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promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/eval_flow_with_composite_image/flow.dag.yaml | inputs:
image_list:
type: list
default:
- data:image/jpg;path: logo.jpg
- data:image/png;path: logo_2.png
image_dict:
type: object
default:
image_1:
data:image/jpg;path: logo.jpg
image_2:
data:image/png;path: logo_2.png
outputs:
output:
type: list
reference: ${python_node.output}
nodes:
- name: python_node
type: python
source:
type: code
path: passthrough_list.py
inputs:
image_list: ${inputs.image_list}
image_dict: ${inputs.image_dict}
- name: aggregate_1
type: python
source:
type: code
path: merge_images.py
inputs:
image_list: ${python_node.output}
image_dict:
- image_1:
data:image/jpg;path: logo.jpg
image_2:
data:image/png;path: logo_2.png
aggregation: true
- name: aggregate_2
type: python
source:
type: code
path: merge_images.py
inputs:
image_list: ${python_node.output}
image_dict: ${inputs.image_dict}
aggregation: true
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/eval_flow_with_composite_image/inputs.jsonl | {"image_list":[{"data:image/jpg;path": "logo.jpg"},{"data:image/jpg;path": "logo_2.png"}],"image_dict":{"image_1": {"data:image/jpg;path": "logo.jpg"},"image_2": {"data:image/png;path": "logo_2.png"}}}
{"image_list":[{"data:image/jpg;path": "logo_2.png"},{"data:image/jpg;path": "logo.jpg"}],"image_dict":{"image_1": {"data:image/jpg;path": "logo_2.png"},"image_2": {"data:image/png;path": "logo.jpg"}}} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/partial_fail/data.jsonl | {"key": "no"}
{"key": "raise"}
{"key": "matter"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/partial_fail/flow.dag.yaml | inputs:
key:
type: string
outputs:
output:
type: string
reference: ${print_env.output.value}
nodes:
- name: print_env
type: python
source:
type: code
path: print_env.py
inputs:
key: ${inputs.key}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/partial_fail/print_env.py | import os
from promptflow import tool
@tool
def get_env_var(key: str):
if key == "raise":
raise Exception("expected raise!")
print(os.environ.get(key))
# get from env var
return {"value": os.environ.get(key)}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/all_depedencies_bypassed_with_activate_met/pass_through.py | from promptflow import tool
@tool
def pass_through(input1: str="Execution") -> str:
return input1 | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/all_depedencies_bypassed_with_activate_met/flow.dag.yaml | inputs:
text:
type: string
default: hi
outputs:
output:
type: string
reference: ${nodeB.output}
nodes:
- name: nodeA
type: python
source:
type: code
path: pass_through.py
inputs:
input1: ${inputs.text}
activate:
when: ${inputs.text}
is: world
- name: nodeB
type: python
source:
type: code
path: pass_through.py
inputs:
input1: ${nodeA.output}
activate:
when: ${inputs.text}
is: hi
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/all_depedencies_bypassed_with_activate_met/inputs.json | {
"text": "hi"
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/all_depedencies_bypassed_with_activate_met/expected_result.json | [
{
"expected_node_count": 2,
"expected_outputs": {
"output": "Execution"
},
"expected_bypassed_nodes": [
"nodeA"
]
}
] | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_dict_input/print_val.py | from promptflow import tool
@tool
def print_val(val, origin_val):
print(val)
print(origin_val)
if not isinstance(origin_val, dict):
raise TypeError(f"key must be a dict, got {type(origin_val)}")
return val
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_dict_input/get_dict_val.py | from promptflow import tool
@tool
def get_dict_val(key):
# get from env var
print(key)
if not isinstance(key, dict):
raise TypeError(f"key must be a dict, got {type(key)}")
return {"value": f"{key}: {type(key)}", "origin_value": key}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_dict_input/flow.dag.yaml | inputs:
key:
type: object
outputs:
output:
type: string
reference: ${get_dict_val.output.value}
nodes:
- name: get_dict_val
type: python
source:
type: code
path: get_dict_val.py
inputs:
key: ${inputs.key}
- name: print_val
type: python
source:
type: code
