCode": 404}'
headers:
connection:
- keep-alive
content-length:
- '777'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.044'
status:
code: 404
message: Run runId=32263d2c-f56a-4298-9fe3-f90ab65f59c6 was not found
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_get_details_against_partial_completed_run.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.029'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.059'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.099'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.125'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:53:29 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/numbers.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '290'
content-md5:
- O6LvdPMlN/PM6b7fPh75Jw==
content-type:
- application/octet-stream
last-modified:
- Tue, 26 Dec 2023 09:52:29 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Tue, 26 Dec 2023 09:52:29 GMT
x-ms-meta-name:
- 229ce463-c199-4588-a9c4-c30e7a4bd25c
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 4cda6a90-97ca-4ad5-b420-5e347369f614
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:53:30 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/numbers.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.082'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.097'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:53:34 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/two/flow.dag.yaml
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '242'
content-md5:
- ySItjr6//pwsGdjLZfgq0A==
content-type:
- application/octet-stream
last-modified:
- Tue, 26 Dec 2023 09:53:17 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Tue, 26 Dec 2023 09:52:31 GMT
x-ms-meta-name:
- 5b163be8-ab29-4f62-bef0-cd64d56ab269
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:53:35 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/two/flow.dag.yaml
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/two/flow.dag.yaml", "runId":
"run1", "runDisplayName": "run1", "runExperimentName": "", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/numbers.jsonl"},
"inputsMapping": {"number": "${data.value}"}, "connections": {}, "environmentVariables":
{}, "runtimeName": "fake-runtime-name", "sessionId": "000000000000000000000000000000000000000000000000",
"sessionSetupMode": "SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '783'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"run1"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '6.387'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run1
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "mod_two", "type": "python", "source":
{"type": "code", "path": "mod_two.py"}, "inputs": {"number": "${inputs.number}"},
"tool": "mod_two.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "mod_two.py", "type": "python", "inputs":
{"number": {"type": ["int"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "mod_two.py", "function": "mod_two",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"number": {"type": "int", "is_chat_input": false}}, "outputs": {"output":
{"type": "int", "reference": "${mod_two.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run1/flowRuns/run1",
"flowRunId": "run1", "flowRunDisplayName": "run1", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/7e5ac781513436b66626132fefb20d1f/numbers.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"number": "${data.value}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run1/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "d15d3732-36a4-45ac-b53b-e1fe695b2e77",
"studioPortalEndpoint": "https://ml.azure.com/runs/run1?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12860'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.458'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run1
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "mod_two", "type": "python", "source":
{"type": "code", "path": "mod_two.py"}, "inputs": {"number": "${inputs.number}"},
"tool": "mod_two.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "mod_two.py", "type": "python", "inputs":
{"number": {"type": ["int"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "mod_two.py", "function": "mod_two",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"number": {"type": "int", "is_chat_input": false}}, "outputs": {"output":
{"type": "int", "reference": "${mod_two.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run1/flowRuns/run1",
"flowRunId": "run1", "flowRunDisplayName": "run1", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/7e5ac781513436b66626132fefb20d1f/numbers.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"number": "${data.value}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run1/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "d15d3732-36a4-45ac-b53b-e1fe695b2e77",
"studioPortalEndpoint": "https://ml.azure.com/runs/run1?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12860'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.472'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run1
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "mod_two", "type": "python", "source":
{"type": "code", "path": "mod_two.py"}, "inputs": {"number": "${inputs.number}"},
"tool": "mod_two.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "mod_two.py", "type": "python", "inputs":
{"number": {"type": ["int"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "mod_two.py", "function": "mod_two",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"number": {"type": "int", "is_chat_input": false}}, "outputs": {"output":
{"type": "int", "reference": "${mod_two.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run1/flowRuns/run1",
"flowRunId": "run1", "flowRunDisplayName": "run1", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/7e5ac781513436b66626132fefb20d1f/numbers.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"number": "${data.value}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run1/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "d15d3732-36a4-45ac-b53b-e1fe695b2e77",
"studioPortalEndpoint": "https://ml.azure.com/runs/run1?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12860'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.262'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run1
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "mod_two", "type": "python", "source":
{"type": "code", "path": "mod_two.py"}, "inputs": {"number": "${inputs.number}"},
"tool": "mod_two.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "mod_two.py", "type": "python", "inputs":
{"number": {"type": ["int"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "mod_two.py", "function": "mod_two",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"number": {"type": "int", "is_chat_input": false}}, "outputs": {"output":
{"type": "int", "reference": "${mod_two.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run1/flowRuns/run1",
"flowRunId": "run1", "flowRunDisplayName": "run1", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/7e5ac781513436b66626132fefb20d1f/numbers.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"number": "${data.value}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run1/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "d15d3732-36a4-45ac-b53b-e1fe695b2e77",
"studioPortalEndpoint": "https://ml.azure.com/runs/run1?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12860'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.273'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run1
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "mod_two", "type": "python", "source":
{"type": "code", "path": "mod_two.py"}, "inputs": {"number": "${inputs.number}"},
"tool": "mod_two.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "mod_two.py", "type": "python", "inputs":
{"number": {"type": ["int"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "mod_two.py", "function": "mod_two",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"number": {"type": "int", "is_chat_input": false}}, "outputs": {"output":
{"type": "int", "reference": "${mod_two.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run1/flowRuns/run1",
"flowRunId": "run1", "flowRunDisplayName": "run1", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/7e5ac781513436b66626132fefb20d1f/numbers.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"number": "${data.value}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run1/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "d15d3732-36a4-45ac-b53b-e1fe695b2e77",
"studioPortalEndpoint": "https://ml.azure.com/runs/run1?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12860'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.576'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run1
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "mod_two", "type": "python", "source":
{"type": "code", "path": "mod_two.py"}, "inputs": {"number": "${inputs.number}"},
"tool": "mod_two.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "mod_two.py", "type": "python", "inputs":
{"number": {"type": ["int"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "mod_two.py", "function": "mod_two",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"number": {"type": "int", "is_chat_input": false}}, "outputs": {"output":
{"type": "int", "reference": "${mod_two.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run1/flowRuns/run1",
"flowRunId": "run1", "flowRunDisplayName": "run1", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/7e5ac781513436b66626132fefb20d1f/numbers.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"number": "${data.value}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run1/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "d15d3732-36a4-45ac-b53b-e1fe695b2e77",
"studioPortalEndpoint": "https://ml.azure.com/runs/run1?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12860'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.422'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run1
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "mod_two", "type": "python", "source":
{"type": "code", "path": "mod_two.py"}, "inputs": {"number": "${inputs.number}"},
"tool": "mod_two.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "mod_two.py", "type": "python", "inputs":
{"number": {"type": ["int"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "mod_two.py", "function": "mod_two",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"number": {"type": "int", "is_chat_input": false}}, "outputs": {"output":
{"type": "int", "reference": "${mod_two.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run1/flowRuns/run1",
"flowRunId": "run1", "flowRunDisplayName": "run1", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/7e5ac781513436b66626132fefb20d1f/numbers.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"number": "${data.value}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run1/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "d15d3732-36a4-45ac-b53b-e1fe695b2e77",
"studioPortalEndpoint": "https://ml.azure.com/runs/run1?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12860'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.279'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run1/childRuns?endIndex=24&startIndex=0
response:
body:
string: '[{"run_id": "run1_2", "status": "Completed", "error": null, "inputs":
{"number": 2, "line_number": 2}, "output": {"output": 2}, "metrics": null,
"request": null, "parent_run_id": "run1", "root_run_id": "run1", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:53:58.36557Z",
"end_time": "2024-01-12T08:53:58.379665Z", "index": 2, "api_calls": [{"name":
"mod_two", "type": "Tool", "inputs": {"number": 2}, "output": {"value": 2},
"start_time": 1705049638.376116, "end_time": 1705049638.377043, "error": null,
"children": null, "node_name": "mod_two"}], "variant_id": "", "name": "",
"description": "", "tags": null, "system_metrics": {"duration": 0.014095,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"output": 2}, "upload_metrics": false}, {"run_id": "run1_1", "status": "Failed",
"error": {"message": "Execution failure in ''mod_two'': (Exception) cannot
mod 2!", "messageFormat": "Execution failure in ''{node_name}'': {error_type_and_message}",
"messageParameters": {"node_name": "mod_two", "error_type_and_message": "(Exception)
cannot mod 2!"}, "referenceCode": "Tool/__pf_main__", "code": "UserError",
"innerError": {"code": "ToolExecutionError", "innerError": null}, "additionalInfo":
[{"type": "ToolExecutionErrorDetails", "info": {"type": "Exception", "message":
"cannot mod 2!", "traceback": "Traceback (most recent call last):\n File
\"/mnt/host/service/app/39649/requests/run1/mod_two.py\", line 7, in mod_two\n raise
Exception(\"cannot mod 2!\")\nException: cannot mod 2!\n", "filename": "/mnt/host/service/app/39649/requests/run1/mod_two.py",
"lineno": 7, "name": "mod_two"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_two'': (Exception) cannot mod 2!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 2!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\n", "innerException":
null}}}, "inputs": {"number": 1, "line_number": 1}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run1", "root_run_id": "run1", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:53:58.382319Z",
"end_time": "2024-01-12T08:53:58.499971Z", "index": 1, "api_calls": [{"name":
"mod_two", "type": "Tool", "inputs": {"number": 1}, "output": null, "start_time":
1705049638.40109, "end_time": 1705049638.401905, "error": {"message": "cannot
mod 2!", "type": "Exception"}, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.117652, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run1_0", "status":
"Completed", "error": null, "inputs": {"number": 0, "line_number": 0}, "output":
{"output": 0}, "metrics": null, "request": null, "parent_run_id": "run1",
"root_run_id": "run1", "source_run_id": null, "flow_id": "default_flow_id",
"start_time": "2024-01-12T08:53:58.298983Z", "end_time": "2024-01-12T08:53:58.326471Z",
"index": 0, "api_calls": [{"name": "mod_two", "type": "Tool", "inputs": {"number":
0}, "output": {"value": 0}, "start_time": 1705049638.316181, "end_time": 1705049638.316979,
"error": null, "children": null, "node_name": "mod_two"}], "variant_id": "",
"name": "", "description": "", "tags": null, "system_metrics": {"duration":
0.027488, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0},
"result": {"output": 0}, "upload_metrics": false}, {"run_id": "run1_4", "status":
"Completed", "error": null, "inputs": {"number": 4, "line_number": 4}, "output":
{"output": 4}, "metrics": null, "request": null, "parent_run_id": "run1",
"root_run_id": "run1", "source_run_id": null, "flow_id": "default_flow_id",
"start_time": "2024-01-12T08:53:58.445979Z", "end_time": "2024-01-12T08:53:58.472475Z",
"index": 4, "api_calls": [{"name": "mod_two", "type": "Tool", "inputs": {"number":
4}, "output": {"value": 4}, "start_time": 1705049638.469504, "end_time": 1705049638.470396,
"error": null, "children": null, "node_name": "mod_two"}], "variant_id": "",
"name": "", "description": "", "tags": null, "system_metrics": {"duration":
0.026496, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0},
"result": {"output": 4}, "upload_metrics": false}, {"run_id": "run1_3", "status":
"Failed", "error": {"message": "Execution failure in ''mod_two'': (Exception)
cannot mod 2!", "messageFormat": "Execution failure in ''{node_name}'': {error_type_and_message}",
"messageParameters": {"node_name": "mod_two", "error_type_and_message": "(Exception)
cannot mod 2!"}, "referenceCode": "Tool/__pf_main__", "code": "UserError",
"innerError": {"code": "ToolExecutionError", "innerError": null}, "additionalInfo":
[{"type": "ToolExecutionErrorDetails", "info": {"type": "Exception", "message":
"cannot mod 2!", "traceback": "Traceback (most recent call last):\n File
\"/mnt/host/service/app/39649/requests/run1/mod_two.py\", line 7, in mod_two\n raise
Exception(\"cannot mod 2!\")\nException: cannot mod 2!\n", "filename": "/mnt/host/service/app/39649/requests/run1/mod_two.py",
"lineno": 7, "name": "mod_two"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_two'': (Exception) cannot mod 2!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 2!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\n", "innerException":
null}}}, "inputs": {"number": 3, "line_number": 3}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run1", "root_run_id": "run1", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:53:58.440354Z",
"end_time": "2024-01-12T08:53:58.453661Z", "index": 3, "api_calls": [{"name":
"mod_two", "type": "Tool", "inputs": {"number": 3}, "output": null, "start_time":
1705049638.445455, "end_time": 1705049638.448284, "error": {"message": "cannot
mod 2!", "type": "Exception"}, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.013307, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run1_7", "status":
"Failed", "error": {"message": "Execution failure in ''mod_two'': (Exception)
cannot mod 2!", "messageFormat": "Execution failure in ''{node_name}'': {error_type_and_message}",
"messageParameters": {"node_name": "mod_two", "error_type_and_message": "(Exception)
cannot mod 2!"}, "referenceCode": "Tool/__pf_main__", "code": "UserError",
"innerError": {"code": "ToolExecutionError", "innerError": null}, "additionalInfo":
[{"type": "ToolExecutionErrorDetails", "info": {"type": "Exception", "message":
"cannot mod 2!", "traceback": "Traceback (most recent call last):\n File
\"/mnt/host/service/app/39649/requests/run1/mod_two.py\", line 7, in mod_two\n raise
Exception(\"cannot mod 2!\")\nException: cannot mod 2!\n", "filename": "/mnt/host/service/app/39649/requests/run1/mod_two.py",
"lineno": 7, "name": "mod_two"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_two'': (Exception) cannot mod 2!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 2!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\n", "innerException":
null}}}, "inputs": {"number": 7, "line_number": 7}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run1", "root_run_id": "run1", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:53:58.508983Z",
"end_time": "2024-01-12T08:53:58.621053Z", "index": 7, "api_calls": [{"name":
"mod_two", "type": "Tool", "inputs": {"number": 7}, "output": null, "start_time":
1705049638.512829, "end_time": 1705049638.513634, "error": {"message": "cannot
mod 2!", "type": "Exception"}, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.11207, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run1_8", "status":
"Completed", "error": null, "inputs": {"number": 8, "line_number": 8}, "output":
{"output": 8}, "metrics": null, "request": null, "parent_run_id": "run1",
"root_run_id": "run1", "source_run_id": null, "flow_id": "default_flow_id",
"start_time": "2024-01-12T08:53:58.529121Z", "end_time": "2024-01-12T08:53:58.538356Z",
"index": 8, "api_calls": [{"name": "mod_two", "type": "Tool", "inputs": {"number":
8}, "output": {"value": 8}, "start_time": 1705049638.535074, "end_time": 1705049638.535882,
"error": null, "children": null, "node_name": "mod_two"}], "variant_id": "",
"name": "", "description": "", "tags": null, "system_metrics": {"duration":
0.009235, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0},
"result": {"output": 8}, "upload_metrics": false}, {"run_id": "run1_6", "status":
"Completed", "error": null, "inputs": {"number": 6, "line_number": 6}, "output":
{"output": 6}, "metrics": null, "request": null, "parent_run_id": "run1",
"root_run_id": "run1", "source_run_id": null, "flow_id": "default_flow_id",
"start_time": "2024-01-12T08:53:58.481907Z", "end_time": "2024-01-12T08:53:58.489299Z",
"index": 6, "api_calls": [{"name": "mod_two", "type": "Tool", "inputs": {"number":
6}, "output": {"value": 6}, "start_time": 1705049638.486027, "end_time": 1705049638.487006,
"error": null, "children": null, "node_name": "mod_two"}], "variant_id": "",
"name": "", "description": "", "tags": null, "system_metrics": {"duration":
0.007392, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0},
"result": {"output": 6}, "upload_metrics": false}, {"run_id": "run1_9", "status":
"Failed", "error": {"message": "Execution failure in ''mod_two'': (Exception)
cannot mod 2!", "messageFormat": "Execution failure in ''{node_name}'': {error_type_and_message}",
"messageParameters": {"node_name": "mod_two", "error_type_and_message": "(Exception)
cannot mod 2!"}, "referenceCode": "Tool/__pf_main__", "code": "UserError",
"innerError": {"code": "ToolExecutionError", "innerError": null}, "additionalInfo":
[{"type": "ToolExecutionErrorDetails", "info": {"type": "Exception", "message":
"cannot mod 2!", "traceback": "Traceback (most recent call last):\n File
\"/mnt/host/service/app/39649/requests/run1/mod_two.py\", line 7, in mod_two\n raise
Exception(\"cannot mod 2!\")\nException: cannot mod 2!\n", "filename": "/mnt/host/service/app/39649/requests/run1/mod_two.py",
"lineno": 7, "name": "mod_two"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_two'': (Exception) cannot mod 2!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 2!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\n", "innerException":
null}}}, "inputs": {"number": 9, "line_number": 9}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run1", "root_run_id": "run1", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:53:58.529591Z",
"end_time": "2024-01-12T08:53:58.643284Z", "index": 9, "api_calls": [{"name":
"mod_two", "type": "Tool", "inputs": {"number": 9}, "output": null, "start_time":
1705049638.534116, "end_time": 1705049638.535141, "error": {"message": "cannot
mod 2!", "type": "Exception"}, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.113693, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run1_10", "status":
"Completed", "error": null, "inputs": {"number": 10, "line_number": 10}, "output":
{"output": 10}, "metrics": null, "request": null, "parent_run_id": "run1",
"root_run_id": "run1", "source_run_id": null, "flow_id": "default_flow_id",
"start_time": "2024-01-12T08:53:58.567671Z", "end_time": "2024-01-12T08:53:58.573553Z",
"index": 10, "api_calls": [{"name": "mod_two", "type": "Tool", "inputs": {"number":
10}, "output": {"value": 10}, "start_time": 1705049638.570297, "end_time":
1705049638.571094, "error": null, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.005882, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": {"output": 10}, "upload_metrics": false}, {"run_id": "run1_11",
"status": "Failed", "error": {"message": "Execution failure in ''mod_two'':
(Exception) cannot mod 2!", "messageFormat": "Execution failure in ''{node_name}'':
{error_type_and_message}", "messageParameters": {"node_name": "mod_two", "error_type_and_message":
"(Exception) cannot mod 2!"}, "referenceCode": "Tool/__pf_main__", "code":
"UserError", "innerError": {"code": "ToolExecutionError", "innerError": null},
"additionalInfo": [{"type": "ToolExecutionErrorDetails", "info": {"type":
"Exception", "message": "cannot mod 2!", "traceback": "Traceback (most recent
call last):\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\nException: cannot
mod 2!\n", "filename": "/mnt/host/service/app/39649/requests/run1/mod_two.py",
"lineno": 7, "name": "mod_two"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_two'': (Exception) cannot mod 2!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 2!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\n", "innerException":
null}}}, "inputs": {"number": 11, "line_number": 11}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run1", "root_run_id": "run1", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:53:58.623786Z",
"end_time": "2024-01-12T08:53:58.634409Z", "index": 11, "api_calls": [{"name":
"mod_two", "type": "Tool", "inputs": {"number": 11}, "output": null, "start_time":
1705049638.627165, "end_time": 1705049638.629035, "error": {"message": "cannot
mod 2!", "type": "Exception"}, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.010623, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run1_5", "status":
"Failed", "error": {"message": "Execution failure in ''mod_two'': (Exception)
cannot mod 2!", "messageFormat": "Execution failure in ''{node_name}'': {error_type_and_message}",
"messageParameters": {"node_name": "mod_two", "error_type_and_message": "(Exception)
cannot mod 2!"}, "referenceCode": "Tool/__pf_main__", "code": "UserError",
"innerError": {"code": "ToolExecutionError", "innerError": null}, "additionalInfo":
[{"type": "ToolExecutionErrorDetails", "info": {"type": "Exception", "message":
"cannot mod 2!", "traceback": "Traceback (most recent call last):\n File
\"/mnt/host/service/app/39649/requests/run1/mod_two.py\", line 7, in mod_two\n raise
Exception(\"cannot mod 2!\")\nException: cannot mod 2!\n", "filename": "/mnt/host/service/app/39649/requests/run1/mod_two.py",
"lineno": 7, "name": "mod_two"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_two'': (Exception) cannot mod 2!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 2!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\n", "innerException":
null}}}, "inputs": {"number": 5, "line_number": 5}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run1", "root_run_id": "run1", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:53:58.478106Z",
"end_time": "2024-01-12T08:53:58.485903Z", "index": 5, "api_calls": [{"name":
"mod_two", "type": "Tool", "inputs": {"number": 5}, "output": null, "start_time":
1705049638.480935, "end_time": 1705049638.481815, "error": {"message": "cannot
mod 2!", "type": "Exception"}, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.007797, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run1_12", "status":
"Completed", "error": null, "inputs": {"number": 12, "line_number": 12}, "output":
{"output": 12}, "metrics": null, "request": null, "parent_run_id": "run1",
"root_run_id": "run1", "source_run_id": null, "flow_id": "default_flow_id",
"start_time": "2024-01-12T08:53:58.857735Z", "end_time": "2024-01-12T08:53:58.8594Z",
"index": 12, "api_calls": [{"name": "mod_two", "type": "Tool", "inputs": {"number":
12}, "output": {"value": 12}, "start_time": 1705049638.85876, "end_time":
1705049638.858846, "error": null, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.001665, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": {"output": 12}, "upload_metrics": false}, {"run_id": "run1_13",
"status": "Failed", "error": {"message": "Execution failure in ''mod_two'':
(Exception) cannot mod 2!", "messageFormat": "Execution failure in ''{node_name}'':
{error_type_and_message}", "messageParameters": {"node_name": "mod_two", "error_type_and_message":
"(Exception) cannot mod 2!"}, "referenceCode": "Tool/__pf_main__", "code":
"UserError", "innerError": {"code": "ToolExecutionError", "innerError": null},
"additionalInfo": [{"type": "ToolExecutionErrorDetails", "info": {"type":
"Exception", "message": "cannot mod 2!", "traceback": "Traceback (most recent
call last):\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\nException: cannot
mod 2!\n", "filename": "/mnt/host/service/app/39649/requests/run1/mod_two.py",
"lineno": 7, "name": "mod_two"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_two'': (Exception) cannot mod 2!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 2!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\n", "innerException":
null}}}, "inputs": {"number": 13, "line_number": 13}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run1", "root_run_id": "run1", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:53:59.081618Z",
"end_time": "2024-01-12T08:53:59.084304Z", "index": 13, "api_calls": [{"name":
"mod_two", "type": "Tool", "inputs": {"number": 13}, "output": null, "start_time":
1705049639.082711, "end_time": 1705049639.082963, "error": {"message": "cannot
mod 2!", "type": "Exception"}, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.002686, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run1_14", "status":
"Completed", "error": null, "inputs": {"number": 14, "line_number": 14}, "output":
{"output": 14}, "metrics": null, "request": null, "parent_run_id": "run1",
"root_run_id": "run1", "source_run_id": null, "flow_id": "default_flow_id",
"start_time": "2024-01-12T08:53:59.095533Z", "end_time": "2024-01-12T08:53:59.097688Z",
"index": 14, "api_calls": [{"name": "mod_two", "type": "Tool", "inputs": {"number":
14}, "output": {"value": 14}, "start_time": 1705049639.096824, "end_time":
1705049639.096905, "error": null, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.002155, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": {"output": 14}, "upload_metrics": false}, {"run_id": "run1_15",
"status": "Failed", "error": {"message": "Execution failure in ''mod_two'':
(Exception) cannot mod 2!", "messageFormat": "Execution failure in ''{node_name}'':
{error_type_and_message}", "messageParameters": {"node_name": "mod_two", "error_type_and_message":
"(Exception) cannot mod 2!"}, "referenceCode": "Tool/__pf_main__", "code":
"UserError", "innerError": {"code": "ToolExecutionError", "innerError": null},
"additionalInfo": [{"type": "ToolExecutionErrorDetails", "info": {"type":
"Exception", "message": "cannot mod 2!", "traceback": "Traceback (most recent
call last):\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\nException: cannot
mod 2!\n", "filename": "/mnt/host/service/app/39649/requests/run1/mod_two.py",
"lineno": 7, "name": "mod_two"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_two'': (Exception) cannot mod 2!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 2!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\n", "innerException":
null}}}, "inputs": {"number": 15, "line_number": 15}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run1", "root_run_id": "run1", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:53:59.11042Z",
"end_time": "2024-01-12T08:53:59.112899Z", "index": 15, "api_calls": [{"name":
"mod_two", "type": "Tool", "inputs": {"number": 15}, "output": null, "start_time":
1705049639.111395, "end_time": 1705049639.111456, "error": {"message": "cannot
mod 2!", "type": "Exception"}, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.002479, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run1_16", "status":
"Completed", "error": null, "inputs": {"number": 16, "line_number": 16}, "output":
{"output": 16}, "metrics": null, "request": null, "parent_run_id": "run1",
"root_run_id": "run1", "source_run_id": null, "flow_id": "default_flow_id",
"start_time": "2024-01-12T08:53:59.122603Z", "end_time": "2024-01-12T08:53:59.125415Z",
"index": 16, "api_calls": [{"name": "mod_two", "type": "Tool", "inputs": {"number":
16}, "output": {"value": 16}, "start_time": 1705049639.123932, "end_time":
1705049639.124128, "error": null, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.002812, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": {"output": 16}, "upload_metrics": false}, {"run_id": "run1_17",
"status": "Failed", "error": {"message": "Execution failure in ''mod_two'':
(Exception) cannot mod 2!", "messageFormat": "Execution failure in ''{node_name}'':
{error_type_and_message}", "messageParameters": {"node_name": "mod_two", "error_type_and_message":
"(Exception) cannot mod 2!"}, "referenceCode": "Tool/__pf_main__", "code":
"UserError", "innerError": {"code": "ToolExecutionError", "innerError": null},
"additionalInfo": [{"type": "ToolExecutionErrorDetails", "info": {"type":
"Exception", "message": "cannot mod 2!", "traceback": "Traceback (most recent
call last):\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\nException: cannot
mod 2!\n", "filename": "/mnt/host/service/app/39649/requests/run1/mod_two.py",
"lineno": 7, "name": "mod_two"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_two'': (Exception) cannot mod 2!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 2!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\n", "innerException":
null}}}, "inputs": {"number": 17, "line_number": 17}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run1", "root_run_id": "run1", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:53:59.201596Z",
"end_time": "2024-01-12T08:53:59.204779Z", "index": 17, "api_calls": [{"name":
"mod_two", "type": "Tool", "inputs": {"number": 17}, "output": null, "start_time":
1705049639.202943, "end_time": 1705049639.203028, "error": {"message": "cannot
mod 2!", "type": "Exception"}, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.003183, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run1_18", "status":
"Completed", "error": null, "inputs": {"number": 18, "line_number": 18}, "output":
{"output": 18}, "metrics": null, "request": null, "parent_run_id": "run1",
"root_run_id": "run1", "source_run_id": null, "flow_id": "default_flow_id",
"start_time": "2024-01-12T08:53:59.216109Z", "end_time": "2024-01-12T08:53:59.21858Z",
"index": 18, "api_calls": [{"name": "mod_two", "type": "Tool", "inputs": {"number":
18}, "output": {"value": 18}, "start_time": 1705049639.217608, "end_time":
1705049639.217688, "error": null, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.002471, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": {"output": 18}, "upload_metrics": false}, {"run_id": "run1_19",
"status": "Failed", "error": {"message": "Execution failure in ''mod_two'':
(Exception) cannot mod 2!", "messageFormat": "Execution failure in ''{node_name}'':
{error_type_and_message}", "messageParameters": {"node_name": "mod_two", "error_type_and_message":
"(Exception) cannot mod 2!"}, "referenceCode": "Tool/__pf_main__", "code":
"UserError", "innerError": {"code": "ToolExecutionError", "innerError": null},
"additionalInfo": [{"type": "ToolExecutionErrorDetails", "info": {"type":
"Exception", "message": "cannot mod 2!", "traceback": "Traceback (most recent
call last):\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\nException: cannot
mod 2!\n", "filename": "/mnt/host/service/app/39649/requests/run1/mod_two.py",
"lineno": 7, "name": "mod_two"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_two'': (Exception) cannot mod 2!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 2!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\n", "innerException":
null}}}, "inputs": {"number": 19, "line_number": 19}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run1", "root_run_id": "run1", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:53:59.231917Z",
"end_time": "2024-01-12T08:53:59.267557Z", "index": 19, "api_calls": [{"name":
"mod_two", "type": "Tool", "inputs": {"number": 19}, "output": null, "start_time":
1705049639.233619, "end_time": 1705049639.233699, "error": {"message": "cannot
mod 2!", "type": "Exception"}, "children": null, "node_name": "mod_two"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.03564, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}]'
headers:
connection:
- keep-alive
content-length:
- '57297'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.805'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run1/childRuns?endIndex=49&startIndex=25
response:
body:
string: '[]'
headers:
connection:
- keep-alive
content-length:
- '2'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '0.746'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.077'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.118'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:55:07 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/three/flow.dag.yaml
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '248'
content-md5:
- B3pfhMEmUOazTzjlKaw6Sw==
content-type:
- application/octet-stream
last-modified:
- Tue, 26 Dec 2023 10:04:33 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Tue, 26 Dec 2023 09:54:37 GMT
x-ms-meta-name:
- 613ead8f-69ca-4c47-9cba-01f0dd473279
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:55:08 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/three/flow.dag.yaml
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/three/flow.dag.yaml", "runId":
"run2", "runDisplayName": "run2", "runExperimentName": "", "variantRunId": "run1",
"batchDataInput": {}, "inputsMapping": {"number": "${run.outputs.output}"},
"connections": {}, "environmentVariables": {}, "runtimeName": "fake-runtime-name",
"sessionId": "000000000000000000000000000000000000000000000000", "sessionSetupMode":
"SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '734'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"run2"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '6.653'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run2
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "mod_three", "type": "python", "source":
{"type": "code", "path": "mod_three.py"}, "inputs": {"number": "${inputs.number}"},
"tool": "mod_three.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "mod_three.py", "type": "python",
"inputs": {"number": {"type": ["int"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "mod_three.py", "function": "mod_three",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"number": {"type": "int", "is_chat_input": false}}, "outputs": {"output":
{"type": "int", "reference": "${mod_three.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run2/flowRuns/run2",
"flowRunId": "run2", "flowRunDisplayName": "run2", "batchDataInput": {}, "flowRunType":
"FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci", "inputsMapping":
{"number": "${run.outputs.output}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run2/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "a25bab13-d2d7-4c36-83bf-96979de95507",
"studioPortalEndpoint": "https://ml.azure.com/runs/run2?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12766'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.225'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run2
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "mod_three", "type": "python", "source":
{"type": "code", "path": "mod_three.py"}, "inputs": {"number": "${inputs.number}"},
"tool": "mod_three.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAACgElEQVR4nGWSz2vcVRTFP/e9NzOZ1KDGohASslLEH6VLV0ak4l/QpeDCrfQPcNGliODKnVm4EBdBsIjQIlhciKW0ycKFVCSNbYnjdDLtmPnmO/nO9917XcxMkjYX3uLx7nnn3HOuMK2Nix4fP78ZdrYXVkLVWjf3l3B1B+HpcjzGFtmqa6cePz7/x0dnn1n5qhj3iBJPYREIURAJuCtpY8PjReDbrf9WG7H1fuefwQU9qKztTcMJT+PNnEFvjGVDBDlSsH6p/9MLzy6+NxwVqI8RAg4IPmWedMckdLYP6O6UpIaQfvyyXG012+e79/ZfHukoS1ISMT2hGTB1RkUmNgQ5QZ0w+a2VWDq73MbdEWmfnnv6UWe7oNzPaLapl5CwuLTXK9WUGBuCjqekzhP+z52ZXOrKMD3OJg0Hh778aiOuvpnYvp05d6GJO4iAO4QAe/eV36/X5LFRV4Zmn+AdkqlL8Vjp3oVioOz+WTPzzYEgsN+fgPLYyJVheSbPPVl2ikeGZRjtG52/8rHuaV9VOlpP2OtKyVndcRVCSqOhsvxa4vW359i6OuKdD+aP8Q4SYPdOzS/flGjt1JUSaMqZ5nwa1Y8qWb/Ud/eZZkHisYezEM0m+fcelDr8F1SqW2LNK6r1jXQwyLzy1hxvrLXZulry7ocL+FS6G4QIu3fG/Px1gdYeW7LIgXU2P/115TOA5G7e3Rmj2aS/m7l5pThiZzrCcE/d1XHzbln373nw7y6veeoUm5KCNKT/IPPwbiY1hYd/l5MIT65BMFt87sU4v9D7/JMflr44uV6hGh1+L4RCkg6z5iK2tAhNLeLsNGwYA4fDYnC/drvuuFxe86NV/x+Ut27g0FvykgAAAABJRU5ErkJggg==",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "mod_three.py", "type": "python",
"inputs": {"number": {"type": ["int"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "mod_three.py", "function": "mod_three",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"number": {"type": "int", "is_chat_input": false}}, "outputs": {"output":
{"type": "int", "reference": "${mod_three.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run2/flowRuns/run2",
"flowRunId": "run2", "flowRunDisplayName": "run2", "batchDataInput": {}, "flowRunType":
"FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci", "inputsMapping":
{"number": "${run.outputs.output}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run2/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "a25bab13-d2d7-4c36-83bf-96979de95507",
"studioPortalEndpoint": "https://ml.azure.com/runs/run2?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12766'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.496'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run2
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "mod_three", "type": "python", "source":
{"type": "code", "path": "mod_three.py"}, "inputs": {"number": "${inputs.number}"},
"tool": "mod_three.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "mod_three.py", "type": "python",
"inputs": {"number": {"type": ["int"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "mod_three.py", "function": "mod_three",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"number": {"type": "int", "is_chat_input": false}}, "outputs": {"output":
{"type": "int", "reference": "${mod_three.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run2/flowRuns/run2",
"flowRunId": "run2", "flowRunDisplayName": "run2", "batchDataInput": {}, "flowRunType":
"FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci", "inputsMapping":
{"number": "${run.outputs.output}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run2/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "a25bab13-d2d7-4c36-83bf-96979de95507",
"studioPortalEndpoint": "https://ml.azure.com/runs/run2?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12766'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.245'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run2
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "mod_three", "type": "python", "source":
{"type": "code", "path": "mod_three.py"}, "inputs": {"number": "${inputs.number}"},
"tool": "mod_three.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "mod_three.py", "type": "python",
"inputs": {"number": {"type": ["int"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "mod_three.py", "function": "mod_three",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"number": {"type": "int", "is_chat_input": false}}, "outputs": {"output":
{"type": "int", "reference": "${mod_three.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run2/flowRuns/run2",
"flowRunId": "run2", "flowRunDisplayName": "run2", "batchDataInput": {}, "flowRunType":
"FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci", "inputsMapping":
{"number": "${run.outputs.output}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run2/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "a25bab13-d2d7-4c36-83bf-96979de95507",
"studioPortalEndpoint": "https://ml.azure.com/runs/run2?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12766'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.381'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run2
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "mod_three", "type": "python", "source":
{"type": "code", "path": "mod_three.py"}, "inputs": {"number": "${inputs.number}"},
"tool": "mod_three.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "mod_three.py", "type": "python",
"inputs": {"number": {"type": ["int"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "mod_three.py", "function": "mod_three",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"number": {"type": "int", "is_chat_input": false}}, "outputs": {"output":
{"type": "int", "reference": "${mod_three.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run2/flowRuns/run2",
"flowRunId": "run2", "flowRunDisplayName": "run2", "batchDataInput": {}, "flowRunType":
"FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci", "inputsMapping":
{"number": "${run.outputs.output}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run2/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "a25bab13-d2d7-4c36-83bf-96979de95507",
"studioPortalEndpoint": "https://ml.azure.com/runs/run2?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12766'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.410'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run2
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "mod_three", "type": "python", "source":
{"type": "code", "path": "mod_three.py"}, "inputs": {"number": "${inputs.number}"},
"tool": "mod_three.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "mod_three.py", "type": "python",
"inputs": {"number": {"type": ["int"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "mod_three.py", "function": "mod_three",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"number": {"type": "int", "is_chat_input": false}}, "outputs": {"output":
{"type": "int", "reference": "${mod_three.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run2/flowRuns/run2",
"flowRunId": "run2", "flowRunDisplayName": "run2", "batchDataInput": {}, "flowRunType":
"FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci", "inputsMapping":
{"number": "${run.outputs.output}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run2/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "a25bab13-d2d7-4c36-83bf-96979de95507",
"studioPortalEndpoint": "https://ml.azure.com/runs/run2?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12766'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.408'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run2
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "mod_three", "type": "python", "source":
{"type": "code", "path": "mod_three.py"}, "inputs": {"number": "${inputs.number}"},
"tool": "mod_three.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "mod_three.py", "type": "python",
"inputs": {"number": {"type": ["int"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "mod_three.py", "function": "mod_three",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"number": {"type": "int", "is_chat_input": false}}, "outputs": {"output":
{"type": "int", "reference": "${mod_three.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run2/flowRuns/run2",
"flowRunId": "run2", "flowRunDisplayName": "run2", "batchDataInput": {}, "flowRunType":
"FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci", "inputsMapping":
{"number": "${run.outputs.output}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run2/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "a25bab13-d2d7-4c36-83bf-96979de95507",
"studioPortalEndpoint": "https://ml.azure.com/runs/run2?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12766'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.451'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run2/childRuns?endIndex=24&startIndex=0
response:
body:
string: '[{"run_id": "run2_0", "status": "Completed", "error": null, "inputs":
{"number": 0, "line_number": 0}, "output": {"output": 0}, "metrics": null,
"request": null, "parent_run_id": "run2", "root_run_id": "run2", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:55:31.465237Z",
"end_time": "2024-01-12T08:55:31.475743Z", "index": 0, "api_calls": [{"name":
"mod_three", "type": "Tool", "inputs": {"number": 0}, "output": {"value":
0}, "start_time": 1705049731.472262, "end_time": 1705049731.473128, "error":
null, "children": null, "node_name": "mod_three"}], "variant_id": "", "name":
"", "description": "", "tags": null, "system_metrics": {"duration": 0.010506,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"output": 0}, "upload_metrics": false}, {"run_id": "run2_12", "status": "Completed",
"error": null, "inputs": {"number": 12, "line_number": 12}, "output": {"output":
12}, "metrics": null, "request": null, "parent_run_id": "run2", "root_run_id":
"run2", "source_run_id": null, "flow_id": "default_flow_id", "start_time":
"2024-01-12T08:55:31.656075Z", "end_time": "2024-01-12T08:55:31.661754Z",
"index": 12, "api_calls": [{"name": "mod_three", "type": "Tool", "inputs":
{"number": 12}, "output": {"value": 12}, "start_time": 1705049731.658932,
"end_time": 1705049731.659931, "error": null, "children": null, "node_name":
"mod_three"}], "variant_id": "", "name": "", "description": "", "tags": null,
"system_metrics": {"duration": 0.005679, "prompt_tokens": 0, "completion_tokens":
0, "total_tokens": 0}, "result": {"output": 12}, "upload_metrics": false},
{"run_id": "run2_2", "status": "Failed", "error": {"message": "Execution failure
in ''mod_three'': (Exception) cannot mod 3!", "messageFormat": "Execution
failure in ''{node_name}'': {error_type_and_message}", "messageParameters":
{"node_name": "mod_three", "error_type_and_message": "(Exception) cannot mod
3!"}, "referenceCode": "Tool/__pf_main__", "code": "UserError", "innerError":
{"code": "ToolExecutionError", "innerError": null}, "additionalInfo": [{"type":
"ToolExecutionErrorDetails", "info": {"type": "Exception", "message": "cannot
mod 3!", "traceback": "Traceback (most recent call last):\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\nException: cannot
mod 3!\n", "filename": "/mnt/host/service/app/39649/requests/run2/mod_three.py",
"lineno": 7, "name": "mod_three"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_three'': (Exception) cannot mod 3!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 3!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\n", "innerException":
null}}}, "inputs": {"number": 2, "line_number": 2}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run2", "root_run_id": "run2", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:55:31.490355Z",
"end_time": "2024-01-12T08:55:31.575384Z", "index": 2, "api_calls": [{"name":
"mod_three", "type": "Tool", "inputs": {"number": 2}, "output": null, "start_time":
1705049731.497823, "end_time": 1705049731.498797, "error": {"message": "cannot
mod 3!", "type": "Exception"}, "children": null, "node_name": "mod_three"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.085029, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run2_4", "status":
"Failed", "error": {"message": "Execution failure in ''mod_three'': (Exception)
cannot mod 3!", "messageFormat": "Execution failure in ''{node_name}'': {error_type_and_message}",
"messageParameters": {"node_name": "mod_three", "error_type_and_message":
"(Exception) cannot mod 3!"}, "referenceCode": "Tool/__pf_main__", "code":
"UserError", "innerError": {"code": "ToolExecutionError", "innerError": null},
"additionalInfo": [{"type": "ToolExecutionErrorDetails", "info": {"type":
"Exception", "message": "cannot mod 3!", "traceback": "Traceback (most recent
call last):\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\nException: cannot
mod 3!\n", "filename": "/mnt/host/service/app/39649/requests/run2/mod_three.py",
"lineno": 7, "name": "mod_three"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_three'': (Exception) cannot mod 3!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 3!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\n", "innerException":
null}}}, "inputs": {"number": 4, "line_number": 4}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run2", "root_run_id": "run2", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:55:31.535972Z",
"end_time": "2024-01-12T08:55:31.773764Z", "index": 4, "api_calls": [{"name":
"mod_three", "type": "Tool", "inputs": {"number": 4}, "output": null, "start_time":
1705049731.548995, "end_time": 1705049731.550238, "error": {"message": "cannot
mod 3!", "type": "Exception"}, "children": null, "node_name": "mod_three"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.237792, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run2_8", "status":
"Failed", "error": {"message": "Execution failure in ''mod_three'': (Exception)
cannot mod 3!", "messageFormat": "Execution failure in ''{node_name}'': {error_type_and_message}",
"messageParameters": {"node_name": "mod_three", "error_type_and_message":
"(Exception) cannot mod 3!"}, "referenceCode": "Tool/__pf_main__", "code":
"UserError", "innerError": {"code": "ToolExecutionError", "innerError": null},
"additionalInfo": [{"type": "ToolExecutionErrorDetails", "info": {"type":
"Exception", "message": "cannot mod 3!", "traceback": "Traceback (most recent
call last):\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\nException: cannot
mod 3!\n", "filename": "/mnt/host/service/app/39649/requests/run2/mod_three.py",
"lineno": 7, "name": "mod_three"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_three'': (Exception) cannot mod 3!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 3!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\n", "innerException":
null}}}, "inputs": {"number": 8, "line_number": 8}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run2", "root_run_id": "run2", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:55:31.559578Z",
"end_time": "2024-01-12T08:55:31.789137Z", "index": 8, "api_calls": [{"name":
"mod_three", "type": "Tool", "inputs": {"number": 8}, "output": null, "start_time":
1705049731.584465, "end_time": 1705049731.585312, "error": {"message": "cannot
mod 3!", "type": "Exception"}, "children": null, "node_name": "mod_three"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.229559, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run2_6", "status":
"Completed", "error": null, "inputs": {"number": 6, "line_number": 6}, "output":
{"output": 6}, "metrics": null, "request": null, "parent_run_id": "run2",
"root_run_id": "run2", "source_run_id": null, "flow_id": "default_flow_id",
"start_time": "2024-01-12T08:55:31.555822Z", "end_time": "2024-01-12T08:55:31.564102Z",
"index": 6, "api_calls": [{"name": "mod_three", "type": "Tool", "inputs":
{"number": 6}, "output": {"value": 6}, "start_time": 1705049731.561458, "end_time":
1705049731.562356, "error": null, "children": null, "node_name": "mod_three"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.00828, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": {"output": 6}, "upload_metrics": false}, {"run_id": "run2_16",
"status": "Failed", "error": {"message": "Execution failure in ''mod_three'':
(Exception) cannot mod 3!", "messageFormat": "Execution failure in ''{node_name}'':
{error_type_and_message}", "messageParameters": {"node_name": "mod_three",
"error_type_and_message": "(Exception) cannot mod 3!"}, "referenceCode": "Tool/__pf_main__",
"code": "UserError", "innerError": {"code": "ToolExecutionError", "innerError":
null}, "additionalInfo": [{"type": "ToolExecutionErrorDetails", "info": {"type":
"Exception", "message": "cannot mod 3!", "traceback": "Traceback (most recent
