status
stringclasses 1
value | repo_name
stringclasses 31
values | repo_url
stringclasses 31
values | issue_id
int64 1
104k
| title
stringlengths 4
233
| body
stringlengths 0
186k
⌀ | issue_url
stringlengths 38
56
| pull_url
stringlengths 37
54
| before_fix_sha
stringlengths 40
40
| after_fix_sha
stringlengths 40
40
| report_datetime
unknown | language
stringclasses 5
values | commit_datetime
unknown | updated_file
stringlengths 7
188
| chunk_content
stringlengths 1
1.03M
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 7,034 | Loading online PDFs gives temporary file path as source in metadata | Hi,
first up, thank you for making langchain! I was playing around a little and found a minor issue with loading online PDFs, and would like to start contributing to langchain maybe by fixing this.
### System Info
langchain 0.0.220, google collab, python 3.10
### Who can help?
_No response_
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [X] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
```python
from langchain.document_loaders import PyMuPDFLoader
loader = PyMuPDFLoader('https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf')
pages = loader.load()
pages[0].metadata
```
<img width="977" alt="image" src="https://github.com/hwchase17/langchain/assets/21276922/4ededc60-bb03-4502-a8c8-3c221ab109c4">
### Expected behavior
Instead of giving the temporary file path, which is not useful and deleted shortly after, it could be more helpful if the source is set to be the URL passed to it. This would require some fixes in the `langchain/document_loaders/pdf.py` file. | https://github.com/langchain-ai/langchain/issues/7034 | https://github.com/langchain-ai/langchain/pull/13274 | 6f64cb5078bb71007d25fff847541fd8f7713c0c | 9bd6e9df365e966938979511237c035a02fb4fa9 | "2023-07-01T23:24:53Z" | python | "2023-11-29T20:07:46Z" | libs/langchain/langchain/document_loaders/pdf.py | """Load file."""
parser = PDFPlumberParser(
text_kwargs=self.text_kwargs,
dedupe=self.dedupe,
extract_images=self.extract_images,
)
blob = Blob.from_path(self.file_path)
return parser.parse(blob)
class AmazonTextractPDFLoader(BasePDFLoader):
"""Load `PDF` files from a local file system, HTTP or S3.
To authenticate, the AWS client uses the following methods to
automatically load credentials:
https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html
If a specific credential profile should be used, you must pass
the name of the profile from the ~/.aws/credentials file that is to be used.
Make sure the credentials / roles used have the required policies to
access the Amazon Textract service.
Example:
.. code-block:: python
from langchain.document_loaders import AmazonTextractPDFLoader
loader = AmazonTextractPDFLoader(
file_path="s3://pdfs/myfile.pdf"
)
document = loader.load()
"""
def __init__( |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 7,034 | Loading online PDFs gives temporary file path as source in metadata | Hi,
first up, thank you for making langchain! I was playing around a little and found a minor issue with loading online PDFs, and would like to start contributing to langchain maybe by fixing this.
### System Info
langchain 0.0.220, google collab, python 3.10
### Who can help?
_No response_
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [X] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
```python
from langchain.document_loaders import PyMuPDFLoader
loader = PyMuPDFLoader('https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf')
pages = loader.load()
pages[0].metadata
```
<img width="977" alt="image" src="https://github.com/hwchase17/langchain/assets/21276922/4ededc60-bb03-4502-a8c8-3c221ab109c4">
### Expected behavior
Instead of giving the temporary file path, which is not useful and deleted shortly after, it could be more helpful if the source is set to be the URL passed to it. This would require some fixes in the `langchain/document_loaders/pdf.py` file. | https://github.com/langchain-ai/langchain/issues/7034 | https://github.com/langchain-ai/langchain/pull/13274 | 6f64cb5078bb71007d25fff847541fd8f7713c0c | 9bd6e9df365e966938979511237c035a02fb4fa9 | "2023-07-01T23:24:53Z" | python | "2023-11-29T20:07:46Z" | libs/langchain/langchain/document_loaders/pdf.py | self,
file_path: str,
textract_features: Optional[Sequence[str]] = None,
client: Optional[Any] = None,
credentials_profile_name: Optional[str] = None,
region_name: Optional[str] = None,
endpoint_url: Optional[str] = None,
headers: Optional[Dict] = None,
) -> None:
"""Initialize the loader.
Args:
file_path: A file, url or s3 path for input file
textract_features: Features to be used for extraction, each feature
should be passed as a str that conforms to the enum
`Textract_Features`, see `amazon-textract-caller` pkg
client: boto3 textract client (Optional)
credentials_profile_name: AWS profile name, if not default (Optional)
region_name: AWS region, eg us-east-1 (Optional)
endpoint_url: endpoint url for the textract service (Optional)
"""
super().__init__(file_path, headers=headers)
try:
import textractcaller as tc
except ImportError:
raise ModuleNotFoundError(
"Could not import amazon-textract-caller python package. "
"Please install it with `pip install amazon-textract-caller`."
)
if textract_features: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 7,034 | Loading online PDFs gives temporary file path as source in metadata | Hi,
first up, thank you for making langchain! I was playing around a little and found a minor issue with loading online PDFs, and would like to start contributing to langchain maybe by fixing this.
### System Info
langchain 0.0.220, google collab, python 3.10
### Who can help?
_No response_
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [X] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
```python
from langchain.document_loaders import PyMuPDFLoader
loader = PyMuPDFLoader('https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf')
pages = loader.load()
pages[0].metadata
```
<img width="977" alt="image" src="https://github.com/hwchase17/langchain/assets/21276922/4ededc60-bb03-4502-a8c8-3c221ab109c4">
### Expected behavior
Instead of giving the temporary file path, which is not useful and deleted shortly after, it could be more helpful if the source is set to be the URL passed to it. This would require some fixes in the `langchain/document_loaders/pdf.py` file. | https://github.com/langchain-ai/langchain/issues/7034 | https://github.com/langchain-ai/langchain/pull/13274 | 6f64cb5078bb71007d25fff847541fd8f7713c0c | 9bd6e9df365e966938979511237c035a02fb4fa9 | "2023-07-01T23:24:53Z" | python | "2023-11-29T20:07:46Z" | libs/langchain/langchain/document_loaders/pdf.py | features = [tc.Textract_Features[x] for x in textract_features]
else:
features = []
if credentials_profile_name or region_name or endpoint_url:
try:
import boto3
if credentials_profile_name is not None:
session = boto3.Session(profile_name=credentials_profile_name)
else:
session = boto3.Session()
client_params = {}
if region_name:
client_params["region_name"] = region_name
if endpoint_url:
client_params["endpoint_url"] = endpoint_url
client = session.client("textract", **client_params)
except ImportError:
raise ModuleNotFoundError(
"Could not import boto3 python package. "
"Please install it with `pip install boto3`."
)
except Exception as e:
raise ValueError(
"Could not load credentials to authenticate with AWS client. "
"Please check that credentials in the specified "
"profile name are valid."
) from e
self.parser = AmazonTextractPDFParser(textract_features=features, client=client)
def load(self) -> List[Document]: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 7,034 | Loading online PDFs gives temporary file path as source in metadata | Hi,
first up, thank you for making langchain! I was playing around a little and found a minor issue with loading online PDFs, and would like to start contributing to langchain maybe by fixing this.
### System Info
langchain 0.0.220, google collab, python 3.10
### Who can help?
_No response_
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [X] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
```python
from langchain.document_loaders import PyMuPDFLoader
loader = PyMuPDFLoader('https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf')
pages = loader.load()
pages[0].metadata
```
<img width="977" alt="image" src="https://github.com/hwchase17/langchain/assets/21276922/4ededc60-bb03-4502-a8c8-3c221ab109c4">
### Expected behavior
Instead of giving the temporary file path, which is not useful and deleted shortly after, it could be more helpful if the source is set to be the URL passed to it. This would require some fixes in the `langchain/document_loaders/pdf.py` file. | https://github.com/langchain-ai/langchain/issues/7034 | https://github.com/langchain-ai/langchain/pull/13274 | 6f64cb5078bb71007d25fff847541fd8f7713c0c | 9bd6e9df365e966938979511237c035a02fb4fa9 | "2023-07-01T23:24:53Z" | python | "2023-11-29T20:07:46Z" | libs/langchain/langchain/document_loaders/pdf.py | """Load given path as pages."""
return list(self.lazy_load())
def lazy_load(
self,
) -> Iterator[Document]:
"""Lazy load documents"""
if self.web_path and self._is_s3_url(self.web_path):
blob = Blob(path=self.web_path)
else:
blob = Blob.from_path(self.file_path)
if AmazonTextractPDFLoader._get_number_of_pages(blob) > 1:
raise ValueError(
f"the file {blob.path} is a multi-page document, \
but not stored on S3. \
Textract requires multi-page documents to be on S3."
)
yield from self.parser.parse(blob)
@staticmethod
def _get_number_of_pages(blob: Blob) -> int: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 7,034 | Loading online PDFs gives temporary file path as source in metadata | Hi,
first up, thank you for making langchain! I was playing around a little and found a minor issue with loading online PDFs, and would like to start contributing to langchain maybe by fixing this.
### System Info
langchain 0.0.220, google collab, python 3.10
### Who can help?
_No response_
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [X] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
```python
from langchain.document_loaders import PyMuPDFLoader
loader = PyMuPDFLoader('https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf')
pages = loader.load()
pages[0].metadata
```
<img width="977" alt="image" src="https://github.com/hwchase17/langchain/assets/21276922/4ededc60-bb03-4502-a8c8-3c221ab109c4">
### Expected behavior
Instead of giving the temporary file path, which is not useful and deleted shortly after, it could be more helpful if the source is set to be the URL passed to it. This would require some fixes in the `langchain/document_loaders/pdf.py` file. | https://github.com/langchain-ai/langchain/issues/7034 | https://github.com/langchain-ai/langchain/pull/13274 | 6f64cb5078bb71007d25fff847541fd8f7713c0c | 9bd6e9df365e966938979511237c035a02fb4fa9 | "2023-07-01T23:24:53Z" | python | "2023-11-29T20:07:46Z" | libs/langchain/langchain/document_loaders/pdf.py | try:
import pypdf
from PIL import Image, ImageSequence
except ImportError:
raise ModuleNotFoundError(
"Could not import pypdf or Pilloe python package. "
"Please install it with `pip install pypdf Pillow`."
)
if blob.mimetype == "application/pdf":
with blob.as_bytes_io() as input_pdf_file:
pdf_reader = pypdf.PdfReader(input_pdf_file)
return len(pdf_reader.pages)
elif blob.mimetype == "image/tiff":
num_pages = 0
img = Image.open(blob.as_bytes())
for _, _ in enumerate(ImageSequence.Iterator(img)):
num_pages += 1
return num_pages
elif blob.mimetype in ["image/png", "image/jpeg"]:
return 1
else:
raise ValueError(f"unsupported mime type: {blob.mimetype}")
class DocumentIntelligenceLoader(BasePDFLoader): |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 7,034 | Loading online PDFs gives temporary file path as source in metadata | Hi,
first up, thank you for making langchain! I was playing around a little and found a minor issue with loading online PDFs, and would like to start contributing to langchain maybe by fixing this.
### System Info
langchain 0.0.220, google collab, python 3.10
### Who can help?
_No response_
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [X] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
```python
from langchain.document_loaders import PyMuPDFLoader
loader = PyMuPDFLoader('https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf')
pages = loader.load()
pages[0].metadata
```
<img width="977" alt="image" src="https://github.com/hwchase17/langchain/assets/21276922/4ededc60-bb03-4502-a8c8-3c221ab109c4">
### Expected behavior
Instead of giving the temporary file path, which is not useful and deleted shortly after, it could be more helpful if the source is set to be the URL passed to it. This would require some fixes in the `langchain/document_loaders/pdf.py` file. | https://github.com/langchain-ai/langchain/issues/7034 | https://github.com/langchain-ai/langchain/pull/13274 | 6f64cb5078bb71007d25fff847541fd8f7713c0c | 9bd6e9df365e966938979511237c035a02fb4fa9 | "2023-07-01T23:24:53Z" | python | "2023-11-29T20:07:46Z" | libs/langchain/langchain/document_loaders/pdf.py | """Loads a PDF with Azure Document Intelligence"""
def __init__(
self,
file_path: str,
client: Any,
model: str = "prebuilt-document",
headers: Optional[Dict] = None,
) -> None:
"""
Initialize the object for file processing with Azure Document Intelligence
(formerly Form Recognizer).
This constructor initializes a DocumentIntelligenceParser object to be used
for parsing files using the Azure Document Intelligence API. The load method |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 7,034 | Loading online PDFs gives temporary file path as source in metadata | Hi,
first up, thank you for making langchain! I was playing around a little and found a minor issue with loading online PDFs, and would like to start contributing to langchain maybe by fixing this.