path: print_val.py
inputs:
val: ${get_dict_val.output.value}
origin_val: ${get_dict_val.output.origin_value}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_dict_input | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_dict_input/.promptflow/flow.tools.json | {
"package": {},
"code": {
"print_val.py": {
"name": "print_val.py",
"type": "python",
"inputs": {
"key": {
"type": [
"object"
]
}
},
"source": "print_val.py",
"function": "get_val"
}
}
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/unordered_nodes_with_skip/flow.dag.yaml | name: node_wrong_order
inputs:
text:
type: string
skip:
type: bool
outputs:
result:
type: string
reference: ${third_node}
nodes:
- name: third_node
type: python
source:
type: code
path: test.py
inputs:
text: ${second_node}
- name: first_node
type: python
source:
type: code
path: test.py
inputs:
text: ${inputs.text}
- name: second_node
type: python
source:
type: code
path: test.py
inputs:
text: ${first_node}
skip:
when: ${inputs.skip}
is: true
return: ${inputs.text}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/eval-classification-accuracy/data.jsonl | {"groundtruth": "App","prediction": "App"}
{"groundtruth": "Channel","prediction": "Channel"}
{"groundtruth": "Academic","prediction": "Academic"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/eval-classification-accuracy/calculate_accuracy.py | from typing import List
from promptflow import log_metric, tool
@tool
def calculate_accuracy(grades: List[str]):
result = []
for index in range(len(grades)):
grade = grades[index]
result.append(grade)
# calculate accuracy for each variant
accuracy = round((result.count("Correct") / len(result)), 2)
log_metric("accuracy", accuracy)
return result
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/eval-classification-accuracy/grade.py | from promptflow import tool
@tool
def grade(groundtruth: str, prediction: str):
return "Correct" if groundtruth.lower() == prediction.lower() else "Incorrect"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/eval-classification-accuracy/flow.dag.yaml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
inputs:
groundtruth:
type: string
description: Please specify the groundtruth column, which contains the true label
to the outputs that your flow produces.
default: APP
prediction:
type: string
description: Please specify the prediction column, which contains the predicted
outputs that your flow produces.
default: APP
outputs:
grade:
type: string
reference: ${grade.output}
nodes:
- name: grade
type: python
source:
type: code
path: grade.py
inputs:
groundtruth: ${inputs.groundtruth}
prediction: ${inputs.prediction}
- name: calculate_accuracy
type: python
source:
type: code
path: calculate_accuracy.py
inputs:
grades: ${grade.output}
aggregation: true
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/failed_flow/hello.py | import os
import openai
from dotenv import load_dotenv
from promptflow import tool
# The inputs section will change based on the arguments of the tool function, after you save the code
# Adding type to arguments and return value will help the system show the types properly
# Please update the function name/signature per need
def to_bool(value) -> bool:
return str(value).lower() == "true"
@tool
def my_python_tool(input1: str) -> str:
return 'hello '
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/failed_flow/flow.dag.yaml | inputs:
text:
type: string
outputs:
output_prompt:
type: string
reference: ${echo_my_prompt.output}
nodes:
- inputs:
text: ${inputs.text}
name: echo_my_prompt
type: python
source:
type: code
path: hello.py
node_variants: {}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/external_files/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: {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/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/external_files/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("input is not valid, error: {}".format(e))
return {"category": "None", "evidence": "None"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/external_files/summarize_text_content.jinja2 | Please summarize the following text in one paragraph. 100 words.
Do not add any information that is not in the text.