call last):\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\nException: cannot
mod 3!\n", "filename": "/mnt/host/service/app/39649/requests/run2/mod_three.py",
"lineno": 7, "name": "mod_three"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_three'': (Exception) cannot mod 3!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 3!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\n", "innerException":
null}}}, "inputs": {"number": 16, "line_number": 16}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run2", "root_run_id": "run2", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:55:31.744907Z",
"end_time": "2024-01-12T08:55:31.817842Z", "index": 16, "api_calls": [{"name":
"mod_three", "type": "Tool", "inputs": {"number": 16}, "output": null, "start_time":
1705049731.747285, "end_time": 1705049731.747465, "error": {"message": "cannot
mod 3!", "type": "Exception"}, "children": null, "node_name": "mod_three"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.072935, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run2_10", "status":
"Failed", "error": {"message": "Execution failure in ''mod_three'': (Exception)
cannot mod 3!", "messageFormat": "Execution failure in ''{node_name}'': {error_type_and_message}",
"messageParameters": {"node_name": "mod_three", "error_type_and_message":
"(Exception) cannot mod 3!"}, "referenceCode": "Tool/__pf_main__", "code":
"UserError", "innerError": {"code": "ToolExecutionError", "innerError": null},
"additionalInfo": [{"type": "ToolExecutionErrorDetails", "info": {"type":
"Exception", "message": "cannot mod 3!", "traceback": "Traceback (most recent
call last):\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\nException: cannot
mod 3!\n", "filename": "/mnt/host/service/app/39649/requests/run2/mod_three.py",
"lineno": 7, "name": "mod_three"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_three'': (Exception) cannot mod 3!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 3!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\n", "innerException":
null}}}, "inputs": {"number": 10, "line_number": 10}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run2", "root_run_id": "run2", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:55:31.59072Z",
"end_time": "2024-01-12T08:55:31.604864Z", "index": 10, "api_calls": [{"name":
"mod_three", "type": "Tool", "inputs": {"number": 10}, "output": null, "start_time":
1705049731.59849, "end_time": 1705049731.600113, "error": {"message": "cannot
mod 3!", "type": "Exception"}, "children": null, "node_name": "mod_three"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.014144, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run2_14", "status":
"Failed", "error": {"message": "Execution failure in ''mod_three'': (Exception)
cannot mod 3!", "messageFormat": "Execution failure in ''{node_name}'': {error_type_and_message}",
"messageParameters": {"node_name": "mod_three", "error_type_and_message":
"(Exception) cannot mod 3!"}, "referenceCode": "Tool/__pf_main__", "code":
"UserError", "innerError": {"code": "ToolExecutionError", "innerError": null},
"additionalInfo": [{"type": "ToolExecutionErrorDetails", "info": {"type":
"Exception", "message": "cannot mod 3!", "traceback": "Traceback (most recent
call last):\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\nException: cannot
mod 3!\n", "filename": "/mnt/host/service/app/39649/requests/run2/mod_three.py",
"lineno": 7, "name": "mod_three"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''mod_three'': (Exception) cannot mod 3!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 3!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\n", "innerException":
null}}}, "inputs": {"number": 14, "line_number": 14}, "output": null, "metrics":
null, "request": null, "parent_run_id": "run2", "root_run_id": "run2", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:55:31.736285Z",
"end_time": "2024-01-12T08:55:31.745117Z", "index": 14, "api_calls": [{"name":
"mod_three", "type": "Tool", "inputs": {"number": 14}, "output": null, "start_time":
1705049731.739545, "end_time": 1705049731.740525, "error": {"message": "cannot
mod 3!", "type": "Exception"}, "children": null, "node_name": "mod_three"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.008832, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}, {"run_id": "run2_18", "status":
"Completed", "error": null, "inputs": {"number": 18, "line_number": 18}, "output":
{"output": 18}, "metrics": null, "request": null, "parent_run_id": "run2",
"root_run_id": "run2", "source_run_id": null, "flow_id": "default_flow_id",
"start_time": "2024-01-12T08:55:31.890045Z", "end_time": "2024-01-12T08:55:31.891993Z",
"index": 18, "api_calls": [{"name": "mod_three", "type": "Tool", "inputs":
{"number": 18}, "output": {"value": 18}, "start_time": 1705049731.891255,
"end_time": 1705049731.891333, "error": null, "children": null, "node_name":
"mod_three"}], "variant_id": "", "name": "", "description": "", "tags": null,
"system_metrics": {"duration": 0.001948, "prompt_tokens": 0, "completion_tokens":
0, "total_tokens": 0}, "result": {"output": 18}, "upload_metrics": false}]'
headers:
connection:
- keep-alive
content-length:
- '32873'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.930'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run2/childRuns?endIndex=49&startIndex=25
response:
body:
string: '[]'
headers:
connection:
- keep-alive
content-length:
- '2'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '0.727'
status:
code: 200
message: OK
- request:
body: '{"runId": "run1", "selectRunMetadata": true, "selectRunDefinition": true,
"selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705049621, "rootRunId": "run1", "createdUtc":
"2024-01-12T08:53:41.7311265+00:00", "createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": {"error": {"code": "UserError", "severity":
null, "message": "Execution failure in ''mod_two'': (Exception) cannot mod
2!", "messageFormat": "{\"totalChildRuns\": 20, \"userErrorChildRuns\": 10,
\"systemErrorChildRuns\": 0, \"errorDetails\": [{\"code\": \"UserError/ToolExecutionError\",
\"messageFormat\": \"Execution failure in ''{node_name}'': {error_type_and_message}\",
\"count\": 10}]}", "messageParameters": {"node_name": "mod_two", "error_type_and_message":
"(Exception) cannot mod 2!"}, "referenceCode": "Tool/__pf_main__", "detailsUri":
null, "target": null, "details": [], "innerError": {"code": "ToolExecutionError",
"innerError": null}, "debugInfo": {"type": "ToolExecutionError", "message":
"Execution failure in ''mod_two'': (Exception) cannot mod 2!", "stackTrace":
"\nThe above exception was the direct cause of the following exception:\n\nTraceback
(most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 2!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\n", "innerException":
null, "data": null, "errorResponse": null}, "data": null, "errorResponse":
null}, "additionalInfo": [{"type": "ToolExecutionErrorDetails", "info": {"type":
"Exception", "message": "cannot mod 2!", "traceback": "Traceback (most recent
call last):\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\nException: cannot
mod 2!\n", "filename": "/mnt/host/service/app/39649/requests/run1/mod_two.py",
"lineno": 7, "name": "mod_two"}}]}, "correlation": null, "environment": null,
"location": null, "time": "2024-01-12T08:54:32.157997+00:00", "componentName":
"promptflow-runtime/20231204.v4 Designer/1.0 promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0) promptflow/1.2.0rc1"}, "warnings":
null, "revision": 7, "statusRevision": 3, "runUuid": "08457cff-a0cf-4b93-8b58-24b47e6e2f06",
"parentRunUuid": null, "rootRunUuid": "08457cff-a0cf-4b93-8b58-24b47e6e2f06",
"lastStartTimeUtc": null, "currentComputeTime": null, "computeDuration": "00:00:34.5206194",
"effectiveStartTimeUtc": null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "18a66f5f-dbdf-4c17-9dd7-1634712a9cbe",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:54:31.4291957+00:00", "duration":
"00:00:34.5206194", "cancelationReason": null, "currentAttemptId": 1, "runId":
"run1", "parentRunId": null, "experimentId": "f65cb39a-0d28-4b06-9ef9-b962ed9df8d0",
"status": "Completed", "startTimeUtc": "2024-01-12T08:53:57.8643652+00:00",
"endTimeUtc": "2024-01-12T08:54:32.3849846+00:00", "scheduleId": null, "displayName":
"run1", "name": null, "dataContainerId": "dcid.run1", "description": null,
"hidden": false, "runType": "azureml.promptflow.FlowRun", "runTypeV2": {"orchestrator":
null, "traits": [], "attribution": "PromptFlow", "computeType": "AmlcDsi"},
"properties": {"azureml.promptflow.runtime_name": "test-runtime-ci", "azureml.promptflow.runtime_version":
"20231204.v4", "azureml.promptflow.definition_file_name": "flow.dag.yaml",
"azureml.promptflow.session_id": "357876c0a66919ba9791ba9723d3eb045181f10b65c806ea",
"azureml.promptflow.flow_lineage_id": "3df9ed48cf83e1a38799b0a91f06e0825173b507d07391d1d91ec0253c1cda5c",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/ceb856845f8689bdee2da5a26bd95bab/two/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/7e5ac781513436b66626132fefb20d1f/numbers.jsonl",
"azureml.promptflow.inputs_mapping": "{\"number\":\"${data.value}\"}", "_azureml.evaluation_run":
"promptflow.BatchRun", "azureml.promptflow.snapshot_id": "d15d3732-36a4-45ac-b53b-e1fe695b2e77",
"azureml.promptflow.total_tokens": "0", "_azureml.evaluate_artifacts": "[{\"path\":
\"instance_results.jsonl\", \"type\": \"table\"}]"}, "parameters": {}, "actionUris":
{}, "scriptName": null, "target": null, "uniqueChildRunComputeTargets": [],
"tags": {}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": {"debug_info": {"assetId":
"azureml://locations/eastus/workspaces/00000/data/azureml_run1_output_data_debug_info/versions/1",
"type": "UriFolder"}, "flow_outputs": {"assetId": "azureml://locations/eastus/workspaces/00000/data/azureml_run1_output_data_flow_outputs/versions/1",
"type": "UriFolder"}}}, "runDefinition": null, "jobSpecification": null, "systemSettings":
null}'
headers:
connection:
- keep-alive
content-length:
- '9907'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.053'
status:
code: 200
message: OK
- request:
body: '{"runId": "run2", "selectRunMetadata": true, "selectRunDefinition": true,
"selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705049714, "rootRunId": "run2", "createdUtc":
"2024-01-12T08:55:14.362818+00:00", "createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": {"error": {"code": "UserError", "severity":
null, "message": "Execution failure in ''mod_three'': (Exception) cannot mod
3!", "messageFormat": "{\"totalChildRuns\": 10, \"userErrorChildRuns\": 6,
\"systemErrorChildRuns\": 0, \"errorDetails\": [{\"code\": \"UserError/ToolExecutionError\",
\"messageFormat\": \"Execution failure in ''{node_name}'': {error_type_and_message}\",
\"count\": 6}]}", "messageParameters": {"node_name": "mod_three", "error_type_and_message":
"(Exception) cannot mod 3!"}, "referenceCode": "Tool/__pf_main__", "detailsUri":
null, "target": null, "details": [], "innerError": {"code": "ToolExecutionError",
"innerError": null}, "debugInfo": {"type": "ToolExecutionError", "message":
"Execution failure in ''mod_three'': (Exception) cannot mod 3!", "stackTrace":
"\nThe above exception was the direct cause of the following exception:\n\nTraceback
(most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"cannot mod 3!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\n", "innerException":
null, "data": null, "errorResponse": null}, "data": null, "errorResponse":
null}, "additionalInfo": [{"type": "ToolExecutionErrorDetails", "info": {"type":
"Exception", "message": "cannot mod 3!", "traceback": "Traceback (most recent
call last):\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\nException: cannot
mod 3!\n", "filename": "/mnt/host/service/app/39649/requests/run2/mod_three.py",
"lineno": 7, "name": "mod_three"}}]}, "correlation": null, "environment":
null, "location": null, "time": "2024-01-12T08:56:05.377066+00:00", "componentName":
"promptflow-runtime/20231204.v4 Designer/1.0 promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0) promptflow/1.2.0rc1"}, "warnings":
null, "revision": 7, "statusRevision": 3, "runUuid": "b80a9962-ed21-4dfb-85b0-2548b1649f39",
"parentRunUuid": null, "rootRunUuid": "b80a9962-ed21-4dfb-85b0-2548b1649f39",
"lastStartTimeUtc": null, "currentComputeTime": null, "computeDuration": "00:00:34.5231338",
"effectiveStartTimeUtc": null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "18a66f5f-dbdf-4c17-9dd7-1634712a9cbe",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:56:04.2209326+00:00", "duration":
"00:00:34.5231338", "cancelationReason": null, "currentAttemptId": 1, "runId":
"run2", "parentRunId": null, "experimentId": "3a00e270-37b9-49be-a74e-ac675487979e",
"status": "Completed", "startTimeUtc": "2024-01-12T08:55:31.0651672+00:00",
"endTimeUtc": "2024-01-12T08:56:05.588301+00:00", "scheduleId": null, "displayName":
"run2", "name": null, "dataContainerId": "dcid.run2", "description": null,
"hidden": false, "runType": "azureml.promptflow.FlowRun", "runTypeV2": {"orchestrator":
null, "traits": [], "attribution": "PromptFlow", "computeType": "AmlcDsi"},
"properties": {"azureml.promptflow.runtime_name": "test-runtime-ci", "azureml.promptflow.runtime_version":
"20231204.v4", "azureml.promptflow.definition_file_name": "flow.dag.yaml",
"azureml.promptflow.session_id": "c9399af7028d644e85f3624a0b026432068432621519ab8f",
"azureml.promptflow.flow_lineage_id": "77a36a2606b22ee30674046884962374e57e822acdeccac7750905d98e944580",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/f0722e3fb27e86b101670dbb5e85554c/three/flow.dag.yaml",
"azureml.promptflow.input_run_id": "run1", "azureml.promptflow.inputs_mapping":
"{\"number\":\"${run.outputs.output}\"}", "_azureml.evaluation_run": "promptflow.BatchRun",
"azureml.promptflow.snapshot_id": "a25bab13-d2d7-4c36-83bf-96979de95507",
"azureml.promptflow.total_tokens": "0", "_azureml.evaluate_artifacts": "[{\"path\":
\"instance_results.jsonl\", \"type\": \"table\"}]"}, "parameters": {}, "actionUris":
{}, "scriptName": null, "target": null, "uniqueChildRunComputeTargets": [],
"tags": {}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": {"debug_info": {"assetId":
"azureml://locations/eastus/workspaces/00000/data/azureml_run2_output_data_debug_info/versions/1",
"type": "UriFolder"}, "flow_outputs": {"assetId": "azureml://locations/eastus/workspaces/00000/data/azureml_run2_output_data_flow_outputs/versions/1",
"type": "UriFolder"}}}, "runDefinition": null, "jobSpecification": null, "systemSettings":
null}'
headers:
connection:
- keep-alive
content-length:
- '9865'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.037'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run1/logContent
response:
body:
string: '"2024-01-12 08:53:45 +0000 49 promptflow-runtime INFO [run1]
Receiving v2 bulk run request e51d6436-3ed9-4576-b848-1967710c148c: {\"flow_id\":
\"run1\", \"flow_run_id\": \"run1\", \"flow_source\": {\"flow_source_type\":
1, \"flow_source_info\": {\"snapshot_id\": \"d15d3732-36a4-45ac-b53b-e1fe695b2e77\"},
\"flow_dag_file\": \"flow.dag.yaml\"}, \"log_path\": \"https://promptfloweast4063704120.blob.core.windows.net/azureml/ExperimentRun/dcid.run1/logs/azureml/executionlogs.txt?sv=2019-07-07&sr=b&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T08%3A43%3A40Z&ske=2024-01-13T16%3A53%3A40Z&sks=b&skv=2019-07-07&st=2024-01-12T08%3A43%3A44Z&se=2024-01-12T16%3A53%3A44Z&sp=rcw\",
\"app_insights_instrumentation_key\": \"InstrumentationKey=**data_scrubbed**;IngestionEndpoint=https://eastus-6.in.applicationinsights.azure.com/;LiveEndpoint=https://eastus.livediagnostics.monitor.azure.com/\",
\"data_inputs\": {\"data\": \"azureml://datastores/workspaceblobstore/paths/LocalUpload/7e5ac781513436b66626132fefb20d1f/numbers.jsonl\"},
\"inputs_mapping\": {\"number\": \"${data.value}\"}, \"azure_storage_setting\":
{\"azure_storage_mode\": 1, \"storage_account_name\": \"promptfloweast4063704120\",
\"blob_container_name\": \"azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5\",
\"flow_artifacts_root_path\": \"promptflow/PromptFlowArtifacts/run1\", \"blob_container_sas_token\":
\"?sv=2019-07-07&sr=c&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T08%3A53%3A45Z&ske=2024-01-19T08%3A53%3A45Z&sks=b&skv=2019-07-07&se=2024-01-19T08%3A53%3A45Z&sp=racwl\",
\"output_datastore_name\": \"workspaceblobstore\"}}\n2024-01-12 08:53:45 +0000 49
promptflow-runtime INFO Runtime version: 20231204.v4. PromptFlow version:
1.2.0rc1\n2024-01-12 08:53:45 +0000 49 promptflow-runtime INFO Updating
run1 to Status.Preparing...\n2024-01-12 08:53:45 +0000 49 promptflow-runtime
INFO Downloading snapshot to /mnt/host/service/app/39649/requests/run1\n2024-01-12
08:53:45 +0000 49 promptflow-runtime INFO Get snapshot sas url for
d15d3732-36a4-45ac-b53b-e1fe695b2e77...\n2024-01-12 08:53:52 +0000 49
promptflow-runtime INFO Downloading snapshot d15d3732-36a4-45ac-b53b-e1fe695b2e77
from uri https://promptfloweast4063704120.blob.core.windows.net/snapshotzips/promptflow-eastus:3e123da1-f9a5-4c91-9234-8d9ffbb39ff5:snapshotzip/d15d3732-36a4-45ac-b53b-e1fe695b2e77.zip...\n2024-01-12
08:53:52 +0000 49 promptflow-runtime INFO Downloaded file /mnt/host/service/app/39649/requests/run1/d15d3732-36a4-45ac-b53b-e1fe695b2e77.zip
with size 509 for snapshot d15d3732-36a4-45ac-b53b-e1fe695b2e77.\n2024-01-12
08:53:52 +0000 49 promptflow-runtime INFO Download snapshot d15d3732-36a4-45ac-b53b-e1fe695b2e77
completed.\n2024-01-12 08:53:52 +0000 49 promptflow-runtime INFO Successfully
download snapshot to /mnt/host/service/app/39649/requests/run1\n2024-01-12
08:53:52 +0000 49 promptflow-runtime INFO About to execute a python
flow.\n2024-01-12 08:53:52 +0000 49 promptflow-runtime INFO Use spawn
method to start child process.\n2024-01-12 08:53:52 +0000 49 promptflow-runtime
INFO Starting to check process 6280 status for run run1\n2024-01-12 08:53:52
+0000 49 promptflow-runtime INFO Start checking run status for run
run1\n2024-01-12 08:53:56 +0000 6280 promptflow-runtime INFO [49--6280]
Start processing flowV2......\n2024-01-12 08:53:56 +0000 6280 promptflow-runtime
INFO Runtime version: 20231204.v4. PromptFlow version: 1.2.0rc1\n2024-01-12
08:53:56 +0000 6280 promptflow-runtime INFO Setting mlflow tracking
uri...\n2024-01-12 08:53:56 +0000 6280 promptflow-runtime INFO Validating
''AzureML Data Scientist'' user authentication...\n2024-01-12 08:53:56 +0000 6280
promptflow-runtime INFO Successfully validated ''AzureML Data Scientist''
user authentication.\n2024-01-12 08:53:56 +0000 6280 promptflow-runtime
INFO Using AzureMLRunStorageV2\n2024-01-12 08:53:56 +0000 6280 promptflow-runtime
INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
08:53:56 +0000 6280 promptflow-runtime INFO Initialized blob service
client for AzureMLRunTracker.\n2024-01-12 08:53:56 +0000 6280 promptflow-runtime
INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
08:53:57 +0000 6280 promptflow-runtime INFO Resolve data from url finished
in 0.6618335284292698 seconds\n2024-01-12 08:53:57 +0000 6280 promptflow-runtime
INFO Starting the aml run ''run1''...\n2024-01-12 08:53:58 +0000 6280
execution.bulk INFO Using fork, process count: 16\n2024-01-12 08:53:58
+0000 6335 execution.bulk INFO Process 6335 started.\n2024-01-12
08:53:58 +0000 6351 execution.bulk INFO Process 6351 started.\n2024-01-12
08:53:58 +0000 6345 execution.bulk INFO Process 6345 started.\n2024-01-12
08:53:58 +0000 6280 execution.bulk INFO Process name: ForkProcess-62:2,
Process id: 6335, Line number: 0 start execution.\n2024-01-12 08:53:58 +0000 6379
execution.bulk INFO Process 6379 started.\n2024-01-12 08:53:58 +0000 6382
execution.bulk INFO Process 6382 started.\n2024-01-12 08:53:58 +0000 6387
execution.bulk INFO Process 6387 started.\n2024-01-12 08:53:58 +0000 6351
execution ERROR Node mod_two in line 1 failed. Exception: Execution
failure in ''mod_two'': (Exception) cannot mod 2!.\nTraceback (most recent
call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\nException: cannot
mod 2!\n\nThe above exception was the direct cause of the following exception:\n\nTraceback
(most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\npromptflow._core._errors.ToolExecutionError: Execution
failure in ''mod_two'': (Exception) cannot mod 2!\n2024-01-12 08:53:58 +0000 6362
execution.bulk INFO Process 6362 started.\n2024-01-12 08:53:58 +0000 6369
execution.bulk INFO Process 6369 started.\n2024-01-12 08:53:58 +0000 6280
execution.bulk INFO Process name: ForkProcess-62:6, Process id: 6351,
Line number: 1 start execution.\n2024-01-12 08:53:58 +0000 6351 execution ERROR Execution
of one node has failed. Cancelling all running nodes: mod_two.\n2024-01-12
08:53:58 +0000 6367 execution.bulk INFO Process 6367 started.\n2024-01-12
08:53:58 +0000 6398 execution.bulk INFO Process 6398 started.\n2024-01-12
08:53:58 +0000 6280 execution.bulk INFO Process name: ForkProcess-62:3,
Process id: 6345, Line number: 2 start execution.\n2024-01-12 08:53:58 +0000 6422
execution.bulk INFO Process 6422 started.\n2024-01-12 08:53:58 +0000 6280
execution.bulk INFO Process name: ForkProcess-62:8, Process id: 6379,
Line number: 3 start execution.\n2024-01-12 08:53:58 +0000 6369 execution ERROR Node
mod_two in line 7 failed. Exception: Execution failure in ''mod_two'': (Exception)
cannot mod 2!.\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\nException: cannot
mod 2!\n\nThe above exception was the direct cause of the following exception:\n\nTraceback
(most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\npromptflow._core._errors.ToolExecutionError: Execution
failure in ''mod_two'': (Exception) cannot mod 2!\n2024-01-12 08:53:58 +0000 6391
execution.bulk INFO Process 6391 started.\n2024-01-12 08:53:58 +0000 6367
execution ERROR Node mod_two in line 9 failed. Exception: Execution
failure in ''mod_two'': (Exception) cannot mod 2!.\nTraceback (most recent
call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\nException: cannot
mod 2!\n\nThe above exception was the direct cause of the following exception:\n\nTraceback
(most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\npromptflow._core._errors.ToolExecutionError: Execution
failure in ''mod_two'': (Exception) cannot mod 2!\n2024-01-12 08:53:58 +0000 6280
execution.bulk INFO Process name: ForkProcess-62:9, Process id: 6382,
Line number: 4 start execution.\n2024-01-12 08:53:58 +0000 6369 execution ERROR Execution
of one node has failed. Cancelling all running nodes: mod_two.\n2024-01-12
08:53:58 +0000 6439 execution.bulk INFO Process 6439 started.\n2024-01-12
08:53:58 +0000 6280 execution.bulk INFO Process name: ForkProcess-62:10,
Process id: 6387, Line number: 5 start execution.\n2024-01-12 08:53:58 +0000 6367
execution ERROR Execution of one node has failed. Cancelling all
running nodes: mod_two.\n2024-01-12 08:53:58 +0000 6403 execution.bulk INFO Process
6403 started.\n2024-01-12 08:53:58 +0000 6280 execution.bulk INFO Process
name: ForkProcess-62:7, Process id: 6362, Line number: 6 start execution.\n2024-01-12
08:53:58 +0000 6280 execution.bulk INFO Process name: ForkProcess-62:4,
Process id: 6369, Line number: 7 start execution.\n2024-01-12 08:53:58 +0000 6280
execution.bulk INFO Process name: ForkProcess-62:11, Process id: 6398,
Line number: 8 start execution.\n2024-01-12 08:53:58 +0000 6280 execution.bulk INFO Process
name: ForkProcess-62:5, Process id: 6367, Line number: 9 start execution.\n2024-01-12
08:53:58 +0000 6280 execution.bulk INFO Process name: ForkProcess-62:14,
Process id: 6422, Line number: 10 start execution.\n2024-01-12 08:53:58 +0000 6280
execution.bulk INFO Process name: ForkProcess-62:12, Process id: 6391,
Line number: 11 start execution.\n2024-01-12 08:53:58 +0000 6280 execution.bulk INFO Process
name: ForkProcess-62:3, Process id: 6345, Line number: 2 completed.\n2024-01-12
08:53:58 +0000 6280 execution.bulk INFO Process name: ForkProcess-62:6,
Process id: 6351, Line number: 1 completed.\n2024-01-12 08:53:58 +0000 6280
execution.bulk INFO Process name: ForkProcess-62:9, Process id: 6382,
Line number: 4 completed.\n2024-01-12 08:53:58 +0000 6280 execution.bulk INFO Process
name: ForkProcess-62:8, Process id: 6379, Line number: 3 completed.\n2024-01-12
08:53:58 +0000 6280 execution.bulk INFO Process name: ForkProcess-62:2,
Process id: 6335, Line number: 0 completed.\n2024-01-12 08:53:58 +0000 6280
execution.bulk INFO Process name: ForkProcess-62:4, Process id: 6369,
Line number: 7 completed.\n2024-01-12 08:53:58 +0000 6280 execution.bulk INFO Finished
6 / 20 lines.\n2024-01-12 08:53:58 +0000 6280 execution.bulk INFO Finished
6 / 20 lines.\n2024-01-12 08:53:58 +0000 6280 execution.bulk INFO Process
name: ForkProcess-62:7, Process id: 6362, Line number: 6 completed.\n2024-01-12
08:53:58 +0000 6280 execution.bulk INFO Process name: ForkProcess-62:11,
Process id: 6398, Line number: 8 completed.\n2024-01-12 08:53:58 +0000 6280
execution.bulk INFO Process name: ForkProcess-62:5, Process id: 6367,
Line number: 9 completed.\n2024-01-12 08:53:58 +0000 6280 execution.bulk INFO Process
name: ForkProcess-62:9, Process id: 6382, Line number: 12 start execution.\n2024-01-12
08:53:58 +0000 6280 execution.bulk INFO Process name: ForkProcess-62:14,
Process id: 6422, Line number: 10 completed.\n2024-01-12 08:53:58 +0000 6280
execution.bulk INFO Finished 10 / 20 lines.\n2024-01-12 08:53:58 +0000 6280
execution.bulk INFO Finished 10 / 20 lines.\n2024-01-12 08:53:58 +0000 6280
execution.bulk INFO Finished 10 / 20 lines.\n2024-01-12 08:53:58 +0000 6280
execution.bulk INFO Process name: ForkProcess-62:12, Process id: 6391,
Line number: 11 completed.\n2024-01-12 08:53:58 +0000 6280 execution.bulk INFO Average
execution time for completed lines: 0.11 seconds. Estimated time for incomplete
lines: 1.54 seconds.\n2024-01-12 08:53:58 +0000 6280 execution.bulk INFO Process
name: ForkProcess-62:10, Process id: 6387, Line number: 5 completed.\n2024-01-12
08:53:58 +0000 6280 execution.bulk INFO Average execution time
for completed lines: 0.11 seconds. Estimated time for incomplete lines: 1.54
seconds.\n2024-01-12 08:53:58 +0000 6280 execution.bulk INFO Finished
12 / 20 lines.\n2024-01-12 08:53:58 +0000 6280 execution.bulk INFO Finished
12 / 20 lines.\n2024-01-12 08:53:58 +0000 6280 execution.bulk INFO Finished
12 / 20 lines.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Finished
12 / 20 lines.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Average
execution time for completed lines: 0.07 seconds. Estimated time for incomplete
lines: 0.7 seconds.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Average
execution time for completed lines: 0.07 seconds. Estimated time for incomplete
lines: 0.7 seconds.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Average
execution time for completed lines: 0.07 seconds. Estimated time for incomplete
lines: 0.7 seconds.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Process
name: ForkProcess-62:9, Process id: 6382, Line number: 12 completed.\n2024-01-12
08:53:59 +0000 6369 execution ERROR Node mod_two in line 19
failed. Exception: Execution failure in ''mod_two'': (Exception) cannot mod
2!.\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run1/mod_two.py\",
line 7, in mod_two\n raise Exception(\"cannot mod 2!\")\nException: cannot
mod 2!\n\nThe above exception was the direct cause of the following exception:\n\nTraceback
(most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\npromptflow._core._errors.ToolExecutionError: Execution
failure in ''mod_two'': (Exception) cannot mod 2!\n2024-01-12 08:53:59 +0000 6280
execution.bulk INFO Process name: ForkProcess-62:12, Process id: 6391,
Line number: 13 start execution.\n2024-01-12 08:53:59 +0000 6369 execution ERROR Execution
of one node has failed. Cancelling all running nodes: mod_two.\n2024-01-12
08:53:59 +0000 6280 execution.bulk INFO Process name: ForkProcess-62:3,
Process id: 6345, Line number: 14 start execution.\n2024-01-12 08:53:59 +0000 6280
execution.bulk INFO Process name: ForkProcess-62:10, Process id: 6387,
Line number: 15 start execution.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Process
name: ForkProcess-62:6, Process id: 6351, Line number: 16 start execution.\n2024-01-12
08:53:59 +0000 6280 execution.bulk INFO Average execution time
for completed lines: 0.07 seconds. Estimated time for incomplete lines: 0.56
seconds.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Average
execution time for completed lines: 0.07 seconds. Estimated time for incomplete
lines: 0.56 seconds.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Average
execution time for completed lines: 0.07 seconds. Estimated time for incomplete
lines: 0.56 seconds.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Average
execution time for completed lines: 0.07 seconds. Estimated time for incomplete
lines: 0.56 seconds.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Process
name: ForkProcess-62:8, Process id: 6379, Line number: 17 start execution.\n2024-01-12
08:53:59 +0000 6280 execution.bulk INFO Process name: ForkProcess-62:2,
Process id: 6335, Line number: 18 start execution.\n2024-01-12 08:53:59 +0000 6280
execution.bulk INFO Process name: ForkProcess-62:4, Process id: 6369,
Line number: 19 start execution.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Process
name: ForkProcess-62:12, Process id: 6391, Line number: 13 completed.\n2024-01-12
08:53:59 +0000 6280 execution.bulk INFO Process name: ForkProcess-62:3,
Process id: 6345, Line number: 14 completed.\n2024-01-12 08:53:59 +0000 6280
execution.bulk INFO Process name: ForkProcess-62:10, Process id: 6387,
Line number: 15 completed.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Process
name: ForkProcess-62:6, Process id: 6351, Line number: 16 completed.\n2024-01-12
08:53:59 +0000 6280 execution.bulk INFO Process name: ForkProcess-62:8,
Process id: 6379, Line number: 17 completed.\n2024-01-12 08:53:59 +0000 6280
execution.bulk INFO Finished 18 / 20 lines.\n2024-01-12 08:53:59 +0000 6280
execution.bulk INFO Process name: ForkProcess-62:2, Process id: 6335,
Line number: 18 completed.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Process
name: ForkProcess-62:4, Process id: 6369, Line number: 19 completed.\n2024-01-12
08:53:59 +0000 6280 execution.bulk INFO Finished 20 / 20 lines.\n2024-01-12
08:53:59 +0000 6280 execution.bulk INFO Finished 20 / 20 lines.\n2024-01-12
08:53:59 +0000 6280 execution.bulk INFO Finished 20 / 20 lines.\n2024-01-12
08:53:59 +0000 6280 execution.bulk INFO Average execution time
for completed lines: 0.07 seconds. Estimated time for incomplete lines: 0.14
seconds.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Finished
20 / 20 lines.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Finished
20 / 20 lines.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Average
execution time for completed lines: 0.07 seconds. Estimated time for incomplete
lines: 0.0 seconds.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Average
execution time for completed lines: 0.07 seconds. Estimated time for incomplete
lines: 0.0 seconds.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Average
execution time for completed lines: 0.07 seconds. Estimated time for incomplete
lines: 0.0 seconds.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Average
execution time for completed lines: 0.07 seconds. Estimated time for incomplete
lines: 0.0 seconds.\n2024-01-12 08:53:59 +0000 6280 execution.bulk INFO Average
execution time for completed lines: 0.07 seconds. Estimated time for incomplete
lines: 0.0 seconds.\n2024-01-12 08:54:29 +0000 6280 execution ERROR 10/20
flow run failed, indexes: [1,3,5,7,9,11,13,15,17,19], exception of index 1:
Execution failure in ''mod_two'': (Exception) cannot mod 2!\n2024-01-12 08:54:31
+0000 6280 execution.bulk INFO Upload status summary metrics for
run run1 finished in 1.6117610009387136 seconds\n2024-01-12 08:54:31 +0000 6280
promptflow-runtime INFO Successfully write run properties {\"azureml.promptflow.total_tokens\":
0, \"_azureml.evaluate_artifacts\": \"[{\\\"path\\\": \\\"instance_results.jsonl\\\",
\\\"type\\\": \\\"table\\\"}]\"} with run id ''run1''\n2024-01-12 08:54:31
+0000 6280 execution.bulk INFO Upload RH properties for run run1
finished in 0.08309784904122353 seconds\n2024-01-12 08:54:31 +0000 6280
promptflow-runtime INFO Creating unregistered output Asset for Run run1...\n2024-01-12
08:54:31 +0000 6280 promptflow-runtime INFO Created debug_info Asset:
azureml://locations/eastus/workspaces/00000/data/azureml_run1_output_data_debug_info/versions/1\n2024-01-12
08:54:31 +0000 6280 promptflow-runtime INFO Creating unregistered output
Asset for Run run1...\n2024-01-12 08:54:31 +0000 6280 promptflow-runtime
INFO Created flow_outputs output Asset: azureml://locations/eastus/workspaces/00000/data/azureml_run1_output_data_flow_outputs/versions/1\n2024-01-12
08:54:31 +0000 6280 promptflow-runtime INFO Creating Artifact for Run
run1...\n2024-01-12 08:54:32 +0000 6280 promptflow-runtime INFO Created
instance_results.jsonl Artifact.\n2024-01-12 08:54:32 +0000 6280 promptflow-runtime
INFO Patching run1...\n2024-01-12 08:54:32 +0000 6280 promptflow-runtime
WARNING [run1] Run failed. Execution stackTrace: Traceback (most recent call
last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n [REDACTED:
External StackTrace]\n\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n [REDACTED:
External StackTrace]\n\n2024-01-12 08:54:32 +0000 6280 promptflow-runtime
INFO Ending the aml run ''run1'' with status ''Completed''...\n2024-01-12
08:54:33 +0000 49 promptflow-runtime INFO Process 6280 finished\n2024-01-12
08:54:33 +0000 49 promptflow-runtime INFO [49] Child process finished!\n2024-01-12
08:54:33 +0000 49 promptflow-runtime INFO [run1] End processing bulk
run\n2024-01-12 08:54:33 +0000 49 promptflow-runtime INFO Cleanup
working dir /mnt/host/service/app/39649/requests/run1 for bulk run\n"'
headers:
connection:
- keep-alive
content-length:
- '26914'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '1.063'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run2/logContent
response:
body:
string: '"2024-01-12 08:55:18 +0000 49 promptflow-runtime INFO [run2]
Receiving v2 bulk run request fb3450a2-5971-497b-9704-9f15f2716d12: {\"flow_id\":
\"run2\", \"flow_run_id\": \"run2\", \"flow_source\": {\"flow_source_type\":
1, \"flow_source_info\": {\"snapshot_id\": \"a25bab13-d2d7-4c36-83bf-96979de95507\"},
\"flow_dag_file\": \"flow.dag.yaml\"}, \"log_path\": \"https://promptfloweast4063704120.blob.core.windows.net/azureml/ExperimentRun/dcid.run2/logs/azureml/executionlogs.txt?sv=2019-07-07&sr=b&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T07%3A44%3A44Z&ske=2024-01-13T15%3A54%3A44Z&sks=b&skv=2019-07-07&st=2024-01-12T08%3A45%3A18Z&se=2024-01-12T16%3A55%3A18Z&sp=rcw\",
\"app_insights_instrumentation_key\": \"InstrumentationKey=**data_scrubbed**;IngestionEndpoint=https://eastus-6.in.applicationinsights.azure.com/;LiveEndpoint=https://eastus.livediagnostics.monitor.azure.com/\",
\"data_inputs\": {\"run.outputs\": \"azureml:/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/data/azureml_run1_output_data_flow_outputs/versions/1\"},
\"inputs_mapping\": {\"number\": \"${run.outputs.output}\"}, \"azure_storage_setting\":
{\"azure_storage_mode\": 1, \"storage_account_name\": \"promptfloweast4063704120\",
\"blob_container_name\": \"azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5\",
\"flow_artifacts_root_path\": \"promptflow/PromptFlowArtifacts/run2\", \"blob_container_sas_token\":
\"?sv=2019-07-07&sr=c&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T08%3A55%3A18Z&ske=2024-01-19T08%3A55%3A18Z&sks=b&skv=2019-07-07&se=2024-01-19T08%3A55%3A18Z&sp=racwl\",
\"output_datastore_name\": \"workspaceblobstore\"}}\n2024-01-12 08:55:18 +0000 49
promptflow-runtime INFO Runtime version: 20231204.v4. PromptFlow version:
1.2.0rc1\n2024-01-12 08:55:18 +0000 49 promptflow-runtime INFO Updating
run2 to Status.Preparing...\n2024-01-12 08:55:19 +0000 49 promptflow-runtime
INFO Downloading snapshot to /mnt/host/service/app/39649/requests/run2\n2024-01-12
08:55:19 +0000 49 promptflow-runtime INFO Get snapshot sas url for
a25bab13-d2d7-4c36-83bf-96979de95507...\n2024-01-12 08:55:25 +0000 49
promptflow-runtime INFO Downloading snapshot a25bab13-d2d7-4c36-83bf-96979de95507
from uri https://promptfloweast4063704120.blob.core.windows.net/snapshotzips/promptflow-eastus:3e123da1-f9a5-4c91-9234-8d9ffbb39ff5:snapshotzip/a25bab13-d2d7-4c36-83bf-96979de95507.zip...\n2024-01-12
08:55:25 +0000 49 promptflow-runtime INFO Downloaded file /mnt/host/service/app/39649/requests/run2/a25bab13-d2d7-4c36-83bf-96979de95507.zip
with size 515 for snapshot a25bab13-d2d7-4c36-83bf-96979de95507.\n2024-01-12
08:55:25 +0000 49 promptflow-runtime INFO Download snapshot a25bab13-d2d7-4c36-83bf-96979de95507
completed.\n2024-01-12 08:55:25 +0000 49 promptflow-runtime INFO Successfully
download snapshot to /mnt/host/service/app/39649/requests/run2\n2024-01-12
08:55:25 +0000 49 promptflow-runtime INFO About to execute a python
flow.\n2024-01-12 08:55:25 +0000 49 promptflow-runtime INFO Use spawn
method to start child process.\n2024-01-12 08:55:25 +0000 49 promptflow-runtime
INFO Starting to check process 6515 status for run run2\n2024-01-12 08:55:25
+0000 49 promptflow-runtime INFO Start checking run status for run
run2\n2024-01-12 08:55:29 +0000 6515 promptflow-runtime INFO [49--6515]
Start processing flowV2......\n2024-01-12 08:55:29 +0000 6515 promptflow-runtime
INFO Runtime version: 20231204.v4. PromptFlow version: 1.2.0rc1\n2024-01-12
08:55:29 +0000 6515 promptflow-runtime INFO Setting mlflow tracking
uri...\n2024-01-12 08:55:29 +0000 6515 promptflow-runtime INFO Validating
''AzureML Data Scientist'' user authentication...\n2024-01-12 08:55:29 +0000 6515
promptflow-runtime INFO Successfully validated ''AzureML Data Scientist''
user authentication.\n2024-01-12 08:55:30 +0000 6515 promptflow-runtime
INFO Using AzureMLRunStorageV2\n2024-01-12 08:55:30 +0000 6515 promptflow-runtime
INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
08:55:30 +0000 6515 promptflow-runtime INFO Initialized blob service
client for AzureMLRunTracker.\n2024-01-12 08:55:30 +0000 6515 promptflow-runtime
INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
08:55:30 +0000 6515 promptflow-runtime INFO Resolve data from url finished
in 0.5992864752188325 seconds\n2024-01-12 08:55:30 +0000 6515 promptflow-runtime
INFO Starting the aml run ''run2''...\n2024-01-12 08:55:31 +0000 6515
execution.bulk INFO Using fork, process count: 10\n2024-01-12 08:55:31
+0000 6565 execution.bulk INFO Process 6565 started.\n2024-01-12
08:55:31 +0000 6570 execution.bulk INFO Process 6570 started.\n2024-01-12
08:55:31 +0000 6579 execution.bulk INFO Process 6579 started.\n2024-01-12
08:55:31 +0000 6585 execution.bulk INFO Process 6585 started.\n2024-01-12
08:55:31 +0000 6592 execution.bulk INFO Process 6592 started.\n2024-01-12
08:55:31 +0000 6570 execution ERROR Node mod_three in line
2 failed. Exception: Execution failure in ''mod_three'': (Exception) cannot
mod 3!.\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\nException: cannot
mod 3!\n\nThe above exception was the direct cause of the following exception:\n\nTraceback
(most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\npromptflow._core._errors.ToolExecutionError: Execution
failure in ''mod_three'': (Exception) cannot mod 3!\n2024-01-12 08:55:31 +0000 6570
execution ERROR Execution of one node has failed. Cancelling all
running nodes: mod_three.\n2024-01-12 08:55:31 +0000 6515 execution.bulk INFO Process
name: ForkProcess-64:2, Process id: 6565, Line number: 0 start execution.\n2024-01-12
08:55:31 +0000 6605 execution.bulk INFO Process 6605 started.\n2024-01-12
08:55:31 +0000 6515 execution.bulk INFO Process name: ForkProcess-64:4,
Process id: 6570, Line number: 2 start execution.\n2024-01-12 08:55:31 +0000 6515
execution.bulk INFO Process name: ForkProcess-64:3, Process id: 6579,
Line number: 4 start execution.\n2024-01-12 08:55:31 +0000 6515 execution.bulk INFO Process
name: ForkProcess-64:5, Process id: 6585, Line number: 6 start execution.\n2024-01-12
08:55:31 +0000 6515 execution.bulk INFO Process name: ForkProcess-64:6,
Process id: 6592, Line number: 8 start execution.\n2024-01-12 08:55:31 +0000 6622
execution.bulk INFO Process 6622 started.\n2024-01-12 08:55:31 +0000 6515
execution.bulk INFO Process name: ForkProcess-64:9, Process id: 6605,
Line number: 10 start execution.\n2024-01-12 08:55:31 +0000 6515 execution.bulk INFO Process
name: ForkProcess-64:10, Process id: 6622, Line number: 12 start execution.\n2024-01-12
08:55:31 +0000 6515 execution.bulk INFO Process name: ForkProcess-64:2,
Process id: 6565, Line number: 0 completed.\n2024-01-12 08:55:31 +0000 6515
execution.bulk INFO Finished 1 / 10 lines.\n2024-01-12 08:55:31 +0000 6614
execution.bulk INFO Process 6614 started.\n2024-01-12 08:55:31 +0000 6515
execution.bulk INFO Average execution time for completed lines: 0.36
seconds. Estimated time for incomplete lines: 3.24 seconds.\n2024-01-12 08:55:31
+0000 6579 execution ERROR Node mod_three in line 4 failed.
Exception: Execution failure in ''mod_three'': (Exception) cannot mod 3!.\nTraceback
(most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\nException: cannot
mod 3!\n\nThe above exception was the direct cause of the following exception:\n\nTraceback
(most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\npromptflow._core._errors.ToolExecutionError: Execution
failure in ''mod_three'': (Exception) cannot mod 3!\n2024-01-12 08:55:31 +0000 6515
execution.bulk INFO Process name: ForkProcess-64:11, Process id: 6614,
Line number: 14 start execution.\n2024-01-12 08:55:31 +0000 6592 execution ERROR Node
mod_three in line 8 failed. Exception: Execution failure in ''mod_three'':
(Exception) cannot mod 3!.\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\nException: cannot
mod 3!\n\nThe above exception was the direct cause of the following exception:\n\nTraceback
(most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\npromptflow._core._errors.ToolExecutionError: Execution
failure in ''mod_three'': (Exception) cannot mod 3!\n2024-01-12 08:55:31 +0000 6579
execution ERROR Execution of one node has failed. Cancelling all
running nodes: mod_three.\n2024-01-12 08:55:31 +0000 6515 execution.bulk INFO Process
name: ForkProcess-64:2, Process id: 6565, Line number: 16 start execution.\n2024-01-12
08:55:31 +0000 6592 execution ERROR Execution of one node has
failed. Cancelling all running nodes: mod_three.\n2024-01-12 08:55:31 +0000 6565
execution ERROR Node mod_three in line 16 failed. Exception: Execution
failure in ''mod_three'': (Exception) cannot mod 3!.\nTraceback (most recent
call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39649/requests/run2/mod_three.py\",
line 7, in mod_three\n raise Exception(\"cannot mod 3!\")\nException: cannot
mod 3!\n\nThe above exception was the direct cause of the following exception:\n\nTraceback
(most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\npromptflow._core._errors.ToolExecutionError: Execution
failure in ''mod_three'': (Exception) cannot mod 3!\n2024-01-12 08:55:31 +0000 6515
execution.bulk INFO Process name: ForkProcess-64:10, Process id: 6622,
Line number: 12 completed.\n2024-01-12 08:55:31 +0000 6565 execution ERROR Execution
of one node has failed. Cancelling all running nodes: mod_three.\n2024-01-12
08:55:31 +0000 6515 execution.bulk INFO Process name: ForkProcess-64:4,
Process id: 6570, Line number: 2 completed.\n2024-01-12 08:55:31 +0000 6515
execution.bulk INFO Finished 3 / 10 lines.\n2024-01-12 08:55:31 +0000 6515
execution.bulk INFO Finished 3 / 10 lines.\n2024-01-12 08:55:31 +0000 6515
execution.bulk INFO Average execution time for completed lines: 0.15
seconds. Estimated time for incomplete lines: 1.05 seconds.\n2024-01-12 08:55:31
+0000 6515 execution.bulk INFO Process name: ForkProcess-64:6,
Process id: 6592, Line number: 8 completed.\n2024-01-12 08:55:31 +0000 6515
execution.bulk INFO Process name: ForkProcess-64:3, Process id: 6579,
Line number: 4 completed.\n2024-01-12 08:55:31 +0000 6515 execution.bulk INFO Average
execution time for completed lines: 0.16 seconds. Estimated time for incomplete
lines: 1.12 seconds.\n2024-01-12 08:55:31 +0000 6515 execution.bulk INFO Process
name: ForkProcess-64:5, Process id: 6585, Line number: 6 completed.\n2024-01-12
08:55:31 +0000 6515 execution.bulk INFO Process name: ForkProcess-64:10,
Process id: 6622, Line number: 18 start execution.\n2024-01-12 08:55:31 +0000 6515
execution.bulk INFO Finished 6 / 10 lines.\n2024-01-12 08:55:31 +0000 6515
execution.bulk INFO Finished 6 / 10 lines.\n2024-01-12 08:55:31 +0000 6515
execution.bulk INFO Process name: ForkProcess-64:9, Process id: 6605,
Line number: 10 completed.\n2024-01-12 08:55:31 +0000 6515 execution.bulk INFO Process
name: ForkProcess-64:2, Process id: 6565, Line number: 16 completed.\n2024-01-12
08:55:31 +0000 6515 execution.bulk INFO Finished 8 / 10 lines.\n2024-01-12
08:55:31 +0000 6515 execution.bulk INFO Average execution time
for completed lines: 0.09 seconds. Estimated time for incomplete lines: 0.36
seconds.\n2024-01-12 08:55:31 +0000 6515 execution.bulk INFO Average
execution time for completed lines: 0.1 seconds. Estimated time for incomplete
lines: 0.4 seconds.\n2024-01-12 08:55:32 +0000 6515 execution.bulk INFO Finished
8 / 10 lines.\n2024-01-12 08:55:32 +0000 6515 execution.bulk INFO Finished
8 / 10 lines.\n2024-01-12 08:55:32 +0000 6515 execution.bulk INFO Average
execution time for completed lines: 0.08 seconds. Estimated time for incomplete
lines: 0.16 seconds.\n2024-01-12 08:55:32 +0000 6515 execution.bulk INFO Process
name: ForkProcess-64:11, Process id: 6614, Line number: 14 completed.\n2024-01-12
08:55:32 +0000 6515 execution.bulk INFO Process name: ForkProcess-64:10,
Process id: 6622, Line number: 18 completed.\n2024-01-12 08:55:32 +0000 6515
execution.bulk INFO Average execution time for completed lines: 0.08
seconds. Estimated time for incomplete lines: 0.16 seconds.\n2024-01-12 08:55:32
+0000 6515 execution.bulk INFO Average execution time for completed
lines: 0.09 seconds. Estimated time for incomplete lines: 0.18 seconds.\n2024-01-12
08:55:32 +0000 6515 execution.bulk INFO Finished 10 / 10 lines.\n2024-01-12
08:55:32 +0000 6515 execution.bulk INFO Finished 10 / 10 lines.\n2024-01-12
08:55:32 +0000 6515 execution.bulk INFO Average execution time
for completed lines: 0.08 seconds. Estimated time for incomplete lines: 0.0
seconds.\n2024-01-12 08:55:32 +0000 6515 execution.bulk INFO Average
execution time for completed lines: 0.08 seconds. Estimated time for incomplete
lines: 0.0 seconds.\n2024-01-12 08:56:02 +0000 6515 execution ERROR 6/10
flow run failed, indexes: [1,2,4,5,7,8], exception of index 1: Execution failure
in ''mod_three'': (Exception) cannot mod 3!\n2024-01-12 08:56:04 +0000 6515
execution.bulk INFO Upload status summary metrics for run run2 finished
in 1.3678363300859928 seconds\n2024-01-12 08:56:04 +0000 6515 promptflow-runtime
INFO Successfully write run properties {\"azureml.promptflow.total_tokens\":
0, \"_azureml.evaluate_artifacts\": \"[{\\\"path\\\": \\\"instance_results.jsonl\\\",
\\\"type\\\": \\\"table\\\"}]\"} with run id ''run2''\n2024-01-12 08:56:04
+0000 6515 execution.bulk INFO Upload RH properties for run run2
finished in 0.07642840500921011 seconds\n2024-01-12 08:56:04 +0000 6515
promptflow-runtime INFO Creating unregistered output Asset for Run run2...\n2024-01-12
08:56:04 +0000 6515 promptflow-runtime INFO Created debug_info Asset:
azureml://locations/eastus/workspaces/00000/data/azureml_run2_output_data_debug_info/versions/1\n2024-01-12
08:56:04 +0000 6515 promptflow-runtime INFO Creating unregistered output
Asset for Run run2...\n2024-01-12 08:56:05 +0000 6515 promptflow-runtime
INFO Created flow_outputs output Asset: azureml://locations/eastus/workspaces/00000/data/azureml_run2_output_data_flow_outputs/versions/1\n2024-01-12
08:56:05 +0000 6515 promptflow-runtime INFO Creating Artifact for Run
run2...\n2024-01-12 08:56:05 +0000 6515 promptflow-runtime INFO Created
instance_results.jsonl Artifact.\n2024-01-12 08:56:05 +0000 6515 promptflow-runtime
INFO Patching run2...\n2024-01-12 08:56:05 +0000 6515 promptflow-runtime
WARNING [run2] Run failed. Execution stackTrace: Traceback (most recent call
last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n [REDACTED:
External StackTrace]\n\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n [REDACTED:
External StackTrace]\n\n2024-01-12 08:56:05 +0000 6515 promptflow-runtime
INFO Ending the aml run ''run2'' with status ''Completed''...\n2024-01-12
08:56:06 +0000 49 promptflow-runtime INFO Process 6515 finished\n2024-01-12
08:56:06 +0000 49 promptflow-runtime INFO [49] Child process finished!\n2024-01-12
08:56:06 +0000 49 promptflow-runtime INFO [run2] End processing bulk
run\n2024-01-12 08:56:06 +0000 49 promptflow-runtime INFO Cleanup
working dir /mnt/host/service/app/39649/requests/run2 for bulk run\n"'
headers:
connection:
- keep-alive
content-length:
- '22442'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.427'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_flow_operations_TestFlow_test_get_flow.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.024'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.146'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceworkingdirectory
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceworkingdirectory",
"name": "workspaceworkingdirectory", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
false, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureFile", "accountName": "fake_account_name",
"fileShareName": "fake-file-share-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "None"}, "systemData": {"createdAt":
"2023-04-08T02:53:06.6001169+00:00", "createdBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"createdByType": "Application", "lastModifiedAt": "2023-04-08T02:53:07.2885525+00:00",
"lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a", "lastModifiedByType":
"Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1161'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.088'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceworkingdirectory/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.145'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 03:10:07 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- inherit
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/LocalUpload?restype=directory
response:
body:
string: "\uFEFF<?xml version=\"1.0\" encoding=\"utf-8\"?><Error><Code>ResourceAlreadyExists</Code><Message>The
specified resource already exists.\nRequestId:494627b8-e01a-00db-2b04-45cbb1000000\nTime:2024-01-12T03:10:08.5872550Z</Message></Error>"
headers:
content-length:
- '228'
content-type:
- application/xml
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-error-code:
- ResourceAlreadyExists
x-ms-version:
- '2023-08-03'
status:
code: 409
message: The specified resource already exists.
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 03:10:09 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- inherit
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users?restype=directory
response:
body:
string: "\uFEFF<?xml version=\"1.0\" encoding=\"utf-8\"?><Error><Code>ResourceAlreadyExists</Code><Message>The
specified resource already exists.\nRequestId:2015fefb-201a-0099-7a04-457231000000\nTime:2024-01-12T03:10:10.8558247Z</Message></Error>"
headers:
content-length:
- '228'
content-type:
- application/xml
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-error-code:
- ResourceAlreadyExists
x-ms-version:
- '2023-08-03'
status:
code: 409
message: The specified resource already exists.
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 03:10:10 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- inherit
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users%2Funknown_user?restype=directory
response:
body:
string: "\uFEFF<?xml version=\"1.0\" encoding=\"utf-8\"?><Error><Code>ResourceAlreadyExists</Code><Message>The
specified resource already exists.\nRequestId:e91ceca5-f01a-007e-3004-459dcb000000\nTime:2024-01-12T03:10:11.9389239Z</Message></Error>"
headers:
content-length:
- '228'
content-type:
- application/xml
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-error-code:
- ResourceAlreadyExists
x-ms-version:
- '2023-08-03'
status:
code: 409
message: The specified resource already exists.
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 03:10:12 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- inherit
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users%2Funknown_user%2Fpromptflow?restype=directory
response:
body:
string: "\uFEFF<?xml version=\"1.0\" encoding=\"utf-8\"?><Error><Code>ResourceAlreadyExists</Code><Message>The
specified resource already exists.\nRequestId:dc666209-a01a-0073-2104-45551f000000\nTime:2024-01-12T03:10:12.9765801Z</Message></Error>"
headers:
content-length:
- '228'
content-type:
- application/xml
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-error-code:
- ResourceAlreadyExists
x-ms-version:
- '2023-08-03'
status:
code: 409
message: The specified resource already exists.
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 03:10:13 GMT
x-ms-version:
- '2023-08-03'
method: GET
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users%2Funknown_user%2Fpromptflow%2Fflow_name?restype=directory
response:
body:
string: "\uFEFF<?xml version=\"1.0\" encoding=\"utf-8\"?><Error><Code>ResourceNotFound</Code><Message>The
specified resource does not exist.\nRequestId:37a5a67c-001a-00ec-2304-45191d000000\nTime:2024-01-12T03:10:14.0112840Z</Message></Error>"
headers:
content-length:
- '223'
content-type:
- application/xml
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-error-code:
- ResourceNotFound
x-ms-version:
- '2023-08-03'
status:
code: 404
message: The specified resource does not exist.