### System Info
langchain 0.0.220, google collab, python 3.10
### Who can help?
_No response_
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [X] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
```python
from langchain.document_loaders import PyMuPDFLoader
loader = PyMuPDFLoader('https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf')
pages = loader.load()
pages[0].metadata
```
<img width="977" alt="image" src="https://github.com/hwchase17/langchain/assets/21276922/4ededc60-bb03-4502-a8c8-3c221ab109c4">
### Expected behavior
Instead of giving the temporary file path, which is not useful and deleted shortly after, it could be more helpful if the source is set to be the URL passed to it. This would require some fixes in the `langchain/document_loaders/pdf.py` file. | https://github.com/langchain-ai/langchain/issues/7034 | https://github.com/langchain-ai/langchain/pull/13274 | 6f64cb5078bb71007d25fff847541fd8f7713c0c | 9bd6e9df365e966938979511237c035a02fb4fa9 | "2023-07-01T23:24:53Z" | python | "2023-11-29T20:07:46Z" | libs/langchain/langchain/document_loaders/pdf.py | generates a Document node including metadata (source blob and page number)
for each page.
Parameters:
-----------
file_path : str
The path to the file that needs to be parsed.
client: Any
A DocumentAnalysisClient to perform the analysis of the blob
model : str
The model name or ID to be used for form recognition in Azure.
Examples:
---------
>>> obj = DocumentIntelligenceLoader(
... file_path="path/to/file",
... client=client,
... model="prebuilt-document"
... )
"""
self.parser = DocumentIntelligenceParser(client=client, model=model)
super().__init__(file_path, headers=headers)
def load(self) -> List[Document]:
"""Load given path as pages."""
return list(self.lazy_load())
def lazy_load(
self,
) -> Iterator[Document]:
"""Lazy load given path as pages."""
blob = Blob.from_path(self.file_path)
yield from self.parser.parse(blob) |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | """Tools provide access to various resources and services.
LangChain has a large ecosystem of integrations with various external resources
like local and remote file systems, APIs and databases.
These integrations allow developers to create versatile applications that combine the
power of LLMs with the ability to access, interact with and manipulate external
resources.
When developing an application, developers should inspect the capabilities and
permissions of the tools that underlie the given agent toolkit, and determine
whether permissions of the given toolkit are appropriate for the application.
See [Security](https://python.langchain.com/docs/security) for more information.
"""
import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain.agents.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain.callbacks.base import BaseCallbackManager
from langchain.callbacks.manager import Callbacks
from langchain.chains.api import news_docs, open_meteo_docs, podcast_docs, tmdb_docs
from langchain.chains.api.base import APIChain
from langchain.chains.llm_math.base import LLMMathChain
from langchain.utilities.dalle_image_generator import DallEAPIWrapper
from langchain.utilities.requests import TextRequestsWrapper
from langchain.tools.arxiv.tool import ArxivQueryRun
from langchain.tools.golden_query.tool import GoldenQueryRun
from langchain.tools.pubmed.tool import PubmedQueryRun
from langchain.tools.base import BaseTool |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | from langchain.tools.bing_search.tool import BingSearchRun
from langchain.tools.ddg_search.tool import DuckDuckGoSearchRun
from langchain.tools.google_cloud.texttospeech import GoogleCloudTextToSpeechTool
from langchain.tools.google_lens.tool import GoogleLensQueryRun
from langchain.tools.google_search.tool import GoogleSearchResults, GoogleSearchRun
from langchain.tools.google_scholar.tool import GoogleScholarQueryRun
from langchain.tools.google_finance.tool import GoogleFinanceQueryRun
from langchain.tools.google_trends.tool import GoogleTrendsQueryRun
from langchain.tools.metaphor_search.tool import MetaphorSearchResults
from langchain.tools.google_jobs.tool import GoogleJobsQueryRun
from langchain.tools.google_serper.tool import GoogleSerperResults, GoogleSerperRun
from langchain.tools.searchapi.tool import SearchAPIResults, SearchAPIRun
from langchain.tools.graphql.tool import BaseGraphQLTool
from langchain.tools.human.tool import HumanInputRun
from langchain.tools.requests.tool import (
RequestsDeleteTool,
RequestsGetTool,
RequestsPatchTool,
RequestsPostTool,
RequestsPutTool,
)
from langchain.tools.eleven_labs.text2speech import ElevenLabsText2SpeechTool
from langchain.tools.scenexplain.tool import SceneXplainTool
from langchain.tools.searx_search.tool import SearxSearchResults, SearxSearchRun
from langchain.tools.shell.tool import ShellTool
from langchain.tools.sleep.tool import SleepTool
from langchain.tools.stackexchange.tool import StackExchangeTool
from langchain.tools.wikipedia.tool import WikipediaQueryRun
from langchain.tools.wolfram_alpha.tool import WolframAlphaQueryRun
from langchain.tools.openweathermap.tool import OpenWeatherMapQueryRun |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | from langchain.tools.dataforseo_api_search import DataForSeoAPISearchRun
from langchain.tools.dataforseo_api_search import DataForSeoAPISearchResults
from langchain.tools.memorize.tool import Memorize
from langchain.tools.reddit_search.tool import RedditSearchRun
from langchain.utilities.arxiv import ArxivAPIWrapper
from langchain.utilities.golden_query import GoldenQueryAPIWrapper
from langchain.utilities.pubmed import PubMedAPIWrapper
from langchain.utilities.bing_search import BingSearchAPIWrapper
from langchain.utilities.duckduckgo_search import DuckDuckGoSearchAPIWrapper
from langchain.utilities.google_lens import GoogleLensAPIWrapper
from langchain.utilities.google_jobs import GoogleJobsAPIWrapper
from langchain.utilities.google_search import GoogleSearchAPIWrapper
from langchain.utilities.google_serper import GoogleSerperAPIWrapper
from langchain.utilities.google_scholar import GoogleScholarAPIWrapper
from langchain.utilities.google_finance import GoogleFinanceAPIWrapper
from langchain.utilities.google_trends import GoogleTrendsAPIWrapper
from langchain.utilities.metaphor_search import MetaphorSearchAPIWrapper
from langchain.utilities.awslambda import LambdaWrapper
from langchain.utilities.graphql import GraphQLAPIWrapper
from langchain.utilities.searchapi import SearchApiAPIWrapper
from langchain.utilities.searx_search import SearxSearchWrapper
from langchain.utilities.serpapi import SerpAPIWrapper
from langchain.utilities.stackexchange import StackExchangeAPIWrapper
from langchain.utilities.twilio import TwilioAPIWrapper
from langchain.utilities.wikipedia import WikipediaAPIWrapper
from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper
from langchain.utilities.openweathermap import OpenWeatherMapAPIWrapper
from langchain.utilities.dataforseo_api_search import DataForSeoAPIWrapper
from langchain.utilities.reddit_search import RedditSearchAPIWrapper
def _get_python_repl() -> BaseTool: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | raise ImportError(
"This tool has been moved to langchain experiment. "
"This tool has access to a python REPL. "
"For best practices make sure to sandbox this tool. "
"Read https://github.com/langchain-ai/langchain/blob/master/SECURITY.md "
"To keep using this code as is, install langchain experimental and "
"update relevant imports replacing 'langchain' with 'langchain_experimental'"
)
def _get_tools_requests_get() -> BaseTool: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | return RequestsGetTool(requests_wrapper=TextRequestsWrapper())
def _get_tools_requests_post() -> BaseTool:
return RequestsPostTool(requests_wrapper=TextRequestsWrapper())
def _get_tools_requests_patch() -> BaseTool:
return RequestsPatchTool(requests_wrapper=TextRequestsWrapper())
def _get_tools_requests_put() -> BaseTool:
return RequestsPutTool(requests_wrapper=TextRequestsWrapper())
def _get_tools_requests_delete() -> BaseTool:
return RequestsDeleteTool(requests_wrapper=TextRequestsWrapper())
def _get_terminal() -> BaseTool:
return ShellTool()
def _get_sleep() -> BaseTool:
return SleepTool()
_BASE_TOOLS: Dict[str, Callable[[], BaseTool]] = {
"requests": _get_tools_requests_get,
"requests_get": _get_tools_requests_get,
"requests_post": _get_tools_requests_post,
"requests_patch": _get_tools_requests_patch,
"requests_put": _get_tools_requests_put,
"requests_delete": _get_tools_requests_delete,
"terminal": _get_terminal,
"sleep": _get_sleep,
}
def _get_llm_math(llm: BaseLanguageModel) -> BaseTool: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | return Tool(
name="Calculator",
description="Useful for when you need to answer questions about math.",
func=LLMMathChain.from_llm(llm=llm).run,
coroutine=LLMMathChain.from_llm(llm=llm).arun,
)
def _get_open_meteo_api(llm: BaseLanguageModel) -> BaseTool:
chain = APIChain.from_llm_and_api_docs(
llm,
open_meteo_docs.OPEN_METEO_DOCS,
limit_to_domains=["https://api.open-meteo.com/"],
)
return Tool(
name="Open-Meteo-API",
description="Useful for when you want to get weather information from the OpenMeteo API. The input should be a question in natural language that this API can answer.",
func=chain.run,
)
_LLM_TOOLS: Dict[str, Callable[[BaseLanguageModel], BaseTool]] = {
"llm-math": _get_llm_math,
"open-meteo-api": _get_open_meteo_api,
}
def _get_news_api(llm: BaseLanguageModel, **kwargs: Any) -> BaseTool: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | news_api_key = kwargs["news_api_key"]
chain = APIChain.from_llm_and_api_docs(
llm,
news_docs.NEWS_DOCS,
headers={"X-Api-Key": news_api_key},
limit_to_domains=["https://newsapi.org/"],
)
return Tool(
name="News-API",
description="Use this when you want to get information about the top headlines of current news stories. The input should be a question in natural language that this API can answer.",
func=chain.run,
)
def _get_tmdb_api(llm: BaseLanguageModel, **kwargs: Any) -> BaseTool:
tmdb_bearer_token = kwargs["tmdb_bearer_token"]
chain = APIChain.from_llm_and_api_docs(
llm,
tmdb_docs.TMDB_DOCS,
headers={"Authorization": f"Bearer {tmdb_bearer_token}"},
limit_to_domains=["https://api.themoviedb.org/"],
)
return Tool(
name="TMDB-API",
description="Useful for when you want to get information from The Movie Database. The input should be a question in natural language that this API can answer.",
func=chain.run,
)
def _get_podcast_api(llm: BaseLanguageModel, **kwargs: Any) -> BaseTool: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | listen_api_key = kwargs["listen_api_key"]
chain = APIChain.from_llm_and_api_docs(
llm,
podcast_docs.PODCAST_DOCS,
headers={"X-ListenAPI-Key": listen_api_key},
limit_to_domains=["https://listen-api.listennotes.com/"],
)
return Tool(
name="Podcast-API",
description="Use the Listen Notes Podcast API to search all podcasts or episodes. The input should be a question in natural language that this API can answer.",
func=chain.run,
)
def _get_lambda_api(**kwargs: Any) -> BaseTool:
return Tool(
name=kwargs["awslambda_tool_name"],
description=kwargs["awslambda_tool_description"],
func=LambdaWrapper(**kwargs).run,
)
def _get_wolfram_alpha(**kwargs: Any) -> BaseTool: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | return WolframAlphaQueryRun(api_wrapper=WolframAlphaAPIWrapper(**kwargs))
def _get_google_search(**kwargs: Any) -> BaseTool:
return GoogleSearchRun(api_wrapper=GoogleSearchAPIWrapper(**kwargs))
def _get_wikipedia(**kwargs: Any) -> BaseTool:
return WikipediaQueryRun(api_wrapper=WikipediaAPIWrapper(**kwargs))
def _get_arxiv(**kwargs: Any) -> BaseTool:
return ArxivQueryRun(api_wrapper=ArxivAPIWrapper(**kwargs))
def _get_golden_query(**kwargs: Any) -> BaseTool:
return GoldenQueryRun(api_wrapper=GoldenQueryAPIWrapper(**kwargs))
def _get_pubmed(**kwargs: Any) -> BaseTool:
return PubmedQueryRun(api_wrapper=PubMedAPIWrapper(**kwargs))