Text: {{text}}
Summary:
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_user_output/print_val.py | import sys
from promptflow import tool
@tool
def get_val(key):
# get from env var
print(key)
print("user log")
print("error log", file=sys.stderr) | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_user_output/flow.dag.yaml | inputs:
key:
type: object
outputs:
output:
type: string
reference: ${print_val.output.value}
nodes:
- name: print_val
type: python
source:
type: code
path: print_val.py
inputs:
key: ${inputs.key}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_user_output | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_user_output/.promptflow/flow.tools.json | {
"package": {},
"code": {
"print_val.py": {
"name": "print_val.py",
"type": "python",
"inputs": {
"key": {
"type": [
"object"
]
}
},
"source": "print_val.py",
"function": "get_val"
}
}
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/activate_condition_always_met/pass_through.py | from promptflow import tool
@tool
def pass_through(input1: str) -> str:
return 'hello ' + input1
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/activate_condition_always_met/flow.dag.yaml | inputs:
text:
type: string
default: hello
outputs:
output:
type: string
reference: ${nodeC.output}
nodes:
- name: nodeA
type: python
source:
type: code
path: pass_through.py
inputs:
input1: ${inputs.text}
activate:
when: ${inputs.text}
is: hi
- name: nodeB
type: python
source:
type: code
path: pass_through.py
inputs:
input1: ${inputs.text}
activate:
when: ${inputs.text}
is: hi
- name: nodeC
type: python
source:
type: code
path: summary_result.py
inputs:
input1: ${nodeA.output}
input2: ${nodeB.output}
activate:
when: dummy
is: dummy
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/activate_condition_always_met/summary_result.py | from promptflow import tool
@tool
def summary_result(input1: str="Node A not executed.", input2: str="Node B not executed.") -> str:
return input1 + ' ' + input2
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/activate_condition_always_met/inputs.json | {
"text": "hello"
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/activate_condition_always_met/expected_result.json | [
{
"expected_node_count": 3,
"expected_outputs": {
"output": "Node A not executed. Node B not executed."
},
"expected_bypassed_nodes": [
"nodeA",
"nodeB"
]
}
] | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/basic_with_builtin_llm_node/hello.jinja2 | system:
You are a assistant which can write code. Response should only contain code.
user:
Write a simple {{text}} program that displays the greeting message when executed. | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/basic_with_builtin_llm_node/flow.dag.yaml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
inputs:
text:
type: string
default: Python Hello World!
outputs:
output:
type: string
reference: ${llm.output}
nodes:
- name: hello_prompt
type: prompt
inputs:
text: ${inputs.text}
source:
type: code
path: hello.jinja2
- name: llm
type: llm
inputs:
prompt: ${hello_prompt.output}
deployment_name: gpt-35-turbo
model: gpt-3.5-turbo
max_tokens: '120'
source:
type: code
path: hello.jinja2
connection: azure_open_ai_connection
api: chat
node_variants: {}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_dict_input_with_variant/print_val.py | from promptflow import tool
from promptflow.connections import CustomConnection
@tool
def get_val(key, conn: CustomConnection):
# get from env var
print(key)
if not isinstance(key, dict):
raise TypeError(f"key must be a dict, got {type(key)}")
return {"value": f"{key}: {type(key)}"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_dict_input_with_variant/flow.dag.yaml | inputs:
key:
type: object
outputs:
output:
type: string
reference: ${print_val.output.value}
nodes:
- name: print_val
use_variants: true
type: python
source:
type: code
path: print_val.py
node_variants:
print_val:
default_variant_id: variant1
variants:
variant1:
node:
type: python
source:
type: code
path: print_val.py
inputs:
key: ${inputs.key}
conn: mock_custom_connection | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_environment_variables/flow.dag.yaml | environment_variables:
env1: 2
env2: spawn
env3:
- 1
- 2
- 3
- 4
- 5
env4:
a: 1
b: "2"
inputs:
key:
type: string
outputs:
output:
type: string
reference: ${print_env.output.value}
nodes:
- name: print_env
type: python
source:
type: code
path: print_env.py
inputs:
key: ${inputs.key}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_environment_variables/inputs.jsonl | {"text": "env1"}
{"text": "env2"}
{"text": "env3"}
{"text": "env4"}
{"text": "env5"}
{"text": "env10"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_environment_variables/print_env.py | import os
from promptflow import tool
@tool
def get_env_var(key: str):
print(os.environ.get(key))
# get from env var
return {"value": os.environ.get(key)}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat_flow_without_defined_chat_history/show_answer.py | from promptflow import tool
@tool
def show_answer(chat_answer: str):
print("print:", chat_answer)
return chat_answer
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat_flow_without_defined_chat_history/chat.jinja2 | system:
You are a helpful assistant.