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 03:10:14 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- inherit
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users%2Funknown_user%2Fpromptflow%2Fflow_name?restype=directory
response:
body:
string: ''
headers:
content-length:
- '0'
last-modified:
- Fri, 12 Jan 2024 03:10:15 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-attributes:
- Directory
x-ms-file-change-time:
- '2024-01-12T03:10:15.0262208Z'
x-ms-file-creation-time:
- '2024-01-12T03:10:15.0262208Z'
x-ms-file-id:
- '13835129046796599296'
x-ms-file-last-write-time:
- '2024-01-12T03:10:15.0262208Z'
x-ms-file-parent-id:
- '10088082484072808448'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 03:10:15 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- inherit
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users%2Funknown_user%2Fpromptflow%2Fflow_name%2F__pycache__?restype=directory
response:
body:
string: ''
headers:
content-length:
- '0'
last-modified:
- Fri, 12 Jan 2024 03:10:16 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-attributes:
- Directory
x-ms-file-change-time:
- '2024-01-12T03:10:16.0895486Z'
x-ms-file-creation-time:
- '2024-01-12T03:10:16.0895486Z'
x-ms-file-id:
- '13835093862424510464'
x-ms-file-last-write-time:
- '2024-01-12T03:10:16.0895486Z'
x-ms-file-parent-id:
- '13835129046796599296'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-content-length:
- '14'
x-ms-date:
- Fri, 12 Jan 2024 03:10:16 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- Inherit
x-ms-type:
- file
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users/unknown_user/promptflow/flow_name/.gitattributes
response:
body:
string: ''
headers:
content-length:
- '0'
last-modified:
- Fri, 12 Jan 2024 03:10:17 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-attributes:
- Archive
x-ms-file-change-time:
- '2024-01-12T03:10:17.0911484Z'
x-ms-file-creation-time:
- '2024-01-12T03:10:17.0911484Z'
x-ms-file-id:
- '13835164231168688128'
x-ms-file-last-write-time:
- '2024-01-12T03:10:17.0911484Z'
x-ms-file-parent-id:
- '13835129046796599296'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: '* text eol=lf
'
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '14'
Content-MD5:
- nYmkCopuDuFj82431amzZw==
Content-Type:
- application/octet-stream
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 03:10:17 GMT
x-ms-range:
- bytes=0-13
x-ms-version:
- '2023-08-03'
x-ms-write:
- update
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users/unknown_user/promptflow/flow_name/.gitattributes?comp=range
response:
body:
string: ''
headers:
content-length:
- '0'
content-md5:
- nYmkCopuDuFj82431amzZw==
last-modified:
- Fri, 12 Jan 2024 03:10:18 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-last-write-time:
- '2024-01-12T03:10:18.1285902Z'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-content-length:
- '250'
x-ms-date:
- Fri, 12 Jan 2024 03:10:18 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- Inherit
x-ms-type:
- file
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users/unknown_user/promptflow/flow_name/flow.dag.yaml
response:
body:
string: ''
headers:
content-length:
- '0'
last-modified:
- Fri, 12 Jan 2024 03:10:19 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-attributes:
- Archive
x-ms-file-change-time:
- '2024-01-12T03:10:19.1789755Z'
x-ms-file-creation-time:
- '2024-01-12T03:10:19.1789755Z'
x-ms-file-id:
- '13835076270238466048'
x-ms-file-last-write-time:
- '2024-01-12T03:10:19.1789755Z'
x-ms-file-parent-id:
- '13835129046796599296'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: "inputs:\n name:\n type: string\n default: hod\noutputs:\n result:\n
\ type: string\n reference: ${hello_world.output}\nnodes:\n- name: hello_world\n
\ type: python\n source:\n type: code\n path: hello_world.py\n inputs:\n
\ name: ${inputs.name}\n"
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '250'
Content-MD5:
- CT1FTZp5JScB8fq+HjnINw==
Content-Type:
- application/octet-stream
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 03:10:19 GMT
x-ms-range:
- bytes=0-249
x-ms-version:
- '2023-08-03'
x-ms-write:
- update
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users/unknown_user/promptflow/flow_name/flow.dag.yaml?comp=range
response:
body:
string: ''
headers:
content-length:
- '0'
content-md5:
- CT1FTZp5JScB8fq+HjnINw==
last-modified:
- Fri, 12 Jan 2024 03:10:20 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-last-write-time:
- '2024-01-12T03:10:20.2164176Z'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-content-length:
- '105'
x-ms-date:
- Fri, 12 Jan 2024 03:10:20 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- Inherit
x-ms-type:
- file
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users/unknown_user/promptflow/flow_name/hello_world.py
response:
body:
string: ''
headers:
content-length:
- '0'
last-modified:
- Fri, 12 Jan 2024 03:10:21 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-attributes:
- Archive
x-ms-file-change-time:
- '2024-01-12T03:10:21.2658070Z'
x-ms-file-creation-time:
- '2024-01-12T03:10:21.2658070Z'
x-ms-file-id:
- '13835146638982643712'
x-ms-file-last-write-time:
- '2024-01-12T03:10:21.2658070Z'
x-ms-file-parent-id:
- '13835129046796599296'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: "from promptflow import tool\n\n\n@tool\ndef hello_world(name: str) -> str:\n
\ return f\"Hello World {name}!\"\n"
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '105'
Content-MD5:
- fGMkkiZAjGs8PW/AMiYppA==
Content-Type:
- application/octet-stream
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 03:10:21 GMT
x-ms-range:
- bytes=0-104
x-ms-version:
- '2023-08-03'
x-ms-write:
- update
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users/unknown_user/promptflow/flow_name/hello_world.py?comp=range
response:
body:
string: ''
headers:
content-length:
- '0'
content-md5:
- fGMkkiZAjGs8PW/AMiYppA==
last-modified:
- Fri, 12 Jan 2024 03:10:22 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-last-write-time:
- '2024-01-12T03:10:22.2823416Z'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: '{"flowName": "flow_display_name", "description": "test flow description",
"tags": {"owner": "sdk-test"}, "flowDefinitionFilePath": "Users/unknown_user/promptflow/flow_name/flow.dag.yaml",
"flowType": "default"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '282'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/Flows
response:
body:
string: '{"eTag": {}, "studioPortalEndpoint": "https://ml.azure.com/prompts/flow/3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/b7731056-ea64-481e-ad53-c45f2363c29a/details?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"flowId": "b7731056-ea64-481e-ad53-c45f2363c29a", "flowName": "flow_display_name",
"description": "test flow description", "tags": {"owner": "sdk-test"}, "flowType":
"Default", "experimentId": "00000000-0000-0000-0000-000000000000", "createdDate":
"2024-01-12T03:10:24.9118275Z", "lastModifiedDate": "2024-01-12T03:10:24.9118275Z",
"owner": {"userObjectId": "00000000-0000-0000-0000-000000000000", "userTenantId":
"00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587"},
"flowResourceId": "azureml://locations/eastus/workspaces/00000/flows/b7731056-ea64-481e-ad53-c45f2363c29a",
"isArchived": false, "flowDefinitionFilePath": "Users/unknown_user/promptflow/flow_name/flow.dag.yaml"}'
headers:
connection:
- keep-alive
content-length:
- '1100'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.569'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 03:10:25 GMT
x-ms-version:
- '2023-08-03'
method: HEAD
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users/unknown_user/promptflow/flow_name/flow.dag.yaml
response:
body:
string: ''
headers:
content-length:
- '250'
content-type:
- application/octet-stream
last-modified:
- Fri, 12 Jan 2024 03:10:20 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-attributes:
- Archive
x-ms-file-change-time:
- '2024-01-12T03:10:20.2164176Z'
x-ms-file-creation-time:
- '2024-01-12T03:10:19.1789755Z'
x-ms-file-id:
- '13835076270238466048'
x-ms-file-last-write-time:
- '2024-01-12T03:10:20.2164176Z'
x-ms-file-parent-id:
- '13835129046796599296'
x-ms-type:
- File
x-ms-version:
- '2023-08-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/Flows/b7731056-ea64-481e-ad53-c45f2363c29a?experimentId=00000000-0000-0000-0000-000000000000
response:
body:
string: '{"timestamp": "2024-01-12T03:10:24.9429158+00:00", "eTag": {}, "studioPortalEndpoint":
"https://ml.azure.com/prompts/flow/3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/b7731056-ea64-481e-ad53-c45f2363c29a/details?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"flowId": "b7731056-ea64-481e-ad53-c45f2363c29a", "flowName": "flow_display_name",
"description": "test flow description", "tags": {"owner": "sdk-test"}, "flowType":
"Default", "experimentId": "00000000-0000-0000-0000-000000000000", "createdDate":
"2024-01-12T03:10:24.9118275Z", "lastModifiedDate": "2024-01-12T03:10:24.9118275Z",
"owner": {"userObjectId": "00000000-0000-0000-0000-000000000000", "userTenantId":
"00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587"},
"flowResourceId": "azureml://locations/eastus/workspaces/00000/flows/b7731056-ea64-481e-ad53-c45f2363c29a",
"isArchived": false, "flowDefinitionFilePath": "Users/unknown_user/promptflow/flow_name/flow.dag.yaml"}'
headers:
connection:
- keep-alive
content-length:
- '1148'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.541'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_show_run_details.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.023'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.077'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.110'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.150'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 07:54:16 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/webClassification3.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '379'
content-md5:
- lI/pz9jzTQ7Td3RHPL7y7w==
content-type:
- application/octet-stream
last-modified:
- Mon, 06 Nov 2023 08:30:18 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Mon, 06 Nov 2023 08:30:18 GMT
x-ms-meta-name:
- 94331215-cf7f-452a-9f1a-1d276bc9b0e4
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 3f163752-edb0-4afc-a6f5-b0a670bd7c24
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 07:54:17 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/webClassification3.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.079'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.122'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 07:54:19 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/hello-world/flow.dag.yaml
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '266'
content-md5:
- UZm3TyOoKWjSR23+Up6qUA==
content-type:
- application/octet-stream
last-modified:
- Tue, 19 Dec 2023 06:05:25 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Tue, 19 Dec 2023 06:05:25 GMT
x-ms-meta-name:
- 7b68bf5e-6ef4-4eb3-9f49-28f9a5baad87
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 07:54:21 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/hello-world/flow.dag.yaml
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/hello-world/flow.dag.yaml",
"runId": "batch_run_name", "runDisplayName": "sdk-cli-test-fixture-batch-run-without-llm",
"runExperimentName": "", "batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/webClassification3.jsonl"},
"inputsMapping": {"name": "${data.url}"}, "connections": {}, "environmentVariables":
{}, "runtimeName": "fake-runtime-name", "sessionId": "000000000000000000000000000000000000000000000000",
"sessionSetupMode": "SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '812'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"batch_run_name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '6.861'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "hello_world", "type": "python",
"source": {"type": "code", "path": "hello_world.py"}, "inputs": {"name": "${inputs.name}"},
"tool": "hello_world.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "hello_world.py", "type": "python",
"inputs": {"name": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "hello_world.py", "function":
"hello_world", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"name": {"type": "string", "default": "hod", "is_chat_input":
false}}, "outputs": {"result": {"type": "string", "reference": "${hello_world.output}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/batch_run_name/flowRuns/batch_run_name",
"flowRunId": "batch_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-batch-run-without-llm",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"name": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/batch_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "85a4b96f-edcb-4164-acea-98bd08d40e22",
"studioPortalEndpoint": "https://ml.azure.com/runs/batch_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12912'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.509'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "hello_world", "type": "python",
"source": {"type": "code", "path": "hello_world.py"}, "inputs": {"name": "${inputs.name}"},
"tool": "hello_world.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "hello_world.py", "type": "python",
"inputs": {"name": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "hello_world.py", "function":
"hello_world", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"name": {"type": "string", "default": "hod", "is_chat_input":
false}}, "outputs": {"result": {"type": "string", "reference": "${hello_world.output}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/batch_run_name/flowRuns/batch_run_name",
"flowRunId": "batch_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-batch-run-without-llm",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"name": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/batch_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "85a4b96f-edcb-4164-acea-98bd08d40e22",
"studioPortalEndpoint": "https://ml.azure.com/runs/batch_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12912'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.406'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "hello_world", "type": "python",
"source": {"type": "code", "path": "hello_world.py"}, "inputs": {"name": "${inputs.name}"},
"tool": "hello_world.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAACgElEQVR4nGWSz2vcVRTFP/e9NzOZ1KDGohASslLEH6VLV0ak4l/QpeDCrfQPcNGliODKnVm4EBdBsIjQIlhciKW0ycKFVCSNbYnjdDLtmPnmO/nO9917XcxMkjYX3uLx7nnn3HOuMK2Nix4fP78ZdrYXVkLVWjf3l3B1B+HpcjzGFtmqa6cePz7/x0dnn1n5qhj3iBJPYREIURAJuCtpY8PjReDbrf9WG7H1fuefwQU9qKztTcMJT+PNnEFvjGVDBDlSsH6p/9MLzy6+NxwVqI8RAg4IPmWedMckdLYP6O6UpIaQfvyyXG012+e79/ZfHukoS1ISMT2hGTB1RkUmNgQ5QZ0w+a2VWDq73MbdEWmfnnv6UWe7oNzPaLapl5CwuLTXK9WUGBuCjqekzhP+z52ZXOrKMD3OJg0Hh778aiOuvpnYvp05d6GJO4iAO4QAe/eV36/X5LFRV4Zmn+AdkqlL8Vjp3oVioOz+WTPzzYEgsN+fgPLYyJVheSbPPVl2ikeGZRjtG52/8rHuaV9VOlpP2OtKyVndcRVCSqOhsvxa4vW359i6OuKdD+aP8Q4SYPdOzS/flGjt1JUSaMqZ5nwa1Y8qWb/Ud/eZZkHisYezEM0m+fcelDr8F1SqW2LNK6r1jXQwyLzy1hxvrLXZulry7ocL+FS6G4QIu3fG/Px1gdYeW7LIgXU2P/115TOA5G7e3Rmj2aS/m7l5pThiZzrCcE/d1XHzbln373nw7y6veeoUm5KCNKT/IPPwbiY1hYd/l5MIT65BMFt87sU4v9D7/JMflr44uV6hGh1+L4RCkg6z5iK2tAhNLeLsNGwYA4fDYnC/drvuuFxe86NV/x+Ut27g0FvykgAAAABJRU5ErkJggg==",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "hello_world.py", "type": "python",
"inputs": {"name": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "hello_world.py", "function":
"hello_world", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"name": {"type": "string", "default": "hod", "is_chat_input":
false}}, "outputs": {"result": {"type": "string", "reference": "${hello_world.output}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/batch_run_name/flowRuns/batch_run_name",
"flowRunId": "batch_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-batch-run-without-llm",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"name": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/batch_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "85a4b96f-edcb-4164-acea-98bd08d40e22",
"studioPortalEndpoint": "https://ml.azure.com/runs/batch_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12912'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.537'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "hello_world", "type": "python",
"source": {"type": "code", "path": "hello_world.py"}, "inputs": {"name": "${inputs.name}"},
"tool": "hello_world.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAACgElEQVR4nGWSz2vcVRTFP/e9NzOZ1KDGohASslLEH6VLV0ak4l/QpeDCrfQPcNGliODKnVm4EBdBsIjQIlhciKW0ycKFVCSNbYnjdDLtmPnmO/nO9917XcxMkjYX3uLx7nnn3HOuMK2Nix4fP78ZdrYXVkLVWjf3l3B1B+HpcjzGFtmqa6cePz7/x0dnn1n5qhj3iBJPYREIURAJuCtpY8PjReDbrf9WG7H1fuefwQU9qKztTcMJT+PNnEFvjGVDBDlSsH6p/9MLzy6+NxwVqI8RAg4IPmWedMckdLYP6O6UpIaQfvyyXG012+e79/ZfHukoS1ISMT2hGTB1RkUmNgQ5QZ0w+a2VWDq73MbdEWmfnnv6UWe7oNzPaLapl5CwuLTXK9WUGBuCjqekzhP+z52ZXOrKMD3OJg0Hh778aiOuvpnYvp05d6GJO4iAO4QAe/eV36/X5LFRV4Zmn+AdkqlL8Vjp3oVioOz+WTPzzYEgsN+fgPLYyJVheSbPPVl2ikeGZRjtG52/8rHuaV9VOlpP2OtKyVndcRVCSqOhsvxa4vW359i6OuKdD+aP8Q4SYPdOzS/flGjt1JUSaMqZ5nwa1Y8qWb/Ud/eZZkHisYezEM0m+fcelDr8F1SqW2LNK6r1jXQwyLzy1hxvrLXZulry7ocL+FS6G4QIu3fG/Px1gdYeW7LIgXU2P/115TOA5G7e3Rmj2aS/m7l5pThiZzrCcE/d1XHzbln373nw7y6veeoUm5KCNKT/IPPwbiY1hYd/l5MIT65BMFt87sU4v9D7/JMflr44uV6hGh1+L4RCkg6z5iK2tAhNLeLsNGwYA4fDYnC/drvuuFxe86NV/x+Ut27g0FvykgAAAABJRU5ErkJggg==",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "hello_world.py", "type": "python",
"inputs": {"name": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "hello_world.py", "function":
"hello_world", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"name": {"type": "string", "default": "hod", "is_chat_input":
false}}, "outputs": {"result": {"type": "string", "reference": "${hello_world.output}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/batch_run_name/flowRuns/batch_run_name",
"flowRunId": "batch_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-batch-run-without-llm",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"name": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/batch_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "85a4b96f-edcb-4164-acea-98bd08d40e22",
"studioPortalEndpoint": "https://ml.azure.com/runs/batch_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12912'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.221'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "hello_world", "type": "python",
"source": {"type": "code", "path": "hello_world.py"}, "inputs": {"name": "${inputs.name}"},
"tool": "hello_world.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "hello_world.py", "type": "python",
"inputs": {"name": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "hello_world.py", "function":
"hello_world", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"name": {"type": "string", "default": "hod", "is_chat_input":
false}}, "outputs": {"result": {"type": "string", "reference": "${hello_world.output}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/batch_run_name/flowRuns/batch_run_name",
"flowRunId": "batch_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-batch-run-without-llm",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"name": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/batch_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "85a4b96f-edcb-4164-acea-98bd08d40e22",
"studioPortalEndpoint": "https://ml.azure.com/runs/batch_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12912'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.192'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name/childRuns?endIndex=24&startIndex=0
response:
body:
string: '[{"run_id": "batch_run_name_0", "status": "Completed", "error": null,
"inputs": {"name": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "line_number":
0}, "output": {"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"},
"metrics": null, "request": null, "parent_run_id": "batch_run_name", "root_run_id":
"batch_run_name", "source_run_id": null, "flow_id": "default_flow_id", "start_time":
"2024-01-12T07:54:44.493902Z", "end_time": "2024-01-12T07:54:44.50176Z", "index":
0, "api_calls": [{"name": "hello_world", "type": "Tool", "inputs": {"name":
"https://www.youtube.com/watch?v=o5ZQyXaAv1g"}, "output": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!",
"start_time": 1705046084.496958, "end_time": 1705046084.497766, "error": null,
"children": null, "node_name": "hello_world"}], "variant_id": "", "name":
"", "description": "", "tags": null, "system_metrics": {"duration": 0.007858,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"}, "upload_metrics":
false}, {"run_id": "batch_run_name_1", "status": "Completed", "error": null,
"inputs": {"name": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "line_number":
1}, "output": {"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"},
"metrics": null, "request": null, "parent_run_id": "batch_run_name", "root_run_id":
"batch_run_name", "source_run_id": null, "flow_id": "default_flow_id", "start_time":
"2024-01-12T07:54:44.50188Z", "end_time": "2024-01-12T07:54:44.507707Z", "index":
1, "api_calls": [{"name": "hello_world", "type": "Tool", "inputs": {"name":
"https://www.youtube.com/watch?v=o5ZQyXaAv1g"}, "output": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!",
"start_time": 1705046084.504962, "end_time": 1705046084.505848, "error": null,
"children": null, "node_name": "hello_world"}], "variant_id": "", "name":
"", "description": "", "tags": null, "system_metrics": {"duration": 0.005827,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"}, "upload_metrics":
false}, {"run_id": "batch_run_name_2", "status": "Completed", "error": null,
"inputs": {"name": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "line_number":
2}, "output": {"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"},
"metrics": null, "request": null, "parent_run_id": "batch_run_name", "root_run_id":
"batch_run_name", "source_run_id": null, "flow_id": "default_flow_id", "start_time":
"2024-01-12T07:54:44.620862Z", "end_time": "2024-01-12T07:54:44.62622Z", "index":
2, "api_calls": [{"name": "hello_world", "type": "Tool", "inputs": {"name":
"https://www.youtube.com/watch?v=o5ZQyXaAv1g"}, "output": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!",
"start_time": 1705046084.623683, "end_time": 1705046084.624476, "error": null,
"children": null, "node_name": "hello_world"}], "variant_id": "", "name":
"", "description": "", "tags": null, "system_metrics": {"duration": 0.005358,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"}, "upload_metrics":
false}]'
headers:
connection:
- keep-alive
content-length:
- '3229'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.825'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "hello_world", "type": "python",
"source": {"type": "code", "path": "hello_world.py"}, "inputs": {"name": "${inputs.name}"},
"tool": "hello_world.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "hello_world.py", "type": "python",
"inputs": {"name": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "hello_world.py", "function":
"hello_world", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"name": {"type": "string", "default": "hod", "is_chat_input":
false}}, "outputs": {"result": {"type": "string", "reference": "${hello_world.output}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/batch_run_name/flowRuns/batch_run_name",
"flowRunId": "batch_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-batch-run-without-llm",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"name": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/batch_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "85a4b96f-edcb-4164-acea-98bd08d40e22",
"studioPortalEndpoint": "https://ml.azure.com/runs/batch_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12912'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.266'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name/childRuns?endIndex=24&startIndex=0
response:
body:
string: '[{"run_id": "batch_run_name_0", "status": "Completed", "error": null,
"inputs": {"name": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "line_number":
0}, "output": {"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"},
"metrics": null, "request": null, "parent_run_id": "batch_run_name", "root_run_id":
"batch_run_name", "source_run_id": null, "flow_id": "default_flow_id", "start_time":
"2024-01-12T07:54:44.493902Z", "end_time": "2024-01-12T07:54:44.50176Z", "index":
0, "api_calls": [{"name": "hello_world", "type": "Tool", "inputs": {"name":
"https://www.youtube.com/watch?v=o5ZQyXaAv1g"}, "output": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!",
"start_time": 1705046084.496958, "end_time": 1705046084.497766, "error": null,
"children": null, "node_name": "hello_world"}], "variant_id": "", "name":
"", "description": "", "tags": null, "system_metrics": {"duration": 0.007858,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"}, "upload_metrics":
false}, {"run_id": "batch_run_name_1", "status": "Completed", "error": null,
"inputs": {"name": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "line_number":
1}, "output": {"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"},
"metrics": null, "request": null, "parent_run_id": "batch_run_name", "root_run_id":
"batch_run_name", "source_run_id": null, "flow_id": "default_flow_id", "start_time":
"2024-01-12T07:54:44.50188Z", "end_time": "2024-01-12T07:54:44.507707Z", "index":
1, "api_calls": [{"name": "hello_world", "type": "Tool", "inputs": {"name":
"https://www.youtube.com/watch?v=o5ZQyXaAv1g"}, "output": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!",
"start_time": 1705046084.504962, "end_time": 1705046084.505848, "error": null,
"children": null, "node_name": "hello_world"}], "variant_id": "", "name":
"", "description": "", "tags": null, "system_metrics": {"duration": 0.005827,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"}, "upload_metrics":
false}, {"run_id": "batch_run_name_2", "status": "Completed", "error": null,
"inputs": {"name": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "line_number":
2}, "output": {"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"},
"metrics": null, "request": null, "parent_run_id": "batch_run_name", "root_run_id":
"batch_run_name", "source_run_id": null, "flow_id": "default_flow_id", "start_time":
"2024-01-12T07:54:44.620862Z", "end_time": "2024-01-12T07:54:44.62622Z", "index":
2, "api_calls": [{"name": "hello_world", "type": "Tool", "inputs": {"name":
"https://www.youtube.com/watch?v=o5ZQyXaAv1g"}, "output": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!",
"start_time": 1705046084.623683, "end_time": 1705046084.624476, "error": null,
"children": null, "node_name": "hello_world"}], "variant_id": "", "name":
"", "description": "", "tags": null, "system_metrics": {"duration": 0.005358,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"}, "upload_metrics":
false}]'
headers:
connection:
- keep-alive
content-length:
- '3229'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.920'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "hello_world", "type": "python",
"source": {"type": "code", "path": "hello_world.py"}, "inputs": {"name": "${inputs.name}"},
"tool": "hello_world.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "hello_world.py", "type": "python",
"inputs": {"name": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "hello_world.py", "function":
"hello_world", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"name": {"type": "string", "default": "hod", "is_chat_input":
false}}, "outputs": {"result": {"type": "string", "reference": "${hello_world.output}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/batch_run_name/flowRuns/batch_run_name",
"flowRunId": "batch_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-batch-run-without-llm",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"name": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/batch_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "85a4b96f-edcb-4164-acea-98bd08d40e22",
"studioPortalEndpoint": "https://ml.azure.com/runs/batch_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12912'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.210'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name/childRuns?endIndex=24&startIndex=0
response:
body:
string: '[{"run_id": "batch_run_name_0", "status": "Completed", "error": null,
"inputs": {"name": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "line_number":
0}, "output": {"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"},
"metrics": null, "request": null, "parent_run_id": "batch_run_name", "root_run_id":
"batch_run_name", "source_run_id": null, "flow_id": "default_flow_id", "start_time":
"2024-01-12T07:54:44.493902Z", "end_time": "2024-01-12T07:54:44.50176Z", "index":
0, "api_calls": [{"name": "hello_world", "type": "Tool", "inputs": {"name":
"https://www.youtube.com/watch?v=o5ZQyXaAv1g"}, "output": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!",
"start_time": 1705046084.496958, "end_time": 1705046084.497766, "error": null,
"children": null, "node_name": "hello_world"}], "variant_id": "", "name":
"", "description": "", "tags": null, "system_metrics": {"duration": 0.007858,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"}, "upload_metrics":
false}, {"run_id": "batch_run_name_1", "status": "Completed", "error": null,
"inputs": {"name": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "line_number":
1}, "output": {"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"},
"metrics": null, "request": null, "parent_run_id": "batch_run_name", "root_run_id":
"batch_run_name", "source_run_id": null, "flow_id": "default_flow_id", "start_time":
"2024-01-12T07:54:44.50188Z", "end_time": "2024-01-12T07:54:44.507707Z", "index":
1, "api_calls": [{"name": "hello_world", "type": "Tool", "inputs": {"name":
"https://www.youtube.com/watch?v=o5ZQyXaAv1g"}, "output": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!",
"start_time": 1705046084.504962, "end_time": 1705046084.505848, "error": null,
"children": null, "node_name": "hello_world"}], "variant_id": "", "name":
"", "description": "", "tags": null, "system_metrics": {"duration": 0.005827,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"}, "upload_metrics":
false}, {"run_id": "batch_run_name_2", "status": "Completed", "error": null,
"inputs": {"name": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "line_number":
2}, "output": {"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"},
"metrics": null, "request": null, "parent_run_id": "batch_run_name", "root_run_id":
"batch_run_name", "source_run_id": null, "flow_id": "default_flow_id", "start_time":
"2024-01-12T07:54:44.620862Z", "end_time": "2024-01-12T07:54:44.62622Z", "index":
2, "api_calls": [{"name": "hello_world", "type": "Tool", "inputs": {"name":
"https://www.youtube.com/watch?v=o5ZQyXaAv1g"}, "output": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!",
"start_time": 1705046084.623683, "end_time": 1705046084.624476, "error": null,
"children": null, "node_name": "hello_world"}], "variant_id": "", "name":
"", "description": "", "tags": null, "system_metrics": {"duration": 0.005358,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"}, "upload_metrics":
false}]'
headers:
connection:
- keep-alive
content-length:
- '3229'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '1.005'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name/childRuns?endIndex=49&startIndex=25
response:
body:
string: '[]'
headers:
connection:
- keep-alive
content-length:
- '2'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '0.708'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "hello_world", "type": "python",
"source": {"type": "code", "path": "hello_world.py"}, "inputs": {"name": "${inputs.name}"},
"tool": "hello_world.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "hello_world.py", "type": "python",
"inputs": {"name": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "hello_world.py", "function":
"hello_world", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"name": {"type": "string", "default": "hod", "is_chat_input":
false}}, "outputs": {"result": {"type": "string", "reference": "${hello_world.output}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/batch_run_name/flowRuns/batch_run_name",
"flowRunId": "batch_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-batch-run-without-llm",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"name": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/batch_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "85a4b96f-edcb-4164-acea-98bd08d40e22",
"studioPortalEndpoint": "https://ml.azure.com/runs/batch_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12912'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.214'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name/childRuns?endIndex=24&startIndex=0
response:
body:
string: '[{"run_id": "batch_run_name_0", "status": "Completed", "error": null,
"inputs": {"name": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "line_number":
0}, "output": {"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"},
"metrics": null, "request": null, "parent_run_id": "batch_run_name", "root_run_id":
"batch_run_name", "source_run_id": null, "flow_id": "default_flow_id", "start_time":
"2024-01-12T07:54:44.493902Z", "end_time": "2024-01-12T07:54:44.50176Z", "index":
0, "api_calls": [{"name": "hello_world", "type": "Tool", "inputs": {"name":
"https://www.youtube.com/watch?v=o5ZQyXaAv1g"}, "output": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!",
"start_time": 1705046084.496958, "end_time": 1705046084.497766, "error": null,
"children": null, "node_name": "hello_world"}], "variant_id": "", "name":
"", "description": "", "tags": null, "system_metrics": {"duration": 0.007858,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"}, "upload_metrics":
false}, {"run_id": "batch_run_name_1", "status": "Completed", "error": null,
"inputs": {"name": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "line_number":
1}, "output": {"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"},
"metrics": null, "request": null, "parent_run_id": "batch_run_name", "root_run_id":
"batch_run_name", "source_run_id": null, "flow_id": "default_flow_id", "start_time":
"2024-01-12T07:54:44.50188Z", "end_time": "2024-01-12T07:54:44.507707Z", "index":
1, "api_calls": [{"name": "hello_world", "type": "Tool", "inputs": {"name":
"https://www.youtube.com/watch?v=o5ZQyXaAv1g"}, "output": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!",
"start_time": 1705046084.504962, "end_time": 1705046084.505848, "error": null,
"children": null, "node_name": "hello_world"}], "variant_id": "", "name":
"", "description": "", "tags": null, "system_metrics": {"duration": 0.005827,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"}, "upload_metrics":
false}, {"run_id": "batch_run_name_2", "status": "Completed", "error": null,
"inputs": {"name": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "line_number":
2}, "output": {"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"},
"metrics": null, "request": null, "parent_run_id": "batch_run_name", "root_run_id":
"batch_run_name", "source_run_id": null, "flow_id": "default_flow_id", "start_time":
"2024-01-12T07:54:44.620862Z", "end_time": "2024-01-12T07:54:44.62622Z", "index":
2, "api_calls": [{"name": "hello_world", "type": "Tool", "inputs": {"name":
"https://www.youtube.com/watch?v=o5ZQyXaAv1g"}, "output": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!",
"start_time": 1705046084.623683, "end_time": 1705046084.624476, "error": null,
"children": null, "node_name": "hello_world"}], "variant_id": "", "name":
"", "description": "", "tags": null, "system_metrics": {"duration": 0.005358,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"result": "Hello World https://www.youtube.com/watch?v=o5ZQyXaAv1g!"}, "upload_metrics":
false}]'
headers:
connection:
- keep-alive
content-length:
- '3229'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.993'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name/childRuns?endIndex=49&startIndex=25
response:
body:
string: '[]'
headers:
connection:
- keep-alive
content-length:
- '2'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '0.748'
status:
code: 200
message: OK
- request:
body: '{"runId": "batch_run_name", "selectRunMetadata": true, "selectRunDefinition":
true, "selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705046067, "rootRunId": "batch_run_name",
"createdUtc": "2024-01-12T07:54:27.159305+00:00", "createdBy": {"userObjectId":
"00000000-0000-0000-0000-000000000000", "userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": null, "warnings": null, "revision": 6,
"statusRevision": 3, "runUuid": "605728ab-d8cb-4ce5-a40c-67625a2b9471", "parentRunUuid":
null, "rootRunUuid": "605728ab-d8cb-4ce5-a40c-67625a2b9471", "lastStartTimeUtc":
null, "currentComputeTime": null, "computeDuration": "00:00:03.6893368", "effectiveStartTimeUtc":
null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "18a66f5f-dbdf-4c17-9dd7-1634712a9cbe",
"upn": null}, "lastModifiedUtc": "2024-01-12T07:54:46.9642623+00:00", "duration":
"00:00:03.6893368", "cancelationReason": null, "currentAttemptId": 1, "runId":
"batch_run_name", "parentRunId": null, "experimentId": "b1e733a1-2a5f-4c17-bc34-4d66d2858228",
"status": "Completed", "startTimeUtc": "2024-01-12T07:54:44.1317315+00:00",
"endTimeUtc": "2024-01-12T07:54:47.8210683+00:00", "scheduleId": null, "displayName":
"sdk-cli-test-fixture-batch-run-without-llm", "name": null, "dataContainerId":
"dcid.batch_run_name", "description": null, "hidden": false, "runType": "azureml.promptflow.FlowRun",
"runTypeV2": {"orchestrator": null, "traits": [], "attribution": "PromptFlow",
"computeType": "AmlcDsi"}, "properties": {"azureml.promptflow.runtime_name":
"test-runtime-ci", "azureml.promptflow.runtime_version": "20231204.v4", "azureml.promptflow.definition_file_name":
"flow.dag.yaml", "azureml.promptflow.session_id": "bee356189f7e7f18671a79369c78df4cfb1bbd0c99069074",
"azureml.promptflow.flow_lineage_id": "f7ee724d91e4f4a7501bdc0b66995bc8b57f86b3a526fa2a81c34ebcccbbd912",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/36774154bc3ecde4aa21054b3052221f/hello-world/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl",
"azureml.promptflow.inputs_mapping": "{\"name\":\"${data.url}\"}", "_azureml.evaluation_run":
"promptflow.BatchRun", "azureml.promptflow.snapshot_id": "85a4b96f-edcb-4164-acea-98bd08d40e22",
"azureml.promptflow.total_tokens": "0", "_azureml.evaluate_artifacts": "[{\"path\":
\"instance_results.jsonl\", \"type\": \"table\"}]"}, "parameters": {}, "actionUris":
{}, "scriptName": null, "target": null, "uniqueChildRunComputeTargets": [],
"tags": {}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": {"debug_info": {"assetId":
"azureml://locations/eastus/workspaces/00000/data/azureml_batch_run_name_output_data_debug_info/versions/1",
"type": "UriFolder"}, "flow_outputs": {"assetId": "azureml://locations/eastus/workspaces/00000/data/azureml_batch_run_name_output_data_flow_outputs/versions/1",
"type": "UriFolder"}}}, "runDefinition": null, "jobSpecification": null, "systemSettings":
null}'
headers:
connection:
- keep-alive
content-length:
- '4648'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.041'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name/logContent
response:
body:
string: '"2024-01-12 07:54:31 +0000 49 promptflow-runtime INFO [batch_run_name]
Receiving v2 bulk run request a234ccdf-0cdb-4a6d-b615-45a49ec26dcc: {\"flow_id\":
\"batch_run_name\", \"flow_run_id\": \"batch_run_name\", \"flow_source\":
{\"flow_source_type\": 1, \"flow_source_info\": {\"snapshot_id\": \"85a4b96f-edcb-4164-acea-98bd08d40e22\"},
\"flow_dag_file\": \"flow.dag.yaml\"}, \"log_path\": \"https://promptfloweast4063704120.blob.core.windows.net/azureml/ExperimentRun/dcid.batch_run_name/logs/azureml/executionlogs.txt?sv=2019-07-07&sr=b&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T07%3A43%3A15Z&ske=2024-01-13T15%3A53%3A15Z&sks=b&skv=2019-07-07&st=2024-01-12T07%3A44%3A30Z&se=2024-01-12T15%3A54%3A30Z&sp=rcw\",
\"app_insights_instrumentation_key\": \"InstrumentationKey=**data_scrubbed**;IngestionEndpoint=https://eastus-6.in.applicationinsights.azure.com/;LiveEndpoint=https://eastus.livediagnostics.monitor.azure.com/\",
\"data_inputs\": {\"data\": \"azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl\"},
\"inputs_mapping\": {\"name\": \"${data.url}\"}, \"azure_storage_setting\":
{\"azure_storage_mode\": 1, \"storage_account_name\": \"promptfloweast4063704120\",
\"blob_container_name\": \"azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5\",
\"flow_artifacts_root_path\": \"promptflow/PromptFlowArtifacts/batch_run_name\",
\"blob_container_sas_token\": \"?sv=2019-07-07&sr=c&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T07%3A54%3A31Z&ske=2024-01-19T07%3A54%3A31Z&sks=b&skv=2019-07-07&se=2024-01-19T07%3A54%3A31Z&sp=racwl\",
\"output_datastore_name\": \"workspaceblobstore\"}}\n2024-01-12 07:54:31 +0000 49
promptflow-runtime INFO Runtime version: 20231204.v4. PromptFlow version:
1.2.0rc1\n2024-01-12 07:54:31 +0000 49 promptflow-runtime INFO Updating
batch_run_name to Status.Preparing...\n2024-01-12 07:54:31 +0000 49 promptflow-runtime
INFO Downloading snapshot to /mnt/host/service/app/39649/requests/batch_run_name\n2024-01-12
07:54:32 +0000 49 promptflow-runtime INFO Get snapshot sas url for
85a4b96f-edcb-4164-acea-98bd08d40e22...\n2024-01-12 07:54:38 +0000 49
promptflow-runtime INFO Downloading snapshot 85a4b96f-edcb-4164-acea-98bd08d40e22
from uri https://promptfloweast4063704120.blob.core.windows.net/snapshotzips/promptflow-eastus:3e123da1-f9a5-4c91-9234-8d9ffbb39ff5:snapshotzip/85a4b96f-edcb-4164-acea-98bd08d40e22.zip...\n2024-01-12
07:54:38 +0000 49 promptflow-runtime INFO Downloaded file /mnt/host/service/app/39649/requests/batch_run_name/85a4b96f-edcb-4164-acea-98bd08d40e22.zip
with size 495 for snapshot 85a4b96f-edcb-4164-acea-98bd08d40e22.\n2024-01-12
07:54:38 +0000 49 promptflow-runtime INFO Download snapshot 85a4b96f-edcb-4164-acea-98bd08d40e22
completed.\n2024-01-12 07:54:38 +0000 49 promptflow-runtime INFO Successfully
download snapshot to /mnt/host/service/app/39649/requests/batch_run_name\n2024-01-12
07:54:38 +0000 49 promptflow-runtime INFO About to execute a python
flow.\n2024-01-12 07:54:38 +0000 49 promptflow-runtime INFO Use spawn
method to start child process.\n2024-01-12 07:54:38 +0000 49 promptflow-runtime
INFO Starting to check process 3015 status for run batch_run_name\n2024-01-12
07:54:38 +0000 49 promptflow-runtime INFO Start checking run status
for run batch_run_name\n2024-01-12 07:54:42 +0000 3015 promptflow-runtime
INFO [49--3015] Start processing flowV2......\n2024-01-12 07:54:42 +0000 3015
promptflow-runtime INFO Runtime version: 20231204.v4. PromptFlow version:
1.2.0rc1\n2024-01-12 07:54:42 +0000 3015 promptflow-runtime INFO Setting
mlflow tracking uri...\n2024-01-12 07:54:42 +0000 3015 promptflow-runtime
INFO Validating ''AzureML Data Scientist'' user authentication...\n2024-01-12
07:54:43 +0000 3015 promptflow-runtime INFO Successfully validated
''AzureML Data Scientist'' user authentication.\n2024-01-12 07:54:43 +0000 3015
promptflow-runtime INFO Using AzureMLRunStorageV2\n2024-01-12 07:54:43
+0000 3015 promptflow-runtime INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
07:54:43 +0000 3015 promptflow-runtime INFO Initialized blob service
client for AzureMLRunTracker.\n2024-01-12 07:54:43 +0000 3015 promptflow-runtime
INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
07:54:43 +0000 3015 promptflow-runtime INFO Resolve data from url finished
in 0.5407421309500933 seconds\n2024-01-12 07:54:43 +0000 3015 promptflow-runtime
INFO Starting the aml run ''batch_run_name''...\n2024-01-12 07:54:44 +0000 3015
execution.bulk INFO Using fork, process count: 3\n2024-01-12 07:54:44
+0000 3062 execution.bulk INFO Process 3062 started.\n2024-01-12
07:54:44 +0000 3056 execution.bulk INFO Process 3056 started.\n2024-01-12
07:54:44 +0000 3015 execution.bulk INFO Process name: ForkProcess-36:3,
Process id: 3062, Line number: 0 start execution.\n2024-01-12 07:54:44 +0000 3015
execution.bulk INFO Process name: ForkProcess-36:2, Process id: 3056,
Line number: 1 start execution.\n2024-01-12 07:54:44 +0000 3015 execution.bulk INFO Process
name: ForkProcess-36:3, Process id: 3062, Line number: 0 completed.\n2024-01-12
07:54:44 +0000 3067 execution.bulk INFO Process 3067 started.\n2024-01-12
07:54:44 +0000 3015 execution.bulk INFO Finished 1 / 3 lines.\n2024-01-12
07:54:44 +0000 3015 execution.bulk INFO Process name: ForkProcess-36:4,
Process id: 3067, Line number: 2 start execution.\n2024-01-12 07:54:44 +0000 3015
execution.bulk INFO Average execution time for completed lines: 0.22
seconds. Estimated time for incomplete lines: 0.44 seconds.\n2024-01-12 07:54:44
+0000 3015 execution.bulk INFO Process name: ForkProcess-36:2,
Process id: 3056, Line number: 1 completed.\n2024-01-12 07:54:44 +0000 3015
execution.bulk INFO Finished 2 / 3 lines.\n2024-01-12 07:54:44 +0000 3015
execution.bulk INFO Average execution time for completed lines: 0.14
seconds. Estimated time for incomplete lines: 0.14 seconds.\n2024-01-12 07:54:44
+0000 3015 execution.bulk INFO Process name: ForkProcess-36:4,
Process id: 3067, Line number: 2 completed.\n2024-01-12 07:54:44 +0000 3015
execution.bulk INFO Finished 3 / 3 lines.\n2024-01-12 07:54:44 +0000 3015
execution.bulk INFO Average execution time for completed lines: 0.12
seconds. Estimated time for incomplete lines: 0.0 seconds.\n2024-01-12 07:54:46
+0000 3015 execution.bulk INFO Upload status summary metrics for
run batch_run_name finished in 1.1236545331776142 seconds\n2024-01-12 07:54:46
+0000 3015 promptflow-runtime INFO Successfully write run properties
{\"azureml.promptflow.total_tokens\": 0, \"_azureml.evaluate_artifacts\":
\"[{\\\"path\\\": \\\"instance_results.jsonl\\\", \\\"type\\\": \\\"table\\\"}]\"}
with run id ''batch_run_name''\n2024-01-12 07:54:46 +0000 3015 execution.bulk INFO Upload
RH properties for run batch_run_name finished in 0.07583864592015743 seconds\n2024-01-12
07:54:47 +0000 3015 promptflow-runtime INFO Creating unregistered output
Asset for Run batch_run_name...\n2024-01-12 07:54:47 +0000 3015 promptflow-runtime
INFO Created debug_info Asset: azureml://locations/eastus/workspaces/00000/data/azureml_batch_run_name_output_data_debug_info/versions/1\n2024-01-12
07:54:47 +0000 3015 promptflow-runtime INFO Creating unregistered output
Asset for Run batch_run_name...\n2024-01-12 07:54:47 +0000 3015 promptflow-runtime
INFO Created flow_outputs output Asset: azureml://locations/eastus/workspaces/00000/data/azureml_batch_run_name_output_data_flow_outputs/versions/1\n2024-01-12
07:54:47 +0000 3015 promptflow-runtime INFO Creating Artifact for Run
batch_run_name...\n2024-01-12 07:54:47 +0000 3015 promptflow-runtime INFO Created
instance_results.jsonl Artifact.\n2024-01-12 07:54:47 +0000 3015 promptflow-runtime
INFO Patching batch_run_name...\n2024-01-12 07:54:47 +0000 3015 promptflow-runtime
INFO Ending the aml run ''batch_run_name'' with status ''Completed''...\n2024-01-12
07:54:48 +0000 49 promptflow-runtime INFO Process 3015 finished\n2024-01-12
07:54:49 +0000 49 promptflow-runtime INFO [49] Child process finished!\n2024-01-12
07:54:49 +0000 49 promptflow-runtime INFO [batch_run_name] End processing
bulk run\n2024-01-12 07:54:49 +0000 49 promptflow-runtime INFO Cleanup
working dir /mnt/host/service/app/39649/requests/batch_run_name for bulk run\n"'
headers:
connection:
- keep-alive
content-length:
- '9817'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.661'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_get_detail_against_partial_fail_run.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.023'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.108'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.084'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.145'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:49:52 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/data.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '52'
content-md5:
- kHimciLnA7d3/I2LBUeLNA==
content-type:
- application/octet-stream
last-modified:
- Fri, 22 Sep 2023 09:37:22 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Fri, 22 Sep 2023 09:37:22 GMT
x-ms-meta-name:
- db87715d-65de-40cc-a281-09c0115699f3
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 6666ca9c-d7c3-4d85-b18c-12643adb9046
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:49:53 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/data.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.094'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.128'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:49:56 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/partial_fail/data.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '52'
content-md5:
- kHimciLnA7d3/I2LBUeLNA==
content-type:
- application/octet-stream
last-modified:
- Fri, 22 Sep 2023 09:37:31 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Fri, 22 Sep 2023 09:37:30 GMT
x-ms-meta-name:
- aa1844d8-4898-4daa-8100-6140558fc7c9
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:49:57 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/partial_fail/data.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/partial_fail/flow.dag.yaml",
"runId": "name", "runDisplayName": "name", "runExperimentName": "", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/data.jsonl"},
"inputsMapping": {}, "connections": {}, "environmentVariables": {}, "runtimeName":
"fake-runtime-name", "sessionId": "000000000000000000000000000000000000000000000000",
"sessionSetupMode": "SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '773'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '9.976'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/bbbb2b4cfb3d236b4f9b6110fd82264c/data.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "f36c2e06-b2b3-4ee5-9ed4-127ae490ffa8",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12846'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.208'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/bbbb2b4cfb3d236b4f9b6110fd82264c/data.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "f36c2e06-b2b3-4ee5-9ed4-127ae490ffa8",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12846'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.222'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/bbbb2b4cfb3d236b4f9b6110fd82264c/data.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "f36c2e06-b2b3-4ee5-9ed4-127ae490ffa8",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12846'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.226'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/bbbb2b4cfb3d236b4f9b6110fd82264c/data.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "f36c2e06-b2b3-4ee5-9ed4-127ae490ffa8",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12846'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.208'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/bbbb2b4cfb3d236b4f9b6110fd82264c/data.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "f36c2e06-b2b3-4ee5-9ed4-127ae490ffa8",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12846'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.665'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name/childRuns?endIndex=24&startIndex=0
response:
body:
string: '[{"run_id": "name_0", "status": "Completed", "error": null, "inputs":
{"key": "no", "line_number": 0}, "output": {"output": null}, "metrics": null,
"request": null, "parent_run_id": "name", "root_run_id": "name", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:50:26.771369Z",
"end_time": "2024-01-12T08:50:26.777759Z", "index": 0, "api_calls": [{"name":
"get_env_var", "type": "Tool", "inputs": {"key": "no"}, "output": {"value":
null}, "start_time": 1705049426.774557, "end_time": 1705049426.775613, "error":
null, "children": null, "node_name": "print_env"}], "variant_id": "", "name":
"", "description": "", "tags": null, "system_metrics": {"duration": 0.00639,
"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}, "result":
{"output": null}, "upload_metrics": false}, {"run_id": "name_2", "status":
"Completed", "error": null, "inputs": {"key": "matter", "line_number": 2},
"output": {"output": null}, "metrics": null, "request": null, "parent_run_id":
"name", "root_run_id": "name", "source_run_id": null, "flow_id": "default_flow_id",
"start_time": "2024-01-12T08:50:26.88379Z", "end_time": "2024-01-12T08:50:26.889697Z",
"index": 2, "api_calls": [{"name": "get_env_var", "type": "Tool", "inputs":
{"key": "matter"}, "output": {"value": null}, "start_time": 1705049426.887009,
"end_time": 1705049426.888023, "error": null, "children": null, "node_name":
"print_env"}], "variant_id": "", "name": "", "description": "", "tags": null,
"system_metrics": {"duration": 0.005907, "prompt_tokens": 0, "completion_tokens":
0, "total_tokens": 0}, "result": {"output": null}, "upload_metrics": false},
{"run_id": "name_1", "status": "Failed", "error": {"message": "Execution failure
in ''print_env'': (Exception) expected raise!", "messageFormat": "Execution
failure in ''{node_name}'': {error_type_and_message}", "messageParameters":
{"node_name": "print_env", "error_type_and_message": "(Exception) expected
raise!"}, "referenceCode": "Tool/__pf_main__", "code": "UserError", "innerError":
{"code": "ToolExecutionError", "innerError": null}, "additionalInfo": [{"type":
"ToolExecutionErrorDetails", "info": {"type": "Exception", "message": "expected
raise!", "traceback": "Traceback (most recent call last):\n File \"/mnt/host/service/app/39415/requests/name/print_env.py\",
line 9, in get_env_var\n raise Exception(\"expected raise!\")\nException:
expected raise!\n", "filename": "/mnt/host/service/app/39415/requests/name/print_env.py",
"lineno": 9, "name": "get_env_var"}}], "debugInfo": {"type": "ToolExecutionError",
"message": "Execution failure in ''print_env'': (Exception) expected raise!",
"stackTrace": "\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"expected raise!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39415/requests/name/print_env.py\",
line 9, in get_env_var\n raise Exception(\"expected raise!\")\n", "innerException":
null}}}, "inputs": {"key": "raise", "line_number": 1}, "output": null, "metrics":
null, "request": null, "parent_run_id": "name", "root_run_id": "name", "source_run_id":
null, "flow_id": "default_flow_id", "start_time": "2024-01-12T08:50:26.77979Z",
"end_time": "2024-01-12T08:50:26.953981Z", "index": 1, "api_calls": [{"name":
"get_env_var", "type": "Tool", "inputs": {"key": "raise"}, "output": null,
"start_time": 1705049426.782672, "end_time": 1705049426.783439, "error": {"message":
"expected raise!", "type": "Exception"}, "children": null, "node_name": "print_env"}],
"variant_id": "", "name": "", "description": "", "tags": null, "system_metrics":
{"duration": 0.174191, "prompt_tokens": 0, "completion_tokens": 0, "total_tokens":
0}, "result": null, "upload_metrics": false}]'
headers:
connection:
- keep-alive
content-length:
- '6638'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.729'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name/childRuns?endIndex=49&startIndex=25
response:
body:
string: '[]'
headers:
connection:
- keep-alive
content-length:
- '2'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '1.083'
status:
code: 200
message: OK
- request:
body: '{"runId": "name", "selectRunMetadata": true, "selectRunDefinition": true,
"selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705049404, "rootRunId": "name", "createdUtc":
"2024-01-12T08:50:04.3467507+00:00", "createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": {"error": {"code": "UserError", "severity":
null, "message": "Execution failure in ''print_env'': (Exception) expected
raise!", "messageFormat": "{\"totalChildRuns\": 3, \"userErrorChildRuns\":
1, \"systemErrorChildRuns\": 0, \"errorDetails\": [{\"code\": \"UserError/ToolExecutionError\",
\"messageFormat\": \"Execution failure in ''{node_name}'': {error_type_and_message}\",
\"count\": 1}]}", "messageParameters": {"node_name": "print_env", "error_type_and_message":
"(Exception) expected raise!"}, "referenceCode": "Tool/__pf_main__", "detailsUri":
null, "target": null, "details": [], "innerError": {"code": "ToolExecutionError",
"innerError": null}, "debugInfo": {"type": "ToolExecutionError", "message":
"Execution failure in ''print_env'': (Exception) expected raise!", "stackTrace":
"\nThe above exception was the direct cause of the following exception:\n\nTraceback
(most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 451, in result\n return self.__get_result()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/_base.py\",
line 403, in __get_result\n raise self._exception\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/concurrent/futures/thread.py\",
line 58, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 111, in _exec_single_node_in_thread\n result = context.invoke_tool(node,
f, kwargs=kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\n", "innerException": {"type": "Exception", "message":
"expected raise!", "stackTrace": "Traceback (most recent call last):\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39415/requests/name/print_env.py\",
line 9, in get_env_var\n raise Exception(\"expected raise!\")\n", "innerException":
null, "data": null, "errorResponse": null}, "data": null, "errorResponse":
null}, "additionalInfo": [{"type": "ToolExecutionErrorDetails", "info": {"type":
"Exception", "message": "expected raise!", "traceback": "Traceback (most recent
call last):\n File \"/mnt/host/service/app/39415/requests/name/print_env.py\",
line 9, in get_env_var\n raise Exception(\"expected raise!\")\nException:
expected raise!\n", "filename": "/mnt/host/service/app/39415/requests/name/print_env.py",
"lineno": 9, "name": "get_env_var"}}]}, "correlation": null, "environment":
null, "location": null, "time": "2024-01-12T08:50:30.744399+00:00", "componentName":
"promptflow-runtime/20231204.v4 Designer/1.0 promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0) promptflow/1.2.0rc1"}, "warnings":
null, "revision": 7, "statusRevision": 3, "runUuid": "d689f844-6eae-4a78-a210-4779ec098e1e",
"parentRunUuid": null, "rootRunUuid": "d689f844-6eae-4a78-a210-4779ec098e1e",
"lastStartTimeUtc": null, "currentComputeTime": null, "computeDuration": "00:00:04.8547843",
"effectiveStartTimeUtc": null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "18a66f5f-dbdf-4c17-9dd7-1634712a9cbe",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:50:30.0347672+00:00", "duration":
"00:00:04.8547843", "cancelationReason": null, "currentAttemptId": 1, "runId":
"name", "parentRunId": null, "experimentId": "1848033e-509f-4c52-92ee-f0a0121fe99e",
"status": "Completed", "startTimeUtc": "2024-01-12T08:50:26.1204745+00:00",
"endTimeUtc": "2024-01-12T08:50:30.9752588+00:00", "scheduleId": null, "displayName":
"name", "name": null, "dataContainerId": "dcid.name", "description": null,
"hidden": false, "runType": "azureml.promptflow.FlowRun", "runTypeV2": {"orchestrator":
null, "traits": [], "attribution": "PromptFlow", "computeType": "AmlcDsi"},
"properties": {"azureml.promptflow.runtime_name": "test-runtime-ci", "azureml.promptflow.runtime_version":
"20231204.v4", "azureml.promptflow.definition_file_name": "flow.dag.yaml",
"azureml.promptflow.session_id": "31858a8dfc61a642bb0ab6df4fc3ac7b3807de4ffead00d1",
"azureml.promptflow.flow_lineage_id": "de293df4f50622090c0225852d59cd663b6b629e38728f7444fa0f12255a0647",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/bc20fa079592a8072922533f187e3184/partial_fail/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/bbbb2b4cfb3d236b4f9b6110fd82264c/data.jsonl",
"_azureml.evaluation_run": "promptflow.BatchRun", "azureml.promptflow.snapshot_id":
"f36c2e06-b2b3-4ee5-9ed4-127ae490ffa8", "azureml.promptflow.total_tokens":
"0", "_azureml.evaluate_artifacts": "[{\"path\": \"instance_results.jsonl\",
\"type\": \"table\"}]"}, "parameters": {}, "actionUris": {}, "scriptName":
null, "target": null, "uniqueChildRunComputeTargets": [], "tags": {}, "settings":
{}, "services": {}, "inputDatasets": [], "outputDatasets": [], "runDefinition":
null, "jobSpecification": null, "primaryMetricName": null, "createdFrom":
null, "cancelUri": null, "completeUri": null, "diagnosticsUri": null, "computeRequest":
null, "compute": null, "retainForLifetimeOfWorkspace": false, "queueingInfo":
null, "inputs": null, "outputs": {"debug_info": {"assetId": "azureml://locations/eastus/workspaces/00000/data/azureml_name_output_data_debug_info/versions/1",
"type": "UriFolder"}, "flow_outputs": {"assetId": "azureml://locations/eastus/workspaces/00000/data/azureml_name_output_data_flow_outputs/versions/1",
"type": "UriFolder"}}}, "runDefinition": null, "jobSpecification": null, "systemSettings":
null}'
headers:
connection:
- keep-alive
content-length:
- '9873'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.037'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name/logContent
response:
body:
string: '"2024-01-12 08:50:11 +0000 78 promptflow-runtime INFO [name]
Receiving v2 bulk run request afd6522c-26b0-4e2e-966c-43176d74cb1f: {\"flow_id\":
\"name\", \"flow_run_id\": \"name\", \"flow_source\": {\"flow_source_type\":
1, \"flow_source_info\": {\"snapshot_id\": \"f36c2e06-b2b3-4ee5-9ed4-127ae490ffa8\"},
\"flow_dag_file\": \"flow.dag.yaml\"}, \"log_path\": \"https://promptfloweast4063704120.blob.core.windows.net/azureml/ExperimentRun/dcid.name/logs/azureml/executionlogs.txt?sv=2019-07-07&sr=b&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T07%3A46%3A24Z&ske=2024-01-13T15%3A56%3A24Z&sks=b&skv=2019-07-07&st=2024-01-12T08%3A40%3A10Z&se=2024-01-12T16%3A50%3A10Z&sp=rcw\",
\"app_insights_instrumentation_key\": \"InstrumentationKey=**data_scrubbed**;IngestionEndpoint=https://eastus-6.in.applicationinsights.azure.com/;LiveEndpoint=https://eastus.livediagnostics.monitor.azure.com/\",
\"data_inputs\": {\"data\": \"azureml://datastores/workspaceblobstore/paths/LocalUpload/bbbb2b4cfb3d236b4f9b6110fd82264c/data.jsonl\"},
\"azure_storage_setting\": {\"azure_storage_mode\": 1, \"storage_account_name\":
\"promptfloweast4063704120\", \"blob_container_name\": \"azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5\",
\"flow_artifacts_root_path\": \"promptflow/PromptFlowArtifacts/name\", \"blob_container_sas_token\":
\"?sv=2019-07-07&sr=c&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T08%3A50%3A11Z&ske=2024-01-19T08%3A50%3A11Z&sks=b&skv=2019-07-07&se=2024-01-19T08%3A50%3A11Z&sp=racwl\",
\"output_datastore_name\": \"workspaceblobstore\"}}\n2024-01-12 08:50:11 +0000 78
promptflow-runtime INFO Runtime version: 20231204.v4. PromptFlow version:
1.2.0rc1\n2024-01-12 08:50:11 +0000 78 promptflow-runtime INFO Updating
name to Status.Preparing...\n2024-01-12 08:50:11 +0000 78 promptflow-runtime
INFO Downloading snapshot to /mnt/host/service/app/39415/requests/name\n2024-01-12
08:50:11 +0000 78 promptflow-runtime INFO Get snapshot sas url for
f36c2e06-b2b3-4ee5-9ed4-127ae490ffa8...\n2024-01-12 08:50:18 +0000 78
promptflow-runtime INFO Downloading snapshot f36c2e06-b2b3-4ee5-9ed4-127ae490ffa8
from uri https://promptfloweast4063704120.blob.core.windows.net/snapshotzips/promptflow-eastus:3e123da1-f9a5-4c91-9234-8d9ffbb39ff5:snapshotzip/f36c2e06-b2b3-4ee5-9ed4-127ae490ffa8.zip...\n2024-01-12
08:50:18 +0000 78 promptflow-runtime INFO Downloaded file /mnt/host/service/app/39415/requests/name/f36c2e06-b2b3-4ee5-9ed4-127ae490ffa8.zip
with size 701 for snapshot f36c2e06-b2b3-4ee5-9ed4-127ae490ffa8.\n2024-01-12
08:50:18 +0000 78 promptflow-runtime INFO Download snapshot f36c2e06-b2b3-4ee5-9ed4-127ae490ffa8
completed.\n2024-01-12 08:50:18 +0000 78 promptflow-runtime INFO Successfully
download snapshot to /mnt/host/service/app/39415/requests/name\n2024-01-12
08:50:18 +0000 78 promptflow-runtime INFO About to execute a python
flow.\n2024-01-12 08:50:18 +0000 78 promptflow-runtime INFO Use spawn
method to start child process.\n2024-01-12 08:50:18 +0000 78 promptflow-runtime
INFO Starting to check process 5940 status for run name\n2024-01-12 08:50:18
+0000 78 promptflow-runtime INFO Start checking run status for run
name\n2024-01-12 08:50:22 +0000 5940 promptflow-runtime INFO [78--5940]
Start processing flowV2......\n2024-01-12 08:50:22 +0000 5940 promptflow-runtime
INFO Runtime version: 20231204.v4. PromptFlow version: 1.2.0rc1\n2024-01-12
08:50:22 +0000 5940 promptflow-runtime INFO Setting mlflow tracking
uri...\n2024-01-12 08:50:23 +0000 5940 promptflow-runtime INFO Validating
''AzureML Data Scientist'' user authentication...\n2024-01-12 08:50:25 +0000 5940
promptflow-runtime INFO Successfully validated ''AzureML Data Scientist''
user authentication.\n2024-01-12 08:50:25 +0000 5940 promptflow-runtime
INFO Using AzureMLRunStorageV2\n2024-01-12 08:50:25 +0000 5940 promptflow-runtime
INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
08:50:25 +0000 5940 promptflow-runtime INFO Initialized blob service
client for AzureMLRunTracker.\n2024-01-12 08:50:25 +0000 5940 promptflow-runtime
INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
08:50:25 +0000 5940 promptflow-runtime INFO Resolve data from url finished
in 0.47867807000875473 seconds\n2024-01-12 08:50:25 +0000 5940 promptflow-runtime
INFO Starting the aml run ''name''...\n2024-01-12 08:50:26 +0000 5940
execution WARNING Starting run without column mapping may lead to
unexpected results. Please consult the following documentation for more information:
https://aka.ms/pf/column-mapping\n2024-01-12 08:50:26 +0000 5940 execution.bulk INFO Using
fork, process count: 3\n2024-01-12 08:50:26 +0000 5987 execution.bulk INFO Process
5987 started.\n2024-01-12 08:50:26 +0000 5992 execution.bulk INFO Process
5992 started.\n2024-01-12 08:50:26 +0000 5940 execution.bulk INFO Process
name: ForkProcess-74:3, Process id: 5987, Line number: 0 start execution.\n2024-01-12
08:50:26 +0000 5940 execution.bulk INFO Process name: ForkProcess-74:4,
Process id: 5992, Line number: 1 start execution.\n2024-01-12 08:50:26 +0000 5981
execution.bulk INFO Process 5981 started.\n2024-01-12 08:50:26 +0000 5940
execution.bulk INFO Process name: ForkProcess-74:2, Process id: 5981,
Line number: 2 start execution.\n2024-01-12 08:50:26 +0000 5940 execution.bulk INFO Process
name: ForkProcess-74:3, Process id: 5987, Line number: 0 completed.\n2024-01-12
08:50:26 +0000 5940 execution.bulk INFO Finished 1 / 3 lines.\n2024-01-12
08:50:26 +0000 5992 execution ERROR Node print_env in line
1 failed. Exception: Execution failure in ''print_env'': (Exception) expected
raise!.\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n File \"/mnt/host/service/app/39415/requests/name/print_env.py\",
line 9, in get_env_var\n raise Exception(\"expected raise!\")\nException:
expected raise!\n\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 89, in invoke_tool\n result = self._invoke_tool_with_timer(node, f,
kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 196, in _invoke_tool_with_timer\n raise ToolExecutionError(node_name=node_name,
module=module) from e\npromptflow._core._errors.ToolExecutionError: Execution
failure in ''print_env'': (Exception) expected raise!\n2024-01-12 08:50:26
+0000 5940 execution.bulk INFO Average execution time for completed
lines: 0.24 seconds. Estimated time for incomplete lines: 0.48 seconds.\n2024-01-12
08:50:26 +0000 5992 execution ERROR Execution of one node has
failed. Cancelling all running nodes: print_env.\n2024-01-12 08:50:26 +0000 5940
execution.bulk INFO Process name: ForkProcess-74:2, Process id: 5981,
Line number: 2 completed.\n2024-01-12 08:50:26 +0000 5940 execution.bulk INFO Finished
2 / 3 lines.\n2024-01-12 08:50:27 +0000 5940 execution.bulk INFO Average
execution time for completed lines: 0.16 seconds. Estimated time for incomplete
lines: 0.16 seconds.\n2024-01-12 08:50:27 +0000 5940 execution.bulk INFO Process
name: ForkProcess-74:4, Process id: 5992, Line number: 1 completed.\n2024-01-12
08:50:27 +0000 5940 execution.bulk INFO Finished 3 / 3 lines.\n2024-01-12
08:50:27 +0000 5940 execution.bulk INFO Average execution time
for completed lines: 0.18 seconds. Estimated time for incomplete lines: 0.0
seconds.\n2024-01-12 08:50:28 +0000 5940 execution ERROR 1/3
flow run failed, indexes: [1], exception of index 1: Execution failure in
''print_env'': (Exception) expected raise!\n2024-01-12 08:50:29 +0000 5940
execution.bulk INFO Upload status summary metrics for run name finished
in 1.7115172129124403 seconds\n2024-01-12 08:50:30 +0000 5940 promptflow-runtime
INFO Successfully write run properties {\"azureml.promptflow.total_tokens\":
0, \"_azureml.evaluate_artifacts\": \"[{\\\"path\\\": \\\"instance_results.jsonl\\\",
\\\"type\\\": \\\"table\\\"}]\"} with run id ''name''\n2024-01-12 08:50:30
+0000 5940 execution.bulk INFO Upload RH properties for run name
finished in 0.08352885954082012 seconds\n2024-01-12 08:50:30 +0000 5940
promptflow-runtime INFO Creating unregistered output Asset for Run name...\n2024-01-12
08:50:30 +0000 5940 promptflow-runtime INFO Created debug_info Asset:
azureml://locations/eastus/workspaces/00000/data/azureml_name_output_data_debug_info/versions/1\n2024-01-12
08:50:30 +0000 5940 promptflow-runtime INFO Creating unregistered output
Asset for Run name...\n2024-01-12 08:50:30 +0000 5940 promptflow-runtime
INFO Created flow_outputs output Asset: azureml://locations/eastus/workspaces/00000/data/azureml_name_output_data_flow_outputs/versions/1\n2024-01-12
08:50:30 +0000 5940 promptflow-runtime INFO Creating Artifact for Run
name...\n2024-01-12 08:50:30 +0000 5940 promptflow-runtime INFO Created
instance_results.jsonl Artifact.\n2024-01-12 08:50:30 +0000 5940 promptflow-runtime
INFO Patching name...\n2024-01-12 08:50:30 +0000 5940 promptflow-runtime
WARNING [name] Run failed. Execution stackTrace: Traceback (most recent call
last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/flow_execution_context.py\",
line 185, in _invoke_tool_with_timer\n return f(**kwargs)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/_core/tool.py\",
line 106, in decorated_tool\n output = func(*args, **kwargs)\n [REDACTED:
External StackTrace]\n\nThe above exception was the direct cause of the following
exception:\n\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 804, in _exec\n output, nodes_outputs = self._traverse_nodes(inputs,
context)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 890, in _traverse_nodes\n nodes_outputs, bypassed_nodes = self._submit_to_scheduler(context,
inputs, batch_nodes)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/flow_executor.py\",
line 910, in _submit_to_scheduler\n return FlowNodesScheduler(self._tools_manager,
inputs, nodes, self._node_concurrency, context).execute()\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 69, in execute\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 58, in execute\n self._dag_manager.complete_nodes(self._collect_outputs(completed_futures))\n File
\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/executor/_flow_nodes_scheduler.py\",
line 90, in _collect_outputs\n each_node_result = each_future.result()\n [REDACTED:
External StackTrace]\n\n2024-01-12 08:50:30 +0000 5940 promptflow-runtime
INFO Ending the aml run ''name'' with status ''Completed''...\n2024-01-12
08:50:32 +0000 78 promptflow-runtime INFO Process 5940 finished\n2024-01-12
08:50:32 +0000 78 promptflow-runtime INFO [78] Child process finished!\n2024-01-12
08:50:32 +0000 78 promptflow-runtime INFO [name] End processing bulk
run\n2024-01-12 08:50:32 +0000 78 promptflow-runtime INFO Cleanup
working dir /mnt/host/service/app/39415/requests/name for bulk run\n"'
headers:
connection:
- keep-alive
content-length:
- '13657'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.694'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_stream_failed_run_logs.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.024'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.095'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.097'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.163'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:01:09 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/webClassification3.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '379'
content-md5:
- lI/pz9jzTQ7Td3RHPL7y7w==
content-type:
- application/octet-stream
last-modified:
- Mon, 06 Nov 2023 08:30:18 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Mon, 06 Nov 2023 08:30:18 GMT
x-ms-meta-name:
- 94331215-cf7f-452a-9f1a-1d276bc9b0e4
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 3f163752-edb0-4afc-a6f5-b0a670bd7c24
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:01:10 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/webClassification3.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.075'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.082'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:01:14 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/partial_fail/data.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '52'
content-md5:
- kHimciLnA7d3/I2LBUeLNA==
content-type:
- application/octet-stream
last-modified:
- Fri, 22 Sep 2023 09:37:31 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Fri, 22 Sep 2023 09:37:30 GMT
x-ms-meta-name:
- aa1844d8-4898-4daa-8100-6140558fc7c9
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:01:15 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/partial_fail/data.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/partial_fail/flow.dag.yaml",
"runId": "failed_run_name", "runDisplayName": "sdk-cli-test-fixture-failed-run",
"runExperimentName": "", "batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/webClassification3.jsonl"},
"inputsMapping": {}, "connections": {}, "environmentVariables": {}, "runtimeName":
"fake-runtime-name", "sessionId": "000000000000000000000000000000000000000000000000",
"sessionSetupMode": "SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '782'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"failed_run_name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '6.976'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/failed_run_name/flowRuns/failed_run_name",
"flowRunId": "failed_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-failed-run",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/failed_run_name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "27175d15-f6d8-4792-9072-e2b684753205",
"studioPortalEndpoint": "https://ml.azure.com/runs/failed_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.388'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/failed_run_name/flowRuns/failed_run_name",
"flowRunId": "failed_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-failed-run",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/failed_run_name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "27175d15-f6d8-4792-9072-e2b684753205",
"studioPortalEndpoint": "https://ml.azure.com/runs/failed_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.261'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/failed_run_name/flowRuns/failed_run_name",
"flowRunId": "failed_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-failed-run",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/failed_run_name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "27175d15-f6d8-4792-9072-e2b684753205",
"studioPortalEndpoint": "https://ml.azure.com/runs/failed_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.411'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/failed_run_name/flowRuns/failed_run_name",
"flowRunId": "failed_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-failed-run",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/failed_run_name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "27175d15-f6d8-4792-9072-e2b684753205",
"studioPortalEndpoint": "https://ml.azure.com/runs/failed_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.328'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/failed_run_name/flowRuns/failed_run_name",
"flowRunId": "failed_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-failed-run",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/failed_run_name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "27175d15-f6d8-4792-9072-e2b684753205",
"studioPortalEndpoint": "https://ml.azure.com/runs/failed_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.367'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/failed_run_name/flowRuns/failed_run_name",
"flowRunId": "failed_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-failed-run",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/failed_run_name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "27175d15-f6d8-4792-9072-e2b684753205",
"studioPortalEndpoint": "https://ml.azure.com/runs/failed_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.252'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/failed_run_name/flowRuns/failed_run_name",
"flowRunId": "failed_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-failed-run",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/failed_run_name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "27175d15-f6d8-4792-9072-e2b684753205",
"studioPortalEndpoint": "https://ml.azure.com/runs/failed_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.289'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAACgElEQVR4nGWSz2vcVRTFP/e9NzOZ1KDGohASslLEH6VLV0ak4l/QpeDCrfQPcNGliODKnVm4EBdBsIjQIlhciKW0ycKFVCSNbYnjdDLtmPnmO/nO9917XcxMkjYX3uLx7nnn3HOuMK2Nix4fP78ZdrYXVkLVWjf3l3B1B+HpcjzGFtmqa6cePz7/x0dnn1n5qhj3iBJPYREIURAJuCtpY8PjReDbrf9WG7H1fuefwQU9qKztTcMJT+PNnEFvjGVDBDlSsH6p/9MLzy6+NxwVqI8RAg4IPmWedMckdLYP6O6UpIaQfvyyXG012+e79/ZfHukoS1ISMT2hGTB1RkUmNgQ5QZ0w+a2VWDq73MbdEWmfnnv6UWe7oNzPaLapl5CwuLTXK9WUGBuCjqekzhP+z52ZXOrKMD3OJg0Hh778aiOuvpnYvp05d6GJO4iAO4QAe/eV36/X5LFRV4Zmn+AdkqlL8Vjp3oVioOz+WTPzzYEgsN+fgPLYyJVheSbPPVl2ikeGZRjtG52/8rHuaV9VOlpP2OtKyVndcRVCSqOhsvxa4vW359i6OuKdD+aP8Q4SYPdOzS/flGjt1JUSaMqZ5nwa1Y8qWb/Ud/eZZkHisYezEM0m+fcelDr8F1SqW2LNK6r1jXQwyLzy1hxvrLXZulry7ocL+FS6G4QIu3fG/Px1gdYeW7LIgXU2P/115TOA5G7e3Rmj2aS/m7l5pThiZzrCcE/d1XHzbln373nw7y6veeoUm5KCNKT/IPPwbiY1hYd/l5MIT65BMFt87sU4v9D7/JMflr44uV6hGh1+L4RCkg6z5iK2tAhNLeLsNGwYA4fDYnC/drvuuFxe86NV/x+Ut27g0FvykgAAAABJRU5ErkJggg==",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/failed_run_name/flowRuns/failed_run_name",
"flowRunId": "failed_run_name", "flowRunDisplayName": "sdk-cli-test-fixture-failed-run",
"batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/failed_run_name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "27175d15-f6d8-4792-9072-e2b684753205",
"studioPortalEndpoint": "https://ml.azure.com/runs/failed_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.461'
status:
code: 200
message: OK
- request:
body: '{"runId": "failed_run_name", "selectRunMetadata": true, "selectRunDefinition":
true, "selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705046481, "rootRunId": "failed_run_name",
"createdUtc": "2024-01-12T08:01:21.0459935+00:00", "createdBy": {"userObjectId":
"00000000-0000-0000-0000-000000000000", "userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": {"error": {"code": "UserError", "severity":
null, "message": "The input for batch run is incorrect. Couldn''t find these
mapping relations: ${data.key}. Please make sure your input mapping keys and
values match your YAML input section and input data. For more information,
refer to the following documentation: https://aka.ms/pf/column-mapping", "messageFormat":
"The input for batch run is incorrect. Couldn''t find these mapping relations:
{invalid_relations}. Please make sure your input mapping keys and values match
your YAML input section and input data. For more information, refer to the
following documentation: https://aka.ms/pf/column-mapping", "messageParameters":
{"invalid_relations": "${data.key}"}, "referenceCode": "Executor", "detailsUri":
null, "target": null, "details": [], "innerError": {"code": "ValidationError",
"innerError": {"code": "InputMappingError", "innerError": null}}, "debugInfo":
{"type": "InputMappingError", "message": "The input for batch run is incorrect.