def _get_google_jobs(**kwargs: Any) -> BaseTool:
return GoogleJobsQueryRun(api_wrapper=GoogleJobsAPIWrapper(**kwargs))
def _get_google_lens(**kwargs: Any) -> BaseTool:
return GoogleLensQueryRun(api_wrapper=GoogleLensAPIWrapper(**kwargs))
def _get_google_serper(**kwargs: Any) -> BaseTool:
return GoogleSerperRun(api_wrapper=GoogleSerperAPIWrapper(**kwargs))
def _get_google_scholar(**kwargs: Any) -> BaseTool:
return GoogleScholarQueryRun(api_wrapper=GoogleScholarAPIWrapper(**kwargs))
def _get_google_finance(**kwargs: Any) -> BaseTool:
return GoogleFinanceQueryRun(api_wrapper=GoogleFinanceAPIWrapper(**kwargs))
def _get_google_trends(**kwargs: Any) -> BaseTool:
return GoogleTrendsQueryRun(api_wrapper=GoogleTrendsAPIWrapper(**kwargs))
def _get_google_serper_results_json(**kwargs: Any) -> BaseTool: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | return GoogleSerperResults(api_wrapper=GoogleSerperAPIWrapper(**kwargs))
def _get_google_search_results_json(**kwargs: Any) -> BaseTool:
return GoogleSearchResults(api_wrapper=GoogleSearchAPIWrapper(**kwargs))
def _get_searchapi(**kwargs: Any) -> BaseTool:
return SearchAPIRun(api_wrapper=SearchApiAPIWrapper(**kwargs))
def _get_searchapi_results_json(**kwargs: Any) -> BaseTool:
return SearchAPIResults(api_wrapper=SearchApiAPIWrapper(**kwargs))
def _get_serpapi(**kwargs: Any) -> BaseTool:
return Tool(
name="Search",
description="A search engine. Useful for when you need to answer questions about current events. Input should be a search query.",
func=SerpAPIWrapper(**kwargs).run,
coroutine=SerpAPIWrapper(**kwargs).arun,
)
def _get_stackexchange(**kwargs: Any) -> BaseTool:
return StackExchangeTool(api_wrapper=StackExchangeAPIWrapper(**kwargs))
def _get_dalle_image_generator(**kwargs: Any) -> Tool:
return Tool(
"Dall-E-Image-Generator",
DallEAPIWrapper(**kwargs).run,
"A wrapper around OpenAI DALL-E API. Useful for when you need to generate images from a text description. Input should be an image description.",
)
def _get_twilio(**kwargs: Any) -> BaseTool:
return Tool(
name="Text-Message",
description="Useful for when you need to send a text message to a provided phone number.",
func=TwilioAPIWrapper(**kwargs).run,
)
def _get_searx_search(**kwargs: Any) -> BaseTool: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | return SearxSearchRun(wrapper=SearxSearchWrapper(**kwargs))
def _get_searx_search_results_json(**kwargs: Any) -> BaseTool:
wrapper_kwargs = {k: v for k, v in kwargs.items() if k != "num_results"}
return SearxSearchResults(wrapper=SearxSearchWrapper(**wrapper_kwargs), **kwargs)
def _get_bing_search(**kwargs: Any) -> BaseTool:
return BingSearchRun(api_wrapper=BingSearchAPIWrapper(**kwargs))
def _get_metaphor_search(**kwargs: Any) -> BaseTool:
return MetaphorSearchResults(api_wrapper=MetaphorSearchAPIWrapper(**kwargs))
def _get_ddg_search(**kwargs: Any) -> BaseTool:
return DuckDuckGoSearchRun(api_wrapper=DuckDuckGoSearchAPIWrapper(**kwargs))
def _get_human_tool(**kwargs: Any) -> BaseTool:
return HumanInputRun(**kwargs)
def _get_scenexplain(**kwargs: Any) -> BaseTool:
return SceneXplainTool(**kwargs)
def _get_graphql_tool(**kwargs: Any) -> BaseTool:
graphql_endpoint = kwargs["graphql_endpoint"]
wrapper = GraphQLAPIWrapper(graphql_endpoint=graphql_endpoint)
return BaseGraphQLTool(graphql_wrapper=wrapper)
def _get_openweathermap(**kwargs: Any) -> BaseTool:
return OpenWeatherMapQueryRun(api_wrapper=OpenWeatherMapAPIWrapper(**kwargs))
def _get_dataforseo_api_search(**kwargs: Any) -> BaseTool:
return DataForSeoAPISearchRun(api_wrapper=DataForSeoAPIWrapper(**kwargs))
def _get_dataforseo_api_search_json(**kwargs: Any) -> BaseTool:
return DataForSeoAPISearchResults(api_wrapper=DataForSeoAPIWrapper(**kwargs))
def _get_eleven_labs_text2speech(**kwargs: Any) -> BaseTool:
return ElevenLabsText2SpeechTool(**kwargs)
def _get_memorize(llm: BaseLanguageModel, **kwargs: Any) -> BaseTool:
return Memorize(llm=llm)
def _get_google_cloud_texttospeech(**kwargs: Any) -> BaseTool: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | return GoogleCloudTextToSpeechTool(**kwargs)
def _get_reddit_search(**kwargs: Any) -> BaseTool:
return RedditSearchRun(api_wrapper=RedditSearchAPIWrapper(**kwargs))
_EXTRA_LLM_TOOLS: Dict[
str,
Tuple[Callable[[Arg(BaseLanguageModel, "llm"), KwArg(Any)], BaseTool], List[str]],
] = {
"news-api": (_get_news_api, ["news_api_key"]),
"tmdb-api": (_get_tmdb_api, ["tmdb_bearer_token"]),
"podcast-api": (_get_podcast_api, ["listen_api_key"]),
"memorize": (_get_memorize, []),
}
_EXTRA_OPTIONAL_TOOLS: Dict[str, Tuple[Callable[[KwArg(Any)], BaseTool], List[str]]] = {
"wolfram-alpha": (_get_wolfram_alpha, ["wolfram_alpha_appid"]),
"google-search": (_get_google_search, ["google_api_key", "google_cse_id"]),
"google-search-results-json": (
_get_google_search_results_json,
["google_api_key", "google_cse_id", "num_results"],
),
"searx-search-results-json": (
_get_searx_search_results_json,
["searx_host", "engines", "num_results", "aiosession"],
),
"bing-search": (_get_bing_search, ["bing_subscription_key", "bing_search_url"]),
"metaphor-search": (_get_metaphor_search, ["metaphor_api_key"]),
"ddg-search": (_get_ddg_search, []),
"google-lens": (_get_google_lens, ["serp_api_key"]),
"google-serper": (_get_google_serper, ["serper_api_key", "aiosession"]),
"google-scholar": ( |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | _get_google_scholar,
["top_k_results", "hl", "lr", "serp_api_key"],
),
"google-finance": (
_get_google_finance,
["serp_api_key"],
),
"google-trends": (
_get_google_trends,
["serp_api_key"],
),
"google-jobs": (
_get_google_jobs,
["serp_api_key"],
),
"google-serper-results-json": (
_get_google_serper_results_json,
["serper_api_key", "aiosession"],
),
"searchapi": (_get_searchapi, ["searchapi_api_key", "aiosession"]),
"searchapi-results-json": (
_get_searchapi_results_json,
["searchapi_api_key", "aiosession"],
),
"serpapi": (_get_serpapi, ["serpapi_api_key", "aiosession"]),
"dalle-image-generator": (_get_dalle_image_generator, ["openai_api_key"]),
"twilio": (_get_twilio, ["account_sid", "auth_token", "from_number"]),
"searx-search": (_get_searx_search, ["searx_host", "engines", "aiosession"]),
"wikipedia": (_get_wikipedia, ["top_k_results", "lang"]),
"arxiv": ( |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | _get_arxiv,
["top_k_results", "load_max_docs", "load_all_available_meta"],
),
"golden-query": (_get_golden_query, ["golden_api_key"]),
"pubmed": (_get_pubmed, ["top_k_results"]),
"human": (_get_human_tool, ["prompt_func", "input_func"]),
"awslambda": (
_get_lambda_api,
["awslambda_tool_name", "awslambda_tool_description", "function_name"],
),
"stackexchange": (_get_stackexchange, []),
"sceneXplain": (_get_scenexplain, []),
"graphql": (_get_graphql_tool, ["graphql_endpoint"]),
"openweathermap-api": (_get_openweathermap, ["openweathermap_api_key"]),
"dataforseo-api-search": (
_get_dataforseo_api_search,
["api_login", "api_password", "aiosession"],
),
"dataforseo-api-search-json": (
_get_dataforseo_api_search_json,
["api_login", "api_password", "aiosession"],
),
"eleven_labs_text2speech": (_get_eleven_labs_text2speech, ["eleven_api_key"]),
"google_cloud_texttospeech": (_get_google_cloud_texttospeech, []),
"reddit_search": (
_get_reddit_search,
["reddit_client_id", "reddit_client_secret", "reddit_user_agent"],
),
}
def _handle_callbacks( |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | callback_manager: Optional[BaseCallbackManager], callbacks: Callbacks
) -> Callbacks:
if callback_manager is not None:
warnings.warn(
"callback_manager is deprecated. Please use callbacks instead.",
DeprecationWarning,
)
if callbacks is not None:
raise ValueError(
"Cannot specify both callback_manager and callbacks arguments."
)
return callback_manager
return callbacks
def load_huggingface_tool(
task_or_repo_id: str,
model_repo_id: Optional[str] = None,
token: Optional[str] = None,
remote: bool = False,
**kwargs: Any,
) -> BaseTool:
"""Loads a tool from the HuggingFace Hub.
Args:
task_or_repo_id: Task or model repo id.
model_repo_id: Optional model repo id.
token: Optional token.
remote: Optional remote. Defaults to False. |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | **kwargs:
Returns:
A tool.
"""
try:
from transformers import load_tool
except ImportError:
raise ImportError(
"HuggingFace tools require the libraries `transformers>=4.29.0`"
" and `huggingface_hub>=0.14.1` to be installed."
" Please install it with"
" `pip install --upgrade transformers huggingface_hub`."
)
hf_tool = load_tool(
task_or_repo_id,
model_repo_id=model_repo_id,
token=token,
remote=remote,
**kwargs,
)
outputs = hf_tool.outputs
if set(outputs) != {"text"}:
raise NotImplementedError("Multimodal outputs not supported yet.")
inputs = hf_tool.inputs
if set(inputs) != {"text"}:
raise NotImplementedError("Multimodal inputs not supported yet.")
return Tool.from_function(
hf_tool.__call__, name=hf_tool.name, description=hf_tool.description
)
def load_tools( |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | tool_names: List[str],
llm: Optional[BaseLanguageModel] = None,
callbacks: Callbacks = None,
**kwargs: Any,
) -> List[BaseTool]:
"""Load tools based on their name.
Tools allow agents to interact with various resources and services like
APIs, databases, file systems, etc.
Please scope the permissions of each tools to the minimum required for the
application.
For example, if an application only needs to read from a database,
the database tool should not be given write permissions. Moreover
consider scoping the permissions to only allow accessing specific
tables and impose user-level quota for limiting resource usage.
Please read the APIs of the individual tools to determine which configuration
they support.
See [Security](https://python.langchain.com/docs/security) for more information.
Args:
tool_names: name of tools to load.
llm: An optional language model, may be needed to initialize certain tools.
callbacks: Optional callback manager or list of callback handlers.
If not provided, default global callback manager will be used.
Returns: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | List of tools.
"""
tools = []
callbacks = _handle_callbacks(
callback_manager=kwargs.get("callback_manager"), callbacks=callbacks
)
for name in tool_names:
if name == "requests":
warnings.warn(
"tool name `requests` is deprecated - "
"please use `requests_all` or specify the requests method"
)
if name == "requests_all":
requests_method_tools = [
_tool for _tool in _BASE_TOOLS if _tool.startswith("requests_")
]
tool_names.extend(requests_method_tools)
elif name in _BASE_TOOLS:
tools.append(_BASE_TOOLS[name]())
elif name in _LLM_TOOLS:
if llm is None:
raise ValueError(f"Tool {name} requires an LLM to be provided")
tool = _LLM_TOOLS[name](llm)
tools.append(tool)
elif name in _EXTRA_LLM_TOOLS:
if llm is None:
raise ValueError(f"Tool {name} requires an LLM to be provided") |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/agents/load_tools.py | _get_llm_tool_func, extra_keys = _EXTRA_LLM_TOOLS[name]
missing_keys = set(extra_keys).difference(kwargs)
if missing_keys:
raise ValueError(
f"Tool {name} requires some parameters that were not "
f"provided: {missing_keys}"
)
sub_kwargs = {k: kwargs[k] for k in extra_keys}
tool = _get_llm_tool_func(llm=llm, **sub_kwargs)
tools.append(tool)
elif name in _EXTRA_OPTIONAL_TOOLS:
_get_tool_func, extra_keys = _EXTRA_OPTIONAL_TOOLS[name]
sub_kwargs = {k: kwargs[k] for k in extra_keys if k in kwargs}
tool = _get_tool_func(**sub_kwargs)
tools.append(tool)
else:
raise ValueError(f"Got unknown tool {name}")
if callbacks is not None:
for tool in tools:
tool.callbacks = callbacks
return tools
def get_all_tool_names() -> List[str]:
"""Get a list of all possible tool names."""
return (
list(_BASE_TOOLS)
+ list(_EXTRA_OPTIONAL_TOOLS)
+ list(_EXTRA_LLM_TOOLS)
+ list(_LLM_TOOLS)
) |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | """**Tools** are classes that an Agent uses to interact with the world.
Each tool has a **description**. Agent uses the description to choose the right
tool for the job.