{% for item in chat_history %}
user:
{{item.inputs.question}}
assistant:
{{item.outputs.answer}}
{% endfor %}
user:
{{question}} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat_flow_without_defined_chat_history/flow.dag.yaml | inputs:
chat_history:
type: list
is_chat_history: false
question:
type: string
is_chat_input: true
default: What is ChatGPT?
outputs:
answer:
type: string
reference: ${show_answer.output}
is_chat_output: true
nodes:
- inputs:
deployment_name: gpt-35-turbo
max_tokens: "256"
temperature: "0.7"
chat_history: ${inputs.chat_history}
question: ${inputs.question}
name: chat_node
type: llm
source:
type: code
path: chat.jinja2
api: chat
provider: AzureOpenAI
connection: azure_open_ai_connection
- name: show_answer
type: python
source:
type: code
path: show_answer.py
inputs:
chat_answer: ${chat_node.output}
node_variants: {}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/generator_tools/echo.py | from promptflow import tool
from char_generator import character_generator
@tool
def echo(text):
"""Echo the input string."""
echo_text = "Echo - " + "".join(character_generator(text))
return echo_text | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/generator_tools/flow.dag.yaml | inputs:
text:
type: string
outputs:
answer:
type: string
reference: ${echo.output}
nodes:
- name: echo
type: python
source:
type: code
path: echo.py
inputs:
text: ${inputs.text}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/generator_tools/char_generator.py | from promptflow import tool
@tool
def character_generator(text: str):
"""Generate characters from a string."""
for char in text:
yield char | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/basic-with-connection/hello.py | import json
import os
import openai
from openai.version import VERSION as OPENAI_VERSION
from promptflow import tool
from promptflow.connections import AzureOpenAIConnection
from promptflow.tools.common import render_jinja_template, parse_chat
# The inputs section will change based on the arguments of the tool function, after you save the code
# Adding type to arguments and return value will help the system show the types properly
# Please update the function name/signature per need
def get_client(connection: AzureOpenAIConnection):
api_key = connection.api_key
conn = dict(
api_key=connection.api_key,
)
if api_key.startswith("sk-"):
from openai import OpenAI as Client
else:
from openai import AzureOpenAI as Client
conn.update(
azure_endpoint=connection.api_base,
api_version=connection.api_version,
)
return Client(**conn)
def to_bool(value) -> bool:
return str(value).lower() == "true"
@tool
def my_python_tool(
prompt: str,
# for AOAI, deployment name is customized by user, not model name.
deployment_name: str,
suffix: str = None,
max_tokens: int = 120,
temperature: float = 1.0,
top_p: float = 1.0,
n: int = 1,
logprobs: int = None,
echo: bool = False,
stop: list = None,
presence_penalty: float = 0,
frequency_penalty: float = 0,
best_of: int = 1,
logit_bias: dict = {},
user: str = "",
connection: AzureOpenAIConnection = None,
**kwargs,
) -> str:
# TODO: remove below type conversion after client can pass json rather than string.
echo = to_bool(echo)
# Assert environment variable resolved
assert os.environ["API_TYPE"] == connection.api_type
if OPENAI_VERSION.startswith("0."):