Couldn''t find these mapping relations: ${data.key}. Please make sure your
input mapping keys and values match your YAML input section and input data.
For more information, refer to the following documentation: https://aka.ms/pf/column-mapping",
"stackTrace": "Traceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/runtime/runtime.py\",
line 671, in execute_bulk_run_request\n batch_engine.run(\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\",
line 147, in run\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\",
line 132, in run\n batch_inputs = batch_input_processor.process_batch_inputs(input_dirs,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 41, in process_batch_inputs\n return self._validate_and_apply_inputs_mapping(input_dicts,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 91, in _validate_and_apply_inputs_mapping\n resolved_inputs = self._apply_inputs_mapping_for_all_lines(inputs,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 163, in _apply_inputs_mapping_for_all_lines\n result = [apply_inputs_mapping(item,
inputs_mapping) for item in merged_list]\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 163, in <listcomp>\n result = [apply_inputs_mapping(item, inputs_mapping)
for item in merged_list]\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 292, in apply_inputs_mapping\n raise InputMappingError(\n", "innerException":
null, "data": null, "errorResponse": null}, "additionalInfo": null}, "correlation":
null, "environment": null, "location": null, "time": "2024-01-12T08:01:41.930978+00:00",
"componentName": "promptflow-runtime/20231204.v4 Designer/1.0 promptflow-sdk/0.0.1
azsdk-python-azuremachinelearningdesignerserviceclient/unknown Python/3.10.13
(Windows-10-10.0.22631-SP0) promptflow/1.2.0rc1"}, "warnings": null, "revision":
7, "statusRevision": 3, "runUuid": "ebad9732-07a7-434c-b7fb-637162729eb8",
"parentRunUuid": null, "rootRunUuid": "ebad9732-07a7-434c-b7fb-637162729eb8",
"lastStartTimeUtc": null, "currentComputeTime": null, "computeDuration": "00:00:01.7835699",
"effectiveStartTimeUtc": null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "18a66f5f-dbdf-4c17-9dd7-1634712a9cbe",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:01:41.5560578+00:00", "duration":
"00:00:01.7835699", "cancelationReason": null, "currentAttemptId": 1, "runId":
"failed_run_name", "parentRunId": null, "experimentId": "1848033e-509f-4c52-92ee-f0a0121fe99e",
"status": "Failed", "startTimeUtc": "2024-01-12T08:01:40.3861186+00:00", "endTimeUtc":
"2024-01-12T08:01:42.1696885+00:00", "scheduleId": null, "displayName": "sdk-cli-test-fixture-failed-run",
"name": null, "dataContainerId": "dcid.failed_run_name", "description": null,
"hidden": false, "runType": "azureml.promptflow.FlowRun", "runTypeV2": {"orchestrator":
null, "traits": [], "attribution": "PromptFlow", "computeType": "AmlcDsi"},
"properties": {"azureml.promptflow.runtime_name": "test-runtime-ci", "azureml.promptflow.runtime_version":
"20231204.v4", "azureml.promptflow.definition_file_name": "flow.dag.yaml",
"azureml.promptflow.session_id": "31858a8dfc61a642bb0ab6df4fc3ac7b3807de4ffead00d1",
"azureml.promptflow.flow_lineage_id": "de293df4f50622090c0225852d59cd663b6b629e38728f7444fa0f12255a0647",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/bc20fa079592a8072922533f187e3184/partial_fail/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl",
"_azureml.evaluation_run": "promptflow.BatchRun", "azureml.promptflow.snapshot_id":
"27175d15-f6d8-4792-9072-e2b684753205", "azureml.promptflow.total_tokens":
"0", "_azureml.evaluate_artifacts": "[{\"path\": \"instance_results.jsonl\",
\"type\": \"table\"}]"}, "parameters": {}, "actionUris": {}, "scriptName":
null, "target": null, "uniqueChildRunComputeTargets": [], "tags": {}, "settings":
{}, "services": {}, "inputDatasets": [], "outputDatasets": [], "runDefinition":
null, "jobSpecification": null, "primaryMetricName": null, "createdFrom":
null, "cancelUri": null, "completeUri": null, "diagnosticsUri": null, "computeRequest":
null, "compute": null, "retainForLifetimeOfWorkspace": false, "queueingInfo":
null, "inputs": null, "outputs": {"debug_info": {"assetId": "azureml://locations/eastus/workspaces/00000/data/azureml_failed_run_name_output_data_debug_info/versions/1",
"type": "UriFolder"}}}, "runDefinition": null, "jobSpecification": null, "systemSettings":
null}'
headers:
connection:
- keep-alive
content-length:
- '7988'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.048'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/failed_run_name/logContent
response:
body:
string: '"2024-01-12 08:01:25 +0000 49 promptflow-runtime INFO [failed_run_name]
Receiving v2 bulk run request 74219027-a510-47c5-b30f-f9a2e05d3f12: {\"flow_id\":
\"failed_run_name\", \"flow_run_id\": \"failed_run_name\", \"flow_source\":
{\"flow_source_type\": 1, \"flow_source_info\": {\"snapshot_id\": \"27175d15-f6d8-4792-9072-e2b684753205\"},
\"flow_dag_file\": \"flow.dag.yaml\"}, \"log_path\": \"https://promptfloweast4063704120.blob.core.windows.net/azureml/ExperimentRun/dcid.failed_run_name/logs/azureml/executionlogs.txt?sv=2019-07-07&sr=b&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T07%3A42%3A25Z&ske=2024-01-13T15%3A52%3A25Z&sks=b&skv=2019-07-07&st=2024-01-12T07%3A51%3A24Z&se=2024-01-12T16%3A01%3A24Z&sp=rcw\",
\"app_insights_instrumentation_key\": \"InstrumentationKey=**data_scrubbed**;IngestionEndpoint=https://eastus-6.in.applicationinsights.azure.com/;LiveEndpoint=https://eastus.livediagnostics.monitor.azure.com/\",
\"data_inputs\": {\"data\": \"azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl\"},
\"azure_storage_setting\": {\"azure_storage_mode\": 1, \"storage_account_name\":
\"promptfloweast4063704120\", \"blob_container_name\": \"azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5\",
\"flow_artifacts_root_path\": \"promptflow/PromptFlowArtifacts/failed_run_name\",
\"blob_container_sas_token\": \"?sv=2019-07-07&sr=c&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T08%3A01%3A25Z&ske=2024-01-19T08%3A01%3A25Z&sks=b&skv=2019-07-07&se=2024-01-19T08%3A01%3A25Z&sp=racwl\",
\"output_datastore_name\": \"workspaceblobstore\"}}\n2024-01-12 08:01:25 +0000 49
promptflow-runtime INFO Runtime version: 20231204.v4. PromptFlow version:
1.2.0rc1\n2024-01-12 08:01:25 +0000 49 promptflow-runtime INFO Updating
failed_run_name to Status.Preparing...\n2024-01-12 08:01:25 +0000 49
promptflow-runtime INFO Downloading snapshot to /mnt/host/service/app/39649/requests/failed_run_name\n2024-01-12
08:01:25 +0000 49 promptflow-runtime INFO Get snapshot sas url for
27175d15-f6d8-4792-9072-e2b684753205...\n2024-01-12 08:01:32 +0000 49
promptflow-runtime INFO Downloading snapshot 27175d15-f6d8-4792-9072-e2b684753205
from uri https://promptfloweast4063704120.blob.core.windows.net/snapshotzips/promptflow-eastus:3e123da1-f9a5-4c91-9234-8d9ffbb39ff5:snapshotzip/27175d15-f6d8-4792-9072-e2b684753205.zip...\n2024-01-12
08:01:32 +0000 49 promptflow-runtime INFO Downloaded file /mnt/host/service/app/39649/requests/failed_run_name/27175d15-f6d8-4792-9072-e2b684753205.zip
with size 701 for snapshot 27175d15-f6d8-4792-9072-e2b684753205.\n2024-01-12
08:01:32 +0000 49 promptflow-runtime INFO Download snapshot 27175d15-f6d8-4792-9072-e2b684753205
completed.\n2024-01-12 08:01:32 +0000 49 promptflow-runtime INFO Successfully
download snapshot to /mnt/host/service/app/39649/requests/failed_run_name\n2024-01-12
08:01:32 +0000 49 promptflow-runtime INFO About to execute a python
flow.\n2024-01-12 08:01:32 +0000 49 promptflow-runtime INFO Use spawn
method to start child process.\n2024-01-12 08:01:32 +0000 49 promptflow-runtime
INFO Starting to check process 3429 status for run failed_run_name\n2024-01-12
08:01:32 +0000 49 promptflow-runtime INFO Start checking run status
for run failed_run_name\n2024-01-12 08:01:36 +0000 3429 promptflow-runtime
INFO [49--3429] Start processing flowV2......\n2024-01-12 08:01:36 +0000 3429
promptflow-runtime INFO Runtime version: 20231204.v4. PromptFlow version:
1.2.0rc1\n2024-01-12 08:01:36 +0000 3429 promptflow-runtime INFO Setting
mlflow tracking uri...\n2024-01-12 08:01:36 +0000 3429 promptflow-runtime
INFO Validating ''AzureML Data Scientist'' user authentication...\n2024-01-12
08:01:36 +0000 3429 promptflow-runtime INFO Successfully validated
''AzureML Data Scientist'' user authentication.\n2024-01-12 08:01:36 +0000 3429
promptflow-runtime INFO Using AzureMLRunStorageV2\n2024-01-12 08:01:36
+0000 3429 promptflow-runtime INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
08:01:37 +0000 3429 promptflow-runtime INFO Initialized blob service
client for AzureMLRunTracker.\n2024-01-12 08:01:37 +0000 3429 promptflow-runtime
INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
08:01:40 +0000 3429 promptflow-runtime INFO Resolve data from url finished
in 2.9352363562211394 seconds\n2024-01-12 08:01:40 +0000 3429 promptflow-runtime
INFO Starting the aml run ''failed_run_name''...\n2024-01-12 08:01:40
+0000 3429 execution WARNING Starting run without column mapping
may lead to unexpected results. Please consult the following documentation
for more information: https://aka.ms/pf/column-mapping\n2024-01-12 08:01:40
+0000 3429 execution.bulk ERROR Error occurred while executing batch
run. Exception: The input for batch run is incorrect. Couldn''t find these
mapping relations: ${data.key}. Please make sure your input mapping keys and
values match your YAML input section and input data. For more information,
refer to the following documentation: https://aka.ms/pf/column-mapping\n2024-01-12
08:01:40 +0000 3429 promptflow-runtime ERROR Run failed_run_name failed.
Exception: {\n \"message\": \"The input for batch run is incorrect. Couldn''t
find these mapping relations: ${data.key}. Please make sure your input mapping
keys and values match your YAML input section and input data. For more information,
refer to the following documentation: https://aka.ms/pf/column-mapping\",\n \"messageFormat\":
\"The input for batch run is incorrect. Couldn''t find these mapping relations:
{invalid_relations}. Please make sure your input mapping keys and values match
your YAML input section and input data. For more information, refer to the
following documentation: https://aka.ms/pf/column-mapping\",\n \"messageParameters\":
{\n \"invalid_relations\": \"${data.key}\"\n },\n \"referenceCode\":
\"Executor\",\n \"code\": \"UserError\",\n \"innerError\": {\n \"code\":
\"ValidationError\",\n \"innerError\": {\n \"code\": \"InputMappingError\",\n \"innerError\":
null\n }\n },\n \"debugInfo\": {\n \"type\": \"InputMappingError\",\n \"message\":
\"The input for batch run is incorrect. Couldn''t find these mapping relations:
${data.key}. Please make sure your input mapping keys and values match your
YAML input section and input data. For more information, refer to the following
documentation: https://aka.ms/pf/column-mapping\",\n \"stackTrace\": \"Traceback
(most recent call last):\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/runtime/runtime.py\\\",
line 671, in execute_bulk_run_request\\n batch_engine.run(\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\\\",
line 147, in run\\n raise e\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\\\",
line 132, in run\\n batch_inputs = batch_input_processor.process_batch_inputs(input_dirs,
inputs_mapping)\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\\\",
line 41, in process_batch_inputs\\n return self._validate_and_apply_inputs_mapping(input_dicts,
inputs_mapping)\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\\\",
line 91, in _validate_and_apply_inputs_mapping\\n resolved_inputs = self._apply_inputs_mapping_for_all_lines(inputs,
inputs_mapping)\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\\\",
line 163, in _apply_inputs_mapping_for_all_lines\\n result = [apply_inputs_mapping(item,
inputs_mapping) for item in merged_list]\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\\\",
line 163, in <listcomp>\\n result = [apply_inputs_mapping(item, inputs_mapping)
for item in merged_list]\\n File \\\"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\\\",
line 292, in apply_inputs_mapping\\n raise InputMappingError(\\n\",\n \"innerException\":
null\n }\n}\nTraceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/runtime/runtime.py\",
line 671, in execute_bulk_run_request\n batch_engine.run(\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\",
line 147, in run\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\",
line 132, in run\n batch_inputs = batch_input_processor.process_batch_inputs(input_dirs,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 41, in process_batch_inputs\n return self._validate_and_apply_inputs_mapping(input_dicts,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 91, in _validate_and_apply_inputs_mapping\n resolved_inputs = self._apply_inputs_mapping_for_all_lines(inputs,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 163, in _apply_inputs_mapping_for_all_lines\n result = [apply_inputs_mapping(item,
inputs_mapping) for item in merged_list]\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 163, in <listcomp>\n result = [apply_inputs_mapping(item, inputs_mapping)
for item in merged_list]\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 292, in apply_inputs_mapping\n raise InputMappingError(\npromptflow.batch._errors.InputMappingError:
The input for batch run is incorrect. Couldn''t find these mapping relations:
${data.key}. Please make sure your input mapping keys and values match your
YAML input section and input data. For more information, refer to the following
documentation: https://aka.ms/pf/column-mapping\n2024-01-12 08:01:41 +0000 3429
execution.bulk INFO Upload status summary metrics for run failed_run_name
finished in 0.7801888957619667 seconds\n2024-01-12 08:01:41 +0000 3429
promptflow-runtime INFO Successfully write run properties {\"azureml.promptflow.total_tokens\":
0, \"_azureml.evaluate_artifacts\": \"[{\\\"path\\\": \\\"instance_results.jsonl\\\",
\\\"type\\\": \\\"table\\\"}]\"} with run id ''failed_run_name''\n2024-01-12
08:01:41 +0000 3429 execution.bulk INFO Upload RH properties for
run failed_run_name finished in 0.08418271783739328 seconds\n2024-01-12 08:01:41
+0000 3429 promptflow-runtime INFO Creating unregistered output Asset
for Run failed_run_name...\n2024-01-12 08:01:41 +0000 3429 promptflow-runtime
INFO Created debug_info Asset: azureml://locations/eastus/workspaces/00000/data/azureml_failed_run_name_output_data_debug_info/versions/1\n2024-01-12
08:01:41 +0000 3429 promptflow-runtime INFO Patching failed_run_name...\n2024-01-12
08:01:41 +0000 3429 promptflow-runtime WARNING [failed_run_name] Run failed.
Execution stackTrace: Traceback (most recent call last):\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/runtime/runtime.py\",
line 671, in execute_bulk_run_request\n batch_engine.run(\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\",
line 147, in run\n raise e\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_engine.py\",
line 132, in run\n batch_inputs = batch_input_processor.process_batch_inputs(input_dirs,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 41, in process_batch_inputs\n return self._validate_and_apply_inputs_mapping(input_dicts,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 91, in _validate_and_apply_inputs_mapping\n resolved_inputs = self._apply_inputs_mapping_for_all_lines(inputs,
inputs_mapping)\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 163, in _apply_inputs_mapping_for_all_lines\n result = [apply_inputs_mapping(item,
inputs_mapping) for item in merged_list]\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 163, in <listcomp>\n result = [apply_inputs_mapping(item, inputs_mapping)
for item in merged_list]\n File \"/azureml-envs/prompt-flow/runtime/lib/python3.10/site-packages/promptflow/batch/_batch_inputs_processor.py\",
line 292, in apply_inputs_mapping\n raise InputMappingError(\n\n2024-01-12
08:01:42 +0000 3429 promptflow-runtime INFO Ending the aml run ''failed_run_name''
with status ''Failed''...\n2024-01-12 08:01:43 +0000 49 promptflow-runtime
INFO Process 3429 finished\n2024-01-12 08:01:43 +0000 49 promptflow-runtime
INFO [49] Child process finished!\n2024-01-12 08:01:43 +0000 49 promptflow-runtime
INFO [failed_run_name] End processing bulk run\n2024-01-12 08:01:43 +0000 49
promptflow-runtime ERROR Submit flow request failed Code: 400 InnerException
type: InputMappingError Exception type hierarchy: UserError/ValidationError/InputMappingError\n2024-01-12
08:01:43 +0000 49 promptflow-runtime INFO Cleanup working dir /mnt/host/service/app/39649/requests/failed_run_name
for bulk run\n"'
headers:
connection:
- keep-alive
content-length:
- '15117'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.766'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_default_run_display_name.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.024'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.064'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.064'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.118'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:26:03 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '49'
content-md5:
- quXiEreYvPinSj0HsaNa/g==
content-type:
- application/octet-stream
last-modified:
- Wed, 08 Nov 2023 04:26:09 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Wed, 08 Nov 2023 04:26:09 GMT
x-ms-meta-name:
- c4092674-5e53-4c17-b78d-75353ae0edb6
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 579021dc-8ac8-4c73-8110-4642bd00c69b
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:26:04 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.072'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.089'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:26:08 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '245'
content-md5:
- F+JA0a3CxcLYZ0ANRdlZbA==
content-type:
- application/octet-stream
last-modified:
- Wed, 29 Nov 2023 02:51:35 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Thu, 17 Aug 2023 10:30:09 GMT
x-ms-meta-name:
- 56efdd28-6297-4baa-aad3-be46f4b768a2
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:26:09 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/print_env_var/flow.dag.yaml",
"runId": "name", "runDisplayName": "name", "runExperimentName": "", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/env_var_names.jsonl"},
"inputsMapping": {}, "connections": {}, "environmentVariables": {"API_BASE":
"${azure_open_ai_connection.api_base}"}, "runtimeName": "fake-runtime-name",
"sessionId": "000000000000000000000000000000000000000000000000", "sessionSetupMode":
"SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '834'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '7.150'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/c32a61842e439cecc022ebcff5dc0da4/env_var_names.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "9edd066b-dcf6-4639-933d-6ffb8be07a2c",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.409'
status:
code: 200
message: OK
- request:
body: '{"runId": "name", "selectRunMetadata": true, "selectRunDefinition": true,
"selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705047976, "rootRunId": "name", "createdUtc":
"2024-01-12T08:26:15.9964375+00:00", "createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": null, "warnings": null, "revision": 3,
"statusRevision": 1, "runUuid": "bb6b107f-d6e6-4948-8460-9be91342a76c", "parentRunUuid":
null, "rootRunUuid": "bb6b107f-d6e6-4948-8460-9be91342a76c", "lastStartTimeUtc":
null, "currentComputeTime": "00:00:00", "computeDuration": null, "effectiveStartTimeUtc":
null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:26:20.3894992+00:00", "duration":
null, "cancelationReason": null, "currentAttemptId": 1, "runId": "name", "parentRunId":
null, "experimentId": "6a87c3ae-5a75-4c5d-9eb9-5203b0062282", "status": "Preparing",
"startTimeUtc": null, "endTimeUtc": null, "scheduleId": null, "displayName":
"name", "name": null, "dataContainerId": "dcid.name", "description": null,
"hidden": false, "runType": "azureml.promptflow.FlowRun", "runTypeV2": {"orchestrator":
null, "traits": [], "attribution": "PromptFlow", "computeType": "AmlcDsi"},
"properties": {"azureml.promptflow.runtime_name": "test-runtime-ci", "azureml.promptflow.runtime_version":
"20231204.v4", "azureml.promptflow.definition_file_name": "flow.dag.yaml",
"azureml.promptflow.session_id": "62adccc385dd5d078797bdd0d2e1c55e120f3d5216885b81",
"azureml.promptflow.flow_lineage_id": "f1efdb93dcf9b3c17e246e7bcf0e2c7398d7bc289f8dd2c3d8f808eacc63c31f",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/3360ae705933fb90bcd290241ca0ece9/print_env_var/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/c32a61842e439cecc022ebcff5dc0da4/env_var_names.jsonl",
"_azureml.evaluation_run": "promptflow.BatchRun", "azureml.promptflow.snapshot_id":
"9edd066b-dcf6-4639-933d-6ffb8be07a2c"}, "parameters": {}, "actionUris": {},
"scriptName": null, "target": null, "uniqueChildRunComputeTargets": [], "tags":
{}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": null}, "runDefinition":
null, "jobSpecification": null, "systemSettings": null}'
headers:
connection:
- keep-alive
content-length:
- '3849'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.066'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_basic_evaluation.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.029'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.098'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.077'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.099'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:15:32 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/webClassification3.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '379'
content-md5:
- lI/pz9jzTQ7Td3RHPL7y7w==
content-type:
- application/octet-stream
last-modified:
- Mon, 06 Nov 2023 08:30:18 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Mon, 06 Nov 2023 08:30:18 GMT
x-ms-meta-name:
- 94331215-cf7f-452a-9f1a-1d276bc9b0e4
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 3f163752-edb0-4afc-a6f5-b0a670bd7c24
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:15:33 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/webClassification3.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.082'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.082'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:15:36 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/web_classification/classify_with_llm.jinja2
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '853'
content-md5:
- ylTeNqjvuOvtzEZJ/X5n3A==
content-type:
- application/octet-stream
last-modified:
- Fri, 12 Jan 2024 08:13:57 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Fri, 12 Jan 2024 08:13:56 GMT
x-ms-meta-name:
- 950201e8-c52c-4b15-ada1-5e58de9b2f4d
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:15:38 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/web_classification/classify_with_llm.jinja2
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/web_classification/flow.dag.yaml",
"runId": "batch_run_name", "runDisplayName": "batch_run_name", "runExperimentName":
"", "nodeVariant": "${summarize_text_content.variant_0}", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/webClassification3.jsonl"},
"inputsMapping": {"url": "${data.url}"}, "connections": {}, "environmentVariables":
{}, "runtimeName": "fake-runtime-name", "sessionId": "000000000000000000000000000000000000000000000000",
"sessionSetupMode": "SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '873'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"batch_run_name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '6.627'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "fetch_text_content_from_url", "type":
"python", "source": {"type": "code", "path": "fetch_text_content_from_url.py"},
"inputs": {"fetch_url": "${inputs.url}"}, "tool": "fetch_text_content_from_url.py",
"reduce": false}, {"name": "prepare_examples", "type": "python", "source":
{"type": "code", "path": "prepare_examples.py"}, "inputs": {}, "tool": "prepare_examples.py",
"reduce": false}, {"name": "classify_with_llm", "type": "llm", "source": {"type":
"code", "path": "classify_with_llm.jinja2"}, "inputs": {"deployment_name":
"gpt-35-turbo", "suffix": "", "max_tokens": "128", "temperature": "0.1", "top_p":
"1.0", "logprobs": "", "echo": "False", "stop": "", "presence_penalty": "0",
"frequency_penalty": "0", "best_of": "1", "logit_bias": "", "url": "${inputs.url}",
"examples": "${prepare_examples.output}", "text_content": "${summarize_text_content.output}"},
"tool": "classify_with_llm.jinja2", "reduce": false, "api": "chat", "provider":
"AzureOpenAI", "connection": "azure_open_ai_connection", "module": "promptflow.tools.aoai"},
{"name": "convert_to_dict", "type": "python", "source": {"type": "code", "path":
"convert_to_dict.py"}, "inputs": {"input_str": "${classify_with_llm.output}"},
"tool": "convert_to_dict.py", "reduce": false}, {"name": "summarize_text_content",
"type": "llm", "source": {"type": "code", "path": "summarize_text_content.jinja2"},
"inputs": {"deployment_name": "gpt-35-turbo", "suffix": "", "max_tokens":
"128", "temperature": "0.2", "top_p": "1.0", "logprobs": "", "echo": "False",
"stop": "", "presence_penalty": "0", "frequency_penalty": "0", "best_of":
"1", "logit_bias": "", "text": "${fetch_text_content_from_url.output}"}, "tool":
"summarize_text_content.jinja2", "reduce": false, "api": "chat", "provider":
"AzureOpenAI", "connection": "azure_open_ai_connection", "module": "promptflow.tools.aoai"}],
"tools": [{"name": "Content Safety (Text Analyze)", "type": "python", "inputs":
{"connection": {"type": ["AzureContentSafetyConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "hate_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "self_harm_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "sexual_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "text": {"type":
["string"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "violence_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"}},
"description": "Use Azure Content Safety to detect harmful content.", "module":
"promptflow.tools.azure_content_safety", "function": "analyze_text", "is_builtin":
true, "package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "classify_with_llm.jinja2", "type":
"prompt", "inputs": {"examples": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "text_content":
{"type": ["string"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "url": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "classify_with_llm.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}, {"name":
"convert_to_dict.py", "type": "python", "inputs": {"input_str": {"type": ["string"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"}},
"source": "convert_to_dict.py", "function": "convert_to_dict", "is_builtin":
false, "enable_kwargs": false, "tool_state": "stable"}, {"name": "fetch_text_content_from_url.py",
"type": "python", "inputs": {"fetch_url": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "fetch_text_content_from_url.py",
"function": "fetch_text_content_from_url", "is_builtin": false, "enable_kwargs":
false, "tool_state": "stable"}, {"name": "prepare_examples.py", "type": "python",
"source": "prepare_examples.py", "function": "prepare_examples", "is_builtin":
false, "enable_kwargs": false, "tool_state": "stable"}, {"name": "summarize_text_content.jinja2",
"type": "prompt", "inputs": {"text": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "summarize_text_content.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}, {"name":
"summarize_text_content__variant_1.jinja2", "type": "prompt", "inputs": {"text":
{"type": ["string"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "source": "summarize_text_content__variant_1.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"url": {"type": "string", "default": "https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h",
"is_chat_input": false}}, "outputs": {"category": {"type": "string", "reference":
"${convert_to_dict.output.category}", "evaluation_only": false, "is_chat_output":
false}, "evidence": {"type": "string", "reference": "${convert_to_dict.output.evidence}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/batch_run_name/flowRuns/batch_run_name",
"flowRunId": "batch_run_name", "flowRunDisplayName": "batch_run_name", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"url": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/batch_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "83cbe8e6-2d19-46c6-8fba-7875fdb033e1",
"studioPortalEndpoint": "https://ml.azure.com/runs/batch_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '16239'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.263'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "fetch_text_content_from_url", "type":
"python", "source": {"type": "code", "path": "fetch_text_content_from_url.py"},
"inputs": {"fetch_url": "${inputs.url}"}, "tool": "fetch_text_content_from_url.py",
"reduce": false}, {"name": "prepare_examples", "type": "python", "source":
{"type": "code", "path": "prepare_examples.py"}, "inputs": {}, "tool": "prepare_examples.py",
"reduce": false}, {"name": "classify_with_llm", "type": "llm", "source": {"type":
"code", "path": "classify_with_llm.jinja2"}, "inputs": {"deployment_name":
"gpt-35-turbo", "suffix": "", "max_tokens": "128", "temperature": "0.1", "top_p":
"1.0", "logprobs": "", "echo": "False", "stop": "", "presence_penalty": "0",
"frequency_penalty": "0", "best_of": "1", "logit_bias": "", "url": "${inputs.url}",
"examples": "${prepare_examples.output}", "text_content": "${summarize_text_content.output}"},
"tool": "classify_with_llm.jinja2", "reduce": false, "api": "chat", "provider":
"AzureOpenAI", "connection": "azure_open_ai_connection", "module": "promptflow.tools.aoai"},
{"name": "convert_to_dict", "type": "python", "source": {"type": "code", "path":
"convert_to_dict.py"}, "inputs": {"input_str": "${classify_with_llm.output}"},
"tool": "convert_to_dict.py", "reduce": false}, {"name": "summarize_text_content",
"type": "llm", "source": {"type": "code", "path": "summarize_text_content.jinja2"},
"inputs": {"deployment_name": "gpt-35-turbo", "suffix": "", "max_tokens":
"128", "temperature": "0.2", "top_p": "1.0", "logprobs": "", "echo": "False",
"stop": "", "presence_penalty": "0", "frequency_penalty": "0", "best_of":
"1", "logit_bias": "", "text": "${fetch_text_content_from_url.output}"}, "tool":
"summarize_text_content.jinja2", "reduce": false, "api": "chat", "provider":
"AzureOpenAI", "connection": "azure_open_ai_connection", "module": "promptflow.tools.aoai"}],
"tools": [{"name": "Content Safety (Text Analyze)", "type": "python", "inputs":
{"connection": {"type": ["AzureContentSafetyConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "hate_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "self_harm_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "sexual_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "text": {"type":
["string"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "violence_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"}},
"description": "Use Azure Content Safety to detect harmful content.", "module":
"promptflow.tools.azure_content_safety", "function": "analyze_text", "is_builtin":
true, "package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "classify_with_llm.jinja2", "type":
"prompt", "inputs": {"examples": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "text_content":
{"type": ["string"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "url": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "classify_with_llm.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}, {"name":
"convert_to_dict.py", "type": "python", "inputs": {"input_str": {"type": ["string"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"}},
"source": "convert_to_dict.py", "function": "convert_to_dict", "is_builtin":
false, "enable_kwargs": false, "tool_state": "stable"}, {"name": "fetch_text_content_from_url.py",
"type": "python", "inputs": {"fetch_url": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "fetch_text_content_from_url.py",
"function": "fetch_text_content_from_url", "is_builtin": false, "enable_kwargs":
false, "tool_state": "stable"}, {"name": "prepare_examples.py", "type": "python",
"source": "prepare_examples.py", "function": "prepare_examples", "is_builtin":
false, "enable_kwargs": false, "tool_state": "stable"}, {"name": "summarize_text_content.jinja2",
"type": "prompt", "inputs": {"text": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "summarize_text_content.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}, {"name":
"summarize_text_content__variant_1.jinja2", "type": "prompt", "inputs": {"text":
{"type": ["string"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "source": "summarize_text_content__variant_1.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"url": {"type": "string", "default": "https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h",
"is_chat_input": false}}, "outputs": {"category": {"type": "string", "reference":
"${convert_to_dict.output.category}", "evaluation_only": false, "is_chat_output":
false}, "evidence": {"type": "string", "reference": "${convert_to_dict.output.evidence}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/batch_run_name/flowRuns/batch_run_name",
"flowRunId": "batch_run_name", "flowRunDisplayName": "batch_run_name", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"url": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/batch_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "83cbe8e6-2d19-46c6-8fba-7875fdb033e1",
"studioPortalEndpoint": "https://ml.azure.com/runs/batch_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '16239'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.488'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "fetch_text_content_from_url", "type":
"python", "source": {"type": "code", "path": "fetch_text_content_from_url.py"},
"inputs": {"fetch_url": "${inputs.url}"}, "tool": "fetch_text_content_from_url.py",
"reduce": false}, {"name": "prepare_examples", "type": "python", "source":
{"type": "code", "path": "prepare_examples.py"}, "inputs": {}, "tool": "prepare_examples.py",
"reduce": false}, {"name": "classify_with_llm", "type": "llm", "source": {"type":
"code", "path": "classify_with_llm.jinja2"}, "inputs": {"deployment_name":
"gpt-35-turbo", "suffix": "", "max_tokens": "128", "temperature": "0.1", "top_p":
"1.0", "logprobs": "", "echo": "False", "stop": "", "presence_penalty": "0",
"frequency_penalty": "0", "best_of": "1", "logit_bias": "", "url": "${inputs.url}",
"examples": "${prepare_examples.output}", "text_content": "${summarize_text_content.output}"},
"tool": "classify_with_llm.jinja2", "reduce": false, "api": "chat", "provider":
"AzureOpenAI", "connection": "azure_open_ai_connection", "module": "promptflow.tools.aoai"},
{"name": "convert_to_dict", "type": "python", "source": {"type": "code", "path":
"convert_to_dict.py"}, "inputs": {"input_str": "${classify_with_llm.output}"},
"tool": "convert_to_dict.py", "reduce": false}, {"name": "summarize_text_content",
"type": "llm", "source": {"type": "code", "path": "summarize_text_content.jinja2"},
"inputs": {"deployment_name": "gpt-35-turbo", "suffix": "", "max_tokens":
"128", "temperature": "0.2", "top_p": "1.0", "logprobs": "", "echo": "False",
"stop": "", "presence_penalty": "0", "frequency_penalty": "0", "best_of":
"1", "logit_bias": "", "text": "${fetch_text_content_from_url.output}"}, "tool":
"summarize_text_content.jinja2", "reduce": false, "api": "chat", "provider":
"AzureOpenAI", "connection": "azure_open_ai_connection", "module": "promptflow.tools.aoai"}],
"tools": [{"name": "Content Safety (Text Analyze)", "type": "python", "inputs":
{"connection": {"type": ["AzureContentSafetyConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "hate_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "self_harm_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "sexual_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "text": {"type":
["string"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "violence_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"}},
"description": "Use Azure Content Safety to detect harmful content.", "module":
"promptflow.tools.azure_content_safety", "function": "analyze_text", "is_builtin":
true, "package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "classify_with_llm.jinja2", "type":
"prompt", "inputs": {"examples": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "text_content":
{"type": ["string"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "url": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "classify_with_llm.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}, {"name":
"convert_to_dict.py", "type": "python", "inputs": {"input_str": {"type": ["string"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"}},
"source": "convert_to_dict.py", "function": "convert_to_dict", "is_builtin":
false, "enable_kwargs": false, "tool_state": "stable"}, {"name": "fetch_text_content_from_url.py",
"type": "python", "inputs": {"fetch_url": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "fetch_text_content_from_url.py",
"function": "fetch_text_content_from_url", "is_builtin": false, "enable_kwargs":
false, "tool_state": "stable"}, {"name": "prepare_examples.py", "type": "python",
"source": "prepare_examples.py", "function": "prepare_examples", "is_builtin":
false, "enable_kwargs": false, "tool_state": "stable"}, {"name": "summarize_text_content.jinja2",
"type": "prompt", "inputs": {"text": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "summarize_text_content.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}, {"name":
"summarize_text_content__variant_1.jinja2", "type": "prompt", "inputs": {"text":
{"type": ["string"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "source": "summarize_text_content__variant_1.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"url": {"type": "string", "default": "https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h",
"is_chat_input": false}}, "outputs": {"category": {"type": "string", "reference":
"${convert_to_dict.output.category}", "evaluation_only": false, "is_chat_output":
false}, "evidence": {"type": "string", "reference": "${convert_to_dict.output.evidence}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/batch_run_name/flowRuns/batch_run_name",
"flowRunId": "batch_run_name", "flowRunDisplayName": "batch_run_name", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"url": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/batch_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "83cbe8e6-2d19-46c6-8fba-7875fdb033e1",
"studioPortalEndpoint": "https://ml.azure.com/runs/batch_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '16239'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.469'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "fetch_text_content_from_url", "type":
"python", "source": {"type": "code", "path": "fetch_text_content_from_url.py"},
"inputs": {"fetch_url": "${inputs.url}"}, "tool": "fetch_text_content_from_url.py",
"reduce": false}, {"name": "prepare_examples", "type": "python", "source":
{"type": "code", "path": "prepare_examples.py"}, "inputs": {}, "tool": "prepare_examples.py",
"reduce": false}, {"name": "classify_with_llm", "type": "llm", "source": {"type":
"code", "path": "classify_with_llm.jinja2"}, "inputs": {"deployment_name":
"gpt-35-turbo", "suffix": "", "max_tokens": "128", "temperature": "0.1", "top_p":
"1.0", "logprobs": "", "echo": "False", "stop": "", "presence_penalty": "0",
"frequency_penalty": "0", "best_of": "1", "logit_bias": "", "url": "${inputs.url}",
"examples": "${prepare_examples.output}", "text_content": "${summarize_text_content.output}"},
"tool": "classify_with_llm.jinja2", "reduce": false, "api": "chat", "provider":
"AzureOpenAI", "connection": "azure_open_ai_connection", "module": "promptflow.tools.aoai"},
{"name": "convert_to_dict", "type": "python", "source": {"type": "code", "path":
"convert_to_dict.py"}, "inputs": {"input_str": "${classify_with_llm.output}"},
"tool": "convert_to_dict.py", "reduce": false}, {"name": "summarize_text_content",
"type": "llm", "source": {"type": "code", "path": "summarize_text_content.jinja2"},
"inputs": {"deployment_name": "gpt-35-turbo", "suffix": "", "max_tokens":
"128", "temperature": "0.2", "top_p": "1.0", "logprobs": "", "echo": "False",
"stop": "", "presence_penalty": "0", "frequency_penalty": "0", "best_of":
"1", "logit_bias": "", "text": "${fetch_text_content_from_url.output}"}, "tool":
"summarize_text_content.jinja2", "reduce": false, "api": "chat", "provider":
"AzureOpenAI", "connection": "azure_open_ai_connection", "module": "promptflow.tools.aoai"}],
"tools": [{"name": "Content Safety (Text Analyze)", "type": "python", "inputs":
{"connection": {"type": ["AzureContentSafetyConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "hate_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "self_harm_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "sexual_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "text": {"type":
["string"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "violence_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"}},
"description": "Use Azure Content Safety to detect harmful content.", "module":
"promptflow.tools.azure_content_safety", "function": "analyze_text", "is_builtin":
true, "package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "classify_with_llm.jinja2", "type":
"prompt", "inputs": {"examples": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "text_content":
{"type": ["string"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "url": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "classify_with_llm.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}, {"name":
"convert_to_dict.py", "type": "python", "inputs": {"input_str": {"type": ["string"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"}},
"source": "convert_to_dict.py", "function": "convert_to_dict", "is_builtin":
false, "enable_kwargs": false, "tool_state": "stable"}, {"name": "fetch_text_content_from_url.py",
"type": "python", "inputs": {"fetch_url": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "fetch_text_content_from_url.py",
"function": "fetch_text_content_from_url", "is_builtin": false, "enable_kwargs":
false, "tool_state": "stable"}, {"name": "prepare_examples.py", "type": "python",
"source": "prepare_examples.py", "function": "prepare_examples", "is_builtin":
false, "enable_kwargs": false, "tool_state": "stable"}, {"name": "summarize_text_content.jinja2",
"type": "prompt", "inputs": {"text": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "summarize_text_content.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}, {"name":
"summarize_text_content__variant_1.jinja2", "type": "prompt", "inputs": {"text":
{"type": ["string"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "source": "summarize_text_content__variant_1.jinja2",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"url": {"type": "string", "default": "https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h",
"is_chat_input": false}}, "outputs": {"category": {"type": "string", "reference":
"${convert_to_dict.output.category}", "evaluation_only": false, "is_chat_output":
false}, "evidence": {"type": "string", "reference": "${convert_to_dict.output.evidence}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/batch_run_name/flowRuns/batch_run_name",
"flowRunId": "batch_run_name", "flowRunDisplayName": "batch_run_name", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"url": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/batch_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "83cbe8e6-2d19-46c6-8fba-7875fdb033e1",
"studioPortalEndpoint": "https://ml.azure.com/runs/batch_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '16239'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.256'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.080'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.129'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:16:24 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/webClassification3.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '379'
content-md5:
- lI/pz9jzTQ7Td3RHPL7y7w==
content-type:
- application/octet-stream
last-modified:
- Mon, 06 Nov 2023 08:30:18 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Mon, 06 Nov 2023 08:30:18 GMT
x-ms-meta-name:
- 94331215-cf7f-452a-9f1a-1d276bc9b0e4
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 3f163752-edb0-4afc-a6f5-b0a670bd7c24
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:16:25 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/webClassification3.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.135'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.089'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:16:29 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/eval-classification-accuracy/calculate_accuracy.py
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '409'
content-md5:
- OyENtlqGVUTrY5zKuzo8XA==
content-type:
- application/octet-stream
last-modified:
- Tue, 21 Nov 2023 08:03:40 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Tue, 21 Nov 2023 08:03:39 GMT
x-ms-meta-name:
- fd932777-4f3a-4c1d-9c3a-24d45835d7e1
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:16:30 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/eval-classification-accuracy/calculate_accuracy.py
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/eval-classification-accuracy/flow.dag.yaml",
"runId": "eval_run_name", "runDisplayName": "eval_run_name", "runExperimentName":
"", "variantRunId": "batch_run_name", "batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/webClassification3.jsonl"},
"inputsMapping": {"groundtruth": "${data.answer}", "prediction": "${run.outputs.category}"},
"connections": {}, "environmentVariables": {}, "runtimeName": "fake-runtime-name",
"sessionId": "000000000000000000000000000000000000000000000000", "sessionSetupMode":
"SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '947'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"eval_run_name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '6.931'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/eval_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "grade", "type": "python", "source":
{"type": "code", "path": "grade.py"}, "inputs": {"groundtruth": "${inputs.groundtruth}",
"prediction": "${inputs.prediction}"}, "tool": "grade.py", "reduce": false},
{"name": "calculate_accuracy", "type": "python", "source": {"type": "code",
"path": "calculate_accuracy.py"}, "inputs": {"grades": "${grade.output}"},
"tool": "calculate_accuracy.py", "reduce": true}], "tools": [{"name": "Content
Safety (Text Analyze)", "type": "python", "inputs": {"connection": {"type":
["AzureContentSafetyConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "hate_category": {"type": ["string"], "default":
"medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "self_harm_category": {"type": ["string"], "default":
"medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "sexual_category": {"type": ["string"], "default":
"medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "violence_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "description":
"Use Azure Content Safety to detect harmful content.", "module": "promptflow.tools.azure_content_safety",
"function": "analyze_text", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "enable_kwargs": false, "deprecated_tools":
["content_safety_text.tools.content_safety_text_tool.analyze_text"], "tool_state":
"stable"}, {"name": "Embedding", "type": "python", "inputs": {"connection":
{"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "calculate_accuracy.py", "type":
"python", "inputs": {"grades": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "calculate_accuracy.py",
"function": "calculate_accuracy", "is_builtin": false, "enable_kwargs": false,
"tool_state": "stable"}, {"name": "grade.py", "type": "python", "inputs":
{"groundtruth": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "prediction": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "grade.py",
"function": "grade", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"groundtruth": {"type": "string", "default": "APP",
"description": "Please specify the groundtruth column, which contains the
true label to the outputs that your flow produces.", "is_chat_input": false},
"prediction": {"type": "string", "default": "APP", "description": "Please
specify the prediction column, which contains the predicted outputs that your
flow produces.", "is_chat_input": false}}, "outputs": {"grade": {"type": "string",
"reference": "${grade.output}", "evaluation_only": false, "is_chat_output":
false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/eval_run_name/flowRuns/eval_run_name",
"flowRunId": "eval_run_name", "flowRunDisplayName": "eval_run_name", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"groundtruth": "${data.answer}", "prediction": "${run.outputs.category}"},
"outputDatastoreName": "workspaceblobstore", "childRunBasePath": "promptflow/PromptFlowArtifacts/eval_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "73d0c061-880c-466c-8fb0-b29e9ae7ab66",
"studioPortalEndpoint": "https://ml.azure.com/runs/eval_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '13869'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.388'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/eval_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "grade", "type": "python", "source":
{"type": "code", "path": "grade.py"}, "inputs": {"groundtruth": "${inputs.groundtruth}",
"prediction": "${inputs.prediction}"}, "tool": "grade.py", "reduce": false},
{"name": "calculate_accuracy", "type": "python", "source": {"type": "code",
"path": "calculate_accuracy.py"}, "inputs": {"grades": "${grade.output}"},
"tool": "calculate_accuracy.py", "reduce": true}], "tools": [{"name": "Content
Safety (Text Analyze)", "type": "python", "inputs": {"connection": {"type":
["AzureContentSafetyConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "hate_category": {"type": ["string"], "default":
"medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "self_harm_category": {"type": ["string"], "default":
"medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "sexual_category": {"type": ["string"], "default":
"medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "violence_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "description":
"Use Azure Content Safety to detect harmful content.", "module": "promptflow.tools.azure_content_safety",
"function": "analyze_text", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "enable_kwargs": false, "deprecated_tools":
["content_safety_text.tools.content_safety_text_tool.analyze_text"], "tool_state":
"stable"}, {"name": "Embedding", "type": "python", "inputs": {"connection":
{"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "calculate_accuracy.py", "type":
"python", "inputs": {"grades": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "calculate_accuracy.py",
"function": "calculate_accuracy", "is_builtin": false, "enable_kwargs": false,
"tool_state": "stable"}, {"name": "grade.py", "type": "python", "inputs":
{"groundtruth": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "prediction": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "grade.py",
"function": "grade", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"groundtruth": {"type": "string", "default": "APP",
"description": "Please specify the groundtruth column, which contains the
true label to the outputs that your flow produces.", "is_chat_input": false},
"prediction": {"type": "string", "default": "APP", "description": "Please
specify the prediction column, which contains the predicted outputs that your
flow produces.", "is_chat_input": false}}, "outputs": {"grade": {"type": "string",
"reference": "${grade.output}", "evaluation_only": false, "is_chat_output":
false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/eval_run_name/flowRuns/eval_run_name",
"flowRunId": "eval_run_name", "flowRunDisplayName": "eval_run_name", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"groundtruth": "${data.answer}", "prediction": "${run.outputs.category}"},
"outputDatastoreName": "workspaceblobstore", "childRunBasePath": "promptflow/PromptFlowArtifacts/eval_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "73d0c061-880c-466c-8fb0-b29e9ae7ab66",
"studioPortalEndpoint": "https://ml.azure.com/runs/eval_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '13869'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.270'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/eval_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "grade", "type": "python", "source":
{"type": "code", "path": "grade.py"}, "inputs": {"groundtruth": "${inputs.groundtruth}",
"prediction": "${inputs.prediction}"}, "tool": "grade.py", "reduce": false},
{"name": "calculate_accuracy", "type": "python", "source": {"type": "code",
"path": "calculate_accuracy.py"}, "inputs": {"grades": "${grade.output}"},
"tool": "calculate_accuracy.py", "reduce": true}], "tools": [{"name": "Content
Safety (Text Analyze)", "type": "python", "inputs": {"connection": {"type":
["AzureContentSafetyConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "hate_category": {"type": ["string"], "default":
"medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "self_harm_category": {"type": ["string"], "default":
"medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "sexual_category": {"type": ["string"], "default":
"medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "violence_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "description":
"Use Azure Content Safety to detect harmful content.", "module": "promptflow.tools.azure_content_safety",
"function": "analyze_text", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "enable_kwargs": false, "deprecated_tools":
["content_safety_text.tools.content_safety_text_tool.analyze_text"], "tool_state":
"stable"}, {"name": "Embedding", "type": "python", "inputs": {"connection":
{"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "calculate_accuracy.py", "type":
"python", "inputs": {"grades": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "calculate_accuracy.py",
"function": "calculate_accuracy", "is_builtin": false, "enable_kwargs": false,
"tool_state": "stable"}, {"name": "grade.py", "type": "python", "inputs":
{"groundtruth": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "prediction": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "grade.py",
"function": "grade", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"groundtruth": {"type": "string", "default": "APP",
"description": "Please specify the groundtruth column, which contains the
true label to the outputs that your flow produces.", "is_chat_input": false},
"prediction": {"type": "string", "default": "APP", "description": "Please
specify the prediction column, which contains the predicted outputs that your
flow produces.", "is_chat_input": false}}, "outputs": {"grade": {"type": "string",
"reference": "${grade.output}", "evaluation_only": false, "is_chat_output":
false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/eval_run_name/flowRuns/eval_run_name",
"flowRunId": "eval_run_name", "flowRunDisplayName": "eval_run_name", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"groundtruth": "${data.answer}", "prediction": "${run.outputs.category}"},
"outputDatastoreName": "workspaceblobstore", "childRunBasePath": "promptflow/PromptFlowArtifacts/eval_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "73d0c061-880c-466c-8fb0-b29e9ae7ab66",
"studioPortalEndpoint": "https://ml.azure.com/runs/eval_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '13869'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.336'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/eval_run_name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "grade", "type": "python", "source":
{"type": "code", "path": "grade.py"}, "inputs": {"groundtruth": "${inputs.groundtruth}",
"prediction": "${inputs.prediction}"}, "tool": "grade.py", "reduce": false},
{"name": "calculate_accuracy", "type": "python", "source": {"type": "code",
"path": "calculate_accuracy.py"}, "inputs": {"grades": "${grade.output}"},
"tool": "calculate_accuracy.py", "reduce": true}], "tools": [{"name": "Content
Safety (Text Analyze)", "type": "python", "inputs": {"connection": {"type":
["AzureContentSafetyConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "hate_category": {"type": ["string"], "default":
"medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "self_harm_category": {"type": ["string"], "default":
"medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "sexual_category": {"type": ["string"], "default":
"medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "violence_category":
{"type": ["string"], "default": "medium_sensitivity", "enum": ["disable",
"low_sensitivity", "medium_sensitivity", "high_sensitivity"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "description":
"Use Azure Content Safety to detect harmful content.", "module": "promptflow.tools.azure_content_safety",
"function": "analyze_text", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "enable_kwargs": false, "deprecated_tools":
["content_safety_text.tools.content_safety_text_tool.analyze_text"], "tool_state":
"stable"}, {"name": "Embedding", "type": "python", "inputs": {"connection":
{"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "calculate_accuracy.py", "type":
"python", "inputs": {"grades": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "calculate_accuracy.py",
"function": "calculate_accuracy", "is_builtin": false, "enable_kwargs": false,
"tool_state": "stable"}, {"name": "grade.py", "type": "python", "inputs":
{"groundtruth": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "prediction": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "source": "grade.py",
"function": "grade", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"groundtruth": {"type": "string", "default": "APP",
"description": "Please specify the groundtruth column, which contains the
true label to the outputs that your flow produces.", "is_chat_input": false},
"prediction": {"type": "string", "default": "APP", "description": "Please
specify the prediction column, which contains the predicted outputs that your
flow produces.", "is_chat_input": false}}, "outputs": {"grade": {"type": "string",
"reference": "${grade.output}", "evaluation_only": false, "is_chat_output":
false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/eval_run_name/flowRuns/eval_run_name",
"flowRunId": "eval_run_name", "flowRunDisplayName": "eval_run_name", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"groundtruth": "${data.answer}", "prediction": "${run.outputs.category}"},
"outputDatastoreName": "workspaceblobstore", "childRunBasePath": "promptflow/PromptFlowArtifacts/eval_run_name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "73d0c061-880c-466c-8fb0-b29e9ae7ab66",
"studioPortalEndpoint": "https://ml.azure.com/runs/eval_run_name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '13869'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.366'
status:
code: 200
message: OK
- request:
body: '{"runId": "batch_run_name", "selectRunMetadata": true, "selectRunDefinition":
true, "selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705047344, "rootRunId": "batch_run_name",
"createdUtc": "2024-01-12T08:15:44.0948865+00:00", "createdBy": {"userObjectId":
"00000000-0000-0000-0000-000000000000", "userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": null, "warnings": null, "revision": 6,
"statusRevision": 3, "runUuid": "e52bd2e7-d460-459a-a3ab-07d848ea525d", "parentRunUuid":
null, "rootRunUuid": "e52bd2e7-d460-459a-a3ab-07d848ea525d", "lastStartTimeUtc":
null, "currentComputeTime": null, "computeDuration": "00:00:06.7505192", "effectiveStartTimeUtc":
null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "18a66f5f-dbdf-4c17-9dd7-1634712a9cbe",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:16:06.9067508+00:00", "duration":
"00:00:06.7505192", "cancelationReason": null, "currentAttemptId": 1, "runId":
"batch_run_name", "parentRunId": null, "experimentId": "d30efbeb-f81d-4cfa-b5cc-a0570a049009",
"status": "Completed", "startTimeUtc": "2024-01-12T08:16:01.0613927+00:00",
"endTimeUtc": "2024-01-12T08:16:07.8119119+00:00", "scheduleId": null, "displayName":
"batch_run_name", "name": null, "dataContainerId": "dcid.batch_run_name",
"description": null, "hidden": false, "runType": "azureml.promptflow.FlowRun",
"runTypeV2": {"orchestrator": null, "traits": [], "attribution": "PromptFlow",
"computeType": "AmlcDsi"}, "properties": {"azureml.promptflow.runtime_name":
"test-runtime-ci", "azureml.promptflow.runtime_version": "20231204.v4", "azureml.promptflow.definition_file_name":
"flow.dag.yaml", "azureml.promptflow.session_id": "4dd8f4d5f44dfeb817d3438cf84bd739215d87afd9458597",
"azureml.promptflow.flow_lineage_id": "af1a6951de9be2ce13d3b58b23dbd8b6a0cd8fd4918ad9cb22b28fb8395fbcb0",
"azureml.promptflow.node_variant": "${summarize_text_content.variant_0}",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/a1fa6ef1ead7ff3ce76b36250f6f5461/web_classification/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl",
"azureml.promptflow.inputs_mapping": "{\"url\":\"${data.url}\"}", "_azureml.evaluation_run":
"promptflow.BatchRun", "azureml.promptflow.snapshot_id": "83cbe8e6-2d19-46c6-8fba-7875fdb033e1",
"azureml.promptflow.total_tokens": "2448", "_azureml.evaluate_artifacts":
"[{\"path\": \"instance_results.jsonl\", \"type\": \"table\"}]"}, "parameters":
{}, "actionUris": {}, "scriptName": null, "target": null, "uniqueChildRunComputeTargets":
[], "tags": {}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": {"debug_info": {"assetId":
"azureml://locations/eastus/workspaces/00000/data/azureml_batch_run_name_output_data_debug_info/versions/1",
"type": "UriFolder"}, "flow_outputs": {"assetId": "azureml://locations/eastus/workspaces/00000/data/azureml_batch_run_name_output_data_flow_outputs/versions/1",
"type": "UriFolder"}}}, "runDefinition": null, "jobSpecification": null, "systemSettings":
null}'
headers:
connection:
- keep-alive
content-length:
- '4732'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.049'
status:
code: 200
message: OK
- request:
body: '{"runId": "eval_run_name", "selectRunMetadata": true, "selectRunDefinition":
true, "selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705047396, "rootRunId": "eval_run_name",
"createdUtc": "2024-01-12T08:16:36.0629362+00:00", "createdBy": {"userObjectId":
"00000000-0000-0000-0000-000000000000", "userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": null, "warnings": null, "revision": 6,
"statusRevision": 3, "runUuid": "a3978660-b3ed-4116-b125-6a52e8c8e4cb", "parentRunUuid":