**Class hierarchy:**
.. code-block::
ToolMetaclass --> BaseTool --> <name>Tool # Examples: AIPluginTool, BaseGraphQLTool
<name> # Examples: BraveSearch, HumanInputRun
**Main helpers:**
.. code-block::
CallbackManagerForToolRun, AsyncCallbackManagerForToolRun
"""
from typing import Any
from langchain.tools.base import BaseTool, StructuredTool, Tool, tool
_DEPRECATED_TOOLS = {"PythonAstREPLTool", "PythonREPLTool"}
def _import_ainetwork_app() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | from langchain.tools.ainetwork.app import AINAppOps
return AINAppOps
def _import_ainetwork_owner() -> Any:
from langchain.tools.ainetwork.owner import AINOwnerOps
return AINOwnerOps
def _import_ainetwork_rule() -> Any:
from langchain.tools.ainetwork.rule import AINRuleOps
return AINRuleOps
def _import_ainetwork_transfer() -> Any:
from langchain.tools.ainetwork.transfer import AINTransfer
return AINTransfer
def _import_ainetwork_value() -> Any:
from langchain.tools.ainetwork.value import AINValueOps
return AINValueOps
def _import_arxiv_tool() -> Any:
from langchain.tools.arxiv.tool import ArxivQueryRun
return ArxivQueryRun
def _import_azure_cognitive_services_AzureCogsFormRecognizerTool() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | from langchain.tools.azure_cognitive_services import AzureCogsFormRecognizerTool
return AzureCogsFormRecognizerTool
def _import_azure_cognitive_services_AzureCogsImageAnalysisTool() -> Any:
from langchain.tools.azure_cognitive_services import AzureCogsImageAnalysisTool
return AzureCogsImageAnalysisTool
def _import_azure_cognitive_services_AzureCogsSpeech2TextTool() -> Any:
from langchain.tools.azure_cognitive_services import AzureCogsSpeech2TextTool
return AzureCogsSpeech2TextTool
def _import_azure_cognitive_services_AzureCogsText2SpeechTool() -> Any:
from langchain.tools.azure_cognitive_services import AzureCogsText2SpeechTool
return AzureCogsText2SpeechTool
def _import_azure_cognitive_services_AzureCogsTextAnalyticsHealthTool() -> Any:
from langchain.tools.azure_cognitive_services import (
AzureCogsTextAnalyticsHealthTool,
)
return AzureCogsTextAnalyticsHealthTool
def _import_bing_search_tool_BingSearchResults() -> Any:
from langchain.tools.bing_search.tool import BingSearchResults
return BingSearchResults
def _import_bing_search_tool_BingSearchRun() -> Any:
from langchain.tools.bing_search.tool import BingSearchRun
return BingSearchRun
def _import_brave_search_tool() -> Any:
from langchain.tools.brave_search.tool import BraveSearch
return BraveSearch
def _import_ddg_search_tool_DuckDuckGoSearchResults() -> Any:
from langchain.tools.ddg_search.tool import DuckDuckGoSearchResults
return DuckDuckGoSearchResults
def _import_ddg_search_tool_DuckDuckGoSearchRun() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | from langchain.tools.ddg_search.tool import DuckDuckGoSearchRun
return DuckDuckGoSearchRun
def _import_edenai_EdenAiExplicitImageTool() -> Any:
from langchain.tools.edenai import EdenAiExplicitImageTool
return EdenAiExplicitImageTool
def _import_edenai_EdenAiObjectDetectionTool() -> Any:
from langchain.tools.edenai import EdenAiObjectDetectionTool
return EdenAiObjectDetectionTool
def _import_edenai_EdenAiParsingIDTool() -> Any:
from langchain.tools.edenai import EdenAiParsingIDTool
return EdenAiParsingIDTool
def _import_edenai_EdenAiParsingInvoiceTool() -> Any:
from langchain.tools.edenai import EdenAiParsingInvoiceTool
return EdenAiParsingInvoiceTool
def _import_edenai_EdenAiSpeechToTextTool() -> Any:
from langchain.tools.edenai import EdenAiSpeechToTextTool
return EdenAiSpeechToTextTool
def _import_edenai_EdenAiTextModerationTool() -> Any:
from langchain.tools.edenai import EdenAiTextModerationTool
return EdenAiTextModerationTool
def _import_edenai_EdenAiTextToSpeechTool() -> Any:
from langchain.tools.edenai import EdenAiTextToSpeechTool
return EdenAiTextToSpeechTool
def _import_edenai_EdenaiTool() -> Any:
from langchain.tools.edenai import EdenaiTool
return EdenaiTool
def _import_eleven_labs_text2speech() -> Any:
from langchain.tools.eleven_labs.text2speech import ElevenLabsText2SpeechTool
return ElevenLabsText2SpeechTool
def _import_file_management_CopyFileTool() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | from langchain.tools.file_management import CopyFileTool
return CopyFileTool
def _import_file_management_DeleteFileTool() -> Any:
from langchain.tools.file_management import DeleteFileTool
return DeleteFileTool
def _import_file_management_FileSearchTool() -> Any:
from langchain.tools.file_management import FileSearchTool
return FileSearchTool
def _import_file_management_ListDirectoryTool() -> Any:
from langchain.tools.file_management import ListDirectoryTool
return ListDirectoryTool
def _import_file_management_MoveFileTool() -> Any:
from langchain.tools.file_management import MoveFileTool
return MoveFileTool
def _import_file_management_ReadFileTool() -> Any:
from langchain.tools.file_management import ReadFileTool
return ReadFileTool
def _import_file_management_WriteFileTool() -> Any:
from langchain.tools.file_management import WriteFileTool
return WriteFileTool
def _import_gmail_GmailCreateDraft() -> Any:
from langchain.tools.gmail import GmailCreateDraft
return GmailCreateDraft
def _import_gmail_GmailGetMessage() -> Any:
from langchain.tools.gmail import GmailGetMessage
return GmailGetMessage
def _import_gmail_GmailGetThread() -> Any:
from langchain.tools.gmail import GmailGetThread
return GmailGetThread
def _import_gmail_GmailSearch() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | from langchain.tools.gmail import GmailSearch
return GmailSearch
def _import_gmail_GmailSendMessage() -> Any:
from langchain.tools.gmail import GmailSendMessage
return GmailSendMessage
def _import_google_cloud_texttospeech() -> Any:
from langchain.tools.google_cloud.texttospeech import GoogleCloudTextToSpeechTool
return GoogleCloudTextToSpeechTool
def _import_google_places_tool() -> Any:
from langchain.tools.google_places.tool import GooglePlacesTool
return GooglePlacesTool
def _import_google_search_tool_GoogleSearchResults() -> Any:
from langchain.tools.google_search.tool import GoogleSearchResults
return GoogleSearchResults
def _import_google_search_tool_GoogleSearchRun() -> Any:
from langchain.tools.google_search.tool import GoogleSearchRun
return GoogleSearchRun
def _import_google_serper_tool_GoogleSerperResults() -> Any:
from langchain.tools.google_serper.tool import GoogleSerperResults
return GoogleSerperResults
def _import_google_serper_tool_GoogleSerperRun() -> Any:
from langchain.tools.google_serper.tool import GoogleSerperRun
return GoogleSerperRun
def _import_graphql_tool() -> Any:
from langchain.tools.graphql.tool import BaseGraphQLTool
return BaseGraphQLTool
def _import_human_tool() -> Any:
from langchain.tools.human.tool import HumanInputRun
return HumanInputRun
def _import_ifttt() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | from langchain.tools.ifttt import IFTTTWebhook
return IFTTTWebhook
def _import_interaction_tool() -> Any:
from langchain.tools.interaction.tool import StdInInquireTool
return StdInInquireTool
def _import_jira_tool() -> Any:
from langchain.tools.jira.tool import JiraAction
return JiraAction
def _import_json_tool_JsonGetValueTool() -> Any:
from langchain.tools.json.tool import JsonGetValueTool
return JsonGetValueTool
def _import_json_tool_JsonListKeysTool() -> Any:
from langchain.tools.json.tool import JsonListKeysTool
return JsonListKeysTool
def _import_metaphor_search() -> Any:
from langchain.tools.metaphor_search import MetaphorSearchResults
return MetaphorSearchResults
def _import_office365_create_draft_message() -> Any:
from langchain.tools.office365.create_draft_message import O365CreateDraftMessage
return O365CreateDraftMessage
def _import_office365_events_search() -> Any:
from langchain.tools.office365.events_search import O365SearchEvents
return O365SearchEvents
def _import_office365_messages_search() -> Any:
from langchain.tools.office365.messages_search import O365SearchEmails
return O365SearchEmails
def _import_office365_send_event() -> Any:
from langchain.tools.office365.send_event import O365SendEvent
return O365SendEvent
def _import_office365_send_message() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | from langchain.tools.office365.send_message import O365SendMessage
return O365SendMessage
def _import_office365_utils() -> Any:
from langchain.tools.office365.utils import authenticate
return authenticate
def _import_openapi_utils_api_models() -> Any:
from langchain.tools.openapi.utils.api_models import APIOperation
return APIOperation
def _import_openapi_utils_openapi_utils() -> Any:
from langchain.tools.openapi.utils.openapi_utils import OpenAPISpec
return OpenAPISpec
def _import_openweathermap_tool() -> Any:
from langchain.tools.openweathermap.tool import OpenWeatherMapQueryRun
return OpenWeatherMapQueryRun
def _import_playwright_ClickTool() -> Any:
from langchain.tools.playwright import ClickTool
return ClickTool
def _import_playwright_CurrentWebPageTool() -> Any:
from langchain.tools.playwright import CurrentWebPageTool
return CurrentWebPageTool
def _import_playwright_ExtractHyperlinksTool() -> Any:
from langchain.tools.playwright import ExtractHyperlinksTool
return ExtractHyperlinksTool
def _import_playwright_ExtractTextTool() -> Any:
from langchain.tools.playwright import ExtractTextTool
return ExtractTextTool
def _import_playwright_GetElementsTool() -> Any:
from langchain.tools.playwright import GetElementsTool
return GetElementsTool
def _import_playwright_NavigateBackTool() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | from langchain.tools.playwright import NavigateBackTool
return NavigateBackTool
def _import_playwright_NavigateTool() -> Any:
from langchain.tools.playwright import NavigateTool
return NavigateTool
def _import_plugin() -> Any:
from langchain.tools.plugin import AIPluginTool
return AIPluginTool
def _import_powerbi_tool_InfoPowerBITool() -> Any:
from langchain.tools.powerbi.tool import InfoPowerBITool
return InfoPowerBITool
def _import_powerbi_tool_ListPowerBITool() -> Any:
from langchain.tools.powerbi.tool import ListPowerBITool
return ListPowerBITool
def _import_powerbi_tool_QueryPowerBITool() -> Any:
from langchain.tools.powerbi.tool import QueryPowerBITool
return QueryPowerBITool
def _import_pubmed_tool() -> Any:
from langchain.tools.pubmed.tool import PubmedQueryRun
return PubmedQueryRun
def _import_python_tool_PythonAstREPLTool() -> Any:
raise ImportError(
"This tool has been moved to langchain experiment. "
"This tool has access to a python REPL. "
"For best practices make sure to sandbox this tool. "
"Read https://github.com/langchain-ai/langchain/blob/master/SECURITY.md "
"To keep using this code as is, install langchain experimental and "
"update relevant imports replacing 'langchain' with 'langchain_experimental'"
)
def _import_python_tool_PythonREPLTool() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | raise ImportError(
"This tool has been moved to langchain experiment. "
"This tool has access to a python REPL. "
"For best practices make sure to sandbox this tool. "
"Read https://github.com/langchain-ai/langchain/blob/master/SECURITY.md "
"To keep using this code as is, install langchain experimental and "
"update relevant imports replacing 'langchain' with 'langchain_experimental'"
)
def _import_reddit_search_RedditSearchRun() -> Any:
from langchain.tools.reddit_search.tool import RedditSearchRun
return RedditSearchRun
def _import_render() -> Any:
from langchain.tools.render import format_tool_to_openai_function
return format_tool_to_openai_function
def _import_requests_tool_BaseRequestsTool() -> Any:
from langchain.tools.requests.tool import BaseRequestsTool
return BaseRequestsTool
def _import_requests_tool_RequestsDeleteTool() -> Any:
from langchain.tools.requests.tool import RequestsDeleteTool
return RequestsDeleteTool
def _import_requests_tool_RequestsGetTool() -> Any:
from langchain.tools.requests.tool import RequestsGetTool
return RequestsGetTool
def _import_requests_tool_RequestsPatchTool() -> Any:
from langchain.tools.requests.tool import RequestsPatchTool
return RequestsPatchTool
def _import_requests_tool_RequestsPostTool() -> Any:
from langchain.tools.requests.tool import RequestsPostTool
return RequestsPostTool
def _import_requests_tool_RequestsPutTool() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | from langchain.tools.requests.tool import RequestsPutTool
return RequestsPutTool
def _import_scenexplain_tool() -> Any:
from langchain.tools.scenexplain.tool import SceneXplainTool
return SceneXplainTool
def _import_searx_search_tool_SearxSearchResults() -> Any:
from langchain.tools.searx_search.tool import SearxSearchResults
return SearxSearchResults
def _import_searx_search_tool_SearxSearchRun() -> Any:
from langchain.tools.searx_search.tool import SearxSearchRun
return SearxSearchRun
def _import_shell_tool() -> Any:
from langchain.tools.shell.tool import ShellTool
return ShellTool
def _import_sleep_tool() -> Any:
from langchain.tools.sleep.tool import SleepTool
return SleepTool
def _import_spark_sql_tool_BaseSparkSQLTool() -> Any:
from langchain.tools.spark_sql.tool import BaseSparkSQLTool
return BaseSparkSQLTool
def _import_spark_sql_tool_InfoSparkSQLTool() -> Any:
from langchain.tools.spark_sql.tool import InfoSparkSQLTool
return InfoSparkSQLTool
def _import_spark_sql_tool_ListSparkSQLTool() -> Any:
from langchain.tools.spark_sql.tool import ListSparkSQLTool
return ListSparkSQLTool
def _import_spark_sql_tool_QueryCheckerTool() -> Any:
from langchain.tools.spark_sql.tool import QueryCheckerTool
return QueryCheckerTool
def _import_spark_sql_tool_QuerySparkSQLTool() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | from langchain.tools.spark_sql.tool import QuerySparkSQLTool
return QuerySparkSQLTool
def _import_sql_database_tool_BaseSQLDatabaseTool() -> Any:
from langchain.tools.sql_database.tool import BaseSQLDatabaseTool
return BaseSQLDatabaseTool