response = openai.Completion.create(
prompt=prompt,
engine=deployment_name,
# empty string suffix should be treated as None.
suffix=suffix if suffix else None,
max_tokens=int(max_tokens),
temperature=float(temperature),
top_p=float(top_p),
n=int(n),
logprobs=int(logprobs) if logprobs else None,
echo=echo,
# fix bug "[] is not valid under any of the given schemas-'stop'"
stop=stop if stop else None,
presence_penalty=float(presence_penalty),
frequency_penalty=float(frequency_penalty),
best_of=int(best_of),
# Logit bias must be a dict if we passed it to openai api.
logit_bias=logit_bias if logit_bias else {},
user=user,
request_timeout=30,
**dict(connection),
)
return response.choices[0].text
else:
chat_str = render_jinja_template(prompt, trim_blocks=True, keep_trailing_newline=True, **kwargs)
messages = parse_chat(chat_str)
response = get_client(connection).chat.completions.create(
messages=messages,
model=deployment_name,
max_tokens=int(max_tokens),
temperature=float(temperature),
top_p=float(top_p),
n=int(n),
# fix bug "[] is not valid under any of the given schemas-'stop'"
stop=stop if stop else None,
presence_penalty=float(presence_penalty),
frequency_penalty=float(frequency_penalty),
# Logit bias must be a dict if we passed it to openai api.
logit_bias=logit_bias if logit_bias else {},
user=user
)
return response.choices[0].message.content
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/basic-with-connection/data.jsonl | {"text": "Hello World!"}
{"text": "Hello PromptFlow!"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/basic-with-connection/hello.jinja2 | {# Please replace the template with your own prompt. #}
system:
You task is to generate what I ask
user:
Write a simple {{text}} program that displays the greeting message when executed.
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/basic-with-connection/flow.dag.yaml | inputs:
text:
type: string
outputs:
output_prompt:
type: string
reference: ${echo_my_prompt.output}
nodes:
- inputs:
text: ${inputs.text}
name: hello_prompt
type: prompt
source:
type: code
path: hello.jinja2
- inputs:
prompt: ${hello_prompt.output}
deployment_name: gpt-35-turbo
max_tokens: "120"
connection: azure_open_ai_connection
name: echo_my_prompt
type: python
source:
type: code
path: hello.py
node_variants: {}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/basic-with-connection/inputs.json | {}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/basic-with-connection/samples.json | [{"text": "Hello World!"}]
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/sample_flow_with_functions/run_function.py | from promptflow import tool
import json
def get_current_weather(location, unit="fahrenheit"):
"""Get the current weather in a given location"""
weather_info = {
"location": location,
"temperature": "72",
"unit": unit,
"forecast": ["sunny", "windy"],
}
return weather_info
def get_n_day_weather_forecast(location, format, num_days):
"""Get next num_days weather in a given location"""
weather_info = {
"location": location,
"temperature": "60",
"format": format,
"forecast": ["rainy"],
"num_days": num_days,
}
return weather_info
@tool
def run_function(response_message: dict) -> str:
if "function_call" in response_message:
function_name = response_message["function_call"]["name"]
function_args = json.loads(response_message["function_call"]["arguments"])
print(function_args)
result = globals()[function_name](**function_args)
else:
print("No function call")
if isinstance(response_message, dict):
result = response_message["content"]
else:
result = response_message
return result
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/sample_flow_with_functions/use_functions_with_chat_models.jinja2 | system:
Don't make assumptions about what values to plug into functions. Ask for clarification if a user request is ambiguous.