null, "rootRunUuid": "a3978660-b3ed-4116-b125-6a52e8c8e4cb", "lastStartTimeUtc":
null, "currentComputeTime": null, "computeDuration": "00:00:04.8368673", "effectiveStartTimeUtc":
null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "18a66f5f-dbdf-4c17-9dd7-1634712a9cbe",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:16:57.9353592+00:00", "duration":
"00:00:04.8368673", "cancelationReason": null, "currentAttemptId": 1, "runId":
"eval_run_name", "parentRunId": null, "experimentId": "7bdec279-f99c-4ed3-b0b8-dd75698b8fd0",
"status": "Completed", "startTimeUtc": "2024-01-12T08:16:54.0128269+00:00",
"endTimeUtc": "2024-01-12T08:16:58.8496942+00:00", "scheduleId": null, "displayName":
"eval_run_name", "name": null, "dataContainerId": "dcid.eval_run_name", "description":
null, "hidden": false, "runType": "azureml.promptflow.FlowRun", "runTypeV2":
{"orchestrator": null, "traits": [], "attribution": "PromptFlow", "computeType":
"AmlcDsi"}, "properties": {"azureml.promptflow.runtime_name": "test-runtime-ci",
"azureml.promptflow.runtime_version": "20231204.v4", "azureml.promptflow.definition_file_name":
"flow.dag.yaml", "azureml.promptflow.session_id": "f8e4236a4e78e7f7125bbd811ec7976cb330412723a530f8",
"azureml.promptflow.flow_lineage_id": "26c575d863a85371ef937096728441d8c68c3e737b5a1bfeae5ac8f3b9ccb048",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/1aa3064d06f6170abbc488cc35c713b9/eval-classification-accuracy/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl",
"azureml.promptflow.input_run_id": "batch_run_name", "azureml.promptflow.inputs_mapping":
"{\"groundtruth\":\"${data.answer}\",\"prediction\":\"${run.outputs.category}\"}",
"_azureml.evaluation_run": "promptflow.BatchRun", "azureml.promptflow.snapshot_id":
"73d0c061-880c-466c-8fb0-b29e9ae7ab66", "azureml.promptflow.total_tokens":
"0", "_azureml.evaluate_artifacts": "[{\"path\": \"instance_results.jsonl\",
\"type\": \"table\"}]"}, "parameters": {}, "actionUris": {}, "scriptName":
null, "target": null, "uniqueChildRunComputeTargets": [], "tags": {}, "settings":
{}, "services": {}, "inputDatasets": [], "outputDatasets": [], "runDefinition":
null, "jobSpecification": null, "primaryMetricName": null, "createdFrom":
null, "cancelUri": null, "completeUri": null, "diagnosticsUri": null, "computeRequest":
null, "compute": null, "retainForLifetimeOfWorkspace": false, "queueingInfo":
null, "inputs": null, "outputs": {"debug_info": {"assetId": "azureml://locations/eastus/workspaces/00000/data/azureml_eval_run_name_output_data_debug_info/versions/1",
"type": "UriFolder"}, "flow_outputs": {"assetId": "azureml://locations/eastus/workspaces/00000/data/azureml_eval_run_name_output_data_flow_outputs/versions/1",
"type": "UriFolder"}}}, "runDefinition": null, "jobSpecification": null, "systemSettings":
null}'
headers:
connection:
- keep-alive
content-length:
- '4794'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.066'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/batch_run_name/logContent
response:
body:
string: '"2024-01-12 08:15:48 +0000 106 promptflow-runtime INFO [batch_run_name]
Receiving v2 bulk run request 3fe0e3e1-2e3a-44a7-94c9-4a64bc9388a5: {\"flow_id\":
\"batch_run_name\", \"flow_run_id\": \"batch_run_name\", \"flow_source\":
{\"flow_source_type\": 1, \"flow_source_info\": {\"snapshot_id\": \"83cbe8e6-2d19-46c6-8fba-7875fdb033e1\"},
\"flow_dag_file\": \"flow.dag.yaml\"}, \"connections\": \"**data_scrubbed**\",
\"log_path\": \"https://promptfloweast4063704120.blob.core.windows.net/azureml/ExperimentRun/dcid.batch_run_name/logs/azureml/executionlogs.txt?sv=2019-07-07&sr=b&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T08%3A05%3A43Z&ske=2024-01-13T16%3A15%3A43Z&sks=b&skv=2019-07-07&st=2024-01-12T08%3A05%3A47Z&se=2024-01-12T16%3A15%3A47Z&sp=rcw\",
\"app_insights_instrumentation_key\": \"InstrumentationKey=**data_scrubbed**;IngestionEndpoint=https://eastus-6.in.applicationinsights.azure.com/;LiveEndpoint=https://eastus.livediagnostics.monitor.azure.com/\",
\"data_inputs\": {\"data\": \"azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl\"},
\"inputs_mapping\": {\"url\": \"${data.url}\"}, \"azure_storage_setting\":
{\"azure_storage_mode\": 1, \"storage_account_name\": \"promptfloweast4063704120\",
\"blob_container_name\": \"azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5\",
\"flow_artifacts_root_path\": \"promptflow/PromptFlowArtifacts/batch_run_name\",
\"blob_container_sas_token\": \"?sv=2019-07-07&sr=c&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T08%3A15%3A48Z&ske=2024-01-19T08%3A15%3A48Z&sks=b&skv=2019-07-07&se=2024-01-19T08%3A15%3A48Z&sp=racwl\",
\"output_datastore_name\": \"workspaceblobstore\"}}\n2024-01-12 08:15:48 +0000 106
promptflow-runtime INFO Runtime version: 20231204.v4. PromptFlow version:
1.2.0rc1\n2024-01-12 08:15:48 +0000 106 promptflow-runtime INFO Updating
batch_run_name to Status.Preparing...\n2024-01-12 08:15:48 +0000 106 promptflow-runtime
INFO Downloading snapshot to /mnt/host/service/app/34817/requests/batch_run_name\n2024-01-12
08:15:48 +0000 106 promptflow-runtime INFO Get snapshot sas url for
83cbe8e6-2d19-46c6-8fba-7875fdb033e1...\n2024-01-12 08:15:55 +0000 106
promptflow-runtime INFO Downloading snapshot 83cbe8e6-2d19-46c6-8fba-7875fdb033e1
from uri https://promptfloweast4063704120.blob.core.windows.net/snapshotzips/promptflow-eastus:3e123da1-f9a5-4c91-9234-8d9ffbb39ff5:snapshotzip/83cbe8e6-2d19-46c6-8fba-7875fdb033e1.zip...\n2024-01-12
08:15:55 +0000 106 promptflow-runtime INFO Downloaded file /mnt/host/service/app/34817/requests/batch_run_name/83cbe8e6-2d19-46c6-8fba-7875fdb033e1.zip
with size 5027 for snapshot 83cbe8e6-2d19-46c6-8fba-7875fdb033e1.\n2024-01-12
08:15:55 +0000 106 promptflow-runtime INFO Download snapshot 83cbe8e6-2d19-46c6-8fba-7875fdb033e1
completed.\n2024-01-12 08:15:55 +0000 106 promptflow-runtime INFO Successfully
download snapshot to /mnt/host/service/app/34817/requests/batch_run_name\n2024-01-12
08:15:55 +0000 106 promptflow-runtime INFO About to execute a python
flow.\n2024-01-12 08:15:55 +0000 106 promptflow-runtime INFO Use spawn
method to start child process.\n2024-01-12 08:15:55 +0000 106 promptflow-runtime
INFO Starting to check process 3917 status for run batch_run_name\n2024-01-12
08:15:55 +0000 106 promptflow-runtime INFO Start checking run status
for run batch_run_name\n2024-01-12 08:15:59 +0000 3917 promptflow-runtime
INFO [106--3917] Start processing flowV2......\n2024-01-12 08:15:59 +0000 3917
promptflow-runtime INFO Runtime version: 20231204.v4. PromptFlow version:
1.2.0rc1\n2024-01-12 08:15:59 +0000 3917 promptflow-runtime INFO Setting
mlflow tracking uri...\n2024-01-12 08:15:59 +0000 3917 promptflow-runtime
INFO Validating ''AzureML Data Scientist'' user authentication...\n2024-01-12
08:15:59 +0000 3917 promptflow-runtime INFO Successfully validated
''AzureML Data Scientist'' user authentication.\n2024-01-12 08:15:59 +0000 3917
promptflow-runtime INFO Using AzureMLRunStorageV2\n2024-01-12 08:15:59
+0000 3917 promptflow-runtime INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
08:15:59 +0000 3917 promptflow-runtime INFO Initialized blob service
client for AzureMLRunTracker.\n2024-01-12 08:15:59 +0000 3917 promptflow-runtime
INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
08:16:00 +0000 3917 promptflow-runtime INFO Resolve data from url finished
in 0.7087652487680316 seconds\n2024-01-12 08:16:00 +0000 3917 promptflow-runtime
INFO Starting the aml run ''batch_run_name''...\n2024-01-12 08:16:01 +0000 3917
execution.bulk INFO Using fork, process count: 3\n2024-01-12 08:16:01
+0000 3959 execution.bulk INFO Process 3959 started.\n2024-01-12
08:16:01 +0000 3964 execution.bulk INFO Process 3964 started.\n2024-01-12
08:16:01 +0000 3917 execution.bulk INFO Process name: ForkProcess-30:2,
Process id: 3959, Line number: 0 start execution.\n2024-01-12 08:16:01 +0000 3969
execution.bulk INFO Process 3969 started.\n2024-01-12 08:16:01 +0000 3917
execution.bulk INFO Process name: ForkProcess-30:3, Process id: 3964,
Line number: 1 start execution.\n2024-01-12 08:16:01 +0000 3917 execution.bulk INFO Process
name: ForkProcess-30:4, Process id: 3969, Line number: 2 start execution.\n2024-01-12
08:16:02 +0000 3917 execution.bulk INFO Process name: ForkProcess-30:4,
Process id: 3969, Line number: 2 completed.\n2024-01-12 08:16:02 +0000 3917
execution.bulk INFO Finished 1 / 3 lines.\n2024-01-12 08:16:02 +0000 3917
execution.bulk INFO Process name: ForkProcess-30:3, Process id: 3964,
Line number: 1 completed.\n2024-01-12 08:16:02 +0000 3917 execution.bulk INFO Average
execution time for completed lines: 1.52 seconds. Estimated time for incomplete
lines: 3.04 seconds.\n2024-01-12 08:16:02 +0000 3917 execution.bulk INFO Finished
2 / 3 lines.\n2024-01-12 08:16:02 +0000 3917 execution.bulk INFO Average
execution time for completed lines: 0.78 seconds. Estimated time for incomplete
lines: 0.78 seconds.\n2024-01-12 08:16:03 +0000 3917 execution.bulk INFO Process
name: ForkProcess-30:2, Process id: 3959, Line number: 0 completed.\n2024-01-12
08:16:03 +0000 3917 execution.bulk INFO Finished 3 / 3 lines.\n2024-01-12
08:16:03 +0000 3917 execution.bulk INFO Average execution time
for completed lines: 0.61 seconds. Estimated time for incomplete lines: 0.0
seconds.\n2024-01-12 08:16:06 +0000 3917 execution.bulk INFO Upload
status summary metrics for run batch_run_name finished in 2.639357965439558
seconds\n2024-01-12 08:16:06 +0000 3917 promptflow-runtime INFO Successfully
write run properties {\"azureml.promptflow.total_tokens\": 2448, \"_azureml.evaluate_artifacts\":
\"[{\\\"path\\\": \\\"instance_results.jsonl\\\", \\\"type\\\": \\\"table\\\"}]\"}
with run id ''batch_run_name''\n2024-01-12 08:16:06 +0000 3917 execution.bulk INFO Upload
RH properties for run batch_run_name finished in 0.07268641889095306 seconds\n2024-01-12
08:16:06 +0000 3917 promptflow-runtime INFO Creating unregistered output
Asset for Run batch_run_name...\n2024-01-12 08:16:07 +0000 3917 promptflow-runtime
INFO Created debug_info Asset: azureml://locations/eastus/workspaces/00000/data/azureml_batch_run_name_output_data_debug_info/versions/1\n2024-01-12
08:16:07 +0000 3917 promptflow-runtime INFO Creating unregistered output
Asset for Run batch_run_name...\n2024-01-12 08:16:07 +0000 3917 promptflow-runtime
INFO Created flow_outputs output Asset: azureml://locations/eastus/workspaces/00000/data/azureml_batch_run_name_output_data_flow_outputs/versions/1\n2024-01-12
08:16:07 +0000 3917 promptflow-runtime INFO Creating Artifact for Run
batch_run_name...\n2024-01-12 08:16:07 +0000 3917 promptflow-runtime INFO Created
instance_results.jsonl Artifact.\n2024-01-12 08:16:07 +0000 3917 promptflow-runtime
INFO Patching batch_run_name...\n2024-01-12 08:16:07 +0000 3917 promptflow-runtime
INFO Ending the aml run ''batch_run_name'' with status ''Completed''...\n2024-01-12
08:16:09 +0000 106 promptflow-runtime INFO Process 3917 finished\n2024-01-12
08:16:09 +0000 106 promptflow-runtime INFO [106] Child process finished!\n2024-01-12
08:16:09 +0000 106 promptflow-runtime INFO [batch_run_name] End processing
bulk run\n2024-01-12 08:16:09 +0000 106 promptflow-runtime INFO Cleanup
working dir /mnt/host/service/app/34817/requests/batch_run_name for bulk run\n"'
headers:
connection:
- keep-alive
content-length:
- '9861'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.454'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/eval_run_name/logContent
response:
body:
string: '"2024-01-12 08:16:40 +0000 134 promptflow-runtime INFO [eval_run_name]
Receiving v2 bulk run request abc15e77-e71f-4626-8037-8f58ccd9b423: {\"flow_id\":
\"eval_run_name\", \"flow_run_id\": \"eval_run_name\", \"flow_source\": {\"flow_source_type\":
1, \"flow_source_info\": {\"snapshot_id\": \"73d0c061-880c-466c-8fb0-b29e9ae7ab66\"},
\"flow_dag_file\": \"flow.dag.yaml\"}, \"log_path\": \"https://promptfloweast4063704120.blob.core.windows.net/azureml/ExperimentRun/dcid.eval_run_name/logs/azureml/executionlogs.txt?sv=2019-07-07&sr=b&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T07%3A46%3A24Z&ske=2024-01-13T15%3A56%3A24Z&sks=b&skv=2019-07-07&st=2024-01-12T08%3A06%3A39Z&se=2024-01-12T16%3A16%3A39Z&sp=rcw\",
\"app_insights_instrumentation_key\": \"InstrumentationKey=**data_scrubbed**;IngestionEndpoint=https://eastus-6.in.applicationinsights.azure.com/;LiveEndpoint=https://eastus.livediagnostics.monitor.azure.com/\",
\"data_inputs\": {\"data\": \"azureml://datastores/workspaceblobstore/paths/LocalUpload/74c11bba717480b2d6b04b8e746d09d7/webClassification3.jsonl\",
\"run.outputs\": \"azureml:/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/data/azureml_batch_run_name_output_data_flow_outputs/versions/1\"},
\"inputs_mapping\": {\"groundtruth\": \"${data.answer}\", \"prediction\":
\"${run.outputs.category}\"}, \"azure_storage_setting\": {\"azure_storage_mode\":
1, \"storage_account_name\": \"promptfloweast4063704120\", \"blob_container_name\":
\"azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5\", \"flow_artifacts_root_path\":
\"promptflow/PromptFlowArtifacts/eval_run_name\", \"blob_container_sas_token\":
\"?sv=2019-07-07&sr=c&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=00000000-0000-0000-0000-000000000000&skt=2024-01-12T08%3A16%3A40Z&ske=2024-01-19T08%3A16%3A40Z&sks=b&skv=2019-07-07&se=2024-01-19T08%3A16%3A40Z&sp=racwl\",
\"output_datastore_name\": \"workspaceblobstore\"}}\n2024-01-12 08:16:40 +0000 134
promptflow-runtime INFO Runtime version: 20231204.v4. PromptFlow version:
1.2.0rc1\n2024-01-12 08:16:40 +0000 134 promptflow-runtime INFO Updating
eval_run_name to Status.Preparing...\n2024-01-12 08:16:41 +0000 134 promptflow-runtime
INFO Downloading snapshot to /mnt/host/service/app/38343/requests/eval_run_name\n2024-01-12
08:16:41 +0000 134 promptflow-runtime INFO Get snapshot sas url for
73d0c061-880c-466c-8fb0-b29e9ae7ab66...\n2024-01-12 08:16:47 +0000 134
promptflow-runtime INFO Downloading snapshot 73d0c061-880c-466c-8fb0-b29e9ae7ab66
from uri https://promptfloweast4063704120.blob.core.windows.net/snapshotzips/promptflow-eastus:3e123da1-f9a5-4c91-9234-8d9ffbb39ff5:snapshotzip/73d0c061-880c-466c-8fb0-b29e9ae7ab66.zip...\n2024-01-12
08:16:47 +0000 134 promptflow-runtime INFO Downloaded file /mnt/host/service/app/38343/requests/eval_run_name/73d0c061-880c-466c-8fb0-b29e9ae7ab66.zip
with size 1243 for snapshot 73d0c061-880c-466c-8fb0-b29e9ae7ab66.\n2024-01-12
08:16:47 +0000 134 promptflow-runtime INFO Download snapshot 73d0c061-880c-466c-8fb0-b29e9ae7ab66
completed.\n2024-01-12 08:16:47 +0000 134 promptflow-runtime INFO Successfully
download snapshot to /mnt/host/service/app/38343/requests/eval_run_name\n2024-01-12
08:16:47 +0000 134 promptflow-runtime INFO About to execute a python
flow.\n2024-01-12 08:16:47 +0000 134 promptflow-runtime INFO Use spawn
method to start child process.\n2024-01-12 08:16:47 +0000 134 promptflow-runtime
INFO Starting to check process 4041 status for run eval_run_name\n2024-01-12
08:16:47 +0000 134 promptflow-runtime INFO Start checking run status
for run eval_run_name\n2024-01-12 08:16:51 +0000 4041 promptflow-runtime
INFO [134--4041] Start processing flowV2......\n2024-01-12 08:16:51 +0000 4041
promptflow-runtime INFO Runtime version: 20231204.v4. PromptFlow version:
1.2.0rc1\n2024-01-12 08:16:51 +0000 4041 promptflow-runtime INFO Setting
mlflow tracking uri...\n2024-01-12 08:16:52 +0000 4041 promptflow-runtime
INFO Validating ''AzureML Data Scientist'' user authentication...\n2024-01-12
08:16:52 +0000 4041 promptflow-runtime INFO Successfully validated
''AzureML Data Scientist'' user authentication.\n2024-01-12 08:16:52 +0000 4041
promptflow-runtime INFO Using AzureMLRunStorageV2\n2024-01-12 08:16:52
+0000 4041 promptflow-runtime INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
08:16:52 +0000 4041 promptflow-runtime INFO Initialized blob service
client for AzureMLRunTracker.\n2024-01-12 08:16:52 +0000 4041 promptflow-runtime
INFO Setting mlflow tracking uri to ''azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus''\n2024-01-12
08:16:52 +0000 4041 promptflow-runtime INFO Resolve data from url finished
in 0.45952979754656553 seconds\n2024-01-12 08:16:53 +0000 4041 promptflow-runtime
INFO Resolve data from url finished in 0.7092651706188917 seconds\n2024-01-12
08:16:53 +0000 4041 promptflow-runtime INFO Starting the aml run ''eval_run_name''...\n2024-01-12
08:16:54 +0000 4041 execution.bulk INFO Using fork, process count:
3\n2024-01-12 08:16:54 +0000 4083 execution.bulk INFO Process 4083
started.\n2024-01-12 08:16:54 +0000 4093 execution.bulk INFO Process
4093 started.\n2024-01-12 08:16:54 +0000 4041 execution.bulk INFO Process
name: ForkProcess-38:2, Process id: 4083, Line number: 0 start execution.\n2024-01-12
08:16:54 +0000 4041 execution.bulk INFO Process name: ForkProcess-38:4,
Process id: 4093, Line number: 1 start execution.\n2024-01-12 08:16:54 +0000 4041
execution.bulk INFO Process name: ForkProcess-38:2, Process id: 4083,
Line number: 0 completed.\n2024-01-12 08:16:54 +0000 4088 execution.bulk INFO Process
4088 started.\n2024-01-12 08:16:54 +0000 4041 execution.bulk INFO Finished
1 / 3 lines.\n2024-01-12 08:16:54 +0000 4041 execution.bulk INFO Process
name: ForkProcess-38:4, Process id: 4093, Line number: 1 completed.\n2024-01-12
08:16:54 +0000 4041 execution.bulk INFO Process name: ForkProcess-38:3,
Process id: 4088, Line number: 2 start execution.\n2024-01-12 08:16:54 +0000 4041
execution.bulk INFO Average execution time for completed lines: 0.23
seconds. Estimated time for incomplete lines: 0.46 seconds.\n2024-01-12 08:16:54
+0000 4041 execution.bulk INFO Finished 2 / 3 lines.\n2024-01-12
08:16:54 +0000 4041 execution.bulk INFO Average execution time
for completed lines: 0.13 seconds. Estimated time for incomplete lines: 0.13
seconds.\n2024-01-12 08:16:54 +0000 4041 execution.bulk INFO Process
name: ForkProcess-38:3, Process id: 4088, Line number: 2 completed.\n2024-01-12
08:16:54 +0000 4041 execution.bulk INFO Finished 3 / 3 lines.\n2024-01-12
08:16:54 +0000 4041 execution.bulk INFO Average execution time
for completed lines: 0.13 seconds. Estimated time for incomplete lines: 0.0
seconds.\n2024-01-12 08:16:55 +0000 4041 execution.bulk INFO Executing
aggregation nodes...\n2024-01-12 08:16:55 +0000 4041 execution.bulk INFO Finish
executing aggregation nodes.\n2024-01-12 08:16:57 +0000 4041 execution.bulk INFO Upload
status summary metrics for run eval_run_name finished in 1.7071036528795958
seconds\n2024-01-12 08:16:57 +0000 4041 execution.bulk INFO Upload
metrics for run eval_run_name finished in 0.39980557933449745 seconds\n2024-01-12
08:16:57 +0000 4041 promptflow-runtime INFO Successfully write run
properties {\"azureml.promptflow.total_tokens\": 0, \"_azureml.evaluate_artifacts\":
\"[{\\\"path\\\": \\\"instance_results.jsonl\\\", \\\"type\\\": \\\"table\\\"}]\"}
with run id ''eval_run_name''\n2024-01-12 08:16:57 +0000 4041 execution.bulk INFO Upload
RH properties for run eval_run_name finished in 0.11383599042892456 seconds\n2024-01-12
08:16:58 +0000 4041 promptflow-runtime INFO Creating unregistered output
Asset for Run eval_run_name...\n2024-01-12 08:16:58 +0000 4041 promptflow-runtime
INFO Created debug_info Asset: azureml://locations/eastus/workspaces/00000/data/azureml_eval_run_name_output_data_debug_info/versions/1\n2024-01-12
08:16:58 +0000 4041 promptflow-runtime INFO Creating unregistered output
Asset for Run eval_run_name...\n2024-01-12 08:16:58 +0000 4041 promptflow-runtime
INFO Created flow_outputs output Asset: azureml://locations/eastus/workspaces/00000/data/azureml_eval_run_name_output_data_flow_outputs/versions/1\n2024-01-12
08:16:58 +0000 4041 promptflow-runtime INFO Creating Artifact for Run
eval_run_name...\n2024-01-12 08:16:58 +0000 4041 promptflow-runtime INFO Created
instance_results.jsonl Artifact.\n2024-01-12 08:16:58 +0000 4041 promptflow-runtime
INFO Patching eval_run_name...\n2024-01-12 08:16:58 +0000 4041 promptflow-runtime
INFO Ending the aml run ''eval_run_name'' with status ''Completed''...\n2024-01-12
08:17:00 +0000 134 promptflow-runtime INFO Process 4041 finished\n2024-01-12
08:17:00 +0000 134 promptflow-runtime INFO [134] Child process finished!\n2024-01-12
08:17:00 +0000 134 promptflow-runtime INFO [eval_run_name] End processing
bulk run\n2024-01-12 08:17:00 +0000 134 promptflow-runtime INFO Cleanup
working dir /mnt/host/service/app/38343/requests/eval_run_name for bulk run\n"'
headers:
connection:
- keep-alive
content-length:
- '10623'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.650'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_azure_cli_perf_TestAzureCliPerf_test_pfazure_run_create.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.9.17 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-09-22T05:26:30.7527337+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2024-01-10T09:29:14.5412854+00:00", "lastModifiedBy": "Philip Gao", "lastModifiedByType":
"User"}}'
headers:
cache-control:
- no-cache
content-length:
- '1200'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.078'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.9.17 (Windows-10-10.0.22621-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.160'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.13.0 Python/3.9.17 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Mon, 15 Jan 2024 06:06:51 GMT
x-ms-version:
- '2021-08-06'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/print_input_flow.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '56'
content-md5:
- I/k2vLbQ+WkABQncQUd5Rg==
content-type:
- application/octet-stream
last-modified:
- Tue, 26 Dec 2023 03:34:26 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Tue, 26 Dec 2023 03:34:26 GMT
x-ms-meta-name:
- 489008dc-84bd-4bee-82db-0bb80f7ad272
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- b7185e71-1e33-43b7-b8be-43bdd40e6731
x-ms-version:
- '2021-08-06'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.13.0 Python/3.9.17 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Mon, 15 Jan 2024 06:06:52 GMT
x-ms-version:
- '2021-08-06'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/print_input_flow.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2021-08-06'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.9.17 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-09-22T05:26:30.7527337+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2024-01-10T09:29:14.5412854+00:00", "lastModifiedBy": "Philip Gao", "lastModifiedByType":
"User"}}'
headers:
cache-control:
- no-cache
content-length:
- '1200'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.085'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.9.17 (Windows-10-10.0.22621-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.066'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.13.0 Python/3.9.17 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Mon, 15 Jan 2024 06:06:53 GMT
x-ms-version:
- '2021-08-06'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/print_input_flow/flow.dag.yaml
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '238'
content-md5:
- g6eojZlNZcUGTvvyK1WJEg==
content-type:
- application/octet-stream
last-modified:
- Tue, 26 Dec 2023 03:34:26 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Tue, 26 Dec 2023 03:34:25 GMT
x-ms-meta-name:
- ab2797da-2f87-47a2-9c7a-1cdd447fa102
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2021-08-06'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.13.0 Python/3.9.17 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Mon, 15 Jan 2024 06:06:55 GMT
x-ms-version:
- '2021-08-06'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/print_input_flow/flow.dag.yaml
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2021-08-06'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '[{"iKey": "8b52b368-4c91-4226-b7f7-be52822f0509", "tags": {"ai.cloud.role":
"pfazure", "ai.device.locale": "zh_CN", "ai.device.osVersion": "10.0.22621",
"ai.device.type": "Other", "ai.internal.sdkVersion": "py3.9.17:oc0.11.2:ext1.1.9",
"ai.operation.id": "00000000000000000000000000000000", "ai.operation.parentId":
"|00000000000000000000000000000000.0000000000000000."}, "time": "2024-01-15T06:06:48.727100Z",
"name": "Microsoft.ApplicationInsights.Event", "data": {"baseData": {"name":
"pfazure.run.create.start", "properties": {"request_id": "ab23fd05-6e99-4553-bf58-eea847cd7cb2",
"first_call": true, "activity_name": "pfazure.run.create", "activity_type":
"PublicApi", "user_agent": "promptflow-cli/0.0.1 perf_monitor/1.0", "subscription_id":
"96aede12-2f73-41cb-b983-6d11a904839b", "resource_group_name": "promptflow",
"workspace_name": "promptflow-eastus2euap", "custom_message": "github run: https://github.com/microsoft/promptflow/actions/runs/None",
"level": "INFO", "from_ci": false, "python_version": "3.9.17", "installation_id":
"920feacd-3514-4287-a262-783d110775e1"}, "measurements": {}, "ver": 2}, "baseType":
"EventData"}}]'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '1140'
Content-Type:
- application/json; charset=utf-8
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://dc.services.visualstudio.com/v2.1/track
response:
body:
string: '{"itemsReceived": 1, "itemsAccepted": 0, "errors": [{"index": 0, "statusCode":
307, "message": "Ingestion is allowed only from stamp specific endpoint -
Location: https://eastus-8.in.applicationinsights.azure.com/v2.1/track"}]}'
headers:
cache-control:
- max-age=604800
content-length:
- '217'
content-type:
- application/json; charset=utf-8
location:
- https://eastus-8.in.applicationinsights.azure.com/v2.1/track
server:
- Microsoft-HTTPAPI/2.0
strict-transport-security:
- max-age=31536000
x-content-type-options:
- nosniff
status:
code: 307
message: Temporary Redirect
- request:
body: '[{"iKey": "8b52b368-4c91-4226-b7f7-be52822f0509", "tags": {"ai.cloud.role":
"pfazure", "ai.device.locale": "zh_CN", "ai.device.osVersion": "10.0.22621",
"ai.device.type": "Other", "ai.internal.sdkVersion": "py3.9.17:oc0.11.2:ext1.1.9",
"ai.operation.id": "00000000000000000000000000000000", "ai.operation.parentId":
"|00000000000000000000000000000000.0000000000000000."}, "time": "2024-01-15T06:06:48.727100Z",
"name": "Microsoft.ApplicationInsights.Event", "data": {"baseData": {"name":
"pfazure.run.create.start", "properties": {"request_id": "ab23fd05-6e99-4553-bf58-eea847cd7cb2",
"first_call": true, "activity_name": "pfazure.run.create", "activity_type":
"PublicApi", "user_agent": "promptflow-cli/0.0.1 perf_monitor/1.0", "subscription_id":
"96aede12-2f73-41cb-b983-6d11a904839b", "resource_group_name": "promptflow",
"workspace_name": "promptflow-eastus2euap", "custom_message": "github run: https://github.com/microsoft/promptflow/actions/runs/None",
"level": "INFO", "from_ci": false, "python_version": "3.9.17", "installation_id":
"920feacd-3514-4287-a262-783d110775e1"}, "measurements": {}, "ver": 2}, "baseType":
"EventData"}}]'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '1140'
Content-Type:
- application/json; charset=utf-8
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus-8.in.applicationinsights.azure.com/v2.1/track
response:
body:
string: '{"itemsReceived": 1, "itemsAccepted": 1, "errors": []}'
headers:
content-length:
- '49'
content-type:
- application/json; charset=utf-8
server:
- Microsoft-HTTPAPI/2.0
strict-transport-security:
- max-age=31536000
x-content-type-options:
- nosniff
status:
code: 200
message: OK
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/print_input_flow/flow.dag.yaml",
"runId": "name", "runDisplayName": "name", "runExperimentName": "", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/print_input_flow.jsonl"},
"inputsMapping": {}, "connections": {}, "environmentVariables": {}, "runtimeName":
"fake-runtime-name", "sessionId": "000000000000000000000000000000000000000000000000",
"sessionSetupMode": "SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '787'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.9.17 (Windows-10-10.0.22621-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '8.634'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.9.17 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_input", "type": "python",
"source": {"type": "code", "path": "print_input.py"}, "inputs": {"text": "${inputs.text}"},
"tool": "print_input.py", "reduce": false}], "tools": [{"name": "Azure OpenAI
GPT-4 Turbo with Vision", "type": "custom_llm", "inputs": {"connection": {"type":
["AzureOpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "frequency_penalty":
{"type": ["double"], "default": 0, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "max_tokens": {"type": ["int"], "default":
512, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Azure OpenAI GPT-4 Turbo
with Vision to leverage AOAI vision ability.", "module": "promptflow.tools.aoai_gpt4v",
"class_name": "AzureOpenAI", "function": "chat", "icon": {"dark": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAA2ElEQVR4nJXSzW3CQBAF4DUSTjk+Al1AD0ikESslpBIEheRALhEpgAYSWV8OGUublf/yLuP3PPNmdndS+gdwXZrYDmh7fGE/W+wXbaYd8IYm4rxJPnZ0boI3wZcdJxs/n+AwV7DFK7aFyfQdYIMLPvES8YJNf5yp4jMeeEYdWh38gXOR35YGHe5xabvQdsHv6PLi8qV6gycc8YH3iMfQu6Lh4ASr+F5Hh3XwVWnQYzUkVlX1nccplAb1SN6Y/sfgmlK64VS8wimldIv/0yj2QLkHizG0iWP4AVAfQ34DVQONAAAAAElFTkSuQmCC",
"light": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAx0lEQVR4nJWSwQ2CQBBFX0jAcjgqXUgPJNiIsQQrIVCIFy8GC6ABDcGDX7Mus9n1Xz7zZ+fPsLPwH4bUg0dD2wMPcbR48Uxq4AKU4iSTDwZ1LhWXipN/B3V0J6hjBTvgLHZNonewBXrgDpzEvXSIjN0BE3AACmmF4kl5F6tNzcCoLpW0SvGovFvsb4oZ2AANcAOu4ka6axCcINN3rg654sww+CYsPD0OwjcozFNh/Qcd78tqVbCIW+n+Fky472Bh/Q6SYb1EEy8tDzd+9IsVPAAAAABJRU5ErkJggg=="},
"is_builtin": true, "package": "promptflow-tools", "package_version": "1.0.3",
"default_prompt": "# system:\nAs an AI assistant, your task involves interpreting
images and responding to questions about the image.\nRemember to provide accurate
answers based on the information present in the image.\n\n# user:\nCan you
tell me what the image depicts?\n\n", "enable_kwargs":
false, "tool_state": "preview"}, {"name": "Content Safety (Text Analyze)",
"type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"1.0.3", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": true, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "1.0.3", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Model LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "default": "", "dynamic_list": {"func_path": "promptflow.tools.open_model_llm.list_deployment_names",
"func_kwargs": [{"name": "endpoint", "optional": true, "reference": "${inputs.endpoint}",
"type": ["string"]}]}, "allow_manual_entry": true, "is_multi_select": false,
"input_type": "default"}, "endpoint_name": {"type": ["string"], "dynamic_list":
{"func_path": "promptflow.tools.open_model_llm.list_endpoint_names"}, "allow_manual_entry":
true, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an open model from the Azure Model catalog, deployed to
an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_model_llm", "class_name": "OpenModelLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "1.0.3",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": 512, "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "icon": {"dark": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAA2ElEQVR4nJXSzW3CQBAF4DUSTjk+Al1AD0ikESslpBIEheRALhEpgAYSWV8OGUublf/yLuP3PPNmdndS+gdwXZrYDmh7fGE/W+wXbaYd8IYm4rxJPnZ0boI3wZcdJxs/n+AwV7DFK7aFyfQdYIMLPvES8YJNf5yp4jMeeEYdWh38gXOR35YGHe5xabvQdsHv6PLi8qV6gycc8YH3iMfQu6Lh4ASr+F5Hh3XwVWnQYzUkVlX1nccplAb1SN6Y/sfgmlK64VS8wimldIv/0yj2QLkHizG0iWP4AVAfQ34DVQONAAAAAElFTkSuQmCC",
"light": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAx0lEQVR4nJWSwQ2CQBBFX0jAcjgqXUgPJNiIsQQrIVCIFy8GC6ABDcGDX7Mus9n1Xz7zZ+fPsLPwH4bUg0dD2wMPcbR48Uxq4AKU4iSTDwZ1LhWXipN/B3V0J6hjBTvgLHZNonewBXrgDpzEvXSIjN0BE3AACmmF4kl5F6tNzcCoLpW0SvGovFvsb4oZ2AANcAOu4ka6axCcINN3rg654sww+CYsPD0OwjcozFNh/Qcd78tqVbCIW+n+Fky472Bh/Q6SYb1EEy8tDzd+9IsVPAAAAABJRU5ErkJggg=="},
"is_builtin": true, "package": "promptflow-tools", "package_version": "1.0.3",
"default_prompt": "# system:\nAs an AI assistant, your task involves interpreting
images and responding to questions about the image.\nRemember to provide accurate
answers based on the information present in the image.\n\n# user:\nCan you
tell me what the image depicts?\n\n", "enable_kwargs":
false, "tool_state": "preview"}, {"name": "Serp API", "type": "python", "inputs":
{"connection": {"type": ["SerpConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "engine": {"type": ["string"], "default":
"google", "enum": ["google", "bing"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "location": {"type": ["string"], "default":
"", "allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"num": {"type": ["int"], "default": "10", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "safe": {"type":
["string"], "default": "off", "enum": ["active", "off"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "description":
"Use Serp API to obtain search results from a specific search engine.", "module":
"promptflow.tools.serpapi", "class_name": "SerpAPI", "function": "search",
"is_builtin": true, "package": "promptflow-tools", "package_version": "1.0.3",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Index Lookup",
"type": "python", "inputs": {"acs_content_field": {"type": ["string"], "enabled_by":
"index_type", "enabled_by_value": ["Azure AI Search"], "dynamic_list": {"func_path":
"promptflow_vectordb.tool.common_index_lookup_utils.list_acs_index_fields",
"func_kwargs": [{"name": "acs_connection", "optional": false, "reference":
"${inputs.acs_index_connection}", "type": ["CognitiveSearchConnection"]},
{"name": "acs_index_name", "optional": false, "reference": "${inputs.acs_index_name}",
"type": ["string"]}, {"default": "Edm.String", "name": "field_data_type",
"optional": false, "type": ["string"]}]}, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "uionly_hidden"}, "acs_embedding_field": {"type": ["string"],
"enabled_by": "index_type", "enabled_by_value": ["Azure AI Search"], "dynamic_list":
{"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_acs_index_fields",
"func_kwargs": [{"name": "acs_connection", "optional": false, "reference":
"${inputs.acs_index_connection}", "type": ["CognitiveSearchConnection"]},
{"name": "acs_index_name", "optional": false, "reference": "${inputs.acs_index_name}",
"type": ["string"]}, {"default": "Collection(Edm.Single)", "name": "field_data_type",
"optional": false, "type": ["string"]}]}, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "uionly_hidden"}, "acs_index_connection": {"type": ["CognitiveSearchConnection"],
"enabled_by": "index_type", "enabled_by_value": ["Azure AI Search"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "uionly_hidden"}, "acs_index_name":
{"type": ["string"], "enabled_by": "index_type", "enabled_by_value": ["Azure
AI Search"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_acs_indices",
"func_kwargs": [{"name": "acs_connection", "optional": false, "reference":
"${inputs.acs_index_connection}", "type": ["CognitiveSearchConnection"]}]},
"allow_manual_entry": false, "is_multi_select": false, "input_type": "uionly_hidden"},
"acs_metadata_field": {"type": ["string"], "enabled_by": "index_type", "enabled_by_value":
["Azure AI Search"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_acs_index_fields",
"func_kwargs": [{"name": "acs_connection", "optional": false, "reference":
"${inputs.acs_index_connection}", "type": ["CognitiveSearchConnection"]},
{"name": "acs_index_name", "optional": false, "reference": "${inputs.acs_index_name}",
"type": ["string"]}, {"default": "Edm.String", "name": "field_data_type",
"optional": false, "type": ["string"]}]}, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "uionly_hidden"}, "aoai_embedding_connection": {"type":
["AzureOpenAIConnection"], "enabled_by": "embedding_type", "enabled_by_value":
["Azure OpenAI"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"uionly_hidden"}, "embedding_deployment": {"type": ["string"], "enabled_by":
"embedding_type", "enabled_by_value": ["Azure OpenAI"], "dynamic_list": {"func_path":
"promptflow_vectordb.tool.common_index_lookup_utils.list_aoai_embedding_deployments",
"func_kwargs": [{"name": "aoai_connection", "optional": false, "reference":
"${inputs.aoai_embedding_connection}", "type": ["AzurOpenAIConnection"]}]},
"allow_manual_entry": false, "is_multi_select": false, "input_type": "uionly_hidden"},
"embedding_model": {"type": ["string"], "enabled_by": "embedding_type", "enabled_by_value":
["OpenAI", "Hugging Face"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_embedding_models",
"func_kwargs": [{"name": "embedding_type", "optional": false, "reference":
"${inputs.embedding_type}", "type": ["string"]}]}, "allow_manual_entry": false,
"is_multi_select": false, "input_type": "uionly_hidden"}, "embedding_type":
{"type": ["string"], "enabled_by": "index_type", "enabled_by_value": ["Azure
AI Search", "FAISS", "Pinecone"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_available_embedding_types",
"func_kwargs": [{"name": "index_type", "optional": false, "reference": "${inputs.index_type}",
"type": ["string"]}]}, "allow_manual_entry": false, "is_multi_select": false,
"input_type": "uionly_hidden"}, "faiss_index_path": {"type": ["string"], "enabled_by":
"index_type", "enabled_by_value": ["FAISS"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "uionly_hidden"}, "index_type": {"type":
["string"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_available_index_types"},
"allow_manual_entry": false, "is_multi_select": false, "input_type": "uionly_hidden"},
"mlindex_asset_id": {"type": ["string"], "enabled_by": "index_type", "enabled_by_value":
["Registered Index"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_registered_mlindices"},
"allow_manual_entry": false, "is_multi_select": false, "input_type": "uionly_hidden"},
"mlindex_content": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "generated_by": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.forward_mapping",
"func_kwargs": [{"name": "index_type", "reference": "${inputs.index_type}",
"type": ["string"]}, {"name": "mlindex_asset_id", "optional": true, "reference":
"${inputs.mlindex_asset_id}", "type": ["string"]}, {"name": "mlindex_path",
"optional": true, "reference": "${inputs.mlindex_path}", "type": ["string"]},
{"name": "acs_index_connection", "optional": true, "reference": "${inputs.acs_index_connection}",
"type": ["CognitiveSearchConnection"]}, {"name": "acs_index_name", "optional":
true, "reference": "${inputs.acs_index_name}", "type": ["string"]}, {"name":
"acs_content_field", "optional": true, "reference": "${inputs.acs_content_field}",
"type": ["string"]}, {"name": "acs_embedding_field", "optional": true, "reference":
"${inputs.acs_embedding_field}", "type": ["string"]}, {"name": "acs_metadata_field",
"optional": true, "reference": "${inputs.acs_metadata_field}", "type": ["string"]},
{"name": "semantic_configuration", "optional": true, "reference": "${inputs.semantic_configuration}",
"type": ["string"]}, {"name": "faiss_index_path", "optional": true, "reference":
"${inputs.faiss_index_path}", "type": ["string"]}, {"name": "pinecone_index_connection",
"optional": true, "reference": "${inputs.pinecone_index_connection}", "type":
["string"]}, {"name": "pinecone_index_name", "optional": true, "reference":
"${inputs.pinecone_index_name}", "type": ["string"]}, {"name": "pinecone_content_field",
"optional": true, "reference": "${inputs.pinecone_content_field}", "type":
["string"]}, {"name": "pinecone_metadata_field", "optional": true, "reference":
"${inputs.pinecone_metadata_field}", "type": ["string"]}, {"name": "embedding_type",
"optional": true, "reference": "${inputs.embedding_type}", "type": ["string"]},
{"name": "aoai_embedding_connection", "optional": true, "reference": "${inputs.aoai_embedding_connection}",
"type": ["AzureOpenAIConnection"]}, {"name": "oai_embedding_connection", "optional":
true, "reference": "${inputs.oai_embedding_connection}", "type": ["string"]},
{"name": "embedding_model", "optional": true, "reference": "${inputs.embedding_model}",
"type": ["string"]}, {"name": "embedding_deployment", "optional": true, "reference":
"${inputs.embedding_deployment}", "type": ["string"]}], "reverse_func_path":
"promptflow_vectordb.tool.common_index_lookup_utils.reverse_mapping"}, "input_type":
"default"}, "mlindex_path": {"type": ["string"], "enabled_by": "index_type",
"enabled_by_value": ["MLIndex file from path"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "uionly_hidden"}, "oai_embedding_connection":
{"type": ["OpenAIConnection"], "enabled_by": "embedding_type", "enabled_by_value":
["OpenAI"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"uionly_hidden"}, "pinecone_content_field": {"type": ["string"], "enabled_by":
"index_type", "enabled_by_value": ["Pinecone"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "uionly_hidden"}, "pinecone_index_connection":
{"type": ["PineconeConnection"], "enabled_by": "index_type", "enabled_by_value":
["Pinecone"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_pinecone_connections"},
"allow_manual_entry": false, "is_multi_select": false, "input_type": "uionly_hidden"},
"pinecone_index_name": {"type": ["string"], "enabled_by": "index_type", "enabled_by_value":
["Pinecone"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_pinecone_indices",
"func_kwargs": [{"name": "pinecone_connection_name", "optional": false, "reference":
"${inputs.pinecone_index_connection}", "type": ["string"]}]}, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "uionly_hidden"}, "pinecone_metadata_field":
{"type": ["string"], "enabled_by": "index_type", "enabled_by_value": ["Pinecone"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "uionly_hidden"},
"queries": {"type": ["object"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query_type": {"type": ["string"], "dynamic_list":
{"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_available_query_types",
"func_kwargs": [{"name": "mlindex_content", "optional": false, "reference":
"${inputs.mlindex_content}", "type": ["string"]}]}, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "semantic_configuration":
{"type": ["string"], "enabled_by": "index_type", "enabled_by_value": ["Azure
AI Search"], "dynamic_list": {"func_path": "promptflow_vectordb.tool.common_index_lookup_utils.list_acs_index_semantic_configurations",
"func_kwargs": [{"name": "acs_connection", "optional": false, "reference":
"${inputs.acs_index_connection}", "type": ["CognitiveSearchConnection"]},
{"name": "acs_index_name", "optional": false, "reference": "${inputs.acs_index_name}",
"type": ["string"]}]}, "allow_manual_entry": false, "is_multi_select": false,
"input_type": "uionly_hidden"}, "top_k": {"type": ["int"], "default": 3, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "description":
"Search an AzureML Vector Index for relevant results using one or more text
queries.", "module": "promptflow_vectordb.tool.common_index_lookup", "function":
"search", "is_builtin": true, "package": "promptflow-vectordb", "package_version":
"0.0.1", "enable_kwargs": false, "tool_state": "preview"}, {"name": "Faiss
Index Lookup", "type": "python", "inputs": {"path": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "vector": {"type": ["list"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}}, "description":
"Search vector based query from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_input.py", "type": "python",
"inputs": {"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_input.py", "function":
"print_inputs", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"text": {"type": "string", "is_chat_input": false}},
"outputs": {"output_text": {"type": "string", "reference": "${print_input.output}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus2euap/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/80d5ca5a93c8c6ea7c2fcdf1cd4b9d07/print_input_flow.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "automatic",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "541bf448-5153-4b0a-a34e-c4e39763e775",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '26138'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.292'
status:
code: 200
message: OK
- request:
body: '{"runId": "name", "selectRunMetadata": true, "selectRunDefinition": true,
"selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705298823, "rootRunId": "name", "createdUtc":
"2024-01-15T06:07:03.006454+00:00", "createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": "10032001A114F500", "userIdp": null, "userAltSecId": null, "userIss":
"https://sts.windows.net/00000000-0000-0000-0000-000000000000/", "userTenantId":
"00000000-0000-0000-0000-000000000000", "userName": "Chenyang Zhang", "upn":
null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null, "tokenExpiryTimeUtc":
null, "error": null, "warnings": null, "revision": 3, "statusRevision": 1,
"runUuid": "63400a6e-7d8b-4302-a031-c08f99d265df", "parentRunUuid": null,
"rootRunUuid": "63400a6e-7d8b-4302-a031-c08f99d265df", "lastStartTimeUtc":
null, "currentComputeTime": "00:00:00", "computeDuration": null, "effectiveStartTimeUtc":
null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": "10032001A114F500", "userIdp": null, "userAltSecId": null, "userIss":
"https://sts.windows.net/00000000-0000-0000-0000-000000000000/", "userTenantId":
"00000000-0000-0000-0000-000000000000", "userName": "Chenyang Zhang", "upn":
null}, "lastModifiedUtc": "2024-01-15T06:07:08.4229129+00:00", "duration":
null, "cancelationReason": null, "currentAttemptId": 1, "runId": "name", "parentRunId":
null, "experimentId": "4d67b7d7-dc1c-4699-a53e-318ca24f1f72", "status": "Preparing",
"startTimeUtc": null, "endTimeUtc": null, "scheduleId": null, "displayName":
"name", "name": null, "dataContainerId": "dcid.name", "description": null,
"hidden": false, "runType": "azureml.promptflow.FlowRun", "runTypeV2": {"orchestrator":
null, "traits": [], "attribution": "PromptFlow", "computeType": null}, "properties":
{"azureml.promptflow.runtime_name": "automatic", "azureml.promptflow.runtime_version":
"20240111.v2", "azureml.promptflow.definition_file_name": "flow.dag.yaml",
"azureml.promptflow.session_id": "96c35660d759b526cb14cf69bbb56fcaa90c05a778b147b4",
"azureml.promptflow.flow_lineage_id": "fcb01d4faf8f2137f9d142cc1f3f22ecdf3d485e1435c4c971ff0ee09077f1b5",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/52675845d616ad8b41db77e9ba9e9d4a/print_input_flow/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/80d5ca5a93c8c6ea7c2fcdf1cd4b9d07/print_input_flow.jsonl",
"_azureml.evaluation_run": "promptflow.BatchRun", "azureml.promptflow.snapshot_id":
"541bf448-5153-4b0a-a34e-c4e39763e775"}, "parameters": {}, "actionUris": {},
"scriptName": null, "target": null, "uniqueChildRunComputeTargets": [], "tags":
{}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": null}, "runDefinition":
null, "jobSpecification": null, "systemSettings": null}'
headers:
connection:
- keep-alive
content-length:
- '3709'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.018'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_stream_invalid_run_logs.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.027'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.088'
status:
code: 200
message: OK
- request:
body: '{"runId": "non_exist_run", "selectRunMetadata": true, "selectRunDefinition":
true, "selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"error": {"code": "UserError", "severity": null, "message": "Run runId=non_exist_run
was not found", "messageFormat": "Run {runId} was not found", "messageParameters":
{"runId": "runId=non_exist_run"}, "referenceCode": null, "detailsUri": null,
"target": null, "details": [], "innerError": {"code": "NotFoundError", "innerError":
null}, "debugInfo": null, "additionalInfo": null}, "correlation": {"operation":
"8ae7e1bb4942865bf920115c263c0e78", "request": "7f0871b4a154f85d"}, "environment":
"eastus", "location": "eastus", "time": "2024-01-12T07:58:30.4482197+00:00",
"componentName": "run-history", "statusCode": 404}'
headers:
connection:
- keep-alive
content-length:
- '777'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.046'
status:
code: 404
message: Run runId=f1356823-7551-4ab3-93ba-6d60270b9dc6 was not found
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_telemetry_TestTelemetry_test_custom_event.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/api-version=2023-08-01-preview
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.038'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?api-version=2023-04-01-preview&count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '1.132'
status:
code: 200
message: OK
- request:
body: '{"runId": "not_exist", "selectRunMetadata": true, "selectRunDefinition":
true, "selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '110'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"error": {"code": "UserError", "severity": null, "message": "Run runId=not_exist
was not found", "messageFormat": "Run {runId} was not found", "messageParameters":
{"runId": "runId=not_exist"}, "referenceCode": null, "detailsUri": null, "target":
null, "details": [], "innerError": {"code": "NotFoundError", "innerError":
null}, "debugInfo": null, "additionalInfo": null}, "correlation": {"operation":
"ea26eac5dbeb3bdc99dc95beeb40ac6f", "request": "010bd843f7775527"}, "environment":
"eastus", "location": "eastus", "time": "2023-11-23T04:54:12.8199101+00:00",
"componentName": "run-history", "statusCode": 404}'
headers:
connection:
- keep-alive
content-length:
- '723'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.112'
status:
code: 404
message: Run runId=not_exist was not found
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_telemetry_TestTelemetry_test_inner_function_call.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.025'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.070'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.089'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '2.544'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:17:41 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '49'
content-md5:
- quXiEreYvPinSj0HsaNa/g==
content-type:
- application/octet-stream
last-modified:
- Wed, 08 Nov 2023 04:26:09 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Wed, 08 Nov 2023 04:26:09 GMT
x-ms-meta-name:
- c4092674-5e53-4c17-b78d-75353ae0edb6
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 579021dc-8ac8-4c73-8110-4642bd00c69b
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:17:42 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.083'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.097'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:17:45 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '245'
content-md5:
- F+JA0a3CxcLYZ0ANRdlZbA==
content-type:
- application/octet-stream
last-modified:
- Wed, 29 Nov 2023 02:51:35 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Thu, 17 Aug 2023 10:30:09 GMT
x-ms-meta-name:
- 56efdd28-6297-4baa-aad3-be46f4b768a2
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:17:46 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/print_env_var/flow.dag.yaml",
"runId": "name", "runDisplayName": "name", "runExperimentName": "", "batchDataInput":
{"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/env_var_names.jsonl"},
"inputsMapping": {}, "connections": {}, "environmentVariables": {"API_BASE":
"${azure_open_ai_connection.api_base}"}, "runtimeName": "fake-runtime-name",
"sessionId": "000000000000000000000000000000000000000000000000", "sessionSetupMode":
"SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '834'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '6.825'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "print_env", "type": "python", "source":
{"type": "code", "path": "print_env.py"}, "inputs": {"key": "${inputs.key}"},
"tool": "print_env.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "print_env.py", "type": "python",
"inputs": {"key": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "print_env.py", "function": "get_env_var",
"is_builtin": false, "enable_kwargs": false, "tool_state": "stable"}], "inputs":
{"key": {"type": "string", "is_chat_input": false}}, "outputs": {"output":
{"type": "string", "reference": "${print_env.output.value}", "evaluation_only":
false, "is_chat_output": false}}}, "flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/name/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/c32a61842e439cecc022ebcff5dc0da4/env_var_names.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {}, "outputDatastoreName": "workspaceblobstore", "childRunBasePath":
"promptflow/PromptFlowArtifacts/name/flow_artifacts", "flowDagFileRelativePath":
"flow.dag.yaml", "flowSnapshotId": "30e9e690-d4ea-47fa-b21e-f2d2e3477afb",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12855'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.389'
status:
code: 200
message: OK
- request:
body: '{"runId": "name", "selectRunMetadata": true, "selectRunDefinition": true,
"selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705047472, "rootRunId": "name", "createdUtc":
"2024-01-12T08:17:52.7672482+00:00", "createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": null, "warnings": null, "revision": 3,
"statusRevision": 1, "runUuid": "8d919d93-e46a-485d-a698-02f4c9fdc799", "parentRunUuid":
null, "rootRunUuid": "8d919d93-e46a-485d-a698-02f4c9fdc799", "lastStartTimeUtc":
null, "currentComputeTime": "00:00:00", "computeDuration": null, "effectiveStartTimeUtc":
null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:17:56.9173918+00:00", "duration":
null, "cancelationReason": null, "currentAttemptId": 1, "runId": "name", "parentRunId":
null, "experimentId": "6a87c3ae-5a75-4c5d-9eb9-5203b0062282", "status": "Preparing",
"startTimeUtc": null, "endTimeUtc": null, "scheduleId": null, "displayName":
"name", "name": null, "dataContainerId": "dcid.name", "description": null,
"hidden": false, "runType": "azureml.promptflow.FlowRun", "runTypeV2": {"orchestrator":
null, "traits": [], "attribution": "PromptFlow", "computeType": "AmlcDsi"},
"properties": {"azureml.promptflow.runtime_name": "test-runtime-ci", "azureml.promptflow.runtime_version":
"20231204.v4", "azureml.promptflow.definition_file_name": "flow.dag.yaml",
"azureml.promptflow.session_id": "62adccc385dd5d078797bdd0d2e1c55e120f3d5216885b81",
"azureml.promptflow.flow_lineage_id": "f1efdb93dcf9b3c17e246e7bcf0e2c7398d7bc289f8dd2c3d8f808eacc63c31f",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/3360ae705933fb90bcd290241ca0ece9/print_env_var/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/c32a61842e439cecc022ebcff5dc0da4/env_var_names.jsonl",
"_azureml.evaluation_run": "promptflow.BatchRun", "azureml.promptflow.snapshot_id":
"30e9e690-d4ea-47fa-b21e-f2d2e3477afb"}, "parameters": {}, "actionUris": {},
"scriptName": null, "target": null, "uniqueChildRunComputeTargets": [], "tags":
{}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": null}, "runDefinition":
null, "jobSpecification": null, "systemSettings": null}'
headers:
connection:
- keep-alive
content-length:
- '3849'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.042'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_automatic_runtime_with_resources.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.026'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.053'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.076'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.150'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:46:41 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/webClassification1.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '127'
content-md5:
- i/8q1x5YKzHv3Fd/R8lYUQ==
content-type:
- application/octet-stream
last-modified:
- Fri, 28 Jul 2023 12:34:52 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Fri, 28 Jul 2023 12:34:52 GMT
x-ms-meta-name:
- 13fa99dd-c98e-4f2a-a704-4295d4ed6f68
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 0367c5c6-9f53-4a75-8623-7e53699f0d0b
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:46:42 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/webClassification1.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.075'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.082'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:46:45 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/web_classification/classify_with_llm.jinja2
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '853'
content-md5:
- ylTeNqjvuOvtzEZJ/X5n3A==
content-type:
- application/octet-stream
last-modified:
- Fri, 12 Jan 2024 08:13:57 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Fri, 12 Jan 2024 08:13:56 GMT
x-ms-meta-name:
- 950201e8-c52c-4b15-ada1-5e58de9b2f4d
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:46:46 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/web_classification/classify_with_llm.jinja2
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionDataStoreName": "workspaceblobstore", "flowDefinitionBlobPath":
"LocalUpload/000000000000000000000000000000000000/web_classification/flow.dag.yaml",
"runId": "run_id", "runDisplayName": "run_id", "runExperimentName": "", "nodeVariant":
"${summarize_text_content.variant_0}", "batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/webClassification1.jsonl"},
"inputsMapping": {"url": "${data.url}"}, "connections": {}, "environmentVariables":
{}, "runtimeName": "fake-runtime-name", "sessionId": "000000000000000000000000000000000000000000000000",
"vmSize": "Standard_D2", "maxIdleTimeSeconds": 3600, "sessionSetupMode": "SystemWait",
"flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '920'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"run_id"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '3.485'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/run_id
response:
body:
string: '{"flowRunResourceId": "azureml://locations/eastus/workspaces/00000/flows/run_id/flowRuns/run_id",
"flowRunId": "run_id", "flowRunDisplayName": "run_id", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/107bd3498e44deb2dccc53d2208d32b2/webClassification1.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "automatic",
"inputsMapping": {"url": "${data.url}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/run_id/flow_artifacts",
"studioPortalEndpoint": "https://ml.azure.com/runs/run_id?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '945'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.273'
status:
code: 200
message: OK
- request:
body: '{"runId": "run_id", "selectRunMetadata": true, "selectRunDefinition": true,
"selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705049212, "rootRunId": "run_id", "createdUtc":
"2024-01-12T08:46:52.5382691+00:00", "createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": null, "warnings": null, "revision": 1,
"statusRevision": 0, "runUuid": "2fb0f4b1-9d4b-4dd7-9394-c35727026f45", "parentRunUuid":
null, "rootRunUuid": "2fb0f4b1-9d4b-4dd7-9394-c35727026f45", "lastStartTimeUtc":
null, "currentComputeTime": "00:00:00", "computeDuration": null, "effectiveStartTimeUtc":
null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:46:52.5382691+00:00", "duration":
null, "cancelationReason": null, "currentAttemptId": 1, "runId": "run_id",
"parentRunId": null, "experimentId": "d30efbeb-f81d-4cfa-b5cc-a0570a049009",
"status": "NotStarted", "startTimeUtc": null, "endTimeUtc": null, "scheduleId":
null, "displayName": "run_id", "name": null, "dataContainerId": "dcid.run_id",
"description": null, "hidden": false, "runType": "azureml.promptflow.FlowRun",
"runTypeV2": {"orchestrator": null, "traits": [], "attribution": "PromptFlow",
"computeType": null}, "properties": {"azureml.promptflow.runtime_name": "automatic",
"azureml.promptflow.runtime_version": "20231218.v2", "azureml.promptflow.definition_file_name":
"flow.dag.yaml", "azureml.promptflow.session_id": "4dd8f4d5f44dfeb817d3438cf84bd739215d87afd9458597",
"azureml.promptflow.flow_lineage_id": "af1a6951de9be2ce13d3b58b23dbd8b6a0cd8fd4918ad9cb22b28fb8395fbcb0",
"azureml.promptflow.node_variant": "${summarize_text_content.variant_0}",
"azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore",
"azureml.promptflow.flow_definition_blob_path": "LocalUpload/a1fa6ef1ead7ff3ce76b36250f6f5461/web_classification/flow.dag.yaml",
"azureml.promptflow.input_data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/107bd3498e44deb2dccc53d2208d32b2/webClassification1.jsonl",
"azureml.promptflow.inputs_mapping": "{\"url\":\"${data.url}\"}", "_azureml.evaluation_run":
"promptflow.BatchRun"}, "parameters": {}, "actionUris": {}, "scriptName":
null, "target": null, "uniqueChildRunComputeTargets": [], "tags": {}, "settings":
{}, "services": {}, "inputDatasets": [], "outputDatasets": [], "runDefinition":
null, "jobSpecification": null, "primaryMetricName": null, "createdFrom":
null, "cancelUri": null, "completeUri": null, "diagnosticsUri": null, "computeRequest":
null, "compute": null, "retainForLifetimeOfWorkspace": false, "queueingInfo":
null, "inputs": null, "outputs": null}, "runDefinition": null, "jobSpecification":
null, "systemSettings": null}'
headers:
connection:
- keep-alive
content-length:
- '3921'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.081'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_run_bulk_with_remote_flow.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.034'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.127'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceworkingdirectory
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceworkingdirectory",
"name": "workspaceworkingdirectory", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
false, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureFile", "accountName": "fake_account_name",
"fileShareName": "fake-file-share-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "None"}, "systemData": {"createdAt":
"2023-04-08T02:53:06.6001169+00:00", "createdBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"createdByType": "Application", "lastModifiedAt": "2023-04-08T02:53:07.2885525+00:00",
"lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a", "lastModifiedByType":
"Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1161'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.088'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceworkingdirectory/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.178'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:20:46 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- inherit
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/LocalUpload?restype=directory
response:
body:
string: "\uFEFF<?xml version=\"1.0\" encoding=\"utf-8\"?><Error><Code>ResourceAlreadyExists</Code><Message>The
specified resource already exists.\nRequestId:6129333d-f01a-008a-1530-45563d000000\nTime:2024-01-12T08:20:47.2521286Z</Message></Error>"
headers:
content-length:
- '228'
content-type:
- application/xml
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-error-code:
- ResourceAlreadyExists
x-ms-version:
- '2023-08-03'
status:
code: 409
message: The specified resource already exists.