def _import_sql_database_tool_InfoSQLDatabaseTool() -> Any:
from langchain.tools.sql_database.tool import InfoSQLDatabaseTool
return InfoSQLDatabaseTool
def _import_sql_database_tool_ListSQLDatabaseTool() -> Any:
from langchain.tools.sql_database.tool import ListSQLDatabaseTool
return ListSQLDatabaseTool
def _import_sql_database_tool_QuerySQLCheckerTool() -> Any:
from langchain.tools.sql_database.tool import QuerySQLCheckerTool
return QuerySQLCheckerTool
def _import_sql_database_tool_QuerySQLDataBaseTool() -> Any:
from langchain.tools.sql_database.tool import QuerySQLDataBaseTool
return QuerySQLDataBaseTool
def _import_stackexchange_tool() -> Any:
from langchain.tools.stackexchange.tool import StackExchangeTool
return StackExchangeTool
def _import_steamship_image_generation() -> Any:
from langchain.tools.steamship_image_generation import SteamshipImageGenerationTool
return SteamshipImageGenerationTool
def _import_vectorstore_tool_VectorStoreQATool() -> Any:
from langchain.tools.vectorstore.tool import VectorStoreQATool
return VectorStoreQATool
def _import_vectorstore_tool_VectorStoreQAWithSourcesTool() -> Any:
from langchain.tools.vectorstore.tool import VectorStoreQAWithSourcesTool
return VectorStoreQAWithSourcesTool
def _import_wikipedia_tool() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | from langchain.tools.wikipedia.tool import WikipediaQueryRun
return WikipediaQueryRun
def _import_wolfram_alpha_tool() -> Any:
from langchain.tools.wolfram_alpha.tool import WolframAlphaQueryRun
return WolframAlphaQueryRun
def _import_yahoo_finance_news() -> Any:
from langchain.tools.yahoo_finance_news import YahooFinanceNewsTool
return YahooFinanceNewsTool
def _import_youtube_search() -> Any:
from langchain.tools.youtube.search import YouTubeSearchTool
return YouTubeSearchTool
def _import_zapier_tool_ZapierNLAListActions() -> Any:
from langchain.tools.zapier.tool import ZapierNLAListActions
return ZapierNLAListActions
def _import_zapier_tool_ZapierNLARunAction() -> Any:
from langchain.tools.zapier.tool import ZapierNLARunAction
return ZapierNLARunAction
def _import_bearly_tool() -> Any:
from langchain.tools.bearly.tool import BearlyInterpreterTool
return BearlyInterpreterTool
def _import_e2b_data_analysis() -> Any:
from langchain.tools.e2b_data_analysis.tool import E2BDataAnalysisTool
return E2BDataAnalysisTool
def __getattr__(name: str) -> Any:
if name == "AINAppOps":
return _import_ainetwork_app()
elif name == "AINOwnerOps":
return _import_ainetwork_owner() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | elif name == "AINRuleOps":
return _import_ainetwork_rule()
elif name == "AINTransfer":
return _import_ainetwork_transfer()
elif name == "AINValueOps":
return _import_ainetwork_value()
elif name == "ArxivQueryRun":
return _import_arxiv_tool()
elif name == "AzureCogsFormRecognizerTool":
return _import_azure_cognitive_services_AzureCogsFormRecognizerTool()
elif name == "AzureCogsImageAnalysisTool":
return _import_azure_cognitive_services_AzureCogsImageAnalysisTool()
elif name == "AzureCogsSpeech2TextTool":
return _import_azure_cognitive_services_AzureCogsSpeech2TextTool()
elif name == "AzureCogsText2SpeechTool":
return _import_azure_cognitive_services_AzureCogsText2SpeechTool()
elif name == "AzureCogsTextAnalyticsHealthTool":
return _import_azure_cognitive_services_AzureCogsTextAnalyticsHealthTool()
elif name == "BingSearchResults":
return _import_bing_search_tool_BingSearchResults()
elif name == "BingSearchRun":
return _import_bing_search_tool_BingSearchRun()
elif name == "BraveSearch":
return _import_brave_search_tool()
elif name == "DuckDuckGoSearchResults":
return _import_ddg_search_tool_DuckDuckGoSearchResults()
elif name == "DuckDuckGoSearchRun":
return _import_ddg_search_tool_DuckDuckGoSearchRun()
elif name == "EdenAiExplicitImageTool":
return _import_edenai_EdenAiExplicitImageTool() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | elif name == "EdenAiObjectDetectionTool":
return _import_edenai_EdenAiObjectDetectionTool()
elif name == "EdenAiParsingIDTool":
return _import_edenai_EdenAiParsingIDTool()
elif name == "EdenAiParsingInvoiceTool":
return _import_edenai_EdenAiParsingInvoiceTool()
elif name == "EdenAiSpeechToTextTool":
return _import_edenai_EdenAiSpeechToTextTool()
elif name == "EdenAiTextModerationTool":
return _import_edenai_EdenAiTextModerationTool()
elif name == "EdenAiTextToSpeechTool":
return _import_edenai_EdenAiTextToSpeechTool()
elif name == "EdenaiTool":
return _import_edenai_EdenaiTool()
elif name == "ElevenLabsText2SpeechTool":
return _import_eleven_labs_text2speech()
elif name == "CopyFileTool":
return _import_file_management_CopyFileTool()
elif name == "DeleteFileTool":
return _import_file_management_DeleteFileTool()
elif name == "FileSearchTool":
return _import_file_management_FileSearchTool()
elif name == "ListDirectoryTool":
return _import_file_management_ListDirectoryTool()
elif name == "MoveFileTool":
return _import_file_management_MoveFileTool()
elif name == "ReadFileTool":
return _import_file_management_ReadFileTool()
elif name == "WriteFileTool":
return _import_file_management_WriteFileTool() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | elif name == "GmailCreateDraft":
return _import_gmail_GmailCreateDraft()
elif name == "GmailGetMessage":
return _import_gmail_GmailGetMessage()
elif name == "GmailGetThread":
return _import_gmail_GmailGetThread()
elif name == "GmailSearch":
return _import_gmail_GmailSearch()
elif name == "GmailSendMessage":
return _import_gmail_GmailSendMessage()
elif name == "GoogleCloudTextToSpeechTool":
return _import_google_cloud_texttospeech()
elif name == "GooglePlacesTool":
return _import_google_places_tool()
elif name == "GoogleSearchResults":
return _import_google_search_tool_GoogleSearchResults()
elif name == "GoogleSearchRun":
return _import_google_search_tool_GoogleSearchRun()
elif name == "GoogleSerperResults":
return _import_google_serper_tool_GoogleSerperResults()
elif name == "GoogleSerperRun":
return _import_google_serper_tool_GoogleSerperRun()
elif name == "BaseGraphQLTool":
return _import_graphql_tool()
elif name == "HumanInputRun":
return _import_human_tool()
elif name == "IFTTTWebhook":
return _import_ifttt()
elif name == "StdInInquireTool":
return _import_interaction_tool() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | elif name == "JiraAction":
return _import_jira_tool()
elif name == "JsonGetValueTool":
return _import_json_tool_JsonGetValueTool()
elif name == "JsonListKeysTool":
return _import_json_tool_JsonListKeysTool()
elif name == "MetaphorSearchResults":
return _import_metaphor_search()
elif name == "O365CreateDraftMessage":
return _import_office365_create_draft_message()
elif name == "O365SearchEvents":
return _import_office365_events_search()
elif name == "O365SearchEmails":
return _import_office365_messages_search()
elif name == "O365SendEvent":
return _import_office365_send_event()
elif name == "O365SendMessage":
return _import_office365_send_message()
elif name == "authenticate":
return _import_office365_utils()
elif name == "APIOperation":
return _import_openapi_utils_api_models()
elif name == "OpenAPISpec":
return _import_openapi_utils_openapi_utils()
elif name == "OpenWeatherMapQueryRun":
return _import_openweathermap_tool()
elif name == "ClickTool":
return _import_playwright_ClickTool()
elif name == "CurrentWebPageTool":
return _import_playwright_CurrentWebPageTool() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | elif name == "ExtractHyperlinksTool":
return _import_playwright_ExtractHyperlinksTool()
elif name == "ExtractTextTool":
return _import_playwright_ExtractTextTool()
elif name == "GetElementsTool":
return _import_playwright_GetElementsTool()
elif name == "NavigateBackTool":
return _import_playwright_NavigateBackTool()
elif name == "NavigateTool":
return _import_playwright_NavigateTool()
elif name == "AIPluginTool":
return _import_plugin()
elif name == "InfoPowerBITool":
return _import_powerbi_tool_InfoPowerBITool()
elif name == "ListPowerBITool":
return _import_powerbi_tool_ListPowerBITool()
elif name == "QueryPowerBITool":
return _import_powerbi_tool_QueryPowerBITool()
elif name == "PubmedQueryRun":
return _import_pubmed_tool()
elif name == "PythonAstREPLTool":
return _import_python_tool_PythonAstREPLTool()
elif name == "PythonREPLTool":
return _import_python_tool_PythonREPLTool()
elif name == "RedditSearchRun":
return _import_reddit_search_RedditSearchRun()
elif name == "format_tool_to_openai_function":
return _import_render()
elif name == "BaseRequestsTool":
return _import_requests_tool_BaseRequestsTool() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | elif name == "RequestsDeleteTool":
return _import_requests_tool_RequestsDeleteTool()
elif name == "RequestsGetTool":
return _import_requests_tool_RequestsGetTool()
elif name == "RequestsPatchTool":
return _import_requests_tool_RequestsPatchTool()
elif name == "RequestsPostTool":
return _import_requests_tool_RequestsPostTool()
elif name == "RequestsPutTool":
return _import_requests_tool_RequestsPutTool()
elif name == "SceneXplainTool":
return _import_scenexplain_tool()
elif name == "SearxSearchResults":
return _import_searx_search_tool_SearxSearchResults()
elif name == "SearxSearchRun":
return _import_searx_search_tool_SearxSearchRun()
elif name == "ShellTool":
return _import_shell_tool()
elif name == "SleepTool":
return _import_sleep_tool()
elif name == "BaseSparkSQLTool":
return _import_spark_sql_tool_BaseSparkSQLTool()
elif name == "InfoSparkSQLTool":
return _import_spark_sql_tool_InfoSparkSQLTool()
elif name == "ListSparkSQLTool":
return _import_spark_sql_tool_ListSparkSQLTool()
elif name == "QueryCheckerTool":
return _import_spark_sql_tool_QueryCheckerTool()
elif name == "QuerySparkSQLTool":
return _import_spark_sql_tool_QuerySparkSQLTool() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | elif name == "BaseSQLDatabaseTool":
return _import_sql_database_tool_BaseSQLDatabaseTool()
elif name == "InfoSQLDatabaseTool":
return _import_sql_database_tool_InfoSQLDatabaseTool()
elif name == "ListSQLDatabaseTool":
return _import_sql_database_tool_ListSQLDatabaseTool()
elif name == "QuerySQLCheckerTool":
return _import_sql_database_tool_QuerySQLCheckerTool()
elif name == "QuerySQLDataBaseTool":
return _import_sql_database_tool_QuerySQLDataBaseTool()
elif name == "StackExchangeTool":
return _import_stackexchange_tool()
elif name == "SteamshipImageGenerationTool":
return _import_steamship_image_generation()
elif name == "VectorStoreQATool":
return _import_vectorstore_tool_VectorStoreQATool()
elif name == "VectorStoreQAWithSourcesTool":
return _import_vectorstore_tool_VectorStoreQAWithSourcesTool()
elif name == "WikipediaQueryRun":
return _import_wikipedia_tool()
elif name == "WolframAlphaQueryRun":
return _import_wolfram_alpha_tool()
elif name == "YahooFinanceNewsTool":
return _import_yahoo_finance_news()
elif name == "YouTubeSearchTool":
return _import_youtube_search()
elif name == "ZapierNLAListActions":
return _import_zapier_tool_ZapierNLAListActions()
elif name == "ZapierNLARunAction":
return _import_zapier_tool_ZapierNLARunAction() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | elif name == "BearlyInterpreterTool":
return _import_bearly_tool()
elif name == "E2BDataAnalysisTool":
return _import_e2b_data_analysis()
else:
raise AttributeError(f"Could not find: {name}")
__all__ = [
"AINAppOps",
"AINOwnerOps",
"AINRuleOps",
"AINTransfer",
"AINValueOps",
"AIPluginTool",
"APIOperation",
"ArxivQueryRun",
"AzureCogsFormRecognizerTool",
"AzureCogsImageAnalysisTool",
"AzureCogsSpeech2TextTool",
"AzureCogsText2SpeechTool",
"AzureCogsTextAnalyticsHealthTool",
"BaseGraphQLTool",
"BaseRequestsTool",
"BaseSQLDatabaseTool",
"BaseSparkSQLTool",
"BaseTool",
"BearlyInterpreterTool",
"BingSearchResults",
"BingSearchRun",
"BraveSearch",
"ClickTool", |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | "CopyFileTool",
"CurrentWebPageTool",
"DeleteFileTool",
"DuckDuckGoSearchResults",
"DuckDuckGoSearchRun",
"E2BDataAnalysisTool",
"EdenAiExplicitImageTool",
"EdenAiObjectDetectionTool",
"EdenAiParsingIDTool",
"EdenAiParsingInvoiceTool",
"EdenAiSpeechToTextTool",
"EdenAiTextModerationTool",
"EdenAiTextToSpeechTool",
"EdenaiTool",
"ElevenLabsText2SpeechTool",
"ExtractHyperlinksTool",
"ExtractTextTool",
"FileSearchTool",
"GetElementsTool",
"GmailCreateDraft",
"GmailGetMessage",
"GmailGetThread",
"GmailSearch",
"GmailSendMessage",
"GoogleCloudTextToSpeechTool",
"GooglePlacesTool",
"GoogleSearchResults",
"GoogleSearchRun",
"GoogleSerperResults",
"GoogleSerperRun", |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | "HumanInputRun",
"IFTTTWebhook",
"InfoPowerBITool",
"InfoSQLDatabaseTool",
"InfoSparkSQLTool",
"JiraAction",
"JsonGetValueTool",
"JsonListKeysTool",
"ListDirectoryTool",
"ListPowerBITool",
"ListSQLDatabaseTool",
"ListSparkSQLTool",
"MetaphorSearchResults",
"MoveFileTool",
"NavigateBackTool",
"NavigateTool",
"O365CreateDraftMessage",
"O365SearchEmails",
"O365SearchEvents",
"O365SendEvent",
"O365SendMessage",
"OpenAPISpec",
"OpenWeatherMapQueryRun",
"PubmedQueryRun",
"RedditSearchRun",
"QueryCheckerTool",
"QueryPowerBITool",
"QuerySQLCheckerTool",
"QuerySQLDataBaseTool",
"QuerySparkSQLTool", |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/tools/__init__.py | "ReadFileTool",
"RequestsDeleteTool",
"RequestsGetTool",
"RequestsPatchTool",
"RequestsPostTool",
"RequestsPutTool",
"SceneXplainTool",
"SearxSearchResults",
"SearxSearchRun",
"ShellTool",
"SleepTool",
"StdInInquireTool",
"StackExchangeTool",
"SteamshipImageGenerationTool",
"StructuredTool",
"Tool",
"VectorStoreQATool",
"VectorStoreQAWithSourcesTool",
"WikipediaQueryRun",
"WolframAlphaQueryRun",
"WriteFileTool",
"YahooFinanceNewsTool",
"YouTubeSearchTool",
"ZapierNLAListActions",
"ZapierNLARunAction",
"authenticate",
"format_tool_to_openai_function",
"tool",
] |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/utilities/__init__.py | """**Utilities** are the integrations with third-part systems and packages.