{% for item in chat_history %}
user:
{{item.inputs.question}}
{% if 'function_call' in item.outputs.llm_output %}
assistant:
Function generation requested, function = {{item.outputs.llm_output.function_call.name}}, args = {{item.outputs.llm_output.function_call.arguments}}
function:
name:
{{item.outputs.llm_output.function_call.name}}
content:
{{item.outputs.answer}}
{% else %}
assistant:
{{item.outputs.llm_output}}}}
{% endif %}}
{% endfor %}
user:
{{question}} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/sample_flow_with_functions/flow.dag.yaml | id: use_functions_with_chat_models
name: Use Functions with Chat Models
inputs:
chat_history:
type: list
default:
- inputs:
question: What is the weather like in Boston?
outputs:
answer: '{"forecast":["sunny","windy"],"location":"Boston","temperature":"72","unit":"fahrenheit"}'
llm_output:
content: null
function_call:
name: get_current_weather
arguments: |-
{
"location": "Boston"
}
role: assistant
is_chat_input: false
question:
type: string
default: How about London next week?
is_chat_input: true
outputs:
answer:
type: string
reference: ${run_function.output}
is_chat_output: true
llm_output:
type: object
reference: ${use_functions_with_chat_models.output}
nodes:
- name: run_function
type: python
source:
type: code
path: run_function.py
inputs:
response_message: ${use_functions_with_chat_models.output}
use_variants: false
- name: use_functions_with_chat_models
type: llm
source:
type: code
path: use_functions_with_chat_models.jinja2
inputs:
deployment_name: gpt-35-turbo
temperature: 0.7
top_p: 1
stop: ""
max_tokens: 256
presence_penalty: 0
frequency_penalty: 0
logit_bias: ""
functions:
- name: get_current_weather
description: Get the current weather in a given location
parameters:
type: object
properties:
location:
type: string
description: The city and state, e.g. San Francisco, CA
unit:
type: string
enum:
- celsius
- fahrenheit
required:
- location
- name: get_n_day_weather_forecast
description: Get an N-day weather forecast
parameters:
type: object
properties:
location:
type: string
description: The city and state, e.g. San Francisco, CA
format:
type: string
enum:
- celsius
- fahrenheit
description: The temperature unit to use. Infer this from the users location.
num_days:
type: integer
description: The number of days to forecast
required:
- location
- format
- num_days
function_call:
name: get_current_weather
chat_history: ${inputs.chat_history}
question: ${inputs.question}
provider: AzureOpenAI
connection: azure_open_ai_connection
api: chat
module: promptflow.tools.aoai
use_variants: false
node_variants: {}
environment:
python_requirements_txt: requirements.txt
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/sample_flow_with_functions/samples.json | [
{
"question": "How about London next week?"
}
] | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/conditional_flow_with_activate/investigation_steps.jinja2 | system:
You are a helpful assistant.
user:
When an incident occurs, there have 3 ways to deal with it, please choose one.
1. {{first_method}}
2. {{second_method}}
3. {{third_method}} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/conditional_flow_with_activate/incident_info_extractor.py | from promptflow import tool
@tool
def extract_incident_info(incident: dict) -> str:
retriever_type = ["icm", "tsg", "kql"]
return {
"retriever": retriever_type[incident["incident_id"]],
"incident_content": incident["incident_content"]
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/conditional_flow_with_activate/tsg_retriever.py | from promptflow import tool
@tool
def tsg_retriever(content: str) -> str:
return "TSG: " + content | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/conditional_flow_with_activate/job_info_extractor.py | from promptflow import tool
@tool
def extract_job_info(incident_content: str) -> str:
print(f"Incident: {incident_content}")
return "Execute job info extractor"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/conditional_flow_with_activate/investigation_method.py | from promptflow import tool
@tool
def choose_investigation_method(method1="Skip job info extractor", method2="Skip incident info extractor"):
method = {}
if method1:
method["first"] = method1
if method2:
method["second"] = method2
return method
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/conditional_flow_with_activate/retriever_summary.py | from promptflow import tool
@tool
def retriever_summary(summary) -> str:
print(f"Summary: {summary}")
return "Execute incident info extractor"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/conditional_flow_with_activate/incident_id_extractor.py | from promptflow import tool
@tool
def extract_incident_id(incident_content: str, incident_id: int):
if incident_id >= 0 and incident_id < 3:
return {
"has_incident_id": True,
"incident_id": incident_id,
"incident_content": incident_content
}
return {
"has_incident_id": False,
"incident_id": incident_id,
"incident_content": incident_content
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/conditional_flow_with_activate/icm_retriever.py | from promptflow import tool