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:20:48 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- inherit
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users?restype=directory
response:
body:
string: "\uFEFF<?xml version=\"1.0\" encoding=\"utf-8\"?><Error><Code>ResourceAlreadyExists</Code><Message>The
specified resource already exists.\nRequestId:86b8d942-f01a-0103-4330-4512e5000000\nTime:2024-01-12T08:20:49.4233757Z</Message></Error>"
headers:
content-length:
- '228'
content-type:
- application/xml
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-error-code:
- ResourceAlreadyExists
x-ms-version:
- '2023-08-03'
status:
code: 409
message: The specified resource already exists.
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:20:49 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- inherit
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users%2Funknown_user?restype=directory
response:
body:
string: "\uFEFF<?xml version=\"1.0\" encoding=\"utf-8\"?><Error><Code>ResourceAlreadyExists</Code><Message>The
specified resource already exists.\nRequestId:ecf357ab-601a-000e-3630-45243c000000\nTime:2024-01-12T08:20:50.4359042Z</Message></Error>"
headers:
content-length:
- '228'
content-type:
- application/xml
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-error-code:
- ResourceAlreadyExists
x-ms-version:
- '2023-08-03'
status:
code: 409
message: The specified resource already exists.
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:20:50 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- inherit
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users%2Funknown_user%2Fpromptflow?restype=directory
response:
body:
string: "\uFEFF<?xml version=\"1.0\" encoding=\"utf-8\"?><Error><Code>ResourceAlreadyExists</Code><Message>The
specified resource already exists.\nRequestId:c3caa163-701a-004f-3930-457cd8000000\nTime:2024-01-12T08:20:51.5247623Z</Message></Error>"
headers:
content-length:
- '228'
content-type:
- application/xml
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-error-code:
- ResourceAlreadyExists
x-ms-version:
- '2023-08-03'
status:
code: 409
message: The specified resource already exists.
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:20:51 GMT
x-ms-version:
- '2023-08-03'
method: GET
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users%2Funknown_user%2Fpromptflow%2Fflow_name?restype=directory
response:
body:
string: "\uFEFF<?xml version=\"1.0\" encoding=\"utf-8\"?><Error><Code>ResourceNotFound</Code><Message>The
specified resource does not exist.\nRequestId:2e1ebc56-901a-00a3-7730-456849000000\nTime:2024-01-12T08:20:52.5499479Z</Message></Error>"
headers:
content-length:
- '223'
content-type:
- application/xml
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-error-code:
- ResourceNotFound
x-ms-version:
- '2023-08-03'
status:
code: 404
message: The specified resource does not exist.
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:20:52 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- inherit
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users%2Funknown_user%2Fpromptflow%2Fflow_name?restype=directory
response:
body:
string: ''
headers:
content-length:
- '0'
last-modified:
- Fri, 12 Jan 2024 08:20:53 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-attributes:
- Directory
x-ms-file-change-time:
- '2024-01-12T08:20:53.5910056Z'
x-ms-file-creation-time:
- '2024-01-12T08:20:53.5910056Z'
x-ms-file-id:
- '13835071872191954944'
x-ms-file-last-write-time:
- '2024-01-12T08:20:53.5910056Z'
x-ms-file-parent-id:
- '10088082484072808448'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:20:53 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- inherit
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users%2Funknown_user%2Fpromptflow%2Fflow_name%2F__pycache__?restype=directory
response:
body:
string: ''
headers:
content-length:
- '0'
last-modified:
- Fri, 12 Jan 2024 08:20:54 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-attributes:
- Directory
x-ms-file-change-time:
- '2024-01-12T08:20:54.6393991Z'
x-ms-file-creation-time:
- '2024-01-12T08:20:54.6393991Z'
x-ms-file-id:
- '13835142240936132608'
x-ms-file-last-write-time:
- '2024-01-12T08:20:54.6393991Z'
x-ms-file-parent-id:
- '13835071872191954944'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-content-length:
- '14'
x-ms-date:
- Fri, 12 Jan 2024 08:20:54 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- Inherit
x-ms-type:
- file
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users/unknown_user/promptflow/flow_name/.gitattributes
response:
body:
string: ''
headers:
content-length:
- '0'
last-modified:
- Fri, 12 Jan 2024 08:20:55 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-attributes:
- Archive
x-ms-file-change-time:
- '2024-01-12T08:20:55.6877941Z'
x-ms-file-creation-time:
- '2024-01-12T08:20:55.6877941Z'
x-ms-file-id:
- '13835107056564043776'
x-ms-file-last-write-time:
- '2024-01-12T08:20:55.6877941Z'
x-ms-file-parent-id:
- '13835071872191954944'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: '* text eol=lf
'
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '14'
Content-MD5:
- nYmkCopuDuFj82431amzZw==
Content-Type:
- application/octet-stream
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:20:55 GMT
x-ms-range:
- bytes=0-13
x-ms-version:
- '2023-08-03'
x-ms-write:
- update
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users/unknown_user/promptflow/flow_name/.gitattributes?comp=range
response:
body:
string: ''
headers:
content-length:
- '0'
content-md5:
- nYmkCopuDuFj82431amzZw==
last-modified:
- Fri, 12 Jan 2024 08:20:56 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-last-write-time:
- '2024-01-12T08:20:56.7202574Z'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-content-length:
- '250'
x-ms-date:
- Fri, 12 Jan 2024 08:20:56 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- Inherit
x-ms-type:
- file
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users/unknown_user/promptflow/flow_name/flow.dag.yaml
response:
body:
string: ''
headers:
content-length:
- '0'
last-modified:
- Fri, 12 Jan 2024 08:20:57 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-attributes:
- Archive
x-ms-file-change-time:
- '2024-01-12T08:20:57.7935437Z'
x-ms-file-creation-time:
- '2024-01-12T08:20:57.7935437Z'
x-ms-file-id:
- '13835177425308221440'
x-ms-file-last-write-time:
- '2024-01-12T08:20:57.7935437Z'
x-ms-file-parent-id:
- '13835071872191954944'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: "inputs:\n name:\n type: string\n default: hod\noutputs:\n result:\n
\ type: string\n reference: ${hello_world.output}\nnodes:\n- name: hello_world\n
\ type: python\n source:\n type: code\n path: hello_world.py\n inputs:\n
\ name: ${inputs.name}\n"
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '250'
Content-MD5:
- CT1FTZp5JScB8fq+HjnINw==
Content-Type:
- application/octet-stream
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:20:57 GMT
x-ms-range:
- bytes=0-249
x-ms-version:
- '2023-08-03'
x-ms-write:
- update
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users/unknown_user/promptflow/flow_name/flow.dag.yaml?comp=range
response:
body:
string: ''
headers:
content-length:
- '0'
content-md5:
- CT1FTZp5JScB8fq+HjnINw==
last-modified:
- Fri, 12 Jan 2024 08:20:58 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-last-write-time:
- '2024-01-12T08:20:58.8299884Z'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-content-length:
- '105'
x-ms-date:
- Fri, 12 Jan 2024 08:20:58 GMT
x-ms-file-attributes:
- none
x-ms-file-creation-time:
- now
x-ms-file-last-write-time:
- now
x-ms-file-permission:
- Inherit
x-ms-type:
- file
x-ms-version:
- '2023-08-03'
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users/unknown_user/promptflow/flow_name/hello_world.py
response:
body:
string: ''
headers:
content-length:
- '0'
last-modified:
- Fri, 12 Jan 2024 08:20:59 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-attributes:
- Archive
x-ms-file-change-time:
- '2024-01-12T08:20:59.8445310Z'
x-ms-file-creation-time:
- '2024-01-12T08:20:59.8445310Z'
x-ms-file-id:
- '13835089464377999360'
x-ms-file-last-write-time:
- '2024-01-12T08:20:59.8445310Z'
x-ms-file-parent-id:
- '13835071872191954944'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: "from promptflow import tool\n\n\n@tool\ndef hello_world(name: str) -> str:\n
\ return f\"Hello World {name}!\"\n"
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '105'
Content-MD5:
- fGMkkiZAjGs8PW/AMiYppA==
Content-Type:
- application/octet-stream
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:20:59 GMT
x-ms-range:
- bytes=0-104
x-ms-version:
- '2023-08-03'
x-ms-write:
- update
method: PUT
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users/unknown_user/promptflow/flow_name/hello_world.py?comp=range
response:
body:
string: ''
headers:
content-length:
- '0'
content-md5:
- fGMkkiZAjGs8PW/AMiYppA==
last-modified:
- Fri, 12 Jan 2024 08:21:00 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-last-write-time:
- '2024-01-12T08:21:00.8660433Z'
x-ms-request-server-encrypted:
- 'true'
x-ms-version:
- '2023-08-03'
status:
code: 201
message: Created
- request:
body: '{"flowName": "flow_display_name", "description": "test flow description",
"tags": {"owner": "sdk-test"}, "flowDefinitionFilePath": "Users/unknown_user/promptflow/flow_name/flow.dag.yaml",
"flowType": "default"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '282'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/Flows
response:
body:
string: '{"eTag": {}, "studioPortalEndpoint": "https://ml.azure.com/prompts/flow/3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/f3886259-e2d7-4acc-880a-69cd2ed547cc/details?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"flowId": "f3886259-e2d7-4acc-880a-69cd2ed547cc", "flowName": "flow_display_name",
"description": "test flow description", "tags": {"owner": "sdk-test"}, "flowType":
"Default", "experimentId": "00000000-0000-0000-0000-000000000000", "createdDate":
"2024-01-12T08:21:03.4561663Z", "lastModifiedDate": "2024-01-12T08:21:03.456185Z",
"owner": {"userObjectId": "00000000-0000-0000-0000-000000000000", "userTenantId":
"00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587"},
"flowResourceId": "azureml://locations/eastus/workspaces/00000/flows/f3886259-e2d7-4acc-880a-69cd2ed547cc",
"isArchived": false, "flowDefinitionFilePath": "Users/unknown_user/promptflow/flow_name/flow.dag.yaml"}'
headers:
connection:
- keep-alive
content-length:
- '1099'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.560'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-file-share/12.14.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:21:03 GMT
x-ms-version:
- '2023-08-03'
method: HEAD
uri: https://fake_account_name.file.core.windows.net/fake-file-share-name/Users/unknown_user/promptflow/flow_name/flow.dag.yaml
response:
body:
string: ''
headers:
content-length:
- '250'
content-type:
- application/octet-stream
last-modified:
- Fri, 12 Jan 2024 08:20:58 GMT
server:
- Windows-Azure-File/1.0 Microsoft-HTTPAPI/2.0
x-ms-file-attributes:
- Archive
x-ms-file-change-time:
- '2024-01-12T08:20:58.8299884Z'
x-ms-file-creation-time:
- '2024-01-12T08:20:57.7935437Z'
x-ms-file-id:
- '13835177425308221440'
x-ms-file-last-write-time:
- '2024-01-12T08:20:58.8299884Z'
x-ms-file-parent-id:
- '13835071872191954944'
x-ms-type:
- File
x-ms-version:
- '2023-08-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1227'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.144'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.206'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:21:07 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/simple_hello_world.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '22'
content-md5:
- SaVvJK8fXJzgPgQkmSaCGA==
content-type:
- application/octet-stream
last-modified:
- Thu, 23 Nov 2023 12:11:21 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Thu, 23 Nov 2023 12:11:20 GMT
x-ms-meta-name:
- 74c8f1fa-9e14-4249-8fec-279efedeb400
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- 2266d840-3ecd-4a91-9e63-8d57e7b0a62e
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.10.13 (Windows-10-10.0.22631-SP0)
x-ms-date:
- Fri, 12 Jan 2024 08:21:08 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/simple_hello_world.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: '{"flowDefinitionResourceId": "azureml://locations/fake-region/workspaces/00000/flows/00000000-0000-0000-0000-000000000000/",
"runId": "name", "runDisplayName": "name", "batchDataInput": {"dataUri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/000000000000000000000000000000000000/simple_hello_world.jsonl"},
"inputsMapping": {"name": "${data.name}"}, "connections": {}, "environmentVariables":
{}, "runtimeName": "fake-runtime-name", "sessionId": "000000000000000000000000000000000000000000000000",
"sessionSetupMode": "SystemWait", "flowLineageId": "0000000000000000000000000000000000000000000000000000000000000000",
"runDisplayNameGenerationType": "UserProvidedMacro"}'
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '727'
Content-Type:
- application/json
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: POST
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/submit
response:
body:
string: '"name"'
headers:
connection:
- keep-alive
content-length:
- '38'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
x-content-type-options:
- nosniff
x-request-time:
- '7.332'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azsdk-python-azuremachinelearningdesignerserviceclient/unknown
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://eastus.api.azureml.ms/flow/api/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/BulkRuns/name
response:
body:
string: '{"flowGraph": {"nodes": [{"name": "hello_world", "type": "python",
"source": {"type": "code", "path": "hello_world.py"}, "inputs": {"name": "${inputs.name}"},
"tool": "hello_world.py", "reduce": false}], "tools": [{"name": "Content Safety
(Text Analyze)", "type": "python", "inputs": {"connection": {"type": ["AzureContentSafetyConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"hate_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"self_harm_category": {"type": ["string"], "default": "medium_sensitivity",
"enum": ["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"sexual_category": {"type": ["string"], "default": "medium_sensitivity", "enum":
["disable", "low_sensitivity", "medium_sensitivity", "high_sensitivity"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"text": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "violence_category": {"type": ["string"],
"default": "medium_sensitivity", "enum": ["disable", "low_sensitivity", "medium_sensitivity",
"high_sensitivity"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Use Azure Content Safety to detect
harmful content.", "module": "promptflow.tools.azure_content_safety", "function":
"analyze_text", "is_builtin": true, "package": "promptflow-tools", "package_version":
"0.0.216", "enable_kwargs": false, "deprecated_tools": ["content_safety_text.tools.content_safety_text_tool.analyze_text"],
"tool_state": "stable"}, {"name": "Embedding", "type": "python", "inputs":
{"connection": {"type": ["AzureOpenAIConnection", "OpenAIConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "deployment_name":
{"type": ["string"], "enabled_by": "connection", "enabled_by_type": ["AzureOpenAIConnection"],
"model_list": ["text-embedding-ada-002", "text-search-ada-doc-001", "text-search-ada-query-001"],
"capabilities": {"completion": false, "chat_completion": false, "embeddings":
true}, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "input": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
"text-search-ada-doc-001", "text-search-ada-query-001"], "enabled_by": "connection",
"enabled_by_type": ["OpenAIConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Open AI''s embedding
model to create an embedding vector representing the input text.", "module":
"promptflow.tools.embedding", "function": "embedding", "is_builtin": true,
"package": "promptflow-tools", "package_version": "0.0.216", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Open Source LLM", "type": "custom_llm",
"inputs": {"api": {"type": ["string"], "enum": ["chat", "completion"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CustomConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "deployment_name": {"type": ["string"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "endpoint_name":
{"type": ["string"], "default": "-- please enter an endpoint name --", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_new_tokens":
{"type": ["int"], "default": 500, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "model_kwargs": {"type": ["object"], "default":
"{}", "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default", "advanced": true}, "temperature": {"type": ["double"], "default":
1.0, "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "top_p": {"type": ["double"], "default": 1.0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default", "advanced": true}},
"description": "Use an Open Source model from the Azure Model catalog, deployed
to an AzureML Online Endpoint for LLM Chat or Completion API calls.", "module":
"promptflow.tools.open_source_llm", "class_name": "OpenSourceLLM", "function":
"call", "icon": "data:image/png;base64,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",
"is_builtin": true, "package": "promptflow-tools", "package_version": "0.0.216",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "OpenAI GPT-4V",
"type": "custom_llm", "inputs": {"connection": {"type": ["OpenAIConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"frequency_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "max_tokens": {"type":
["int"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "model": {"type": ["string"], "enum": ["gpt-4-vision-preview"],
"allow_manual_entry": true, "is_multi_select": false, "input_type": "default"},
"presence_penalty": {"type": ["double"], "default": 0, "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "stop": {"type":
["list"], "default": "", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "temperature": {"type": ["double"], "default": 1,
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"top_p": {"type": ["double"], "default": 1, "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use OpenAI GPT-4V to leverage
vision ability.", "module": "promptflow.tools.openai_gpt4v", "class_name":
"OpenAI", "function": "chat", "is_builtin": true, "package": "promptflow-tools",
"package_version": "0.0.216", "default_prompt": "# system:\nAs an AI assistant,
your task involves interpreting images and responding to questions about the
image.\nRemember to provide accurate answers based on the information present
in the image.\n\n# user:\nCan you tell me what the image depicts?\n\n",
"enable_kwargs": false, "tool_state": "stable"}, {"name": "Serp API", "type":
"python", "inputs": {"connection": {"type": ["SerpConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "engine": {"type":
["string"], "default": "google", "enum": ["google", "bing"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "location": {"type":
["string"], "default": "", "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "num": {"type": ["int"], "default": "10",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"query": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "safe": {"type": ["string"], "default": "off",
"enum": ["active", "off"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Use Serp API to obtain search
results from a specific search engine.", "module": "promptflow.tools.serpapi",
"class_name": "SerpAPI", "function": "search", "is_builtin": true, "package":
"promptflow-tools", "package_version": "0.0.216", "enable_kwargs": false,
"tool_state": "stable"}, {"name": "Faiss Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "top_k": {"type": ["int"], "default": "3",
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"vector": {"type": ["list"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "description": "Search vector based query
from the FAISS index file.", "module": "promptflow_vectordb.tool.faiss_index_lookup",
"class_name": "FaissIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector DB Lookup", "type": "python",
"inputs": {"class_name": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["WeaviateConnection"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "collection_name": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["QdrantConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "connection": {"type":
["CognitiveSearchConnection", "QdrantConnection", "WeaviateConnection"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "index_name": {"type":
["string"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection"],
"allow_manual_entry": false, "is_multi_select": false, "input_type": "default"},
"search_filters": {"type": ["object"], "enabled_by": "connection", "enabled_by_type":
["CognitiveSearchConnection", "QdrantConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}, "search_params": {"type":
["object"], "enabled_by": "connection", "enabled_by_type": ["CognitiveSearchConnection",
"QdrantConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "text_field": {"type": ["string"], "enabled_by":
"connection", "enabled_by_type": ["CognitiveSearchConnection", "QdrantConnection",
"WeaviateConnection"], "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}, "top_k": {"type": ["int"], "default": "3", "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "vector": {"type":
["list"], "allow_manual_entry": false, "is_multi_select": false, "input_type":
"default"}, "vector_field": {"type": ["string"], "enabled_by": "connection",
"enabled_by_type": ["CognitiveSearchConnection"], "allow_manual_entry": false,
"is_multi_select": false, "input_type": "default"}}, "description": "Search
vector based query from existing Vector Database.", "module": "promptflow_vectordb.tool.vector_db_lookup",
"class_name": "VectorDBLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "Vector Index Lookup", "type": "python",
"inputs": {"path": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}, "query": {"type": ["object"], "allow_manual_entry":
false, "is_multi_select": false, "input_type": "default"}, "top_k": {"type":
["int"], "default": "3", "allow_manual_entry": false, "is_multi_select": false,
"input_type": "default"}}, "description": "Search text or vector based query
from AzureML Vector Index.", "module": "promptflow_vectordb.tool.vector_index_lookup",
"class_name": "VectorIndexLookup", "function": "search", "is_builtin": true,
"package": "promptflow-vectordb", "package_version": "0.0.1", "enable_kwargs":
false, "tool_state": "stable"}, {"name": "hello_world.py", "type": "python",
"inputs": {"name": {"type": ["string"], "allow_manual_entry": false, "is_multi_select":
false, "input_type": "default"}}, "source": "hello_world.py", "function":
"hello_world", "is_builtin": false, "enable_kwargs": false, "tool_state":
"stable"}], "inputs": {"name": {"type": "string", "default": "hod", "is_chat_input":
false}}, "outputs": {"result": {"type": "string", "reference": "${hello_world.output}",
"evaluation_only": false, "is_chat_output": false}}}, "flowRunResourceId":
"azureml://locations/eastus/workspaces/00000/flows/f3886259-e2d7-4acc-880a-69cd2ed547cc/flowRuns/name",
"flowRunId": "name", "flowRunDisplayName": "name", "batchDataInput": {"dataUri":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/79f088fae0e502653c43146c9682f425/simple_hello_world.jsonl"},
"flowRunType": "FlowRun", "flowType": "Default", "runtimeName": "test-runtime-ci",
"inputsMapping": {"name": "${data.name}"}, "outputDatastoreName": "workspaceblobstore",
"childRunBasePath": "promptflow/PromptFlowArtifacts/f3886259-e2d7-4acc-880a-69cd2ed547cc/name/flow_artifacts",
"flowDagFileRelativePath": "flow.dag.yaml", "flowSnapshotId": "5003f634-d7a8-42ec-a7a9-519755b1c1fa",
"studioPortalEndpoint": "https://ml.azure.com/runs/name?wsid=/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000"}'
headers:
connection:
- keep-alive
content-length:
- '12944'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.319'
status:
code: 200
message: OK
- request:
body: '{"runId": "name", "selectRunMetadata": true, "selectRunDefinition": true,
"selectJobSpecification": true}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '137'
Content-Type:
- application/json
User-Agent:
- python-requests/2.31.0
method: POST
uri: https://eastus.api.azureml.ms/history/v1.0/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/rundata
response:
body:
string: '{"runMetadata": {"runNumber": 1705047673, "rootRunId": "name", "createdUtc":
"2024-01-12T08:21:13.4108336+00:00", "createdBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "userId": "00000000-0000-0000-0000-000000000000", "token": null,
"tokenExpiryTimeUtc": null, "error": null, "warnings": null, "revision": 3,
"statusRevision": 1, "runUuid": "726be460-9edf-49d2-a74f-066dc85d64ba", "parentRunUuid":
null, "rootRunUuid": "726be460-9edf-49d2-a74f-066dc85d64ba", "lastStartTimeUtc":
null, "currentComputeTime": "00:00:00", "computeDuration": null, "effectiveStartTimeUtc":
null, "lastModifiedBy": {"userObjectId": "00000000-0000-0000-0000-000000000000",
"userPuId": null, "userIdp": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userAltSecId": null, "userIss": "https://sts.windows.net/00000000-0000-0000-0000-000000000000/",
"userTenantId": "00000000-0000-0000-0000-000000000000", "userName": "4cbd0e2e-aae4-4099-b4ba-94d3a4910587",
"upn": null}, "lastModifiedUtc": "2024-01-12T08:21:17.8855829+00:00", "duration":
null, "cancelationReason": null, "currentAttemptId": 1, "runId": "name", "parentRunId":
null, "experimentId": "ea890465-3022-4c1a-b6d8-894897cbe16d", "status": "Preparing",
"startTimeUtc": null, "endTimeUtc": null, "scheduleId": null, "displayName":
"name", "name": null, "dataContainerId": "dcid.name", "description": null,
"hidden": false, "runType": "azureml.promptflow.FlowRun", "runTypeV2": {"orchestrator":
null, "traits": [], "attribution": "PromptFlow", "computeType": "AmlcDsi"},
"properties": {"azureml.promptflow.runtime_name": "test-runtime-ci", "azureml.promptflow.runtime_version":
"20231204.v4", "azureml.promptflow.definition_file_name": "flow.dag.yaml",
"azureml.promptflow.session_id": "f3886259-e2d7-4acc-880a-69cd2ed547cc", "azureml.promptflow.flow_lineage_id":
"f3886259-e2d7-4acc-880a-69cd2ed547cc", "azureml.promptflow.flow_definition_resource_id":
"azureml://locations/eastus/workspaces/00000/flows/f3886259-e2d7-4acc-880a-69cd2ed547cc",
"azureml.promptflow.flow_id": "f3886259-e2d7-4acc-880a-69cd2ed547cc", "azureml.promptflow.input_data":
"azureml://datastores/workspaceblobstore/paths/LocalUpload/79f088fae0e502653c43146c9682f425/simple_hello_world.jsonl",
"azureml.promptflow.inputs_mapping": "{\"name\":\"${data.name}\"}", "_azureml.evaluation_run":
"promptflow.BatchRun", "azureml.promptflow.snapshot_id": "5003f634-d7a8-42ec-a7a9-519755b1c1fa"},
"parameters": {}, "actionUris": {}, "scriptName": null, "target": null, "uniqueChildRunComputeTargets":
[], "tags": {}, "settings": {}, "services": {}, "inputDatasets": [], "outputDatasets":
[], "runDefinition": null, "jobSpecification": null, "primaryMetricName":
null, "createdFrom": null, "cancelUri": null, "completeUri": null, "diagnosticsUri":
null, "computeRequest": null, "compute": null, "retainForLifetimeOfWorkspace":
false, "queueingInfo": null, "inputs": null, "outputs": null}, "runDefinition":
null, "jobSpecification": null, "systemSettings": null}'
headers:
connection:
- keep-alive
content-length:
- '3930'
content-type:
- application/json; charset=utf-8
strict-transport-security:
- max-age=15724800; includeSubDomains; preload
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.045'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_run_bulk_without_retry.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.024'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.074'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_run_bulk_not_exist.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus", "tags": {}, "etag": null, "kind": "Default", "sku": {"name": "Basic",
"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.032'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 promptflow/0.0.1 azure-ai-ml/1.12.1 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.10.13 (Windows-10-10.0.22631-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-04-08T02:53:07.521127+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1372'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
vary:
- Accept-Encoding
x-cache:
- CONFIG_NOCACHE
x-content-type-options:
- nosniff
x-request-time:
- '0.104'
status:
code: 200
message: OK
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_automatic_runtime.yaml | interactions:
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000",
"name": "00000", "type": "Microsoft.MachineLearningServices/workspaces", "location":
"eastus2euap", "tags": {}, "etag": null, "kind": "Default", "sku": {"name":
"Basic", "tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3601'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.019'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores?count=30&isDefault=true&orderByAsc=false
response:
body:
string: '{"value": [{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-09-22T05:26:30.7527337+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-09-22T05:26:31.3199607+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}]}'
headers:
cache-control:
- no-cache
content-length:
- '1378'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.628'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-09-22T05:26:30.7527337+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-09-22T05:26:31.3199607+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1233'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.069'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.114'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Fri, 05 Jan 2024 08:28:55 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '49'
content-md5:
- quXiEreYvPinSj0HsaNa/g==
content-type:
- application/octet-stream
last-modified:
- Tue, 26 Dec 2023 02:27:07 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Tue, 26 Dec 2023 02:27:07 GMT
x-ms-meta-name:
- bcc45cd4-c343-4bd0-8bdd-cecfafea742d
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- be87bd84-d39b-442b-af5a-e8c209d6d10c
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Fri, 05 Jan 2024 08:28:56 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-09-22T05:26:30.7527337+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-09-22T05:26:31.3199607+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1233'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.068'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.106'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Fri, 05 Jan 2024 08:29:00 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '245'
content-md5:
- F+JA0a3CxcLYZ0ANRdlZbA==
content-type:
- application/octet-stream
last-modified:
- Tue, 26 Dec 2023 02:27:07 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Tue, 26 Dec 2023 02:27:07 GMT
x-ms-meta-name:
- 5541d425-c3dc-4f2e-b818-956634d8a470
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Fri, 05 Jan 2024 08:29:01 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-09-22T05:26:30.7527337+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-09-22T05:26:31.3199607+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1233'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.058'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.085'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Fri, 05 Jan 2024 08:29:09 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '49'
content-md5:
- quXiEreYvPinSj0HsaNa/g==
content-type:
- application/octet-stream
last-modified:
- Tue, 26 Dec 2023 02:27:07 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Tue, 26 Dec 2023 02:27:07 GMT
x-ms-meta-name:
- bcc45cd4-c343-4bd0-8bdd-cecfafea742d
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- be87bd84-d39b-442b-af5a-e8c209d6d10c
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Fri, 05 Jan 2024 08:29:10 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/env_var_names.jsonl
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: GET
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore
response:
body:
string: '{"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore",
"name": "workspaceblobstore", "type": "Microsoft.MachineLearningServices/workspaces/datastores",
"properties": {"description": null, "tags": null, "properties": null, "isDefault":
true, "credentials": {"credentialsType": "AccountKey"}, "intellectualProperty":
null, "subscriptionId": "00000000-0000-0000-0000-000000000000", "resourceGroup":
"00000", "datastoreType": "AzureBlob", "accountName": "fake_account_name",
"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-09-22T05:26:30.7527337+00:00", "createdBy":
"779301c0-18b2-4cdc-801b-a0a3368fee0a", "createdByType": "Application", "lastModifiedAt":
"2023-09-22T05:26:31.3199607+00:00", "lastModifiedBy": "779301c0-18b2-4cdc-801b-a0a3368fee0a",
"lastModifiedByType": "Application"}}'
headers:
cache-control:
- no-cache
content-length:
- '1233'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.097'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '0'
User-Agent:
- promptflow-sdk/0.0.1 azure-ai-ml/1.12.0 azsdk-python-mgmt-machinelearningservices/0.1.0
Python/3.11.5 (Windows-10-10.0.22621-SP0)
method: POST
uri: https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/00000/providers/Microsoft.MachineLearningServices/workspaces/00000/datastores/workspaceblobstore/listSecrets
response:
body:
string: '{"secretsType": "AccountKey", "key": "dGhpcyBpcyBmYWtlIGtleQ=="}'
headers:
cache-control:
- no-cache
content-length:
- '134'
content-type:
- application/json; charset=utf-8
expires:
- '-1'
pragma:
- no-cache
strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.083'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Fri, 05 Jan 2024 08:29:13 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/LocalUpload/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
accept-ranges:
- bytes
content-length:
- '245'
content-md5:
- F+JA0a3CxcLYZ0ANRdlZbA==
content-type:
- application/octet-stream
last-modified:
- Tue, 26 Dec 2023 02:27:07 GMT
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
vary:
- Origin
x-ms-blob-type:
- BlockBlob
x-ms-creation-time:
- Tue, 26 Dec 2023 02:27:07 GMT
x-ms-meta-name:
- 5541d425-c3dc-4f2e-b818-956634d8a470
x-ms-meta-upload_status:
- completed
x-ms-meta-version:
- '1'
x-ms-version:
- '2023-11-03'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/xml
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
User-Agent:
- azsdk-python-storage-blob/12.19.0 Python/3.11.5 (Windows-10-10.0.22621-SP0)
x-ms-date:
- Fri, 05 Jan 2024 08:29:14 GMT
x-ms-version:
- '2023-11-03'
method: HEAD
uri: https://fake_account_name.blob.core.windows.net/fake-container-name/az-ml-artifacts/000000000000000000000000000000000000/print_env_var/flow.dag.yaml
response:
body:
string: ''
headers:
server:
- Windows-Azure-Blob/1.0 Microsoft-HTTPAPI/2.0
transfer-encoding:
- chunked
vary:
- Origin
x-ms-error-code:
- BlobNotFound
x-ms-version:
- '2023-11-03'
status:
code: 404
message: The specified blob does not exist.
version: 1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/sample_bulk_run_cloud.yaml | name: flow_run_20230629_101205
flow: ../flows/web_classification
data: ../datas/webClassification1.jsonl
column_mapping:
url: "${data.url}"
variant: ${summarize_text_content.variant_0}
# run config: env related
environment_variables: env_file
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/sample_eval_run.yaml | flow: ../flows/classification_accuracy_evaluation
data: ../datas/webClassification1.jsonl
column_mapping:
groundtruth: "${data.answer}"
prediction: "${run.outputs.category}"
variant_id: "${data.variant_id}"
run: flow_run_20230629_101205 # ./sample_bulk_run.yaml
# run config: env related
environment_variables: env_file
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/bulk_run_invalid_remote_flow_str.yaml | name: flow_run_20230629_101205
description: sample bulk run
# invalid remote flow format should not be supported.
flow: invalid_remote_flow
data: ../datas/webClassification1.jsonl
column_mapping:
url: "${data.url}"
variant: ${summarize_text_content.variant_0}
# run config: env related
environment_variables: env_file
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/bulk_run_invalid_flow_path.yaml | name: flow_run_20230629_101205
description: sample bulk run
# flow relative to current working directory should not be supported.
flow: tests/test_configs/flows/web_classification
data: ../datas/webClassification1.jsonl
column_mapping:
url: "${data.url}"
variant: ${summarize_text_content.variant_0}
# run config: env related
environment_variables: env_file
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/sample_bulk_run_with_resources.yaml | name: flow_run_20230629_101205
flow: ../flows/web_classification
data: ../datas/webClassification1.jsonl
column_mapping:
url: "${data.url}"
variant: ${summarize_text_content.variant_0}
resources:
instance_type: Standard_D2 # optional, server default value
idle_time_before_shutdown_minutes: 60 #optional, server default value
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/run_with_connections_model.yaml | flow: ../flows/web_classification
data: ../datas/webClassification1.jsonl
column_mapping:
url: "${data.url}"
variant: ${summarize_text_content.variant_0}
# run config: env related
environment_variables: env_file
connections:
classify_with_llm:
connection: new_ai_connection
# model is also supported for openai connection
model: test_model | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/run_with_env.yaml | flow: ../flows/print_env_var
data: ../datas/env_var_names.jsonl
# run config: env related
environment_variables:
API_BASE: ${azure_open_ai_connection.api_base}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/run_with_connections.yaml | flow: ../flows/web_classification
data: ../datas/webClassification1.jsonl
column_mapping:
url: "${data.url}"
variant: ${summarize_text_content.variant_0}
# run config: env related
environment_variables: env_file
connections:
classify_with_llm:
connection: new_ai_connection
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/sample_bulk_run.yaml | name: flow_run_20230629_101205
description: sample bulk run
flow: ../flows/web_classification
data: ../datas/webClassification1.jsonl
column_mapping:
url: "${data.url}"
variant: ${summarize_text_content.variant_0}
# run config: env related
environment_variables: env_file
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/env_file | FOO=BAR
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/extra_field.yaml | name: flow_run_20230629_101205
description: sample bulk run
flow: ../flows/web_classification
data: ../datas/webClassification1.jsonl
column_mapping:
url: "${data.url}"
variant: ${summarize_text_content.variant_0}
extra_key: extra_value
# run config: env related
environment_variables: env_file | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/input_with_dict_val.yaml | flow: ../flows/flow_with_dict_input
data: ../datas/webClassification1.jsonl
column_mapping:
key:
val1: 1
val2: 2
url: ${data.url}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/meta.json | {"batch_size": 1} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/instance_results.jsonl | {"line_number": 0, "status": "Completed", "inputs.url": "https://www.youtube.com/watch?v=kYqRtjDBci8", "inputs.line_number": 0, "category": "None", "evidence": "None"}
{"line_number": 1, "status": "Completed", "inputs.url": "https://arxiv.org/abs/2307.04767", "inputs.line_number": 1, "category": "Academic", "evidence": "Both"}
{"line_number": 2, "status": "Completed", "inputs.url": "https://play.google.com/store/apps/details?id=com.twitter.android", "inputs.line_number": 2, "category": "App", "evidence": "Both"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/logs.txt | 2023-12-05 04:03:11 +0000 119 promptflow-runtime INFO [web_classification_variant_0_20231205_120253_104100] Receiving v2 bulk run request 679b46cd-3931-4ade-985f-4d74de5e9536: {"flow_id": "web_classification_variant_0_20231205_120253_104100", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "flow_source": {"flow_source_type": 1, "flow_source_info": {"snapshot_id": "20444e8d-41a6-42c9-a3df-4970aff771df"}, "flow_dag_file": "flow.dag.yaml"}, "connections": "**data_scrubbed**", "log_path": "https://promptfloweast4063704120.blob.core.windows.net/azureml/ExperimentRun/dcid.web_classification_variant_0_20231205_120253_104100/logs/azureml/executionlogs.txt?sv=2019-07-07&sr=b&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=72f988bf-86f1-41af-91ab-2d7cd011db47&skt=2023-12-04T20%3A28%3A14Z&ske=2023-12-06T04%3A38%3A14Z&sks=b&skv=2019-07-07&st=2023-12-05T03%3A53%3A10Z&se=2023-12-05T12%3A03%3A10Z&sp=rcw", "app_insights_instrumentation_key": "InstrumentationKey=**data_scrubbed**;IngestionEndpoint=https://eastus-6.in.applicationinsights.azure.com/;LiveEndpoint=https://eastus.livediagnostics.monitor.azure.com/", "data_inputs": {"data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/70c38e61b28e21cb9ddcd67dbe209f05/data.jsonl"}, "inputs_mapping": {"url": "${data.url}"}, "azure_storage_setting": {"azure_storage_mode": 1, "storage_account_name": "promptfloweast4063704120", "blob_container_name": "azureml-blobstore-3e123da1-f9a5-4c91-9234-8d9ffbb39ff5", "flow_artifacts_root_path": "promptflow/PromptFlowArtifacts/web_classification_variant_0_20231205_120253_104100", "blob_container_sas_token": "?sv=2019-07-07&sr=c&sig=**data_scrubbed**&skoid=55b92eba-d7c7-4afd-ab76-7bb1cd345283&sktid=72f988bf-86f1-41af-91ab-2d7cd011db47&skt=2023-12-05T04%3A03%3A10Z&ske=2023-12-12T04%3A03%3A10Z&sks=b&skv=2019-07-07&se=2023-12-12T04%3A03%3A10Z&sp=racwl", "output_datastore_name": "workspaceblobstore"}}
2023-12-05 04:03:11 +0000 119 promptflow-runtime INFO Runtime version: 20231114.v2. PromptFlow version: 1.0.002.dev3
2023-12-05 04:03:11 +0000 119 promptflow-runtime INFO Updating web_classification_variant_0_20231205_120253_104100 to Status.Preparing...
2023-12-05 04:03:11 +0000 119 promptflow-runtime INFO Use spawn method to start child process.
2023-12-05 04:03:11 +0000 119 promptflow-runtime INFO Starting to check process 2795 status for run web_classification_variant_0_20231205_120253_104100
2023-12-05 04:03:11 +0000 119 promptflow-runtime INFO Start checking run status for run web_classification_variant_0_20231205_120253_104100
2023-12-05 04:03:16 +0000 2795 promptflow-runtime INFO [119--2795] Start processing flowV2......
2023-12-05 04:03:16 +0000 2795 promptflow-runtime INFO Runtime version: 20231114.v2. PromptFlow version: 1.0.002.dev3
2023-12-05 04:03:16 +0000 2795 promptflow-runtime INFO Setting mlflow tracking uri...
2023-12-05 04:03:16 +0000 2795 promptflow-runtime INFO Validating 'AzureML Data Scientist' user authentication...
2023-12-05 04:03:17 +0000 2795 promptflow-runtime INFO Successfully validated 'AzureML Data Scientist' user authentication.
2023-12-05 04:03:17 +0000 2795 promptflow-runtime INFO Using AzureMLRunStorageV2
2023-12-05 04:03:17 +0000 2795 promptflow-runtime INFO Setting mlflow tracking uri to 'azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/promptflow/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus'
2023-12-05 04:03:17 +0000 2795 promptflow-runtime INFO Initialized blob service client for AzureMLRunTracker.
2023-12-05 04:03:17 +0000 2795 promptflow-runtime INFO Setting mlflow tracking uri to 'azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/promptflow/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus'
2023-12-05 04:03:17 +0000 2795 promptflow-runtime INFO Get snapshot sas url for 20444e8d-41a6-42c9-a3df-4970aff771df...
2023-12-05 04:03:23 +0000 2795 promptflow-runtime INFO Downloading snapshot 20444e8d-41a6-42c9-a3df-4970aff771df from uri https://promptfloweast4063704120.blob.core.windows.net/snapshotzips/promptflow-eastus:3e123da1-f9a5-4c91-9234-8d9ffbb39ff5:snapshotzip/20444e8d-41a6-42c9-a3df-4970aff771df.zip...
2023-12-05 04:03:24 +0000 2795 promptflow-runtime INFO Downloaded file /service/app/44783/requests/web_classification_variant_0_20231205_120253_104100/20444e8d-41a6-42c9-a3df-4970aff771df.zip with size 15337 for snapshot 20444e8d-41a6-42c9-a3df-4970aff771df.
2023-12-05 04:03:24 +0000 2795 promptflow-runtime INFO Download snapshot 20444e8d-41a6-42c9-a3df-4970aff771df completed.
2023-12-05 04:03:24 +0000 2795 promptflow-runtime INFO Resolve data from url finished in 0.6008251919411123 seconds
2023-12-05 04:03:24 +0000 2795 promptflow-runtime INFO Starting the aml run 'web_classification_variant_0_20231205_120253_104100'...
2023-12-05 04:03:25 +0000 2795 execution.bulk INFO Using fork, process count: 3
2023-12-05 04:03:25 +0000 2839 execution INFO Process 2839 started.
2023-12-05 04:03:25 +0000 2848 execution INFO Process 2848 started.
2023-12-05 04:03:25 +0000 2795 execution INFO Process name: ForkProcess-20:3, Process id: 2839, Line number: 0 start execution.
2023-12-05 04:03:25 +0000 2795 execution INFO Process name: ForkProcess-20:2, Process id: 2848, Line number: 1 start execution.
2023-12-05 04:03:25 +0000 2843 execution INFO Process 2843 started.
2023-12-05 04:03:25 +0000 2795 execution INFO Process name: ForkProcess-20:4, Process id: 2843, Line number: 2 start execution.
2023-12-05 04:03:27 +0000 2795 execution INFO Process name: ForkProcess-20:3, Process id: 2839, Line number: 0 completed.
2023-12-05 04:03:27 +0000 2795 execution.bulk INFO Finished 1 / 3 lines.
2023-12-05 04:03:27 +0000 2795 execution.bulk INFO Average execution time for completed lines: 2.03 seconds. Estimated time for incomplete lines: 4.06 seconds.
2023-12-05 04:03:28 +0000 2795 execution INFO Process name: ForkProcess-20:2, Process id: 2848, Line number: 1 completed.
2023-12-05 04:03:28 +0000 2795 execution.bulk INFO Finished 2 / 3 lines.
2023-12-05 04:03:28 +0000 2795 execution.bulk INFO Average execution time for completed lines: 1.33 seconds. Estimated time for incomplete lines: 1.33 seconds.
2023-12-05 04:03:28 +0000 2795 execution INFO Process name: ForkProcess-20:4, Process id: 2843, Line number: 2 completed.
2023-12-05 04:03:28 +0000 2795 execution.bulk INFO Finished 3 / 3 lines.
2023-12-05 04:03:28 +0000 2795 execution.bulk INFO Average execution time for completed lines: 1.05 seconds. Estimated time for incomplete lines: 0.0 seconds.