Other LangChain classes use **Utilities** to interact with third-part systems
and packages.
"""
from typing import Any
from langchain.utilities.requests import Requests, RequestsWrapper, TextRequestsWrapper
def _import_alpha_vantage() -> Any:
from langchain.utilities.alpha_vantage import AlphaVantageAPIWrapper
return AlphaVantageAPIWrapper
def _import_apify() -> Any:
from langchain.utilities.apify import ApifyWrapper
return ApifyWrapper
def _import_arcee() -> Any:
from langchain.utilities.arcee import ArceeWrapper
return ArceeWrapper
def _import_arxiv() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/utilities/__init__.py | from langchain.utilities.arxiv import ArxivAPIWrapper
return ArxivAPIWrapper
def _import_awslambda() -> Any:
from langchain.utilities.awslambda import LambdaWrapper
return LambdaWrapper
def _import_bibtex() -> Any:
from langchain.utilities.bibtex import BibtexparserWrapper
return BibtexparserWrapper
def _import_bing_search() -> Any:
from langchain.utilities.bing_search import BingSearchAPIWrapper
return BingSearchAPIWrapper
def _import_brave_search() -> Any:
from langchain.utilities.brave_search import BraveSearchWrapper
return BraveSearchWrapper
def _import_duckduckgo_search() -> Any:
from langchain.utilities.duckduckgo_search import DuckDuckGoSearchAPIWrapper
return DuckDuckGoSearchAPIWrapper
def _import_golden_query() -> Any:
from langchain.utilities.golden_query import GoldenQueryAPIWrapper
return GoldenQueryAPIWrapper
def _import_google_lens() -> Any:
from langchain.utilities.google_lens import GoogleLensAPIWrapper
return GoogleLensAPIWrapper
def _import_google_places_api() -> Any:
from langchain.utilities.google_places_api import GooglePlacesAPIWrapper
return GooglePlacesAPIWrapper
def _import_google_jobs() -> Any:
from langchain.utilities.google_jobs import GoogleJobsAPIWrapper
return GoogleJobsAPIWrapper
def _import_google_scholar() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/utilities/__init__.py | from langchain.utilities.google_scholar import GoogleScholarAPIWrapper
return GoogleScholarAPIWrapper
def _import_google_trends() -> Any:
from langchain.utilities.google_trends import GoogleTrendsAPIWrapper
return GoogleTrendsAPIWrapper
def _import_google_finance() -> Any:
from langchain.utilities.google_finance import GoogleFinanceAPIWrapper
return GoogleFinanceAPIWrapper
def _import_google_search() -> Any:
from langchain.utilities.google_search import GoogleSearchAPIWrapper
return GoogleSearchAPIWrapper
def _import_google_serper() -> Any:
from langchain.utilities.google_serper import GoogleSerperAPIWrapper
return GoogleSerperAPIWrapper
def _import_graphql() -> Any:
from langchain.utilities.graphql import GraphQLAPIWrapper
return GraphQLAPIWrapper
def _import_jira() -> Any:
from langchain.utilities.jira import JiraAPIWrapper
return JiraAPIWrapper
def _import_max_compute() -> Any:
from langchain.utilities.max_compute import MaxComputeAPIWrapper
return MaxComputeAPIWrapper
def _import_metaphor_search() -> Any:
from langchain.utilities.metaphor_search import MetaphorSearchAPIWrapper
return MetaphorSearchAPIWrapper
def _import_openweathermap() -> Any:
from langchain.utilities.openweathermap import OpenWeatherMapAPIWrapper
return OpenWeatherMapAPIWrapper
def _import_outline() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/utilities/__init__.py | from langchain.utilities.outline import OutlineAPIWrapper
return OutlineAPIWrapper
def _import_portkey() -> Any:
from langchain.utilities.portkey import Portkey
return Portkey
def _import_powerbi() -> Any:
from langchain.utilities.powerbi import PowerBIDataset
return PowerBIDataset
def _import_pubmed() -> Any:
from langchain.utilities.pubmed import PubMedAPIWrapper
return PubMedAPIWrapper
def _import_python() -> Any:
from langchain.utilities.python import PythonREPL
return PythonREPL
def _import_scenexplain() -> Any:
from langchain.utilities.scenexplain import SceneXplainAPIWrapper
return SceneXplainAPIWrapper
def _import_searchapi() -> Any:
from langchain.utilities.searchapi import SearchApiAPIWrapper
return SearchApiAPIWrapper
def _import_searx_search() -> Any:
from langchain.utilities.searx_search import SearxSearchWrapper
return SearxSearchWrapper
def _import_serpapi() -> Any:
from langchain.utilities.serpapi import SerpAPIWrapper
return SerpAPIWrapper
def _import_spark_sql() -> Any:
from langchain.utilities.spark_sql import SparkSQL
return SparkSQL
def _import_sql_database() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/utilities/__init__.py | from langchain.utilities.sql_database import SQLDatabase
return SQLDatabase
def _import_stackexchange() -> Any:
from langchain.utilities.stackexchange import StackExchangeAPIWrapper
return StackExchangeAPIWrapper
def _import_tensorflow_datasets() -> Any:
from langchain.utilities.tensorflow_datasets import TensorflowDatasets
return TensorflowDatasets
def _import_twilio() -> Any:
from langchain.utilities.twilio import TwilioAPIWrapper
return TwilioAPIWrapper
def _import_wikipedia() -> Any:
from langchain.utilities.wikipedia import WikipediaAPIWrapper
return WikipediaAPIWrapper
def _import_wolfram_alpha() -> Any:
from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper
return WolframAlphaAPIWrapper
def _import_zapier() -> Any:
from langchain.utilities.zapier import ZapierNLAWrapper
return ZapierNLAWrapper
def __getattr__(name: str) -> Any:
if name == "AlphaVantageAPIWrapper":
return _import_alpha_vantage()
elif name == "ApifyWrapper":
return _import_apify()
elif name == "ArceeWrapper":
return _import_arcee()
elif name == "ArxivAPIWrapper":
return _import_arxiv() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/utilities/__init__.py | elif name == "LambdaWrapper":
return _import_awslambda()
elif name == "BibtexparserWrapper":
return _import_bibtex()
elif name == "BingSearchAPIWrapper":
return _import_bing_search()
elif name == "BraveSearchWrapper":
return _import_brave_search()
elif name == "DuckDuckGoSearchAPIWrapper":
return _import_duckduckgo_search()
elif name == "GoogleLensAPIWrapper":
return _import_google_lens()
elif name == "GoldenQueryAPIWrapper":
return _import_golden_query()
elif name == "GoogleJobsAPIWrapper":
return _import_google_jobs()
elif name == "GoogleScholarAPIWrapper":
return _import_google_scholar()
elif name == "GoogleFinanceAPIWrapper":
return _import_google_finance()
elif name == "GoogleTrendsAPIWrapper":
return _import_google_trends()
elif name == "GooglePlacesAPIWrapper":
return _import_google_places_api()
elif name == "GoogleSearchAPIWrapper":
return _import_google_search()
elif name == "GoogleSerperAPIWrapper":
return _import_google_serper()
elif name == "GraphQLAPIWrapper":
return _import_graphql() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/utilities/__init__.py | elif name == "JiraAPIWrapper":
return _import_jira()
elif name == "MaxComputeAPIWrapper":
return _import_max_compute()
elif name == "MetaphorSearchAPIWrapper":
return _import_metaphor_search()
elif name == "OpenWeatherMapAPIWrapper":
return _import_openweathermap()
elif name == "OutlineAPIWrapper":
return _import_outline()
elif name == "Portkey":
return _import_portkey()
elif name == "PowerBIDataset":
return _import_powerbi()
elif name == "PubMedAPIWrapper":
return _import_pubmed()
elif name == "PythonREPL":
return _import_python()
elif name == "SceneXplainAPIWrapper":
return _import_scenexplain()
elif name == "SearchApiAPIWrapper":
return _import_searchapi()
elif name == "SearxSearchWrapper":
return _import_searx_search()
elif name == "SerpAPIWrapper":
return _import_serpapi()
elif name == "SparkSQL":
return _import_spark_sql()
elif name == "StackExchangeAPIWrapper":
return _import_stackexchange() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/utilities/__init__.py | elif name == "SQLDatabase":
return _import_sql_database()
elif name == "TensorflowDatasets":
return _import_tensorflow_datasets()
elif name == "TwilioAPIWrapper":
return _import_twilio()
elif name == "WikipediaAPIWrapper":
return _import_wikipedia()
elif name == "WolframAlphaAPIWrapper":
return _import_wolfram_alpha()
elif name == "ZapierNLAWrapper":
return _import_zapier()
else:
raise AttributeError(f"Could not find: {name}")
__all__ = [
"AlphaVantageAPIWrapper",
"ApifyWrapper",
"ArceeWrapper",
"ArxivAPIWrapper",
"BibtexparserWrapper",
"BingSearchAPIWrapper",
"BraveSearchWrapper",
"DuckDuckGoSearchAPIWrapper",
"GoldenQueryAPIWrapper",
"GoogleFinanceAPIWrapper",
"GoogleLensAPIWrapper",
"GoogleJobsAPIWrapper",
"GooglePlacesAPIWrapper",
"GoogleScholarAPIWrapper",
"GoogleTrendsAPIWrapper", |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/langchain/utilities/__init__.py | "GoogleSearchAPIWrapper",
"GoogleSerperAPIWrapper",
"GraphQLAPIWrapper",
"JiraAPIWrapper",
"LambdaWrapper",
"MaxComputeAPIWrapper",
"MetaphorSearchAPIWrapper",
"OpenWeatherMapAPIWrapper",
"OutlineAPIWrapper",
"Portkey",
"PowerBIDataset",
"PubMedAPIWrapper",
"PythonREPL",
"Requests",
"RequestsWrapper",
"SQLDatabase",
"SceneXplainAPIWrapper",
"SearchApiAPIWrapper",
"SearxSearchWrapper",
"SerpAPIWrapper",
"SparkSQL",
"StackExchangeAPIWrapper",
"TensorflowDatasets",
"TextRequestsWrapper",
"TwilioAPIWrapper",
"WikipediaAPIWrapper",
"WolframAlphaAPIWrapper",
"ZapierNLAWrapper",
] |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/tests/unit_tests/tools/test_imports.py | from langchain.tools import __all__
EXPECTED_ALL = [
"AINAppOps",
"AINOwnerOps",
"AINRuleOps",
"AINTransfer",
"AINValueOps",
"AIPluginTool",
"APIOperation",
"ArxivQueryRun",
"AzureCogsFormRecognizerTool",
"AzureCogsImageAnalysisTool",
"AzureCogsSpeech2TextTool",
"AzureCogsText2SpeechTool",
"AzureCogsTextAnalyticsHealthTool",
"BaseGraphQLTool",
"BaseRequestsTool",
"BaseSQLDatabaseTool",
"BaseSparkSQLTool",
"BaseTool",
"BearlyInterpreterTool",
"BingSearchResults",
"BingSearchRun",
"BraveSearch",
"ClickTool",
"CopyFileTool",
"CurrentWebPageTool", |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/tests/unit_tests/tools/test_imports.py | "DeleteFileTool",
"DuckDuckGoSearchResults",
"DuckDuckGoSearchRun",
"E2BDataAnalysisTool",
"EdenAiExplicitImageTool",
"EdenAiObjectDetectionTool",
"EdenAiParsingIDTool",
"EdenAiParsingInvoiceTool",
"EdenAiSpeechToTextTool",
"EdenAiTextModerationTool",
"EdenAiTextToSpeechTool",
"EdenaiTool",
"ElevenLabsText2SpeechTool",
"ExtractHyperlinksTool",
"ExtractTextTool",
"FileSearchTool",
"GetElementsTool",
"GmailCreateDraft",
"GmailGetMessage",
"GmailGetThread",
"GmailSearch",
"GmailSendMessage",
"GoogleCloudTextToSpeechTool",
"GooglePlacesTool",
"GoogleSearchResults",
"GoogleSearchRun",
"GoogleSerperResults",
"GoogleSerperRun",
"HumanInputRun",
"IFTTTWebhook", |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/tests/unit_tests/tools/test_imports.py | "InfoPowerBITool",
"InfoSQLDatabaseTool",
"InfoSparkSQLTool",
"JiraAction",
"JsonGetValueTool",
"JsonListKeysTool",
"ListDirectoryTool",
"ListPowerBITool",
"ListSQLDatabaseTool",
"ListSparkSQLTool",
"MetaphorSearchResults",
"MoveFileTool",
"NavigateBackTool",
"NavigateTool",
"O365CreateDraftMessage",
"O365SearchEmails",
"O365SearchEvents",
"O365SendEvent",
"O365SendMessage",
"OpenAPISpec",
"OpenWeatherMapQueryRun",
"PubmedQueryRun",
"RedditSearchRun",
"QueryCheckerTool",
"QueryPowerBITool",
"QuerySQLCheckerTool",
"QuerySQLDataBaseTool",
"QuerySparkSQLTool",
"ReadFileTool",
"RequestsDeleteTool", |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/tests/unit_tests/tools/test_imports.py | "RequestsGetTool",
"RequestsPatchTool",
"RequestsPostTool",
"RequestsPutTool",
"SceneXplainTool",
"SearxSearchResults",
"SearxSearchRun",
"ShellTool",
"SleepTool",
"StackExchangeTool",
"StdInInquireTool",
"SteamshipImageGenerationTool",
"StructuredTool",
"Tool",
"VectorStoreQATool",
"VectorStoreQAWithSourcesTool",
"WikipediaQueryRun",
"WolframAlphaQueryRun",
"WriteFileTool",
"YahooFinanceNewsTool",
"YouTubeSearchTool",
"ZapierNLAListActions",
"ZapierNLARunAction",
"authenticate",
"format_tool_to_openai_function",
"tool",
]
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL) |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/tests/unit_tests/tools/test_public_api.py | """Test the public API of the tools package."""