@tool
def icm_retriever(content: str) -> str:
return "ICM: " + content | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/conditional_flow_with_activate/expected_status_summary.json | {
"incident_id_extractor.completed": 3,
"job_info_extractor.completed": 1,
"job_info_extractor.bypassed": 2,
"incident_info_extractor.completed": 2,
"incident_info_extractor.bypassed": 1,
"icm_retriever.completed": 1,
"icm_retriever.bypassed": 2,
"tsg_retriever.completed": 1,
"tsg_retriever.bypassed": 2,
"kql_tsg_retriever.completed": 1,
"kql_tsg_retriever.bypassed": 2,
"investigation_steps.completed": 2,
"investigation_steps.bypassed": 1,
"retriever_summary.completed": 2,
"retriever_summary.bypassed": 1,
"investigation_method.completed": 3
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/conditional_flow_with_activate/flow.dag.yaml | id: template_standard_flow
name: Template Standard Flow
inputs:
incident_content:
type: string
incident_id:
type: int
outputs:
investigation_method:
type: string
reference: ${investigation_method.output}
nodes:
- name: incident_id_extractor
type: python
source:
type: code
path: incident_id_extractor.py
inputs:
incident_content: ${inputs.incident_content}
incident_id: ${inputs.incident_id}
- name: job_info_extractor
type: python
source:
type: code
path: job_info_extractor.py
inputs:
incident_content: ${incident_id_extractor.output.incident_content}
activate:
when: ${incident_id_extractor.output.has_incident_id}
is: false
- name: incident_info_extractor
type: python
source:
type: code
path: incident_info_extractor.py
inputs:
incident: ${incident_id_extractor.output}
activate:
when: ${incident_id_extractor.output.has_incident_id}
is: true
- name: tsg_retriever
type: python
source:
type: code
path: tsg_retriever.py
inputs:
content: ${incident_info_extractor.output.incident_content}
activate:
when: ${incident_info_extractor.output.retriever}
is: tsg
- name: icm_retriever
type: python
source:
type: code
path: icm_retriever.py
inputs:
content: ${incident_info_extractor.output.incident_content}
activate:
when: ${incident_info_extractor.output.retriever}
is: icm
- name: kql_tsg_retriever
type: python
source:
type: code
path: kql_tsg_retriever.py
inputs:
content: ${incident_info_extractor.output.incident_content}
activate:
when: ${incident_info_extractor.output.retriever}
is: tsg
- name: investigation_steps
type: llm
source:
type: code
path: investigation_steps.jinja2
inputs:
deployment_name: gpt-35-turbo
temperature: 0.7
top_p: 1
stop: ""
max_tokens: 256
presence_penalty: 0
frequency_penalty: 0
logit_bias: ""
first_method: ${icm_retriever.output}
second_method: ${tsg_retriever.output}
third_method: ${kql_tsg_retriever.output}
provider: AzureOpenAI
connection: azure_open_ai_connection
api: chat
module: promptflow.tools.aoai
- name: retriever_summary
type: python
source:
type: code
path: retriever_summary.py
inputs:
summary: ${investigation_steps.output}
- name: investigation_method
type: python
source:
type: code
path: investigation_method.py
inputs:
method1: ${job_info_extractor.output}
method2: ${retriever_summary.output}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/conditional_flow_with_activate/inputs.json | [
{
"incident_id": 1,
"incident_content": "Incident 418856448 : Stale App Deployment for App promptflow"
},
{
"incident_id": 3,
"incident_content": "Incident 418856448 : Stale App Deployment for App promptflow"
},
{
"incident_id": 0,
"incident_content": "Incident 418856448 : Stale App Deployment for App promptflow"
}
] | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/conditional_flow_with_activate/expected_result.json | [
{
"expected_node_count": 9,
"expected_outputs":{
"investigation_method": {
"first": "Skip job info extractor",
"second": "Execute incident info extractor"
}
},
"expected_bypassed_nodes":["job_info_extractor", "icm_retriever"]
},
{
"expected_node_count": 9,
"expected_outputs":{
"investigation_method": {
"first": "Execute job info extractor",
"second": "Skip incident info extractor"
}
},
"expected_bypassed_nodes":["incident_info_extractor", "icm_retriever", "kql_tsg_retriever", "tsg_retriever", "investigation_steps", "retriever_summary"]
},
{
"expected_node_count": 9,
"expected_outputs":{
"investigation_method": {
"first": "Skip job info extractor",
"second": "Execute incident info extractor"
}
},
"expected_bypassed_nodes":["job_info_extractor", "kql_tsg_retriever", "tsg_retriever"]
}
] | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/conditional_flow_with_activate/kql_tsg_retriever.py | from promptflow import tool
@tool
def kql_retriever(content: str) -> str:
return "KQL: " + content | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/custom_connection_flow/flow.dag.yaml | inputs:
key:
type: string
outputs:
output:
type: string
reference: ${print_env.output.value}
nodes:
- name: print_env
type: python
source:
type: code
path: print_env.py
inputs:
key: ${inputs.key}
connection: custom_connection
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/custom_connection_flow/print_env.py | import os