2023-12-05 04:03:32 +0000 2795 execution.bulk INFO Upload status summary metrics for run web_classification_variant_0_20231205_120253_104100 finished in 2.705599319888279 seconds
2023-12-05 04:03:32 +0000 2795 promptflow-runtime INFO Successfully write run properties {"azureml.promptflow.total_tokens": 3316, "_azureml.evaluate_artifacts": "[{\"path\": \"instance_results.jsonl\", \"type\": \"table\"}]"} with run id 'web_classification_variant_0_20231205_120253_104100'
2023-12-05 04:03:32 +0000 2795 execution.bulk INFO Upload RH properties for run web_classification_variant_0_20231205_120253_104100 finished in 0.07165036699734628 seconds
2023-12-05 04:03:32 +0000 2795 promptflow-runtime INFO Creating unregistered output Asset for Run web_classification_variant_0_20231205_120253_104100...
2023-12-05 04:03:32 +0000 2795 promptflow-runtime INFO Created debug_info Asset: azureml://locations/eastus/workspaces/3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/data/azureml_web_classification_variant_0_20231205_120253_104100_output_data_debug_info/versions/1
2023-12-05 04:03:32 +0000 2795 promptflow-runtime INFO Creating unregistered output Asset for Run web_classification_variant_0_20231205_120253_104100...
2023-12-05 04:03:32 +0000 2795 promptflow-runtime INFO Created flow_outputs output Asset: azureml://locations/eastus/workspaces/3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/data/azureml_web_classification_variant_0_20231205_120253_104100_output_data_flow_outputs/versions/1
2023-12-05 04:03:32 +0000 2795 promptflow-runtime INFO Creating Artifact for Run web_classification_variant_0_20231205_120253_104100...
2023-12-05 04:03:33 +0000 2795 promptflow-runtime INFO Created instance_results.jsonl Artifact.
2023-12-05 04:03:33 +0000 2795 promptflow-runtime INFO Patching web_classification_variant_0_20231205_120253_104100...
2023-12-05 04:03:33 +0000 2795 promptflow-runtime INFO Ending the aml run 'web_classification_variant_0_20231205_120253_104100' with status 'Completed'...
2023-12-05 04:03:34 +0000 119 promptflow-runtime INFO Process 2795 finished
2023-12-05 04:03:34 +0000 119 promptflow-runtime INFO [119] Child process finished!
2023-12-05 04:03:34 +0000 119 promptflow-runtime INFO [web_classification_variant_0_20231205_120253_104100] End processing bulk run
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/run_metadata.json | {"name": "web_classification_variant_0_20231205_120253_104100", "created_on": "2023-12-05T04:03:05.951095+00:00", "status": "Completed", "display_name": "web_classification_variant_0_20231205_120253_104100", "description": null, "tags": {}, "properties": {"azureml.promptflow.runtime_name": "hod-ci", "azureml.promptflow.runtime_version": "20231114.v2", "azureml.promptflow.definition_file_name": "flow.dag.yaml", "azureml.promptflow.session_id": "e993078a71de767aeffa1e7f34403abafb105076b5822acf", "azureml.promptflow.flow_lineage_id": "a2759552d623c603e771307d04bf932caf85ea6202ad811e3500d6002aaf9d01", "azureml.promptflow.flow_definition_datastore_name": "workspaceblobstore", "azureml.promptflow.flow_definition_blob_path": "LocalUpload/20c734740ecfef7c7dd12c2024a95c3e/web-classification/flow.dag.yaml", "azureml.promptflow.inputs_mapping": "{\"url\":\"${data.url}\"}", "_azureml.evaluation_run": "promptflow.BatchRun", "azureml.promptflow.snapshot_id": "20444e8d-41a6-42c9-a3df-4970aff771df", "azureml.promptflow.total_tokens": "3316", "_azureml.evaluate_artifacts": "[{\"path\": \"instance_results.jsonl\", \"type\": \"table\"}]"}, "creation_context": {"userObjectId": "c05e0746-e125-4cb3-9213-a8b535eacd79", "userPuId": "10032000324F7449", "userIdp": null, "userAltSecId": null, "userIss": "https://sts.windows.net/72f988bf-86f1-41af-91ab-2d7cd011db47/", "userTenantId": "72f988bf-86f1-41af-91ab-2d7cd011db47", "userName": "Honglin Du", "upn": null}, "start_time": "2023-12-05T04:03:25.057138+00:00", "end_time": "2023-12-05T04:03:33.260979+00:00", "duration": "00:00:08.2038409", "portal_url": "https://ml.azure.com/prompts/flow/bulkrun/run/web_classification_variant_0_20231205_120253_104100/details?wsid=/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/promptflow/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus", "data": "azureml://datastores/workspaceblobstore/paths/LocalUpload/70c38e61b28e21cb9ddcd67dbe209f05/data.jsonl", "data_portal_url": "https://ml.azure.com/data/datastore/workspaceblobstore/edit?wsid=/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/promptflow/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus&activeFilePath=LocalUpload/70c38e61b28e21cb9ddcd67dbe209f05/data.jsonl#browseTab", "output": "azureml://locations/eastus/workspaces/3e123da1-f9a5-4c91-9234-8d9ffbb39ff5/data/azureml_web_classification_variant_0_20231205_120253_104100_output_data_flow_outputs/versions/1", "output_portal_url": "https://ml.azure.com/data/azureml_web_classification_variant_0_20231205_120253_104100_output_data_flow_outputs/1/details?wsid=/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/promptflow/providers/Microsoft.MachineLearningServices/workspaces/promptflow-eastus"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/metrics.json | {} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/snapshot/classify_with_llm.jinja2 | system:
Your task is to classify a given url into one of the following categories:
Movie, App, Academic, Channel, Profile, PDF or None based on the text content information.
The classification will be based on the url, the webpage text content summary, or both.
user:
The selection range of the value of "category" must be within "Movie", "App", "Academic", "Channel", "Profile", "PDF" and "None".
The selection range of the value of "evidence" must be within "Url", "Text content", and "Both".
Here are a few examples:
{% for ex in examples %}
URL: {{ex.url}}
Text content: {{ex.text_content}}
OUTPUT:
{"category": "{{ex.category}}", "evidence": "{{ex.evidence}}"}
{% endfor %}
For a given URL and text content, classify the url to complete the category and indicate evidence:
URL: {{url}}
Text content: {{text_content}}.
OUTPUT: | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/snapshot/fetch_text_content_from_url.py | import bs4
import requests
from promptflow import tool
@tool
def fetch_text_content_from_url(url: str):
# Send a request to the URL
try:
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) "
"Chrome/113.0.0.0 Safari/537.36 Edg/113.0.1774.35"
}
response = requests.get(url, headers=headers)
if response.status_code == 200:
# Parse the HTML content using BeautifulSoup
soup = bs4.BeautifulSoup(response.text, "html.parser")
soup.prettify()
return soup.get_text()[:2000]
else:
msg = (
f"Get url failed with status code {response.status_code}.\nURL: {url}\nResponse: "
f"{response.text[:100]}"
)
print(msg)
return "No available content"
except Exception as e:
print("Get url failed with error: {}".format(e))
return "No available content"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/snapshot/convert_to_dict.py | import json
from promptflow import tool
@tool
def convert_to_dict(input_str: str):
try:
return json.loads(input_str)
except Exception as e:
print("The input is not valid, error: {}".format(e))
return {"category": "None", "evidence": "None"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/snapshot/data.jsonl | {"url": "https://www.youtube.com/watch?v=kYqRtjDBci8", "answer": "Channel", "evidence": "Both"}
{"url": "https://arxiv.org/abs/2307.04767", "answer": "Academic", "evidence": "Both"}
{"url": "https://play.google.com/store/apps/details?id=com.twitter.android", "answer": "App", "evidence": "Both"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/snapshot/summarize_text_content__variant_1.jinja2 | system:
Please summarize some keywords of this paragraph and have some details of each keywords.
Do not add any information that is not in the text.
user:
Text: {{text}}
Summary: | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/snapshot/requirements.txt | promptflow[azure]
promptflow-tools
bs4 | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/snapshot/run.yml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/Run.schema.json
flow: .
data: data.jsonl
variant: ${summarize_text_content.variant_1}
column_mapping:
url: ${data.url}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/snapshot/summarize_text_content.jinja2 | system:
Please summarize the following text in one paragraph. 100 words.
Do not add any information that is not in the text.
user:
Text: {{text}}
Summary: | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/snapshot/README.md | # Web Classification
This is a flow demonstrating multi-class classification with LLM. Given an url, it will classify the url into one web category with just a few shots, simple summarization and classification prompts.
## Tools used in this flow
- LLM Tool
- Python Tool
## What you will learn
In this flow, you will learn
- how to compose a classification flow with LLM.
- how to feed few shots to LLM classifier.
## Prerequisites
Install promptflow sdk and other dependencies:
```bash
pip install -r requirements.txt
```
## Getting Started
### 1. Setup connection
If you are using Azure Open AI, prepare your resource follow this [instruction](https://learn.microsoft.com/en-us/azure/cognitive-services/openai/how-to/create-resource?pivots=web-portal) and get your `api_key` if you don't have one.
```bash
# Override keys with --set to avoid yaml file changes
pf connection create --file ../../../connections/azure_openai.yml --set api_key=<your_api_key> api_base=<your_api_base> --name open_ai_connection
```
If you using OpenAI, sign up account [OpenAI website](https://openai.com/), login and [find personal API key](https://platform.openai.com/account/api-keys).
```shell
pf connection create --file ../../../connections/openai.yml --set api_key=<your_api_key>
```
### 2. Configure the flow with your connection
`flow.dag.yaml` is already configured with connection named `open_ai_connection`.
### 3. Test flow with single line data
```bash
# test with default input value in flow.dag.yaml
pf flow test --flow .
# test with user specified inputs
pf flow test --flow . --inputs url='https://www.youtube.com/watch?v=kYqRtjDBci8'
```
### 4. Run with multi-line data
```bash
# create run using command line args
pf run create --flow . --data ./data.jsonl --column-mapping url='${data.url}' --stream
# (Optional) create a random run name
run_name="web_classification_"$(openssl rand -hex 12)
# create run using yaml file, run_name will be used in following contents, --name is optional
pf run create --file run.yml --stream --name $run_name
```
You can also skip providing `column-mapping` if provided data has same column name as the flow.
Reference [here](https://aka.ms/pf/column-mapping) for default behavior when `column-mapping` not provided in CLI.
```bash
# list run
pf run list
# show run
pf run show --name $run_name
# show run outputs
pf run show-details --name $run_name
```
### 5. Run with classification evaluation flow
create `evaluation` run:
```bash
# (Optional) save previous run name into variable, and create a new random run name for further use
prev_run_name=$run_name
run_name="classification_accuracy_"$(openssl rand -hex 12)
# create run using command line args
pf run create --flow ../../evaluation/eval-classification-accuracy --data ./data.jsonl --column-mapping groundtruth='${data.answer}' prediction='${run.outputs.category}' --run $prev_run_name --stream
# create run using yaml file, --name is optional
pf run create --file run_evaluation.yml --run $prev_run_name --stream --name $run_name
```
```bash
pf run show-details --name $run_name
pf run show-metrics --name $run_name
pf run visualize --name $run_name
```
### 6. Submit run to cloud
```bash
# set default workspace
az account set -s <your_subscription_id>
az configure --defaults group=<your_resource_group_name> workspace=<your_workspace_name>
# create run
pfazure run create --flow . --data ./data.jsonl --column-mapping url='${data.url}' --stream --runtime example-runtime-ci
# pfazure run create --flow . --data ./data.jsonl --column-mapping url='${data.url}' --stream # automatic runtime
# (Optional) create a new random run name for further use
run_name="web_classification_"$(openssl rand -hex 12)
# create run using yaml file, --name is optional
pfazure run create --file run.yml --runtime example-runtime-ci --name $run_name
# pfazure run create --file run.yml --stream --name $run_name # automatic runtime
pfazure run stream --name $run_name
pfazure run show-details --name $run_name
pfazure run show-metrics --name $run_name
# (Optional) save previous run name into variable, and create a new random run name for further use
prev_run_name=$run_name
run_name="classification_accuracy_"$(openssl rand -hex 12)
# create evaluation run, --name is optional
pfazure run create --flow ../../evaluation/eval-classification-accuracy --data ./data.jsonl --column-mapping groundtruth='${data.answer}' prediction='${run.outputs.category}' --run $prev_run_name --runtime example-runtime-ci
pfazure run create --file run_evaluation.yml --run $prev_run_name --stream --name $run_name --runtime example-runtime-ci
pfazure run stream --name $run_name
pfazure run show --name $run_name
pfazure run show-details --name $run_name
pfazure run show-metrics --name $run_name
pfazure run visualize --name $run_name
``` | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/snapshot/flow.dag.yaml | inputs:
url:
type: string
default: https://play.google.com/store/apps/details?id=com.twitter.android
is_chat_input: false
outputs:
category:
type: string
reference: ${convert_to_dict.output.category}
evaluation_only: false
is_chat_output: false
evidence:
type: string
reference: ${convert_to_dict.output.evidence}
evaluation_only: false
is_chat_output: false
nodes:
- name: fetch_text_content_from_url
type: python
source:
type: code
path: fetch_text_content_from_url.py
inputs:
url: "${inputs.url}"
aggregation: false
- name: prepare_examples
type: python
source:
type: code
path: prepare_examples.py
inputs: {}
aggregation: false
- name: classify_with_llm
type: llm
source:
type: code
path: classify_with_llm.jinja2
inputs:
deployment_name: "gpt-35-turbo"
model: "gpt-3.5-turbo"
max_tokens: 128
temperature: 0.2
url: "${inputs.url}"
text_content: "${summarize_text_content.output}"
examples: "${prepare_examples.output}"
api: chat
connection: open_ai_connection
aggregation: false
- name: convert_to_dict
type: python
source:
type: code
path: convert_to_dict.py
inputs:
input_str: "${classify_with_llm.output}"
aggregation: false
- name: summarize_text_content
type: llm
source:
type: code
path: summarize_text_content.jinja2
inputs:
deployment_name: "gpt-35-turbo"
model: "gpt-3.5-turbo"
max_tokens: 128
temperature: 0.2
text: "${fetch_text_content_from_url.output}"
api: chat
connection: open_ai_connection
aggregation: false
environment:
python_requirements_txt: requirements.txt
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/snapshot/run_evaluation.yml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/Run.schema.json
flow: ../../evaluation/eval-classification-accuracy
data: data.jsonl
run: web_classification_variant_1_20230724_173442_973403 # replace with your run name
column_mapping:
groundtruth: ${data.answer}
prediction: ${run.outputs.category} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/snapshot/prepare_examples.py | from promptflow import tool
@tool
def prepare_examples():
return [
{
"url": "https://play.google.com/store/apps/details?id=com.spotify.music",
"text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and "
"original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. "
"It has a variety of features such as creating and sharing music playlists, discovering "
"new music, and listening to popular and exclusive podcasts. It also has a Premium "
"subscription option which allows users to download and listen offline, and access "
"ad-free music. It is available on all devices and has a variety of genres and artists "
"to choose from.",
"category": "App",
"evidence": "Both",
},
{
"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw",
"text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL "
"games on YouTube. It is available in 2023 and is subject to the terms and privacy policy "
"of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.",
"category": "Channel",
"evidence": "URL",
},
{
"url": "https://arxiv.org/abs/2303.04671",
"text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and "
"receiving not only languages but also images, providing complex visual questions or "
"visual editing instructions, and providing feedback and asking for corrected results. "
"It incorporates different Visual Foundation Models and is publicly available. Experiments "
"show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with "
"the help of Visual Foundation Models.",
"category": "Academic",
"evidence": "Text content",
},
{
"url": "https://ab.politiaromana.ro/",
"text_content": "There is no content available for this text.",
"category": "None",
"evidence": "None",
},
]
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/flow_artifacts/000000000_000000024.jsonl | {"line_number": 0, "run_info": {"run_id": "web_classification_variant_0_20231205_120253_104100_0", "status": "Completed", "error": null, "inputs": {"url": "https://www.youtube.com/watch?v=kYqRtjDBci8", "line_number": 0}, "output": {"category": "None", "evidence": "None"}, "metrics": null, "request": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100", "root_run_id": "web_classification_variant_0_20231205_120253_104100", "source_run_id": null, "flow_id": "default_flow_id", "start_time": "2023-12-05T04:03:25.562559Z", "end_time": "2023-12-05T04:03:27.343463Z", "index": 0, "api_calls": [{"name": "fetch_text_content_from_url", "type": "Tool", "inputs": {"url": "https://www.youtube.com/watch?v=kYqRtjDBci8"}, "output": "Amazing! The prompt flow in Azure AI speeds up the building of my LLM application. - YouTubeAboutPressCopyrightContact usCreatorsAdvertiseDevelopersTermsPrivacyPolicy & SafetyHow YouTube worksTest new featuresNFL Sunday Ticket\u00a9 2023 Google LLC", "start_time": 1701749005.566919, "end_time": 1701749006.619194, "error": null, "children": null, "node_name": "fetch_text_content_from_url"}, {"name": "prepare_examples", "type": "Tool", "inputs": {}, "output": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}], "start_time": 1701749005.568033, "end_time": 1701749005.572487, "error": null, "children": null, "node_name": "prepare_examples"}, {"name": "AzureOpenAI.chat", "type": "Tool", "inputs": {"prompt": "system:\nPlease summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text.\n\nuser:\nText: {{text}}\nSummary: ", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "text": "Amazing! The prompt flow in Azure AI speeds up the building of my LLM application. - YouTubeAboutPressCopyrightContact usCreatorsAdvertiseDevelopersTermsPrivacyPolicy & SafetyHow YouTube worksTest new featuresNFL Sunday Ticket\u00a9 2023 Google LLC"}, "output": "The author expresses their excitement about the prompt flow feature in Azure AI, which has helped them accelerate the development of their LLM application.", "start_time": 1701749006.622094, "end_time": 1701749006.993613, "error": null, "children": [{"name": "openai.api_resources.chat_completion.ChatCompletion.create", "type": "LLM", "inputs": {"api_base": "https://gpt-test-eus.openai.azure.com/", "api_type": "azure", "api_version": "2023-07-01-preview", "engine": "gpt-35-turbo", "messages": [{"role": "system", "content": "Please summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text."}, {"role": "user", "content": "Text: Amazing! The prompt flow in Azure AI speeds up the building of my LLM application. - YouTubeAboutPressCopyrightContact usCreatorsAdvertiseDevelopersTermsPrivacyPolicy & SafetyHow YouTube worksTest new featuresNFL Sunday Ticket\u00a9 2023 Google LLC\nSummary: "}], "temperature": 0.2, "top_p": 1.0, "n": 1, "stream": false, "stop": null, "max_tokens": 128, "presence_penalty": 0.0, "frequency_penalty": 0.0, "logit_bias": {}, "user": ""}, "output": {"id": "chatcmpl-8SGwYh2QixabybRzI9vKPfKwl9deg", "object": "chat.completion", "created": 1701749006, "model": "gpt-35-turbo", "prompt_filter_results": [{"prompt_index": 0, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "choices": [{"index": 0, "finish_reason": "stop", "message": {"role": "assistant", "content": "The author expresses their excitement about the prompt flow feature in Azure AI, which has helped them accelerate the development of their LLM application."}, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "usage": {"prompt_tokens": 92, "completion_tokens": 27, "total_tokens": 119}}, "start_time": 1701749006.627222, "end_time": 1701749006.993502, "error": null, "children": null, "node_name": null}], "node_name": "summarize_text_content"}, {"name": "AzureOpenAI.chat", "type": "Tool", "inputs": {"prompt": "system:\nYour task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both.\n\nuser:\nThe selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\n{% for ex in examples %}\nURL: {{ex.url}}\nText content: {{ex.text_content}}\nOUTPUT:\n{\"category\": \"{{ex.category}}\", \"evidence\": \"{{ex.evidence}}\"}\n\n{% endfor %}\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: {{url}}\nText content: {{text_content}}.\nOUTPUT:", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "url": "https://www.youtube.com/watch?v=kYqRtjDBci8", "text_content": "The author expresses their excitement about the prompt flow feature in Azure AI, which has helped them accelerate the development of their LLM application.", "examples": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}]}, "output": "{\"category\": \"None\", \"evidence\": \"None\"}", "start_time": 1701749006.996314, "end_time": 1701749007.334935, "error": null, "children": [{"name": "openai.api_resources.chat_completion.ChatCompletion.create", "type": "LLM", "inputs": {"api_base": "https://gpt-test-eus.openai.azure.com/", "api_type": "azure", "api_version": "2023-07-01-preview", "engine": "gpt-35-turbo", "messages": [{"role": "system", "content": "Your task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both."}, {"role": "user", "content": "The selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\nURL: https://play.google.com/store/apps/details?id=com.spotify.music\nText content: Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.\nOUTPUT:\n{\"category\": \"App\", \"evidence\": \"Both\"}\n\nURL: https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw\nText content: NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.\nOUTPUT:\n{\"category\": \"Channel\", \"evidence\": \"URL\"}\n\nURL: https://arxiv.org/abs/2303.04671\nText content: Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.\nOUTPUT:\n{\"category\": \"Academic\", \"evidence\": \"Text content\"}\n\nURL: https://ab.politiaromana.ro/\nText content: There is no content available for this text.\nOUTPUT:\n{\"category\": \"None\", \"evidence\": \"None\"}\n\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: https://www.youtube.com/watch?v=kYqRtjDBci8\nText content: The author expresses their excitement about the prompt flow feature in Azure AI, which has helped them accelerate the development of their LLM application..\nOUTPUT:"}], "temperature": 0.2, "top_p": 1.0, "n": 1, "stream": false, "stop": null, "max_tokens": 128, "presence_penalty": 0.0, "frequency_penalty": 0.0, "logit_bias": {}, "user": ""}, "output": {"id": "chatcmpl-8SGwZ2wUSr8u0pse8KUjbPgz08Cvt", "object": "chat.completion", "created": 1701749007, "model": "gpt-35-turbo", "prompt_filter_results": [{"prompt_index": 0, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "choices": [{"index": 0, "finish_reason": "stop", "message": {"role": "assistant", "content": "{\"category\": \"None\", \"evidence\": \"None\"}"}, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "usage": {"prompt_tokens": 596, "completion_tokens": 13, "total_tokens": 609}}, "start_time": 1701749006.99988, "end_time": 1701749007.33482, "error": null, "children": null, "node_name": null}], "node_name": "classify_with_llm"}, {"name": "convert_to_dict", "type": "Tool", "inputs": {"input_str": "{\"category\": \"None\", \"evidence\": \"None\"}"}, "output": {"category": "None", "evidence": "None"}, "start_time": 1701749007.337123, "end_time": 1701749007.3376, "error": null, "children": null, "node_name": "convert_to_dict"}], "variant_id": "", "name": "", "description": "", "tags": null, "system_metrics": {"duration": 1.780904, "total_tokens": 728}, "result": {"category": "None", "evidence": "None"}, "upload_metrics": false}, "start_time": "2023-12-05T04:03:25.562559", "end_time": "2023-12-05T04:03:27.343463", "name": "", "description": "", "status": "Completed", "tags": null}
{"line_number": 1, "run_info": {"run_id": "web_classification_variant_0_20231205_120253_104100_1", "status": "Completed", "error": null, "inputs": {"url": "https://arxiv.org/abs/2307.04767", "line_number": 1}, "output": {"category": "Academic", "evidence": "Both"}, "metrics": null, "request": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100", "root_run_id": "web_classification_variant_0_20231205_120253_104100", "source_run_id": null, "flow_id": "default_flow_id", "start_time": "2023-12-05T04:03:25.604746Z", "end_time": "2023-12-05T04:03:27.963985Z", "index": 1, "api_calls": [{"name": "fetch_text_content_from_url", "type": "Tool", "inputs": {"url": "https://arxiv.org/abs/2307.04767"}, "output": "\n\n\n [2307.04767] Semantic-SAM: Segment and Recognize Anything at Any Granularity\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\nSkip to main content\n\n\n\n\n\nWe gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate\n\n\n\n\n\n > cs > arXiv:2307.04767\n \n\n\n\n\n\nHelp | Advanced Search\n\n\n\n\nAll fields\nTitle\nAuthor\nAbstract\nComments\nJournal reference\nACM classification\nMSC classification\nReport number\narXiv identifier\nDOI\nORCID\narXiv author ID\nHelp pages\nFull text\n\n\n\n\nSearch\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nopen search\n\n\n\n\n\n\nGO\n\n\n\nopen navigation menu\n\n\nquick links\n\nLogin\nHelp Pages\nAbout\n\n\n\n\n\n\n\n\n\n\n\n\nComputer Science > Computer Vision and Pattern Recognition\n\n\narXiv:2307.04767 (cs)\n \n\n\n\n\n [Submitted on 10 Jul 2023]\nTitle:Semantic-SAM: Segment and Recognize Anything at Any Granularity\nAuthors:Feng Li, Hao Zhang, Peize Sun, Xueyan Zou, Shilong Liu, Jianwei Yang, Chunyuan Li, Lei Zhang, Jianfeng Gao Download a PDF of the paper titled Semantic-SAM: Segment and Recognize Anything at Any Granularity, by Feng Li and 8 other authors\nDownload PDF\n\nAbstract:In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity. Our model offers two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, we consolidate multiple datasets across three granularities and introduce decoupled classification for objects and parts. This allows our model to capture rich semantic information. For the multi-granularity capability, we propose a multi-choice learning scheme during training, enabling each click to generate masks at multiple levels that correspond to multiple ground-truth masks. Notably, this work represents the first attempt to jointly train a model on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate that our model successfully achieves semantic-awareness and granularity-abundance. Furthermore, co", "start_time": 1701749005.608924, "end_time": 1701749006.032803, "error": null, "children": null, "node_name": "fetch_text_content_from_url"}, {"name": "prepare_examples", "type": "Tool", "inputs": {}, "output": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}], "start_time": 1701749005.610052, "end_time": 1701749005.617312, "error": null, "children": null, "node_name": "prepare_examples"}, {"name": "AzureOpenAI.chat", "type": "Tool", "inputs": {"prompt": "system:\nPlease summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text.\n\nuser:\nText: {{text}}\nSummary: ", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "text": "\n\n\n [2307.04767] Semantic-SAM: Segment and Recognize Anything at Any Granularity\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\nSkip to main content\n\n\n\n\n\nWe gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate\n\n\n\n\n\n > cs > arXiv:2307.04767\n \n\n\n\n\n\nHelp | Advanced Search\n\n\n\n\nAll fields\nTitle\nAuthor\nAbstract\nComments\nJournal reference\nACM classification\nMSC classification\nReport number\narXiv identifier\nDOI\nORCID\narXiv author ID\nHelp pages\nFull text\n\n\n\n\nSearch\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nopen search\n\n\n\n\n\n\nGO\n\n\n\nopen navigation menu\n\n\nquick links\n\nLogin\nHelp Pages\nAbout\n\n\n\n\n\n\n\n\n\n\n\n\nComputer Science > Computer Vision and Pattern Recognition\n\n\narXiv:2307.04767 (cs)\n \n\n\n\n\n [Submitted on 10 Jul 2023]\nTitle:Semantic-SAM: Segment and Recognize Anything at Any Granularity\nAuthors:Feng Li, Hao Zhang, Peize Sun, Xueyan Zou, Shilong Liu, Jianwei Yang, Chunyuan Li, Lei Zhang, Jianfeng Gao Download a PDF of the paper titled Semantic-SAM: Segment and Recognize Anything at Any Granularity, by Feng Li and 8 other authors\nDownload PDF\n\nAbstract:In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity. Our model offers two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, we consolidate multiple datasets across three granularities and introduce decoupled classification for objects and parts. This allows our model to capture rich semantic information. For the multi-granularity capability, we propose a multi-choice learning scheme during training, enabling each click to generate masks at multiple levels that correspond to multiple ground-truth masks. Notably, this work represents the first attempt to jointly train a model on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate that our model successfully achieves semantic-awareness and granularity-abundance. Furthermore, co"}, "output": "The paper introduces Semantic-SAM, a universal image segmentation model that can segment and recognize objects at any desired granularity. The model has two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, the model consolidates multiple datasets and introduces decoupled classification for objects and parts. This allows the model to capture rich semantic information. For multi-granularity capability, a multi-choice learning scheme is proposed during training, generating masks at multiple levels. The model is trained on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate the success of the model in achieving semantic-awareness and", "start_time": 1701749006.035773, "end_time": 1701749007.668153, "error": null, "children": [{"name": "openai.api_resources.chat_completion.ChatCompletion.create", "type": "LLM", "inputs": {"api_base": "https://gpt-test-eus.openai.azure.com/", "api_type": "azure", "api_version": "2023-07-01-preview", "engine": "gpt-35-turbo", "messages": [{"role": "system", "content": "Please summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text."}, {"role": "user", "content": "Text: \n\n\n [2307.04767] Semantic-SAM: Segment and Recognize Anything at Any Granularity\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\nSkip to main content\n\n\n\n\n\nWe gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate\n\n\n\n\n\n > cs > arXiv:2307.04767\n \n\n\n\n\n\nHelp | Advanced Search\n\n\n\n\nAll fields\nTitle\nAuthor\nAbstract\nComments\nJournal reference\nACM classification\nMSC classification\nReport number\narXiv identifier\nDOI\nORCID\narXiv author ID\nHelp pages\nFull text\n\n\n\n\nSearch\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nopen search\n\n\n\n\n\n\nGO\n\n\n\nopen navigation menu\n\n\nquick links\n\nLogin\nHelp Pages\nAbout\n\n\n\n\n\n\n\n\n\n\n\n\nComputer Science > Computer Vision and Pattern Recognition\n\n\narXiv:2307.04767 (cs)\n \n\n\n\n\n [Submitted on 10 Jul 2023]\nTitle:Semantic-SAM: Segment and Recognize Anything at Any Granularity\nAuthors:Feng Li, Hao Zhang, Peize Sun, Xueyan Zou, Shilong Liu, Jianwei Yang, Chunyuan Li, Lei Zhang, Jianfeng Gao Download a PDF of the paper titled Semantic-SAM: Segment and Recognize Anything at Any Granularity, by Feng Li and 8 other authors\nDownload PDF\n\nAbstract:In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity. Our model offers two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, we consolidate multiple datasets across three granularities and introduce decoupled classification for objects and parts. This allows our model to capture rich semantic information. For the multi-granularity capability, we propose a multi-choice learning scheme during training, enabling each click to generate masks at multiple levels that correspond to multiple ground-truth masks. Notably, this work represents the first attempt to jointly train a model on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate that our model successfully achieves semantic-awareness and granularity-abundance. Furthermore, co\nSummary: "}], "temperature": 0.2, "top_p": 1.0, "n": 1, "stream": false, "stop": null, "max_tokens": 128, "presence_penalty": 0.0, "frequency_penalty": 0.0, "logit_bias": {}, "user": ""}, "output": {"id": "chatcmpl-8SGwY6eyhMgFtmIhNkFmO6e2awkvq", "object": "chat.completion", "created": 1701749006, "model": "gpt-35-turbo", "prompt_filter_results": [{"prompt_index": 0, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "choices": [{"index": 0, "finish_reason": "length", "message": {"role": "assistant", "content": "The paper introduces Semantic-SAM, a universal image segmentation model that can segment and recognize objects at any desired granularity. The model has two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, the model consolidates multiple datasets and introduces decoupled classification for objects and parts. This allows the model to capture rich semantic information. For multi-granularity capability, a multi-choice learning scheme is proposed during training, generating masks at multiple levels. The model is trained on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate the success of the model in achieving semantic-awareness and"}, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "usage": {"prompt_tokens": 468, "completion_tokens": 128, "total_tokens": 596}}, "start_time": 1701749006.052093, "end_time": 1701749007.668043, "error": null, "children": null, "node_name": null}], "node_name": "summarize_text_content"}, {"name": "AzureOpenAI.chat", "type": "Tool", "inputs": {"prompt": "system:\nYour task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both.\n\nuser:\nThe selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\n{% for ex in examples %}\nURL: {{ex.url}}\nText content: {{ex.text_content}}\nOUTPUT:\n{\"category\": \"{{ex.category}}\", \"evidence\": \"{{ex.evidence}}\"}\n\n{% endfor %}\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: {{url}}\nText content: {{text_content}}.\nOUTPUT:", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "url": "https://arxiv.org/abs/2307.04767", "text_content": "The paper introduces Semantic-SAM, a universal image segmentation model that can segment and recognize objects at any desired granularity. The model has two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, the model consolidates multiple datasets and introduces decoupled classification for objects and parts. This allows the model to capture rich semantic information. For multi-granularity capability, a multi-choice learning scheme is proposed during training, generating masks at multiple levels. The model is trained on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate the success of the model in achieving semantic-awareness and", "examples": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}]}, "output": "{\"category\": \"Academic\", \"evidence\": \"Both\"}", "start_time": 1701749007.670509, "end_time": 1701749007.956738, "error": null, "children": [{"name": "openai.api_resources.chat_completion.ChatCompletion.create", "type": "LLM", "inputs": {"api_base": "https://gpt-test-eus.openai.azure.com/", "api_type": "azure", "api_version": "2023-07-01-preview", "engine": "gpt-35-turbo", "messages": [{"role": "system", "content": "Your task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both."}, {"role": "user", "content": "The selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\nURL: https://play.google.com/store/apps/details?id=com.spotify.music\nText content: Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.\nOUTPUT:\n{\"category\": \"App\", \"evidence\": \"Both\"}\n\nURL: https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw\nText content: NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.\nOUTPUT:\n{\"category\": \"Channel\", \"evidence\": \"URL\"}\n\nURL: https://arxiv.org/abs/2303.04671\nText content: Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.\nOUTPUT:\n{\"category\": \"Academic\", \"evidence\": \"Text content\"}\n\nURL: https://ab.politiaromana.ro/\nText content: There is no content available for this text.\nOUTPUT:\n{\"category\": \"None\", \"evidence\": \"None\"}\n\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: https://arxiv.org/abs/2307.04767\nText content: The paper introduces Semantic-SAM, a universal image segmentation model that can segment and recognize objects at any desired granularity. The model has two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, the model consolidates multiple datasets and introduces decoupled classification for objects and parts. This allows the model to capture rich semantic information. For multi-granularity capability, a multi-choice learning scheme is proposed during training, generating masks at multiple levels. The model is trained on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate the success of the model in achieving semantic-awareness and.\nOUTPUT:"}], "temperature": 0.2, "top_p": 1.0, "n": 1, "stream": false, "stop": null, "max_tokens": 128, "presence_penalty": 0.0, "frequency_penalty": 0.0, "logit_bias": {}, "user": ""}, "output": {"id": "chatcmpl-8SGwZ8CajHzJc3UkbXeyX6MzNdFcD", "object": "chat.completion", "created": 1701749007, "model": "gpt-35-turbo", "prompt_filter_results": [{"prompt_index": 0, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "choices": [{"index": 0, "finish_reason": "stop", "message": {"role": "assistant", "content": "{\"category\": \"Academic\", \"evidence\": \"Both\"}"}, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "usage": {"prompt_tokens": 695, "completion_tokens": 14, "total_tokens": 709}}, "start_time": 1701749007.675928, "end_time": 1701749007.956625, "error": null, "children": null, "node_name": null}], "node_name": "classify_with_llm"}, {"name": "convert_to_dict", "type": "Tool", "inputs": {"input_str": "{\"category\": \"Academic\", \"evidence\": \"Both\"}"}, "output": {"category": "Academic", "evidence": "Both"}, "start_time": 1701749007.959116, "end_time": 1701749007.959648, "error": null, "children": null, "node_name": "convert_to_dict"}], "variant_id": "", "name": "", "description": "", "tags": null, "system_metrics": {"duration": 2.359239, "total_tokens": 1305}, "result": {"category": "Academic", "evidence": "Both"}, "upload_metrics": false}, "start_time": "2023-12-05T04:03:25.604746", "end_time": "2023-12-05T04:03:27.963985", "name": "", "description": "", "status": "Completed", "tags": null}
{"line_number": 2, "run_info": {"run_id": "web_classification_variant_0_20231205_120253_104100_2", "status": "Completed", "error": null, "inputs": {"url": "https://play.google.com/store/apps/details?id=com.twitter.android", "line_number": 2}, "output": {"category": "App", "evidence": "Both"}, "metrics": null, "request": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100", "root_run_id": "web_classification_variant_0_20231205_120253_104100", "source_run_id": null, "flow_id": "default_flow_id", "start_time": "2023-12-05T04:03:25.734275Z", "end_time": "2023-12-05T04:03:28.477166Z", "index": 2, "api_calls": [{"name": "fetch_text_content_from_url", "type": "Tool", "inputs": {"url": "https://play.google.com/store/apps/details?id=com.twitter.android"}, "output": "X - Apps on Google Playgoogle_logo PlayGamesAppsMovies & TVBooksKidsnonesearchhelp_outline Sign in with Googleplay_appsLibrary & devicespaymentPayments & subscriptionsreviewsMy Play activityredeemOffersPlay PasssettingsSettingsPrivacy Policy \u2022 Terms of ServiceGamesAppsMovies & TVBooksKidsXX Corp.Contains adsIn-app purchases3.8star21.5M reviews1B+DownloadsMature 17+infoInstallShareAdd to wishlistAbout this apparrow_forwardThe X app is the trusted global digital town square for everyone.With X, you can:- Post content for the world to see and join public conversations- Stay up to date on breaking news and follow your interests- Stay better informed with extra context from Community Notes- Go live with Spaces for audio or stream live video- Communicate privately with Direct Messages- Subscribe to X Premium to expand your reach, get a blue checkmark, and more- Earn a living creating exclusive content for your paid subscribers and share in the ad revenue generated in replies to your posts- Create and join Communities around topics and interests, from sports to music to technology- Upload and watch videos up to 3 hours in length- Write and read long form posts like essays and blogs- Connect directly with your customers to help your business growUpdated onDec 4, 2023#6 top grossing socialSocialData safetyarrow_forwardSafety starts with understanding how developers collect and share your data. Data privacy and security practices may vary based on your use, region, and age. The developer provided this information and may update it over time.No data shared with third partiesLearn more about how developers declare sharingThis app may collect these data typesLocation, Personal info and 9 othersData is encrypted in transitYou can request that data be deletedSee detailsRatings and reviewsRatings and reviews are verifiedinfo_outlinearrow_forwardRatings and reviews are verifiedinfo_outlinephone_androidPhonetablet_androidTabletwatchWatchlaptopChromebooktvTV3.820.8M reviews54321Alex S", "start_time": 1701749005.738373, "end_time": 1701749006.384366, "error": null, "children": null, "node_name": "fetch_text_content_from_url"}, {"name": "prepare_examples", "type": "Tool", "inputs": {}, "output": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}], "start_time": 1701749005.739604, "end_time": 1701749005.74123, "error": null, "children": null, "node_name": "prepare_examples"}, {"name": "AzureOpenAI.chat", "type": "Tool", "inputs": {"prompt": "system:\nPlease summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text.\n\nuser:\nText: {{text}}\nSummary: ", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "text": "X - Apps on Google Playgoogle_logo PlayGamesAppsMovies & TVBooksKidsnonesearchhelp_outline Sign in with Googleplay_appsLibrary & devicespaymentPayments & subscriptionsreviewsMy Play activityredeemOffersPlay PasssettingsSettingsPrivacy Policy \u2022 Terms of ServiceGamesAppsMovies & TVBooksKidsXX Corp.Contains adsIn-app purchases3.8star21.5M reviews1B+DownloadsMature 17+infoInstallShareAdd to wishlistAbout this apparrow_forwardThe X app is the trusted global digital town square for everyone.With X, you can:- Post content for the world to see and join public conversations- Stay up to date on breaking news and follow your interests- Stay better informed with extra context from Community Notes- Go live with Spaces for audio or stream live video- Communicate privately with Direct Messages- Subscribe to X Premium to expand your reach, get a blue checkmark, and more- Earn a living creating exclusive content for your paid subscribers and share in the ad revenue generated in replies to your posts- Create and join Communities around topics and interests, from sports to music to technology- Upload and watch videos up to 3 hours in length- Write and read long form posts like essays and blogs- Connect directly with your customers to help your business growUpdated onDec 4, 2023#6 top grossing socialSocialData safetyarrow_forwardSafety starts with understanding how developers collect and share your data. Data privacy and security practices may vary based on your use, region, and age. The developer provided this information and may update it over time.No data shared with third partiesLearn more about how developers declare sharingThis app may collect these data typesLocation, Personal info and 9 othersData is encrypted in transitYou can request that data be deletedSee detailsRatings and reviewsRatings and reviews are verifiedinfo_outlinearrow_forwardRatings and reviews are verifiedinfo_outlinephone_androidPhonetablet_androidTabletwatchWatchlaptopChromebooktvTV3.820.8M reviews54321Alex S"}, "output": "The X app is a global digital platform where users can post content, join public conversations, stay updated on breaking news, and follow their interests. It offers features such as Community Notes for extra context, Spaces for live audio or video streaming, Direct Messages for private communication, and the option to subscribe to X Premium for expanded reach and exclusive content creation. Users can also create and join Communities, upload and watch videos, and write and read long-form posts. The app prioritizes data safety and allows users to request data deletion. It has a rating of 3.8 stars based on 21.5 million reviews and has been downloaded over", "start_time": 1701749006.386894, "end_time": 1701749008.123235, "error": null, "children": [{"name": "openai.api_resources.chat_completion.ChatCompletion.create", "type": "LLM", "inputs": {"api_base": "https://gpt-test-eus.openai.azure.com/", "api_type": "azure", "api_version": "2023-07-01-preview", "engine": "gpt-35-turbo", "messages": [{"role": "system", "content": "Please summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text."}, {"role": "user", "content": "Text: X - Apps on Google Playgoogle_logo PlayGamesAppsMovies & TVBooksKidsnonesearchhelp_outline Sign in with Googleplay_appsLibrary & devicespaymentPayments & subscriptionsreviewsMy Play activityredeemOffersPlay PasssettingsSettingsPrivacy Policy \u2022 Terms of ServiceGamesAppsMovies & TVBooksKidsXX Corp.Contains adsIn-app purchases3.8star21.5M reviews1B+DownloadsMature 17+infoInstallShareAdd to wishlistAbout this apparrow_forwardThe X app is the trusted global digital town square for everyone.With X, you can:- Post content for the world to see and join public conversations- Stay up to date on breaking news and follow your interests- Stay better informed with extra context from Community Notes- Go live with Spaces for audio or stream live video- Communicate privately with Direct Messages- Subscribe to X Premium to expand your reach, get a blue checkmark, and more- Earn a living creating exclusive content for your paid subscribers and share in the ad revenue generated in replies to your posts- Create and join Communities around topics and interests, from sports to music to technology- Upload and watch videos up to 3 hours in length- Write and read long form posts like essays and blogs- Connect directly with your customers to help your business growUpdated onDec 4, 2023#6 top grossing socialSocialData safetyarrow_forwardSafety starts with understanding how developers collect and share your data. Data privacy and security practices may vary based on your use, region, and age. The developer provided this information and may update it over time.No data shared with third partiesLearn more about how developers declare sharingThis app may collect these data typesLocation, Personal info and 9 othersData is encrypted in transitYou can request that data be deletedSee detailsRatings and reviewsRatings and reviews are verifiedinfo_outlinearrow_forwardRatings and reviews are verifiedinfo_outlinephone_androidPhonetablet_androidTabletwatchWatchlaptopChromebooktvTV3.820.8M reviews54321Alex S\nSummary: "}], "temperature": 0.2, "top_p": 1.0, "n": 1, "stream": false, "stop": null, "max_tokens": 128, "presence_penalty": 0.0, "frequency_penalty": 0.0, "logit_bias": {}, "user": ""}, "output": {"id": "chatcmpl-8SGwYyQcqIQLNvDERxnNkJ8Tv4wIf", "object": "chat.completion", "created": 1701749006, "model": "gpt-35-turbo", "prompt_filter_results": [{"prompt_index": 0, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "choices": [{"index": 0, "finish_reason": "length", "message": {"role": "assistant", "content": "The X app is a global digital platform where users can post content, join public conversations, stay updated on breaking news, and follow their interests. It offers features such as Community Notes for extra context, Spaces for live audio or video streaming, Direct Messages for private communication, and the option to subscribe to X Premium for expanded reach and exclusive content creation. Users can also create and join Communities, upload and watch videos, and write and read long-form posts. The app prioritizes data safety and allows users to request data deletion. It has a rating of 3.8 stars based on 21.5 million reviews and has been downloaded over"}, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "usage": {"prompt_tokens": 448, "completion_tokens": 128, "total_tokens": 576}}, "start_time": 1701749006.391002, "end_time": 1701749008.123107, "error": null, "children": null, "node_name": null}], "node_name": "summarize_text_content"}, {"name": "AzureOpenAI.chat", "type": "Tool", "inputs": {"prompt": "system:\nYour task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both.\n\nuser:\nThe selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\n{% for ex in examples %}\nURL: {{ex.url}}\nText content: {{ex.text_content}}\nOUTPUT:\n{\"category\": \"{{ex.category}}\", \"evidence\": \"{{ex.evidence}}\"}\n\n{% endfor %}\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: {{url}}\nText content: {{text_content}}.\nOUTPUT:", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "url": "https://play.google.com/store/apps/details?id=com.twitter.android", "text_content": "The X app is a global digital platform where users can post content, join public conversations, stay updated on breaking news, and follow their interests. It offers features such as Community Notes for extra context, Spaces for live audio or video streaming, Direct Messages for private communication, and the option to subscribe to X Premium for expanded reach and exclusive content creation. Users can also create and join Communities, upload and watch videos, and write and read long-form posts. The app prioritizes data safety and allows users to request data deletion. It has a rating of 3.8 stars based on 21.5 million reviews and has been downloaded over", "examples": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}]}, "output": "{\"category\": \"App\", \"evidence\": \"Both\"}", "start_time": 1701749008.126513, "end_time": 1701749008.469702, "error": null, "children": [{"name": "openai.api_resources.chat_completion.ChatCompletion.create", "type": "LLM", "inputs": {"api_base": "https://gpt-test-eus.openai.azure.com/", "api_type": "azure", "api_version": "2023-07-01-preview", "engine": "gpt-35-turbo", "messages": [{"role": "system", "content": "Your task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both."}, {"role": "user", "content": "The selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\nURL: https://play.google.com/store/apps/details?id=com.spotify.music\nText content: Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.\nOUTPUT:\n{\"category\": \"App\", \"evidence\": \"Both\"}\n\nURL: https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw\nText content: NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.\nOUTPUT:\n{\"category\": \"Channel\", \"evidence\": \"URL\"}\n\nURL: https://arxiv.org/abs/2303.04671\nText content: Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.\nOUTPUT:\n{\"category\": \"Academic\", \"evidence\": \"Text content\"}\n\nURL: https://ab.politiaromana.ro/\nText content: There is no content available for this text.\nOUTPUT:\n{\"category\": \"None\", \"evidence\": \"None\"}\n\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: https://play.google.com/store/apps/details?id=com.twitter.android\nText content: The X app is a global digital platform where users can post content, join public conversations, stay updated on breaking news, and follow their interests. It offers features such as Community Notes for extra context, Spaces for live audio or video streaming, Direct Messages for private communication, and the option to subscribe to X Premium for expanded reach and exclusive content creation. Users can also create and join Communities, upload and watch videos, and write and read long-form posts. The app prioritizes data safety and allows users to request data deletion. It has a rating of 3.8 stars based on 21.5 million reviews and has been downloaded over.\nOUTPUT:"}], "temperature": 0.2, "top_p": 1.0, "n": 1, "stream": false, "stop": null, "max_tokens": 128, "presence_penalty": 0.0, "frequency_penalty": 0.0, "logit_bias": {}, "user": ""}, "output": {"id": "chatcmpl-8SGwaHVVKGYxKtoLEQKFdvAmblBBc", "object": "chat.completion", "created": 1701749008, "model": "gpt-35-turbo", "prompt_filter_results": [{"prompt_index": 0, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "choices": [{"index": 0, "finish_reason": "stop", "message": {"role": "assistant", "content": "{\"category\": \"App\", \"evidence\": \"Both\"}"}, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "usage": {"prompt_tokens": 694, "completion_tokens": 13, "total_tokens": 707}}, "start_time": 1701749008.130586, "end_time": 1701749008.469585, "error": null, "children": null, "node_name": null}], "node_name": "classify_with_llm"}, {"name": "convert_to_dict", "type": "Tool", "inputs": {"input_str": "{\"category\": \"App\", \"evidence\": \"Both\"}"}, "output": {"category": "App", "evidence": "Both"}, "start_time": 1701749008.472326, "end_time": 1701749008.472859, "error": null, "children": null, "node_name": "convert_to_dict"}], "variant_id": "", "name": "", "description": "", "tags": null, "system_metrics": {"duration": 2.742891, "total_tokens": 1283}, "result": {"category": "App", "evidence": "Both"}, "upload_metrics": false}, "start_time": "2023-12-05T04:03:25.734275", "end_time": "2023-12-05T04:03:28.477166", "name": "", "description": "", "status": "Completed", "tags": null}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/flow_outputs/output.jsonl | {"line_number": 0, "category": "None", "evidence": "None"}
{"line_number": 1, "category": "Academic", "evidence": "Both"}