from langchain.tools import __all__ as public_api
_EXPECTED = [
"AINAppOps",
"AINOwnerOps",
"AINRuleOps",
"AINTransfer",
"AINValueOps",
"AIPluginTool",
"APIOperation",
"ArxivQueryRun",
"AzureCogsFormRecognizerTool",
"AzureCogsImageAnalysisTool",
"AzureCogsSpeech2TextTool",
"AzureCogsText2SpeechTool",
"AzureCogsTextAnalyticsHealthTool",
"BaseGraphQLTool",
"BaseRequestsTool",
"BaseSQLDatabaseTool",
"BaseSparkSQLTool",
"BaseTool",
"BearlyInterpreterTool",
"BingSearchResults",
"BingSearchRun",
"BraveSearch",
"ClickTool",
"CopyFileTool",
"CurrentWebPageTool",
"DeleteFileTool",
"DuckDuckGoSearchResults", |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/tests/unit_tests/tools/test_public_api.py | "DuckDuckGoSearchRun",
"E2BDataAnalysisTool",
"EdenAiExplicitImageTool",
"EdenAiObjectDetectionTool",
"EdenAiParsingIDTool",
"EdenAiParsingInvoiceTool",
"EdenAiSpeechToTextTool",
"EdenAiTextModerationTool",
"EdenAiTextToSpeechTool",
"EdenaiTool",
"ElevenLabsText2SpeechTool",
"ExtractHyperlinksTool",
"ExtractTextTool",
"FileSearchTool",
"GetElementsTool",
"GmailCreateDraft",
"GmailGetMessage",
"GmailGetThread",
"GmailSearch",
"GmailSendMessage",
"GoogleCloudTextToSpeechTool",
"GooglePlacesTool",
"GoogleSearchResults",
"GoogleSearchRun",
"GoogleSerperResults",
"GoogleSerperRun",
"HumanInputRun",
"IFTTTWebhook",
"InfoPowerBITool",
"InfoSQLDatabaseTool", |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/tests/unit_tests/tools/test_public_api.py | "InfoSparkSQLTool",
"JiraAction",
"JsonGetValueTool",
"JsonListKeysTool",
"ListDirectoryTool",
"ListPowerBITool",
"ListSQLDatabaseTool",
"ListSparkSQLTool",
"MetaphorSearchResults",
"MoveFileTool",
"NavigateBackTool",
"NavigateTool",
"O365CreateDraftMessage",
"O365SearchEmails",
"O365SearchEvents",
"O365SendEvent",
"O365SendMessage",
"OpenAPISpec",
"OpenWeatherMapQueryRun",
"PubmedQueryRun",
"RedditSearchRun",
"QueryCheckerTool",
"QueryPowerBITool",
"QuerySQLCheckerTool",
"QuerySQLDataBaseTool",
"QuerySparkSQLTool",
"ReadFileTool",
"RequestsDeleteTool",
"RequestsGetTool",
"RequestsPatchTool", |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/tests/unit_tests/tools/test_public_api.py | "RequestsPostTool",
"RequestsPutTool",
"SceneXplainTool",
"SearxSearchResults",
"SearxSearchRun",
"ShellTool",
"SleepTool",
"StdInInquireTool",
"StackExchangeTool",
"SteamshipImageGenerationTool",
"StructuredTool",
"Tool",
"VectorStoreQATool",
"VectorStoreQAWithSourcesTool",
"WikipediaQueryRun",
"WolframAlphaQueryRun",
"WriteFileTool",
"YahooFinanceNewsTool",
"YouTubeSearchTool",
"ZapierNLAListActions",
"ZapierNLARunAction",
"authenticate",
"format_tool_to_openai_function",
"tool",
]
def test_public_api() -> None:
"""Test for regressions or changes in the public API."""
assert set(public_api) == set(_EXPECTED) |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/tests/unit_tests/utilities/test_imports.py | from langchain.utilities import __all__
EXPECTED_ALL = [
"AlphaVantageAPIWrapper",
"ApifyWrapper",
"ArceeWrapper",
"ArxivAPIWrapper",
"BibtexparserWrapper",
"BingSearchAPIWrapper",
"BraveSearchWrapper",
"DuckDuckGoSearchAPIWrapper",
"GoldenQueryAPIWrapper",
"GoogleFinanceAPIWrapper",
"GoogleJobsAPIWrapper",
"GoogleLensAPIWrapper",
"GooglePlacesAPIWrapper",
"GoogleScholarAPIWrapper",
"GoogleSearchAPIWrapper",
"GoogleSerperAPIWrapper",
"GoogleTrendsAPIWrapper", |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 12,039 | Tools for Dictionary APIs | ### Feature request
It would be nice to have agents that could access dictionary APIs such as the Merriam-Webster API or Urban Dictionary API (for slang).
### Motivation
It can be useful to be able to look up definitions for words using a dictionary to provide additional context. With no current dictionary tools available, it would be beneficial for there to be an implemented dictionary tool available at all.
### Your contribution
We will open a PR that adds a new tool for accessing the Merriam-Webster Collegiate Dictionary API (https://dictionaryapi.com/products/api-collegiate-dictionary[/](https://www.dictionaryapi.com/)), which provides definitions for English words, as soon as possible. In the future this could be extended to support other Merriam-Webster APIs such as their Medical Dictionary API (https://dictionaryapi.com/products/api-medical-dictionary) or Spanish-English Dictionary API (https://dictionaryapi.com/products/api-spanish-dictionary).
We may also open another PR for Urban Dictionary API integration. | https://github.com/langchain-ai/langchain/issues/12039 | https://github.com/langchain-ai/langchain/pull/12044 | f3dd4a10cffd507a1300abf0f7729e95072f44eb | c2e3963da4b7c6650fc37acfa8ea39a355e7dae9 | "2023-10-19T18:31:45Z" | python | "2023-11-30T01:28:29Z" | libs/langchain/tests/unit_tests/utilities/test_imports.py | "GraphQLAPIWrapper",
"JiraAPIWrapper",
"LambdaWrapper",
"MaxComputeAPIWrapper",
"MetaphorSearchAPIWrapper",
"OpenWeatherMapAPIWrapper",
"OutlineAPIWrapper",
"Portkey",
"PowerBIDataset",
"PubMedAPIWrapper",
"PythonREPL",
"Requests",
"RequestsWrapper",
"SQLDatabase",
"SceneXplainAPIWrapper",
"SearchApiAPIWrapper",
"SearxSearchWrapper",
"SerpAPIWrapper",
"SparkSQL",
"StackExchangeAPIWrapper",
"TensorflowDatasets",
"TextRequestsWrapper",
"TwilioAPIWrapper",
"WikipediaAPIWrapper",
"WolframAlphaAPIWrapper",
"ZapierNLAWrapper",
]
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL) |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | """
**LLM** classes provide
access to the large language model (**LLM**) APIs and services.