from promptflow import tool
from promptflow.connections import CustomConnection
@tool
def get_env_var(key: str, connection: CustomConnection):
# get from env var
return {"value": os.environ.get(key)}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/custom_connection_flow | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/custom_connection_flow/.promptflow/flow.tools.json | {
"package": {},
"code": {
"print_env.py": {
"type": "python",
"inputs": {
"key": {
"type": [
"string"
]
}
},
"function": "get_env_var"
}
}
}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs | promptflow_repo/promptflow/src/promptflow/tests/test_configs/recordings/test_run_operations_TestFlowRun_test_input_mapping_with_dict.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":
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"tier": "Basic"}, "properties": {"discoveryUrl": "https://eastus.api.azureml.ms/discovery"}}'
headers:
cache-control:
- no-cache
content-length:
- '3630'
content-type:
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expires:
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pragma:
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strict-transport-security:
- max-age=31536000; includeSubDomains
transfer-encoding:
- chunked
vary:
- Accept-Encoding,Accept-Encoding
x-content-type-options:
- nosniff
x-request-time:
- '0.028'
status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
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- keep-alive
User-Agent:
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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",
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"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
"https", "serviceDataAccessAuthIdentity": "WorkspaceSystemAssignedIdentity"},
"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
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headers:
cache-control:
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content-length:
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content-type:
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expires:
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pragma:
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strict-transport-security:
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status:
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message: OK
- request:
body: null
headers:
Accept:
- application/json
Accept-Encoding:
- gzip, deflate
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- keep-alive
User-Agent:
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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",
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"containerName": "fake-container-name", "endpoint": "core.windows.net", "protocol":
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"systemData": {"createdAt": "2023-04-08T02:53:06.5886442+00:00", "createdBy":
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"is_builtin": true, "package": "promptflow-tools", "package_version": "1.1.0rc2",
"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":
"1.1.0rc2", "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": "1.1.0rc2", "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": "1.1.0rc2",
"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": "1.1.0rc2",
"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": "1.1.0rc2",
"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":
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"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":
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"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":
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false, "input_type": "default"}, "model": {"type": ["string"], "enum": ["text-embedding-ada-002",
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"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":
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"package": "promptflow-tools", "package_version": "1.1.0rc2", "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": "1.1.0rc2",
"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": "1.1.0rc2",
"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": "1.1.0rc2",
"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",
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"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":
"1.1.0rc2", "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": "1.1.0rc2", "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": "1.1.0rc2",
"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": "1.1.0rc2",
"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": "1.1.0rc2",
"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,
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"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}",
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| 0 |
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