{"line_number": 2, "category": "App", "evidence": "Both"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/fetch_text_content_from_url/000000001.jsonl | {"node_name": "fetch_text_content_from_url", "line_number": 1, "run_info": {"node": "fetch_text_content_from_url", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_fetch_text_content_from_url_1", "status": "Completed", "inputs": {"url": "https://arxiv.org/abs/2307.04767"}, "output": "\n\n\n [2307.04767] Semantic-SAM: Segment and Recognize Anything at Any Granularity\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\nSkip to main content\n\n\n\n\n\nWe gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate\n\n\n\n\n\n > cs > arXiv:2307.04767\n \n\n\n\n\n\nHelp | Advanced Search\n\n\n\n\nAll fields\nTitle\nAuthor\nAbstract\nComments\nJournal reference\nACM classification\nMSC classification\nReport number\narXiv identifier\nDOI\nORCID\narXiv author ID\nHelp pages\nFull text\n\n\n\n\nSearch\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nopen search\n\n\n\n\n\n\nGO\n\n\n\nopen navigation menu\n\n\nquick links\n\nLogin\nHelp Pages\nAbout\n\n\n\n\n\n\n\n\n\n\n\n\nComputer Science > Computer Vision and Pattern Recognition\n\n\narXiv:2307.04767 (cs)\n \n\n\n\n\n [Submitted on 10 Jul 2023]\nTitle:Semantic-SAM: Segment and Recognize Anything at Any Granularity\nAuthors:Feng Li, Hao Zhang, Peize Sun, Xueyan Zou, Shilong Liu, Jianwei Yang, Chunyuan Li, Lei Zhang, Jianfeng Gao Download a PDF of the paper titled Semantic-SAM: Segment and Recognize Anything at Any Granularity, by Feng Li and 8 other authors\nDownload PDF\n\nAbstract:In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity. Our model offers two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, we consolidate multiple datasets across three granularities and introduce decoupled classification for objects and parts. This allows our model to capture rich semantic information. For the multi-granularity capability, we propose a multi-choice learning scheme during training, enabling each click to generate masks at multiple levels that correspond to multiple ground-truth masks. Notably, this work represents the first attempt to jointly train a model on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate that our model successfully achieves semantic-awareness and granularity-abundance. Furthermore, co", "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_1", "start_time": "2023-12-05T04:03:25.608387Z", "end_time": "2023-12-05T04:03:26.033037Z", "index": 1, "api_calls": [{"name": "fetch_text_content_from_url", "type": "Tool", "inputs": {"url": "https://arxiv.org/abs/2307.04767"}, "output": "\n\n\n [2307.04767] Semantic-SAM: Segment and Recognize Anything at Any Granularity\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\nSkip to main content\n\n\n\n\n\nWe gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate\n\n\n\n\n\n > cs > arXiv:2307.04767\n \n\n\n\n\n\nHelp | Advanced Search\n\n\n\n\nAll fields\nTitle\nAuthor\nAbstract\nComments\nJournal reference\nACM classification\nMSC classification\nReport number\narXiv identifier\nDOI\nORCID\narXiv author ID\nHelp pages\nFull text\n\n\n\n\nSearch\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nopen search\n\n\n\n\n\n\nGO\n\n\n\nopen navigation menu\n\n\nquick links\n\nLogin\nHelp Pages\nAbout\n\n\n\n\n\n\n\n\n\n\n\n\nComputer Science > Computer Vision and Pattern Recognition\n\n\narXiv:2307.04767 (cs)\n \n\n\n\n\n [Submitted on 10 Jul 2023]\nTitle:Semantic-SAM: Segment and Recognize Anything at Any Granularity\nAuthors:Feng Li, Hao Zhang, Peize Sun, Xueyan Zou, Shilong Liu, Jianwei Yang, Chunyuan Li, Lei Zhang, Jianfeng Gao Download a PDF of the paper titled Semantic-SAM: Segment and Recognize Anything at Any Granularity, by Feng Li and 8 other authors\nDownload PDF\n\nAbstract:In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity. Our model offers two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, we consolidate multiple datasets across three granularities and introduce decoupled classification for objects and parts. This allows our model to capture rich semantic information. For the multi-granularity capability, we propose a multi-choice learning scheme during training, enabling each click to generate masks at multiple levels that correspond to multiple ground-truth masks. Notably, this work represents the first attempt to jointly train a model on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate that our model successfully achieves semantic-awareness and granularity-abundance. Furthermore, co", "start_time": 1701749005.608924, "end_time": 1701749006.032803, "error": null, "children": null, "node_name": "fetch_text_content_from_url"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"duration": 0.42465}, "result": "\n\n\n [2307.04767] Semantic-SAM: Segment and Recognize Anything at Any Granularity\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\nSkip to main content\n\n\n\n\n\nWe gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate\n\n\n\n\n\n > cs > arXiv:2307.04767\n \n\n\n\n\n\nHelp | Advanced Search\n\n\n\n\nAll fields\nTitle\nAuthor\nAbstract\nComments\nJournal reference\nACM classification\nMSC classification\nReport number\narXiv identifier\nDOI\nORCID\narXiv author ID\nHelp pages\nFull text\n\n\n\n\nSearch\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nopen search\n\n\n\n\n\n\nGO\n\n\n\nopen navigation menu\n\n\nquick links\n\nLogin\nHelp Pages\nAbout\n\n\n\n\n\n\n\n\n\n\n\n\nComputer Science > Computer Vision and Pattern Recognition\n\n\narXiv:2307.04767 (cs)\n \n\n\n\n\n [Submitted on 10 Jul 2023]\nTitle:Semantic-SAM: Segment and Recognize Anything at Any Granularity\nAuthors:Feng Li, Hao Zhang, Peize Sun, Xueyan Zou, Shilong Liu, Jianwei Yang, Chunyuan Li, Lei Zhang, Jianfeng Gao Download a PDF of the paper titled Semantic-SAM: Segment and Recognize Anything at Any Granularity, by Feng Li and 8 other authors\nDownload PDF\n\nAbstract:In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity. Our model offers two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, we consolidate multiple datasets across three granularities and introduce decoupled classification for objects and parts. This allows our model to capture rich semantic information. For the multi-granularity capability, we propose a multi-choice learning scheme during training, enabling each click to generate masks at multiple levels that correspond to multiple ground-truth masks. Notably, this work represents the first attempt to jointly train a model on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate that our model successfully achieves semantic-awareness and granularity-abundance. Furthermore, co"}, "start_time": "2023-12-05T04:03:25.608387", "end_time": "2023-12-05T04:03:26.033037", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/fetch_text_content_from_url/000000000.jsonl | {"node_name": "fetch_text_content_from_url", "line_number": 0, "run_info": {"node": "fetch_text_content_from_url", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_fetch_text_content_from_url_0", "status": "Completed", "inputs": {"url": "https://www.youtube.com/watch?v=kYqRtjDBci8"}, "output": "Amazing! The prompt flow in Azure AI speeds up the building of my LLM application. - YouTubeAboutPressCopyrightContact usCreatorsAdvertiseDevelopersTermsPrivacyPolicy & SafetyHow YouTube worksTest new featuresNFL Sunday Ticket\u00a9 2023 Google LLC", "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_0", "start_time": "2023-12-05T04:03:25.566290Z", "end_time": "2023-12-05T04:03:26.619414Z", "index": 0, "api_calls": [{"name": "fetch_text_content_from_url", "type": "Tool", "inputs": {"url": "https://www.youtube.com/watch?v=kYqRtjDBci8"}, "output": "Amazing! The prompt flow in Azure AI speeds up the building of my LLM application. - YouTubeAboutPressCopyrightContact usCreatorsAdvertiseDevelopersTermsPrivacyPolicy & SafetyHow YouTube worksTest new featuresNFL Sunday Ticket\u00a9 2023 Google LLC", "start_time": 1701749005.566919, "end_time": 1701749006.619194, "error": null, "children": null, "node_name": "fetch_text_content_from_url"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"duration": 1.053124}, "result": "Amazing! The prompt flow in Azure AI speeds up the building of my LLM application. - YouTubeAboutPressCopyrightContact usCreatorsAdvertiseDevelopersTermsPrivacyPolicy & SafetyHow YouTube worksTest new featuresNFL Sunday Ticket\u00a9 2023 Google LLC"}, "start_time": "2023-12-05T04:03:25.566290", "end_time": "2023-12-05T04:03:26.619414", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/fetch_text_content_from_url/000000002.jsonl | {"node_name": "fetch_text_content_from_url", "line_number": 2, "run_info": {"node": "fetch_text_content_from_url", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_fetch_text_content_from_url_2", "status": "Completed", "inputs": {"url": "https://play.google.com/store/apps/details?id=com.twitter.android"}, "output": "X - Apps on Google Playgoogle_logo PlayGamesAppsMovies & TVBooksKidsnonesearchhelp_outline Sign in with Googleplay_appsLibrary & devicespaymentPayments & subscriptionsreviewsMy Play activityredeemOffersPlay PasssettingsSettingsPrivacy Policy \u2022 Terms of ServiceGamesAppsMovies & TVBooksKidsXX Corp.Contains adsIn-app purchases3.8star21.5M reviews1B+DownloadsMature 17+infoInstallShareAdd to wishlistAbout this apparrow_forwardThe X app is the trusted global digital town square for everyone.With X, you can:- Post content for the world to see and join public conversations- Stay up to date on breaking news and follow your interests- Stay better informed with extra context from Community Notes- Go live with Spaces for audio or stream live video- Communicate privately with Direct Messages- Subscribe to X Premium to expand your reach, get a blue checkmark, and more- Earn a living creating exclusive content for your paid subscribers and share in the ad revenue generated in replies to your posts- Create and join Communities around topics and interests, from sports to music to technology- Upload and watch videos up to 3 hours in length- Write and read long form posts like essays and blogs- Connect directly with your customers to help your business growUpdated onDec 4, 2023#6 top grossing socialSocialData safetyarrow_forwardSafety starts with understanding how developers collect and share your data. Data privacy and security practices may vary based on your use, region, and age. The developer provided this information and may update it over time.No data shared with third partiesLearn more about how developers declare sharingThis app may collect these data typesLocation, Personal info and 9 othersData is encrypted in transitYou can request that data be deletedSee detailsRatings and reviewsRatings and reviews are verifiedinfo_outlinearrow_forwardRatings and reviews are verifiedinfo_outlinephone_androidPhonetablet_androidTabletwatchWatchlaptopChromebooktvTV3.820.8M reviews54321Alex S", "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_2", "start_time": "2023-12-05T04:03:25.737699Z", "end_time": "2023-12-05T04:03:26.384654Z", "index": 2, "api_calls": [{"name": "fetch_text_content_from_url", "type": "Tool", "inputs": {"url": "https://play.google.com/store/apps/details?id=com.twitter.android"}, "output": "X - Apps on Google Playgoogle_logo PlayGamesAppsMovies & TVBooksKidsnonesearchhelp_outline Sign in with Googleplay_appsLibrary & devicespaymentPayments & subscriptionsreviewsMy Play activityredeemOffersPlay PasssettingsSettingsPrivacy Policy \u2022 Terms of ServiceGamesAppsMovies & TVBooksKidsXX Corp.Contains adsIn-app purchases3.8star21.5M reviews1B+DownloadsMature 17+infoInstallShareAdd to wishlistAbout this apparrow_forwardThe X app is the trusted global digital town square for everyone.With X, you can:- Post content for the world to see and join public conversations- Stay up to date on breaking news and follow your interests- Stay better informed with extra context from Community Notes- Go live with Spaces for audio or stream live video- Communicate privately with Direct Messages- Subscribe to X Premium to expand your reach, get a blue checkmark, and more- Earn a living creating exclusive content for your paid subscribers and share in the ad revenue generated in replies to your posts- Create and join Communities around topics and interests, from sports to music to technology- Upload and watch videos up to 3 hours in length- Write and read long form posts like essays and blogs- Connect directly with your customers to help your business growUpdated onDec 4, 2023#6 top grossing socialSocialData safetyarrow_forwardSafety starts with understanding how developers collect and share your data. Data privacy and security practices may vary based on your use, region, and age. The developer provided this information and may update it over time.No data shared with third partiesLearn more about how developers declare sharingThis app may collect these data typesLocation, Personal info and 9 othersData is encrypted in transitYou can request that data be deletedSee detailsRatings and reviewsRatings and reviews are verifiedinfo_outlinearrow_forwardRatings and reviews are verifiedinfo_outlinephone_androidPhonetablet_androidTabletwatchWatchlaptopChromebooktvTV3.820.8M reviews54321Alex S", "start_time": 1701749005.738373, "end_time": 1701749006.384366, "error": null, "children": null, "node_name": "fetch_text_content_from_url"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"duration": 0.646955}, "result": "X - Apps on Google Playgoogle_logo PlayGamesAppsMovies & TVBooksKidsnonesearchhelp_outline Sign in with Googleplay_appsLibrary & devicespaymentPayments & subscriptionsreviewsMy Play activityredeemOffersPlay PasssettingsSettingsPrivacy Policy \u2022 Terms of ServiceGamesAppsMovies & TVBooksKidsXX Corp.Contains adsIn-app purchases3.8star21.5M reviews1B+DownloadsMature 17+infoInstallShareAdd to wishlistAbout this apparrow_forwardThe X app is the trusted global digital town square for everyone.With X, you can:- Post content for the world to see and join public conversations- Stay up to date on breaking news and follow your interests- Stay better informed with extra context from Community Notes- Go live with Spaces for audio or stream live video- Communicate privately with Direct Messages- Subscribe to X Premium to expand your reach, get a blue checkmark, and more- Earn a living creating exclusive content for your paid subscribers and share in the ad revenue generated in replies to your posts- Create and join Communities around topics and interests, from sports to music to technology- Upload and watch videos up to 3 hours in length- Write and read long form posts like essays and blogs- Connect directly with your customers to help your business growUpdated onDec 4, 2023#6 top grossing socialSocialData safetyarrow_forwardSafety starts with understanding how developers collect and share your data. Data privacy and security practices may vary based on your use, region, and age. The developer provided this information and may update it over time.No data shared with third partiesLearn more about how developers declare sharingThis app may collect these data typesLocation, Personal info and 9 othersData is encrypted in transitYou can request that data be deletedSee detailsRatings and reviewsRatings and reviews are verifiedinfo_outlinearrow_forwardRatings and reviews are verifiedinfo_outlinephone_androidPhonetablet_androidTabletwatchWatchlaptopChromebooktvTV3.820.8M reviews54321Alex S"}, "start_time": "2023-12-05T04:03:25.737699", "end_time": "2023-12-05T04:03:26.384654", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/classify_with_llm/000000001.jsonl | {"node_name": "classify_with_llm", "line_number": 1, "run_info": {"node": "classify_with_llm", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_classify_with_llm_1", "status": "Completed", "inputs": {"prompt": "system:\nYour task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both.\n\nuser:\nThe selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\n{% for ex in examples %}\nURL: {{ex.url}}\nText content: {{ex.text_content}}\nOUTPUT:\n{\"category\": \"{{ex.category}}\", \"evidence\": \"{{ex.evidence}}\"}\n\n{% endfor %}\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: {{url}}\nText content: {{text_content}}.\nOUTPUT:", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "url": "https://arxiv.org/abs/2307.04767", "text_content": "The paper introduces Semantic-SAM, a universal image segmentation model that can segment and recognize objects at any desired granularity. The model has two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, the model consolidates multiple datasets and introduces decoupled classification for objects and parts. This allows the model to capture rich semantic information. For multi-granularity capability, a multi-choice learning scheme is proposed during training, generating masks at multiple levels. The model is trained on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate the success of the model in achieving semantic-awareness and", "examples": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}]}, "output": "{\"category\": \"Academic\", \"evidence\": \"Both\"}", "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_1", "start_time": "2023-12-05T04:03:27.670281Z", "end_time": "2023-12-05T04:03:27.957477Z", "index": 1, "api_calls": [{"name": "AzureOpenAI.chat", "type": "Tool", "inputs": {"prompt": "system:\nYour task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both.\n\nuser:\nThe selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\n{% for ex in examples %}\nURL: {{ex.url}}\nText content: {{ex.text_content}}\nOUTPUT:\n{\"category\": \"{{ex.category}}\", \"evidence\": \"{{ex.evidence}}\"}\n\n{% endfor %}\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: {{url}}\nText content: {{text_content}}.\nOUTPUT:", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "url": "https://arxiv.org/abs/2307.04767", "text_content": "The paper introduces Semantic-SAM, a universal image segmentation model that can segment and recognize objects at any desired granularity. The model has two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, the model consolidates multiple datasets and introduces decoupled classification for objects and parts. This allows the model to capture rich semantic information. For multi-granularity capability, a multi-choice learning scheme is proposed during training, generating masks at multiple levels. The model is trained on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate the success of the model in achieving semantic-awareness and", "examples": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}]}, "output": "{\"category\": \"Academic\", \"evidence\": \"Both\"}", "start_time": 1701749007.670509, "end_time": 1701749007.956738, "error": null, "children": [{"name": "openai.api_resources.chat_completion.ChatCompletion.create", "type": "LLM", "inputs": {"api_base": "https://gpt-test-eus.openai.azure.com/", "api_type": "azure", "api_version": "2023-07-01-preview", "engine": "gpt-35-turbo", "messages": [{"role": "system", "content": "Your task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both."}, {"role": "user", "content": "The selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\nURL: https://play.google.com/store/apps/details?id=com.spotify.music\nText content: Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.\nOUTPUT:\n{\"category\": \"App\", \"evidence\": \"Both\"}\n\nURL: https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw\nText content: NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.\nOUTPUT:\n{\"category\": \"Channel\", \"evidence\": \"URL\"}\n\nURL: https://arxiv.org/abs/2303.04671\nText content: Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.\nOUTPUT:\n{\"category\": \"Academic\", \"evidence\": \"Text content\"}\n\nURL: https://ab.politiaromana.ro/\nText content: There is no content available for this text.\nOUTPUT:\n{\"category\": \"None\", \"evidence\": \"None\"}\n\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: https://arxiv.org/abs/2307.04767\nText content: The paper introduces Semantic-SAM, a universal image segmentation model that can segment and recognize objects at any desired granularity. The model has two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, the model consolidates multiple datasets and introduces decoupled classification for objects and parts. This allows the model to capture rich semantic information. For multi-granularity capability, a multi-choice learning scheme is proposed during training, generating masks at multiple levels. The model is trained on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate the success of the model in achieving semantic-awareness and.\nOUTPUT:"}], "temperature": 0.2, "top_p": 1.0, "n": 1, "stream": false, "stop": null, "max_tokens": 128, "presence_penalty": 0.0, "frequency_penalty": 0.0, "logit_bias": {}, "user": ""}, "output": {"id": "chatcmpl-8SGwZ8CajHzJc3UkbXeyX6MzNdFcD", "object": "chat.completion", "created": 1701749007, "model": "gpt-35-turbo", "prompt_filter_results": [{"prompt_index": 0, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "choices": [{"index": 0, "finish_reason": "stop", "message": {"role": "assistant", "content": "{\"category\": \"Academic\", \"evidence\": \"Both\"}"}, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "usage": {"prompt_tokens": 695, "completion_tokens": 14, "total_tokens": 709}}, "start_time": 1701749007.675928, "end_time": 1701749007.956625, "error": null, "children": null, "node_name": null}], "node_name": "classify_with_llm"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"prompt_tokens": 695, "completion_tokens": 14, "total_tokens": 709, "duration": 0.287196}, "result": "{\"category\": \"Academic\", \"evidence\": \"Both\"}"}, "start_time": "2023-12-05T04:03:27.670281", "end_time": "2023-12-05T04:03:27.957477", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/classify_with_llm/000000000.jsonl | {"node_name": "classify_with_llm", "line_number": 0, "run_info": {"node": "classify_with_llm", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_classify_with_llm_0", "status": "Completed", "inputs": {"prompt": "system:\nYour task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both.\n\nuser:\nThe selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\n{% for ex in examples %}\nURL: {{ex.url}}\nText content: {{ex.text_content}}\nOUTPUT:\n{\"category\": \"{{ex.category}}\", \"evidence\": \"{{ex.evidence}}\"}\n\n{% endfor %}\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: {{url}}\nText content: {{text_content}}.\nOUTPUT:", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "url": "https://www.youtube.com/watch?v=kYqRtjDBci8", "text_content": "The author expresses their excitement about the prompt flow feature in Azure AI, which has helped them accelerate the development of their LLM application.", "examples": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}]}, "output": "{\"category\": \"None\", \"evidence\": \"None\"}", "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_0", "start_time": "2023-12-05T04:03:26.996107Z", "end_time": "2023-12-05T04:03:27.335701Z", "index": 0, "api_calls": [{"name": "AzureOpenAI.chat", "type": "Tool", "inputs": {"prompt": "system:\nYour task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both.\n\nuser:\nThe selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\n{% for ex in examples %}\nURL: {{ex.url}}\nText content: {{ex.text_content}}\nOUTPUT:\n{\"category\": \"{{ex.category}}\", \"evidence\": \"{{ex.evidence}}\"}\n\n{% endfor %}\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: {{url}}\nText content: {{text_content}}.\nOUTPUT:", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "url": "https://www.youtube.com/watch?v=kYqRtjDBci8", "text_content": "The author expresses their excitement about the prompt flow feature in Azure AI, which has helped them accelerate the development of their LLM application.", "examples": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}]}, "output": "{\"category\": \"None\", \"evidence\": \"None\"}", "start_time": 1701749006.996314, "end_time": 1701749007.334935, "error": null, "children": [{"name": "openai.api_resources.chat_completion.ChatCompletion.create", "type": "LLM", "inputs": {"api_base": "https://gpt-test-eus.openai.azure.com/", "api_type": "azure", "api_version": "2023-07-01-preview", "engine": "gpt-35-turbo", "messages": [{"role": "system", "content": "Your task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both."}, {"role": "user", "content": "The selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\nURL: https://play.google.com/store/apps/details?id=com.spotify.music\nText content: Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.\nOUTPUT:\n{\"category\": \"App\", \"evidence\": \"Both\"}\n\nURL: https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw\nText content: NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.\nOUTPUT:\n{\"category\": \"Channel\", \"evidence\": \"URL\"}\n\nURL: https://arxiv.org/abs/2303.04671\nText content: Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.\nOUTPUT:\n{\"category\": \"Academic\", \"evidence\": \"Text content\"}\n\nURL: https://ab.politiaromana.ro/\nText content: There is no content available for this text.\nOUTPUT:\n{\"category\": \"None\", \"evidence\": \"None\"}\n\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: https://www.youtube.com/watch?v=kYqRtjDBci8\nText content: The author expresses their excitement about the prompt flow feature in Azure AI, which has helped them accelerate the development of their LLM application..\nOUTPUT:"}], "temperature": 0.2, "top_p": 1.0, "n": 1, "stream": false, "stop": null, "max_tokens": 128, "presence_penalty": 0.0, "frequency_penalty": 0.0, "logit_bias": {}, "user": ""}, "output": {"id": "chatcmpl-8SGwZ2wUSr8u0pse8KUjbPgz08Cvt", "object": "chat.completion", "created": 1701749007, "model": "gpt-35-turbo", "prompt_filter_results": [{"prompt_index": 0, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "choices": [{"index": 0, "finish_reason": "stop", "message": {"role": "assistant", "content": "{\"category\": \"None\", \"evidence\": \"None\"}"}, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "usage": {"prompt_tokens": 596, "completion_tokens": 13, "total_tokens": 609}}, "start_time": 1701749006.99988, "end_time": 1701749007.33482, "error": null, "children": null, "node_name": null}], "node_name": "classify_with_llm"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"prompt_tokens": 596, "completion_tokens": 13, "total_tokens": 609, "duration": 0.339594}, "result": "{\"category\": \"None\", \"evidence\": \"None\"}"}, "start_time": "2023-12-05T04:03:26.996107", "end_time": "2023-12-05T04:03:27.335701", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/classify_with_llm/000000002.jsonl | {"node_name": "classify_with_llm", "line_number": 2, "run_info": {"node": "classify_with_llm", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_classify_with_llm_2", "status": "Completed", "inputs": {"prompt": "system:\nYour task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both.\n\nuser:\nThe selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\n{% for ex in examples %}\nURL: {{ex.url}}\nText content: {{ex.text_content}}\nOUTPUT:\n{\"category\": \"{{ex.category}}\", \"evidence\": \"{{ex.evidence}}\"}\n\n{% endfor %}\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: {{url}}\nText content: {{text_content}}.\nOUTPUT:", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "url": "https://play.google.com/store/apps/details?id=com.twitter.android", "text_content": "The X app is a global digital platform where users can post content, join public conversations, stay updated on breaking news, and follow their interests. It offers features such as Community Notes for extra context, Spaces for live audio or video streaming, Direct Messages for private communication, and the option to subscribe to X Premium for expanded reach and exclusive content creation. Users can also create and join Communities, upload and watch videos, and write and read long-form posts. The app prioritizes data safety and allows users to request data deletion. It has a rating of 3.8 stars based on 21.5 million reviews and has been downloaded over", "examples": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}]}, "output": "{\"category\": \"App\", \"evidence\": \"Both\"}", "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_2", "start_time": "2023-12-05T04:03:28.126270Z", "end_time": "2023-12-05T04:03:28.470558Z", "index": 2, "api_calls": [{"name": "AzureOpenAI.chat", "type": "Tool", "inputs": {"prompt": "system:\nYour task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both.\n\nuser:\nThe selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\n{% for ex in examples %}\nURL: {{ex.url}}\nText content: {{ex.text_content}}\nOUTPUT:\n{\"category\": \"{{ex.category}}\", \"evidence\": \"{{ex.evidence}}\"}\n\n{% endfor %}\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: {{url}}\nText content: {{text_content}}.\nOUTPUT:", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "url": "https://play.google.com/store/apps/details?id=com.twitter.android", "text_content": "The X app is a global digital platform where users can post content, join public conversations, stay updated on breaking news, and follow their interests. It offers features such as Community Notes for extra context, Spaces for live audio or video streaming, Direct Messages for private communication, and the option to subscribe to X Premium for expanded reach and exclusive content creation. Users can also create and join Communities, upload and watch videos, and write and read long-form posts. The app prioritizes data safety and allows users to request data deletion. It has a rating of 3.8 stars based on 21.5 million reviews and has been downloaded over", "examples": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}]}, "output": "{\"category\": \"App\", \"evidence\": \"Both\"}", "start_time": 1701749008.126513, "end_time": 1701749008.469702, "error": null, "children": [{"name": "openai.api_resources.chat_completion.ChatCompletion.create", "type": "LLM", "inputs": {"api_base": "https://gpt-test-eus.openai.azure.com/", "api_type": "azure", "api_version": "2023-07-01-preview", "engine": "gpt-35-turbo", "messages": [{"role": "system", "content": "Your task is to classify a given url into one of the following categories:\nMovie, App, Academic, Channel, Profile, PDF or None based on the text content information.\nThe classification will be based on the url, the webpage text content summary, or both."}, {"role": "user", "content": "The selection range of the value of \"category\" must be within \"Movie\", \"App\", \"Academic\", \"Channel\", \"Profile\", \"PDF\" and \"None\".\nThe selection range of the value of \"evidence\" must be within \"Url\", \"Text content\", and \"Both\".\nHere are a few examples:\nURL: https://play.google.com/store/apps/details?id=com.spotify.music\nText content: Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.\nOUTPUT:\n{\"category\": \"App\", \"evidence\": \"Both\"}\n\nURL: https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw\nText content: NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.\nOUTPUT:\n{\"category\": \"Channel\", \"evidence\": \"URL\"}\n\nURL: https://arxiv.org/abs/2303.04671\nText content: Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.\nOUTPUT:\n{\"category\": \"Academic\", \"evidence\": \"Text content\"}\n\nURL: https://ab.politiaromana.ro/\nText content: There is no content available for this text.\nOUTPUT:\n{\"category\": \"None\", \"evidence\": \"None\"}\n\n\nFor a given URL and text content, classify the url to complete the category and indicate evidence:\nURL: https://play.google.com/store/apps/details?id=com.twitter.android\nText content: The X app is a global digital platform where users can post content, join public conversations, stay updated on breaking news, and follow their interests. It offers features such as Community Notes for extra context, Spaces for live audio or video streaming, Direct Messages for private communication, and the option to subscribe to X Premium for expanded reach and exclusive content creation. Users can also create and join Communities, upload and watch videos, and write and read long-form posts. The app prioritizes data safety and allows users to request data deletion. It has a rating of 3.8 stars based on 21.5 million reviews and has been downloaded over.\nOUTPUT:"}], "temperature": 0.2, "top_p": 1.0, "n": 1, "stream": false, "stop": null, "max_tokens": 128, "presence_penalty": 0.0, "frequency_penalty": 0.0, "logit_bias": {}, "user": ""}, "output": {"id": "chatcmpl-8SGwaHVVKGYxKtoLEQKFdvAmblBBc", "object": "chat.completion", "created": 1701749008, "model": "gpt-35-turbo", "prompt_filter_results": [{"prompt_index": 0, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "choices": [{"index": 0, "finish_reason": "stop", "message": {"role": "assistant", "content": "{\"category\": \"App\", \"evidence\": \"Both\"}"}, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "usage": {"prompt_tokens": 694, "completion_tokens": 13, "total_tokens": 707}}, "start_time": 1701749008.130586, "end_time": 1701749008.469585, "error": null, "children": null, "node_name": null}], "node_name": "classify_with_llm"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"prompt_tokens": 694, "completion_tokens": 13, "total_tokens": 707, "duration": 0.344288}, "result": "{\"category\": \"App\", \"evidence\": \"Both\"}"}, "start_time": "2023-12-05T04:03:28.126270", "end_time": "2023-12-05T04:03:28.470558", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/convert_to_dict/000000001.jsonl | {"node_name": "convert_to_dict", "line_number": 1, "run_info": {"node": "convert_to_dict", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_convert_to_dict_1", "status": "Completed", "inputs": {"input_str": "{\"category\": \"Academic\", \"evidence\": \"Both\"}"}, "output": {"category": "Academic", "evidence": "Both"}, "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_1", "start_time": "2023-12-05T04:03:27.958980Z", "end_time": "2023-12-05T04:03:27.959839Z", "index": 1, "api_calls": [{"name": "convert_to_dict", "type": "Tool", "inputs": {"input_str": "{\"category\": \"Academic\", \"evidence\": \"Both\"}"}, "output": {"category": "Academic", "evidence": "Both"}, "start_time": 1701749007.959116, "end_time": 1701749007.959648, "error": null, "children": null, "node_name": "convert_to_dict"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"duration": 0.000859}, "result": {"category": "Academic", "evidence": "Both"}}, "start_time": "2023-12-05T04:03:27.958980", "end_time": "2023-12-05T04:03:27.959839", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/convert_to_dict/000000000.jsonl | {"node_name": "convert_to_dict", "line_number": 0, "run_info": {"node": "convert_to_dict", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_convert_to_dict_0", "status": "Completed", "inputs": {"input_str": "{\"category\": \"None\", \"evidence\": \"None\"}"}, "output": {"category": "None", "evidence": "None"}, "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_0", "start_time": "2023-12-05T04:03:27.337007Z", "end_time": "2023-12-05T04:03:27.337744Z", "index": 0, "api_calls": [{"name": "convert_to_dict", "type": "Tool", "inputs": {"input_str": "{\"category\": \"None\", \"evidence\": \"None\"}"}, "output": {"category": "None", "evidence": "None"}, "start_time": 1701749007.337123, "end_time": 1701749007.3376, "error": null, "children": null, "node_name": "convert_to_dict"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"duration": 0.000737}, "result": {"category": "None", "evidence": "None"}}, "start_time": "2023-12-05T04:03:27.337007", "end_time": "2023-12-05T04:03:27.337744", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/convert_to_dict/000000002.jsonl | {"node_name": "convert_to_dict", "line_number": 2, "run_info": {"node": "convert_to_dict", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_convert_to_dict_2", "status": "Completed", "inputs": {"input_str": "{\"category\": \"App\", \"evidence\": \"Both\"}"}, "output": {"category": "App", "evidence": "Both"}, "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_2", "start_time": "2023-12-05T04:03:28.472153Z", "end_time": "2023-12-05T04:03:28.473016Z", "index": 2, "api_calls": [{"name": "convert_to_dict", "type": "Tool", "inputs": {"input_str": "{\"category\": \"App\", \"evidence\": \"Both\"}"}, "output": {"category": "App", "evidence": "Both"}, "start_time": 1701749008.472326, "end_time": 1701749008.472859, "error": null, "children": null, "node_name": "convert_to_dict"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"duration": 0.000863}, "result": {"category": "App", "evidence": "Both"}}, "start_time": "2023-12-05T04:03:28.472153", "end_time": "2023-12-05T04:03:28.473016", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/prepare_examples/000000001.jsonl | {"node_name": "prepare_examples", "line_number": 1, "run_info": {"node": "prepare_examples", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_prepare_examples_1", "status": "Completed", "inputs": {}, "output": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}], "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_1", "start_time": "2023-12-05T04:03:25.609989Z", "end_time": "2023-12-05T04:03:25.617871Z", "index": 1, "api_calls": [{"name": "prepare_examples", "type": "Tool", "inputs": {}, "output": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}], "start_time": 1701749005.610052, "end_time": 1701749005.617312, "error": null, "children": null, "node_name": "prepare_examples"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"duration": 0.007882}, "result": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}]}, "start_time": "2023-12-05T04:03:25.609989", "end_time": "2023-12-05T04:03:25.617871", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/prepare_examples/000000000.jsonl | {"node_name": "prepare_examples", "line_number": 0, "run_info": {"node": "prepare_examples", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_prepare_examples_0", "status": "Completed", "inputs": {}, "output": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}], "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_0", "start_time": "2023-12-05T04:03:25.567930Z", "end_time": "2023-12-05T04:03:25.573342Z", "index": 0, "api_calls": [{"name": "prepare_examples", "type": "Tool", "inputs": {}, "output": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}], "start_time": 1701749005.568033, "end_time": 1701749005.572487, "error": null, "children": null, "node_name": "prepare_examples"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"duration": 0.005412}, "result": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}]}, "start_time": "2023-12-05T04:03:25.567930", "end_time": "2023-12-05T04:03:25.573342", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/prepare_examples/000000002.jsonl | {"node_name": "prepare_examples", "line_number": 2, "run_info": {"node": "prepare_examples", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_prepare_examples_2", "status": "Completed", "inputs": {}, "output": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}], "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_2", "start_time": "2023-12-05T04:03:25.739510Z", "end_time": "2023-12-05T04:03:25.741692Z", "index": 2, "api_calls": [{"name": "prepare_examples", "type": "Tool", "inputs": {}, "output": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}], "start_time": 1701749005.739604, "end_time": 1701749005.74123, "error": null, "children": null, "node_name": "prepare_examples"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"duration": 0.002182}, "result": [{"url": "https://play.google.com/store/apps/details?id=com.spotify.music", "text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers audiobooks, so users can enjoy thousands of stories. It has a variety of features such as creating and sharing music playlists, discovering new music, and listening to popular and exclusive podcasts. It also has a Premium subscription option which allows users to download and listen offline, and access ad-free music. It is available on all devices and has a variety of genres and artists to choose from.", "category": "App", "evidence": "Both"}, {"url": "https://www.youtube.com/channel/UC_x5XG1OV2P6uZZ5FSM9Ttw", "text_content": "NFL Sunday Ticket is a service offered by Google LLC that allows users to watch NFL games on YouTube. It is available in 2023 and is subject to the terms and privacy policy of Google LLC. It is also subject to YouTube's terms of use and any applicable laws.", "category": "Channel", "evidence": "URL"}, {"url": "https://arxiv.org/abs/2303.04671", "text_content": "Visual ChatGPT is a system that enables users to interact with ChatGPT by sending and receiving not only languages but also images, providing complex visual questions or visual editing instructions, and providing feedback and asking for corrected results. It incorporates different Visual Foundation Models and is publicly available. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.", "category": "Academic", "evidence": "Text content"}, {"url": "https://ab.politiaromana.ro/", "text_content": "There is no content available for this text.", "category": "None", "evidence": "None"}]}, "start_time": "2023-12-05T04:03:25.739510", "end_time": "2023-12-05T04:03:25.741692", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/summarize_text_content/000000001.jsonl | {"node_name": "summarize_text_content", "line_number": 1, "run_info": {"node": "summarize_text_content", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_summarize_text_content_1", "status": "Completed", "inputs": {"prompt": "system:\nPlease summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text.\n\nuser:\nText: {{text}}\nSummary: ", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "text": "\n\n\n [2307.04767] Semantic-SAM: Segment and Recognize Anything at Any Granularity\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\nSkip to main content\n\n\n\n\n\nWe gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate\n\n\n\n\n\n > cs > arXiv:2307.04767\n \n\n\n\n\n\nHelp | Advanced Search\n\n\n\n\nAll fields\nTitle\nAuthor\nAbstract\nComments\nJournal reference\nACM classification\nMSC classification\nReport number\narXiv identifier\nDOI\nORCID\narXiv author ID\nHelp pages\nFull text\n\n\n\n\nSearch\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nopen search\n\n\n\n\n\n\nGO\n\n\n\nopen navigation menu\n\n\nquick links\n\nLogin\nHelp Pages\nAbout\n\n\n\n\n\n\n\n\n\n\n\n\nComputer Science > Computer Vision and Pattern Recognition\n\n\narXiv:2307.04767 (cs)\n \n\n\n\n\n [Submitted on 10 Jul 2023]\nTitle:Semantic-SAM: Segment and Recognize Anything at Any Granularity\nAuthors:Feng Li, Hao Zhang, Peize Sun, Xueyan Zou, Shilong Liu, Jianwei Yang, Chunyuan Li, Lei Zhang, Jianfeng Gao Download a PDF of the paper titled Semantic-SAM: Segment and Recognize Anything at Any Granularity, by Feng Li and 8 other authors\nDownload PDF\n\nAbstract:In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity. Our model offers two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, we consolidate multiple datasets across three granularities and introduce decoupled classification for objects and parts. This allows our model to capture rich semantic information. For the multi-granularity capability, we propose a multi-choice learning scheme during training, enabling each click to generate masks at multiple levels that correspond to multiple ground-truth masks. Notably, this work represents the first attempt to jointly train a model on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate that our model successfully achieves semantic-awareness and granularity-abundance. Furthermore, co"}, "output": "The paper introduces Semantic-SAM, a universal image segmentation model that can segment and recognize objects at any desired granularity. The model has two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, the model consolidates multiple datasets and introduces decoupled classification for objects and parts. This allows the model to capture rich semantic information. For multi-granularity capability, a multi-choice learning scheme is proposed during training, generating masks at multiple levels. The model is trained on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate the success of the model in achieving semantic-awareness and", "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_1", "start_time": "2023-12-05T04:03:26.035429Z", "end_time": "2023-12-05T04:03:27.668794Z", "index": 1, "api_calls": [{"name": "AzureOpenAI.chat", "type": "Tool", "inputs": {"prompt": "system:\nPlease summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text.\n\nuser:\nText: {{text}}\nSummary: ", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "text": "\n\n\n [2307.04767] Semantic-SAM: Segment and Recognize Anything at Any Granularity\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\nSkip to main content\n\n\n\n\n\nWe gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate\n\n\n\n\n\n > cs > arXiv:2307.04767\n \n\n\n\n\n\nHelp | Advanced Search\n\n\n\n\nAll fields\nTitle\nAuthor\nAbstract\nComments\nJournal reference\nACM classification\nMSC classification\nReport number\narXiv identifier\nDOI\nORCID\narXiv author ID\nHelp pages\nFull text\n\n\n\n\nSearch\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nopen search\n\n\n\n\n\n\nGO\n\n\n\nopen navigation menu\n\n\nquick links\n\nLogin\nHelp Pages\nAbout\n\n\n\n\n\n\n\n\n\n\n\n\nComputer Science > Computer Vision and Pattern Recognition\n\n\narXiv:2307.04767 (cs)\n \n\n\n\n\n [Submitted on 10 Jul 2023]\nTitle:Semantic-SAM: Segment and Recognize Anything at Any Granularity\nAuthors:Feng Li, Hao Zhang, Peize Sun, Xueyan Zou, Shilong Liu, Jianwei Yang, Chunyuan Li, Lei Zhang, Jianfeng Gao Download a PDF of the paper titled Semantic-SAM: Segment and Recognize Anything at Any Granularity, by Feng Li and 8 other authors\nDownload PDF\n\nAbstract:In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity. Our model offers two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, we consolidate multiple datasets across three granularities and introduce decoupled classification for objects and parts. This allows our model to capture rich semantic information. For the multi-granularity capability, we propose a multi-choice learning scheme during training, enabling each click to generate masks at multiple levels that correspond to multiple ground-truth masks. Notably, this work represents the first attempt to jointly train a model on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate that our model successfully achieves semantic-awareness and granularity-abundance. Furthermore, co"}, "output": "The paper introduces Semantic-SAM, a universal image segmentation model that can segment and recognize objects at any desired granularity. The model has two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, the model consolidates multiple datasets and introduces decoupled classification for objects and parts. This allows the model to capture rich semantic information. For multi-granularity capability, a multi-choice learning scheme is proposed during training, generating masks at multiple levels. The model is trained on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate the success of the model in achieving semantic-awareness and", "start_time": 1701749006.035773, "end_time": 1701749007.668153, "error": null, "children": [{"name": "openai.api_resources.chat_completion.ChatCompletion.create", "type": "LLM", "inputs": {"api_base": "https://gpt-test-eus.openai.azure.com/", "api_type": "azure", "api_version": "2023-07-01-preview", "engine": "gpt-35-turbo", "messages": [{"role": "system", "content": "Please summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text."}, {"role": "user", "content": "Text: \n\n\n [2307.04767] Semantic-SAM: Segment and Recognize Anything at Any Granularity\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\nSkip to main content\n\n\n\n\n\nWe gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate\n\n\n\n\n\n > cs > arXiv:2307.04767\n \n\n\n\n\n\nHelp | Advanced Search\n\n\n\n\nAll fields\nTitle\nAuthor\nAbstract\nComments\nJournal reference\nACM classification\nMSC classification\nReport number\narXiv identifier\nDOI\nORCID\narXiv author ID\nHelp pages\nFull text\n\n\n\n\nSearch\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nopen search\n\n\n\n\n\n\nGO\n\n\n\nopen navigation menu\n\n\nquick links\n\nLogin\nHelp Pages\nAbout\n\n\n\n\n\n\n\n\n\n\n\n\nComputer Science > Computer Vision and Pattern Recognition\n\n\narXiv:2307.04767 (cs)\n \n\n\n\n\n [Submitted on 10 Jul 2023]\nTitle:Semantic-SAM: Segment and Recognize Anything at Any Granularity\nAuthors:Feng Li, Hao Zhang, Peize Sun, Xueyan Zou, Shilong Liu, Jianwei Yang, Chunyuan Li, Lei Zhang, Jianfeng Gao Download a PDF of the paper titled Semantic-SAM: Segment and Recognize Anything at Any Granularity, by Feng Li and 8 other authors\nDownload PDF\n\nAbstract:In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity. Our model offers two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, we consolidate multiple datasets across three granularities and introduce decoupled classification for objects and parts. This allows our model to capture rich semantic information. For the multi-granularity capability, we propose a multi-choice learning scheme during training, enabling each click to generate masks at multiple levels that correspond to multiple ground-truth masks. Notably, this work represents the first attempt to jointly train a model on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate that our model successfully achieves semantic-awareness and granularity-abundance. Furthermore, co\nSummary: "}], "temperature": 0.2, "top_p": 1.0, "n": 1, "stream": false, "stop": null, "max_tokens": 128, "presence_penalty": 0.0, "frequency_penalty": 0.0, "logit_bias": {}, "user": ""}, "output": {"id": "chatcmpl-8SGwY6eyhMgFtmIhNkFmO6e2awkvq", "object": "chat.completion", "created": 1701749006, "model": "gpt-35-turbo", "prompt_filter_results": [{"prompt_index": 0, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "choices": [{"index": 0, "finish_reason": "length", "message": {"role": "assistant", "content": "The paper introduces Semantic-SAM, a universal image segmentation model that can segment and recognize objects at any desired granularity. The model has two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, the model consolidates multiple datasets and introduces decoupled classification for objects and parts. This allows the model to capture rich semantic information. For multi-granularity capability, a multi-choice learning scheme is proposed during training, generating masks at multiple levels. The model is trained on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate the success of the model in achieving semantic-awareness and"}, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "usage": {"prompt_tokens": 468, "completion_tokens": 128, "total_tokens": 596}}, "start_time": 1701749006.052093, "end_time": 1701749007.668043, "error": null, "children": null, "node_name": null}], "node_name": "summarize_text_content"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"prompt_tokens": 468, "completion_tokens": 128, "total_tokens": 596, "duration": 1.633365}, "result": "The paper introduces Semantic-SAM, a universal image segmentation model that can segment and recognize objects at any desired granularity. The model has two key advantages: semantic-awareness and granularity-abundance. To achieve semantic-awareness, the model consolidates multiple datasets and introduces decoupled classification for objects and parts. This allows the model to capture rich semantic information. For multi-granularity capability, a multi-choice learning scheme is proposed during training, generating masks at multiple levels. The model is trained on SA-1B, generic, and part segmentation datasets. Experimental results and visualizations demonstrate the success of the model in achieving semantic-awareness and"}, "start_time": "2023-12-05T04:03:26.035429", "end_time": "2023-12-05T04:03:27.668794", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/summarize_text_content/000000000.jsonl | {"node_name": "summarize_text_content", "line_number": 0, "run_info": {"node": "summarize_text_content", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_summarize_text_content_0", "status": "Completed", "inputs": {"prompt": "system:\nPlease summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text.\n\nuser:\nText: {{text}}\nSummary: ", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "text": "Amazing! The prompt flow in Azure AI speeds up the building of my LLM application. - YouTubeAboutPressCopyrightContact usCreatorsAdvertiseDevelopersTermsPrivacyPolicy & SafetyHow YouTube worksTest new featuresNFL Sunday Ticket\u00a9 2023 Google LLC"}, "output": "The author expresses their excitement about the prompt flow feature in Azure AI, which has helped them accelerate the development of their LLM application.", "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_0", "start_time": "2023-12-05T04:03:26.621822Z", "end_time": "2023-12-05T04:03:26.994395Z", "index": 0, "api_calls": [{"name": "AzureOpenAI.chat", "type": "Tool", "inputs": {"prompt": "system:\nPlease summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text.\n\nuser:\nText: {{text}}\nSummary: ", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "text": "Amazing! The prompt flow in Azure AI speeds up the building of my LLM application. - YouTubeAboutPressCopyrightContact usCreatorsAdvertiseDevelopersTermsPrivacyPolicy & SafetyHow YouTube worksTest new featuresNFL Sunday Ticket\u00a9 2023 Google LLC"}, "output": "The author expresses their excitement about the prompt flow feature in Azure AI, which has helped them accelerate the development of their LLM application.", "start_time": 1701749006.622094, "end_time": 1701749006.993613, "error": null, "children": [{"name": "openai.api_resources.chat_completion.ChatCompletion.create", "type": "LLM", "inputs": {"api_base": "https://gpt-test-eus.openai.azure.com/", "api_type": "azure", "api_version": "2023-07-01-preview", "engine": "gpt-35-turbo", "messages": [{"role": "system", "content": "Please summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text."}, {"role": "user", "content": "Text: Amazing! The prompt flow in Azure AI speeds up the building of my LLM application. - YouTubeAboutPressCopyrightContact usCreatorsAdvertiseDevelopersTermsPrivacyPolicy & SafetyHow YouTube worksTest new featuresNFL Sunday Ticket\u00a9 2023 Google LLC\nSummary: "}], "temperature": 0.2, "top_p": 1.0, "n": 1, "stream": false, "stop": null, "max_tokens": 128, "presence_penalty": 0.0, "frequency_penalty": 0.0, "logit_bias": {}, "user": ""}, "output": {"id": "chatcmpl-8SGwYh2QixabybRzI9vKPfKwl9deg", "object": "chat.completion", "created": 1701749006, "model": "gpt-35-turbo", "prompt_filter_results": [{"prompt_index": 0, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "choices": [{"index": 0, "finish_reason": "stop", "message": {"role": "assistant", "content": "The author expresses their excitement about the prompt flow feature in Azure AI, which has helped them accelerate the development of their LLM application."}, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "usage": {"prompt_tokens": 92, "completion_tokens": 27, "total_tokens": 119}}, "start_time": 1701749006.627222, "end_time": 1701749006.993502, "error": null, "children": null, "node_name": null}], "node_name": "summarize_text_content"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"prompt_tokens": 92, "completion_tokens": 27, "total_tokens": 119, "duration": 0.372573}, "result": "The author expresses their excitement about the prompt flow feature in Azure AI, which has helped them accelerate the development of their LLM application."}, "start_time": "2023-12-05T04:03:26.621822", "end_time": "2023-12-05T04:03:26.994395", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/web_classification_variant_0_20231205_120253_104100/node_artifacts/summarize_text_content/000000002.jsonl | {"node_name": "summarize_text_content", "line_number": 2, "run_info": {"node": "summarize_text_content", "flow_run_id": "web_classification_variant_0_20231205_120253_104100", "run_id": "web_classification_variant_0_20231205_120253_104100_summarize_text_content_2", "status": "Completed", "inputs": {"prompt": "system:\nPlease summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text.\n\nuser:\nText: {{text}}\nSummary: ", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "text": "X - Apps on Google Playgoogle_logo PlayGamesAppsMovies & TVBooksKidsnonesearchhelp_outline Sign in with Googleplay_appsLibrary & devicespaymentPayments & subscriptionsreviewsMy Play activityredeemOffersPlay PasssettingsSettingsPrivacy Policy \u2022 Terms of ServiceGamesAppsMovies & TVBooksKidsXX Corp.Contains adsIn-app purchases3.8star21.5M reviews1B+DownloadsMature 17+infoInstallShareAdd to wishlistAbout this apparrow_forwardThe X app is the trusted global digital town square for everyone.With X, you can:- Post content for the world to see and join public conversations- Stay up to date on breaking news and follow your interests- Stay better informed with extra context from Community Notes- Go live with Spaces for audio or stream live video- Communicate privately with Direct Messages- Subscribe to X Premium to expand your reach, get a blue checkmark, and more- Earn a living creating exclusive content for your paid subscribers and share in the ad revenue generated in replies to your posts- Create and join Communities around topics and interests, from sports to music to technology- Upload and watch videos up to 3 hours in length- Write and read long form posts like essays and blogs- Connect directly with your customers to help your business growUpdated onDec 4, 2023#6 top grossing socialSocialData safetyarrow_forwardSafety starts with understanding how developers collect and share your data. Data privacy and security practices may vary based on your use, region, and age. The developer provided this information and may update it over time.No data shared with third partiesLearn more about how developers declare sharingThis app may collect these data typesLocation, Personal info and 9 othersData is encrypted in transitYou can request that data be deletedSee detailsRatings and reviewsRatings and reviews are verifiedinfo_outlinearrow_forwardRatings and reviews are verifiedinfo_outlinephone_androidPhonetablet_androidTabletwatchWatchlaptopChromebooktvTV3.820.8M reviews54321Alex S"}, "output": "The X app is a global digital platform where users can post content, join public conversations, stay updated on breaking news, and follow their interests. It offers features such as Community Notes for extra context, Spaces for live audio or video streaming, Direct Messages for private communication, and the option to subscribe to X Premium for expanded reach and exclusive content creation. Users can also create and join Communities, upload and watch videos, and write and read long-form posts. The app prioritizes data safety and allows users to request data deletion. It has a rating of 3.8 stars based on 21.5 million reviews and has been downloaded over", "metrics": null, "error": null, "parent_run_id": "web_classification_variant_0_20231205_120253_104100_2", "start_time": "2023-12-05T04:03:26.386617Z", "end_time": "2023-12-05T04:03:28.124504Z", "index": 2, "api_calls": [{"name": "AzureOpenAI.chat", "type": "Tool", "inputs": {"prompt": "system:\nPlease summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text.\n\nuser:\nText: {{text}}\nSummary: ", "deployment_name": "gpt-35-turbo", "model": "gpt-3.5-turbo", "max_tokens": 128, "temperature": 0.2, "text": "X - Apps on Google Playgoogle_logo PlayGamesAppsMovies & TVBooksKidsnonesearchhelp_outline Sign in with Googleplay_appsLibrary & devicespaymentPayments & subscriptionsreviewsMy Play activityredeemOffersPlay PasssettingsSettingsPrivacy Policy \u2022 Terms of ServiceGamesAppsMovies & TVBooksKidsXX Corp.Contains adsIn-app purchases3.8star21.5M reviews1B+DownloadsMature 17+infoInstallShareAdd to wishlistAbout this apparrow_forwardThe X app is the trusted global digital town square for everyone.With X, you can:- Post content for the world to see and join public conversations- Stay up to date on breaking news and follow your interests- Stay better informed with extra context from Community Notes- Go live with Spaces for audio or stream live video- Communicate privately with Direct Messages- Subscribe to X Premium to expand your reach, get a blue checkmark, and more- Earn a living creating exclusive content for your paid subscribers and share in the ad revenue generated in replies to your posts- Create and join Communities around topics and interests, from sports to music to technology- Upload and watch videos up to 3 hours in length- Write and read long form posts like essays and blogs- Connect directly with your customers to help your business growUpdated onDec 4, 2023#6 top grossing socialSocialData safetyarrow_forwardSafety starts with understanding how developers collect and share your data. Data privacy and security practices may vary based on your use, region, and age. The developer provided this information and may update it over time.No data shared with third partiesLearn more about how developers declare sharingThis app may collect these data typesLocation, Personal info and 9 othersData is encrypted in transitYou can request that data be deletedSee detailsRatings and reviewsRatings and reviews are verifiedinfo_outlinearrow_forwardRatings and reviews are verifiedinfo_outlinephone_androidPhonetablet_androidTabletwatchWatchlaptopChromebooktvTV3.820.8M reviews54321Alex S"}, "output": "The X app is a global digital platform where users can post content, join public conversations, stay updated on breaking news, and follow their interests. It offers features such as Community Notes for extra context, Spaces for live audio or video streaming, Direct Messages for private communication, and the option to subscribe to X Premium for expanded reach and exclusive content creation. Users can also create and join Communities, upload and watch videos, and write and read long-form posts. The app prioritizes data safety and allows users to request data deletion. It has a rating of 3.8 stars based on 21.5 million reviews and has been downloaded over", "start_time": 1701749006.386894, "end_time": 1701749008.123235, "error": null, "children": [{"name": "openai.api_resources.chat_completion.ChatCompletion.create", "type": "LLM", "inputs": {"api_base": "https://gpt-test-eus.openai.azure.com/", "api_type": "azure", "api_version": "2023-07-01-preview", "engine": "gpt-35-turbo", "messages": [{"role": "system", "content": "Please summarize the following text in one paragraph. 100 words.\nDo not add any information that is not in the text."}, {"role": "user", "content": "Text: X - Apps on Google Playgoogle_logo PlayGamesAppsMovies & TVBooksKidsnonesearchhelp_outline Sign in with Googleplay_appsLibrary & devicespaymentPayments & subscriptionsreviewsMy Play activityredeemOffersPlay PasssettingsSettingsPrivacy Policy \u2022 Terms of ServiceGamesAppsMovies & TVBooksKidsXX Corp.Contains adsIn-app purchases3.8star21.5M reviews1B+DownloadsMature 17+infoInstallShareAdd to wishlistAbout this apparrow_forwardThe X app is the trusted global digital town square for everyone.With X, you can:- Post content for the world to see and join public conversations- Stay up to date on breaking news and follow your interests- Stay better informed with extra context from Community Notes- Go live with Spaces for audio or stream live video- Communicate privately with Direct Messages- Subscribe to X Premium to expand your reach, get a blue checkmark, and more- Earn a living creating exclusive content for your paid subscribers and share in the ad revenue generated in replies to your posts- Create and join Communities around topics and interests, from sports to music to technology- Upload and watch videos up to 3 hours in length- Write and read long form posts like essays and blogs- Connect directly with your customers to help your business growUpdated onDec 4, 2023#6 top grossing socialSocialData safetyarrow_forwardSafety starts with understanding how developers collect and share your data. Data privacy and security practices may vary based on your use, region, and age. The developer provided this information and may update it over time.No data shared with third partiesLearn more about how developers declare sharingThis app may collect these data typesLocation, Personal info and 9 othersData is encrypted in transitYou can request that data be deletedSee detailsRatings and reviewsRatings and reviews are verifiedinfo_outlinearrow_forwardRatings and reviews are verifiedinfo_outlinephone_androidPhonetablet_androidTabletwatchWatchlaptopChromebooktvTV3.820.8M reviews54321Alex S\nSummary: "}], "temperature": 0.2, "top_p": 1.0, "n": 1, "stream": false, "stop": null, "max_tokens": 128, "presence_penalty": 0.0, "frequency_penalty": 0.0, "logit_bias": {}, "user": ""}, "output": {"id": "chatcmpl-8SGwYyQcqIQLNvDERxnNkJ8Tv4wIf", "object": "chat.completion", "created": 1701749006, "model": "gpt-35-turbo", "prompt_filter_results": [{"prompt_index": 0, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "choices": [{"index": 0, "finish_reason": "length", "message": {"role": "assistant", "content": "The X app is a global digital platform where users can post content, join public conversations, stay updated on breaking news, and follow their interests. It offers features such as Community Notes for extra context, Spaces for live audio or video streaming, Direct Messages for private communication, and the option to subscribe to X Premium for expanded reach and exclusive content creation. Users can also create and join Communities, upload and watch videos, and write and read long-form posts. The app prioritizes data safety and allows users to request data deletion. It has a rating of 3.8 stars based on 21.5 million reviews and has been downloaded over"}, "content_filter_results": {"hate": {"filtered": false, "severity": "safe"}, "self_harm": {"filtered": false, "severity": "safe"}, "sexual": {"filtered": false, "severity": "safe"}, "violence": {"filtered": false, "severity": "safe"}}}], "usage": {"prompt_tokens": 448, "completion_tokens": 128, "total_tokens": 576}}, "start_time": 1701749006.391002, "end_time": 1701749008.123107, "error": null, "children": null, "node_name": null}], "node_name": "summarize_text_content"}], "variant_id": "", "cached_run_id": null, "cached_flow_run_id": null, "logs": {"stdout": "", "stderr": ""}, "system_metrics": {"prompt_tokens": 448, "completion_tokens": 128, "total_tokens": 576, "duration": 1.737887}, "result": "The X app is a global digital platform where users can post content, join public conversations, stay updated on breaking news, and follow their interests. It offers features such as Community Notes for extra context, Spaces for live audio or video streaming, Direct Messages for private communication, and the option to subscribe to X Premium for expanded reach and exclusive content creation. Users can also create and join Communities, upload and watch videos, and write and read long-form posts. The app prioritizes data safety and allows users to request data deletion. It has a rating of 3.8 stars based on 21.5 million reviews and has been downloaded over"}, "start_time": "2023-12-05T04:03:26.386617", "end_time": "2023-12-05T04:03:28.124504", "status": "Completed"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/illegal/missing_data.yaml | flow: ../flows/classification_accuracy_evaluation
column_mapping:
groundtruth: "${data.answer}"
prediction: "${run.outputs.category}"
run: flow_run_20230629_101205 # ./sample_bulk_run.yaml
# run config: env related
environment_variables: .env
# optional
connections:
node_1:
connection: test_llm_connection
deployment_name: gpt-35-turbo
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/runs/illegal/non_exist_data.yaml | flow: ../flows/classification_accuracy_evaluation
data: not_exist
column_mapping:
groundtruth: "${data.answer}"
prediction: "${run.outputs.category}"
run: flow_run_20230629_101205 # ./sample_bulk_run.yaml
# run config: env related
environment_variables: .env
# optional
connections:
node_1:
connection: test_llm_connection
deployment_name: gpt-35-turbo
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/flow_with_environment/entry.py | # ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------
def my_flow():
"""Simple flow without yaml."""
print("Hello world!")
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/flow_with_environment/flow.dag.yaml | path: ./entry.py
entry: my_flow
environment:
python_requirements_txt: requirements.txt
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/long_running/entry.py | # ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------
import time
def my_flow(input_val) -> str:
"""Simple flow with yaml."""
time.sleep(100)
print(f"Hello world! {input_val}")
return f"Hello world! {input_val}"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/long_running/flow.dag.yaml | path: ./entry.py
entry: my_flow
environment:
python_requirements_txt: requirements.txt | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/dummy_flow_with_trace/entry.py | import asyncio
from promptflow import trace
@trace
async def wait(n: int):
await asyncio.sleep(n)
@trace
async def dummy_llm(prompt: str, model: str, wait_seconds: int):
await wait(wait_seconds)
return prompt
async def my_flow(text: str, models: list = []):
tasks = []
for i, model in enumerate(models):
tasks.append(asyncio.create_task(dummy_llm(text, model, i + 1)))
await asyncio.wait(tasks)
return "dummy_output"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/dummy_flow_with_trace/flow.dag.yaml | path: ./entry.py
entry: my_flow
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/dummy_flow_with_trace/inputs.jsonl | {"text": "text", "models": ["model"]}
{"text": "text", "models": ["model", "model_2", "model_3"]} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/primitive_output/entry.py | # ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------
def my_flow(input_val: str = "gpt"):
"""Simple flow without yaml."""
# print(f"Hello world! {input_val}")
return f"Hello world! {input_val}"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/primitive_output/flow.dag.yaml | path: ./entry.py
entry: my_flow | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/invalid_extra_fields_nodes/entry.py | # ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------
def my_flow():
"""Simple flow without yaml."""
print("Hello world!")
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/invalid_extra_fields_nodes/flow.dag.yaml | entry: my_func
path: ./entry.py
nodes: [] | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/simple_without_yaml/entry.py | # ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------
def my_flow(input_val: str):
"""Simple flow without yaml."""
print(f"Hello world! {input_val}")
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/simple_with_yaml/entry.py | # ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------
def my_flow(input_val: str = "gpt") -> str:
"""Simple flow without yaml."""
return f"Hello world! {input_val}"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/simple_with_yaml/flow.dag.yaml | path: ./entry.py
entry: my_flow | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/invalid_no_path/entry.py | # ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------
def my_flow():
"""Simple flow without yaml."""
print("Hello world!")
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/invalid_no_path/flow.dag.yaml | entry: my_func | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/multiple_entries/entry1.py | # ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------
def my_flow1():
"""Simple flow without yaml."""
print("Hello world!")
def my_flow2():
"""Simple flow without yaml."""
print("Hello world!")
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/multiple_entries/entry2.py | # ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------
def my_flow1():
"""Simple flow without yaml."""
print("Hello world!")
def my_flow2():
"""Simple flow without yaml."""
print("Hello world!")
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/simple_with_req/entry.py | # ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------
def my_flow(input_val) -> str:
"""Simple flow with yaml."""
print(f"Hello world! {input_val}")
return f"Hello world! {input_val}"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/simple_with_req/flow.dag.yaml | path: ./entry.py
entry: my_flow
environment:
python_requirements_txt: requirements.txt | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/flow_with_dataclass_output/entry.py | from dataclasses import dataclass
@dataclass
class Data:
text: str
models: list
def my_flow(text: str = "default_text", models: list = ["default_model"]):
return Data(text=text, models=models)
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/eager_flows/flow_with_dataclass_output/flow.dag.yaml | path: ./entry.py
entry: my_flow | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.