**Class hierarchy:**
.. code-block::
BaseLanguageModel --> BaseLLM --> LLM --> <name> # Examples: AI21, HuggingFaceHub, OpenAI
**Main helpers:**
.. code-block::
LLMResult, PromptValue,
CallbackManagerForLLMRun, AsyncCallbackManagerForLLMRun,
CallbackManager, AsyncCallbackManager,
AIMessage, BaseMessage
"""
from typing import Any, Callable, Dict, Type
from langchain.llms.base import BaseLLM
def _import_ai21() -> Any:
from langchain.llms.ai21 import AI21
return AI21
def _import_aleph_alpha() -> Any:
from langchain.llms.aleph_alpha import AlephAlpha
return AlephAlpha
def _import_amazon_api_gateway() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | from langchain.llms.amazon_api_gateway import AmazonAPIGateway
return AmazonAPIGateway
def _import_anthropic() -> Any:
from langchain.llms.anthropic import Anthropic
return Anthropic
def _import_anyscale() -> Any:
from langchain.llms.anyscale import Anyscale
return Anyscale
def _import_arcee() -> Any:
from langchain.llms.arcee import Arcee
return Arcee
def _import_aviary() -> Any:
from langchain.llms.aviary import Aviary
return Aviary
def _import_azureml_endpoint() -> Any:
from langchain.llms.azureml_endpoint import AzureMLOnlineEndpoint
return AzureMLOnlineEndpoint
def _import_baidu_qianfan_endpoint() -> Any:
from langchain.llms.baidu_qianfan_endpoint import QianfanLLMEndpoint
return QianfanLLMEndpoint
def _import_bananadev() -> Any:
from langchain.llms.bananadev import Banana
return Banana
def _import_baseten() -> Any:
from langchain.llms.baseten import Baseten
return Baseten
def _import_beam() -> Any:
from langchain.llms.beam import Beam
return Beam
def _import_bedrock() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | from langchain.llms.bedrock import Bedrock
return Bedrock
def _import_bittensor() -> Any:
from langchain.llms.bittensor import NIBittensorLLM
return NIBittensorLLM
def _import_cerebriumai() -> Any:
from langchain.llms.cerebriumai import CerebriumAI
return CerebriumAI
def _import_chatglm() -> Any:
from langchain.llms.chatglm import ChatGLM
return ChatGLM
def _import_clarifai() -> Any:
from langchain.llms.clarifai import Clarifai
return Clarifai
def _import_cohere() -> Any:
from langchain.llms.cohere import Cohere
return Cohere
def _import_ctransformers() -> Any:
from langchain.llms.ctransformers import CTransformers
return CTransformers
def _import_ctranslate2() -> Any:
from langchain.llms.ctranslate2 import CTranslate2
return CTranslate2
def _import_databricks() -> Any:
from langchain.llms.databricks import Databricks
return Databricks
def _import_databricks_chat() -> Any:
from langchain.chat_models.databricks import ChatDatabricks
return ChatDatabricks
def _import_deepinfra() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | from langchain.llms.deepinfra import DeepInfra
return DeepInfra
def _import_deepsparse() -> Any:
from langchain.llms.deepsparse import DeepSparse
return DeepSparse
def _import_edenai() -> Any:
from langchain.llms.edenai import EdenAI
return EdenAI
def _import_fake() -> Any:
from langchain.llms.fake import FakeListLLM
return FakeListLLM
def _import_fireworks() -> Any:
from langchain.llms.fireworks import Fireworks
return Fireworks
def _import_forefrontai() -> Any:
from langchain.llms.forefrontai import ForefrontAI
return ForefrontAI
def _import_gigachat() -> Any:
from langchain.llms.gigachat import GigaChat
return GigaChat
def _import_google_palm() -> Any:
from langchain.llms.google_palm import GooglePalm
return GooglePalm
def _import_gooseai() -> Any:
from langchain.llms.gooseai import GooseAI
return GooseAI
def _import_gpt4all() -> Any:
from langchain.llms.gpt4all import GPT4All
return GPT4All
def _import_gradient_ai() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | from langchain.llms.gradient_ai import GradientLLM
return GradientLLM
def _import_huggingface_endpoint() -> Any:
from langchain.llms.huggingface_endpoint import HuggingFaceEndpoint
return HuggingFaceEndpoint
def _import_huggingface_hub() -> Any:
from langchain.llms.huggingface_hub import HuggingFaceHub
return HuggingFaceHub
def _import_huggingface_pipeline() -> Any:
from langchain.llms.huggingface_pipeline import HuggingFacePipeline
return HuggingFacePipeline
def _import_huggingface_text_gen_inference() -> Any:
from langchain.llms.huggingface_text_gen_inference import (
HuggingFaceTextGenInference,
)
return HuggingFaceTextGenInference
def _import_human() -> Any:
from langchain.llms.human import HumanInputLLM
return HumanInputLLM
def _import_javelin_ai_gateway() -> Any:
from langchain.llms.javelin_ai_gateway import JavelinAIGateway
return JavelinAIGateway
def _import_koboldai() -> Any:
from langchain.llms.koboldai import KoboldApiLLM
return KoboldApiLLM
def _import_llamacpp() -> Any:
from langchain.llms.llamacpp import LlamaCpp
return LlamaCpp
def _import_manifest() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | from langchain.llms.manifest import ManifestWrapper
return ManifestWrapper
def _import_minimax() -> Any:
from langchain.llms.minimax import Minimax
return Minimax
def _import_mlflow() -> Any:
from langchain.llms.mlflow import Mlflow
return Mlflow
def _import_mlflow_chat() -> Any:
from langchain.chat_models.mlflow import ChatMlflow
return ChatMlflow
def _import_mlflow_ai_gateway() -> Any:
from langchain.llms.mlflow_ai_gateway import MlflowAIGateway
return MlflowAIGateway
def _import_modal() -> Any:
from langchain.llms.modal import Modal
return Modal
def _import_mosaicml() -> Any:
from langchain.llms.mosaicml import MosaicML
return MosaicML
def _import_nlpcloud() -> Any:
from langchain.llms.nlpcloud import NLPCloud
return NLPCloud
def _import_octoai_endpoint() -> Any:
from langchain.llms.octoai_endpoint import OctoAIEndpoint
return OctoAIEndpoint
def _import_ollama() -> Any:
from langchain.llms.ollama import Ollama
return Ollama
def _import_opaqueprompts() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | from langchain.llms.opaqueprompts import OpaquePrompts
return OpaquePrompts
def _import_azure_openai() -> Any:
from langchain.llms.openai import AzureOpenAI
return AzureOpenAI
def _import_openai() -> Any:
from langchain.llms.openai import OpenAI
return OpenAI
def _import_openai_chat() -> Any:
from langchain.llms.openai import OpenAIChat
return OpenAIChat
def _import_openllm() -> Any:
from langchain.llms.openllm import OpenLLM
return OpenLLM
def _import_openlm() -> Any:
from langchain.llms.openlm import OpenLM
return OpenLM
def _import_pai_eas_endpoint() -> Any:
from langchain.llms.pai_eas_endpoint import PaiEasEndpoint
return PaiEasEndpoint
def _import_petals() -> Any:
from langchain.llms.petals import Petals
return Petals
def _import_pipelineai() -> Any:
from langchain.llms.pipelineai import PipelineAI
return PipelineAI
def _import_predibase() -> Any:
from langchain.llms.predibase import Predibase
return Predibase
def _import_predictionguard() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | from langchain.llms.predictionguard import PredictionGuard
return PredictionGuard
def _import_promptlayer() -> Any:
from langchain.llms.promptlayer_openai import PromptLayerOpenAI
return PromptLayerOpenAI
def _import_promptlayer_chat() -> Any:
from langchain.llms.promptlayer_openai import PromptLayerOpenAIChat
return PromptLayerOpenAIChat
def _import_replicate() -> Any:
from langchain.llms.replicate import Replicate
return Replicate
def _import_rwkv() -> Any:
from langchain.llms.rwkv import RWKV
return RWKV
def _import_sagemaker_endpoint() -> Any:
from langchain.llms.sagemaker_endpoint import SagemakerEndpoint
return SagemakerEndpoint
def _import_self_hosted() -> Any:
from langchain.llms.self_hosted import SelfHostedPipeline
return SelfHostedPipeline
def _import_self_hosted_hugging_face() -> Any:
from langchain.llms.self_hosted_hugging_face import SelfHostedHuggingFaceLLM
return SelfHostedHuggingFaceLLM
def _import_stochasticai() -> Any:
from langchain.llms.stochasticai import StochasticAI
return StochasticAI
def _import_symblai_nebula() -> Any:
from langchain.llms.symblai_nebula import Nebula
return Nebula
def _import_textgen() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | from langchain.llms.textgen import TextGen
return TextGen
def _import_titan_takeoff() -> Any:
from langchain.llms.titan_takeoff import TitanTakeoff
return TitanTakeoff
def _import_titan_takeoff_pro() -> Any:
from langchain.llms.titan_takeoff_pro import TitanTakeoffPro
return TitanTakeoffPro
def _import_together() -> Any:
from langchain.llms.together import Together
return Together
def _import_tongyi() -> Any:
from langchain.llms.tongyi import Tongyi
return Tongyi
def _import_vertex() -> Any:
from langchain.llms.vertexai import VertexAI
return VertexAI
def _import_vertex_model_garden() -> Any:
from langchain.llms.vertexai import VertexAIModelGarden
return VertexAIModelGarden
def _import_vllm() -> Any:
from langchain.llms.vllm import VLLM
return VLLM
def _import_vllm_openai() -> Any:
from langchain.llms.vllm import VLLMOpenAI
return VLLMOpenAI
def _import_watsonxllm() -> Any:
from langchain.llms.watsonxllm import WatsonxLLM
return WatsonxLLM
def _import_writer() -> Any: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | from langchain.llms.writer import Writer
return Writer
def _import_xinference() -> Any:
from langchain.llms.xinference import Xinference
return Xinference
def _import_yandex_gpt() -> Any:
from langchain.llms.yandex import YandexGPT
return YandexGPT
def _import_volcengine_maas() -> Any:
from langchain.llms.volcengine_maas import VolcEngineMaasLLM
return VolcEngineMaasLLM
def __getattr__(name: str) -> Any:
if name == "AI21":
return _import_ai21()
elif name == "AlephAlpha":
return _import_aleph_alpha()
elif name == "AmazonAPIGateway":
return _import_amazon_api_gateway()
elif name == "Anthropic":
return _import_anthropic()
elif name == "Anyscale":
return _import_anyscale()
elif name == "Arcee":
return _import_arcee()
elif name == "Aviary":
return _import_aviary()
elif name == "AzureMLOnlineEndpoint":
return _import_azureml_endpoint()
elif name == "QianfanLLMEndpoint":
return _import_baidu_qianfan_endpoint() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | elif name == "Banana":
return _import_bananadev()
elif name == "Baseten":
return _import_baseten()
elif name == "Beam":
return _import_beam()
elif name == "Bedrock":
return _import_bedrock()
elif name == "NIBittensorLLM":
return _import_bittensor()
elif name == "CerebriumAI":
return _import_cerebriumai()
elif name == "ChatGLM":
return _import_chatglm()
elif name == "Clarifai":
return _import_clarifai()
elif name == "Cohere":
return _import_cohere()
elif name == "CTransformers":
return _import_ctransformers()
elif name == "CTranslate2":
return _import_ctranslate2()
elif name == "Databricks":
return _import_databricks()
elif name == "DeepInfra":
return _import_deepinfra()
elif name == "DeepSparse":
return _import_deepsparse()
elif name == "EdenAI":
return _import_edenai() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | elif name == "FakeListLLM":
return _import_fake()
elif name == "Fireworks":
return _import_fireworks()
elif name == "ForefrontAI":
return _import_forefrontai()
elif name == "GigaChat":
return _import_gigachat()
elif name == "GooglePalm":
return _import_google_palm()
elif name == "GooseAI":
return _import_gooseai()
elif name == "GPT4All":
return _import_gpt4all()
elif name == "GradientLLM":
return _import_gradient_ai()
elif name == "HuggingFaceEndpoint":
return _import_huggingface_endpoint()
elif name == "HuggingFaceHub":
return _import_huggingface_hub()
elif name == "HuggingFacePipeline":
return _import_huggingface_pipeline()
elif name == "HuggingFaceTextGenInference":
return _import_huggingface_text_gen_inference()
elif name == "HumanInputLLM":
return _import_human()
elif name == "JavelinAIGateway":
return _import_javelin_ai_gateway()
elif name == "KoboldApiLLM":
return _import_koboldai() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | elif name == "LlamaCpp":
return _import_llamacpp()
elif name == "ManifestWrapper":
return _import_manifest()
elif name == "Minimax":
return _import_minimax()
elif name == "Mlflow":
return _import_mlflow()
elif name == "MlflowAIGateway":
return _import_mlflow_ai_gateway()
elif name == "Modal":
return _import_modal()
elif name == "MosaicML":
return _import_mosaicml()
elif name == "NLPCloud":
return _import_nlpcloud()
elif name == "OctoAIEndpoint":
return _import_octoai_endpoint()
elif name == "Ollama":
return _import_ollama()
elif name == "OpaquePrompts":
return _import_opaqueprompts()
elif name == "AzureOpenAI":
return _import_azure_openai()
elif name == "OpenAI":
return _import_openai()
elif name == "OpenAIChat":
return _import_openai_chat()
elif name == "OpenLLM":
return _import_openllm() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | elif name == "OpenLM":
return _import_openlm()
elif name == "PaiEasEndpoint":
return _import_pai_eas_endpoint()
elif name == "Petals":
return _import_petals()
elif name == "PipelineAI":
return _import_pipelineai()
elif name == "Predibase":
return _import_predibase()
elif name == "PredictionGuard":
return _import_predictionguard()
elif name == "PromptLayerOpenAI":
return _import_promptlayer()
elif name == "PromptLayerOpenAIChat":
return _import_promptlayer_chat()
elif name == "Replicate":
return _import_replicate()
elif name == "RWKV":
return _import_rwkv()
elif name == "SagemakerEndpoint":
return _import_sagemaker_endpoint()
elif name == "SelfHostedPipeline":
return _import_self_hosted()
elif name == "SelfHostedHuggingFaceLLM":
return _import_self_hosted_hugging_face()
elif name == "StochasticAI":
return _import_stochasticai()
elif name == "Nebula":
return _import_symblai_nebula() |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | elif name == "TextGen":
return _import_textgen()
elif name == "TitanTakeoff":
return _import_titan_takeoff()
elif name == "TitanTakeoffPro":
return _import_titan_takeoff_pro()
elif name == "Together":
return _import_together()
elif name == "Tongyi":
return _import_tongyi()
elif name == "VertexAI":
return _import_vertex()
elif name == "VertexAIModelGarden":
return _import_vertex_model_garden()
elif name == "VLLM":
return _import_vllm()
elif name == "VLLMOpenAI":
return _import_vllm_openai()
elif name == "WatsonxLLM":
return _import_watsonxllm()
elif name == "Writer":
return _import_writer()
elif name == "Xinference":
return _import_xinference()
elif name == "YandexGPT":
return _import_yandex_gpt()
elif name == "VolcEngineMaasLLM":
return _import_volcengine_maas()
elif name == "type_to_cls_dict": |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | type_to_cls_dict: Dict[str, Type[BaseLLM]] = {
k: v() for k, v in get_type_to_cls_dict().items()
}
return type_to_cls_dict
else:
raise AttributeError(f"Could not find: {name}")
__all__ = [
"AI21",
"AlephAlpha",
"AmazonAPIGateway",
"Anthropic",
"Anyscale",
"Arcee",
"Aviary",
"AzureMLOnlineEndpoint",
"AzureOpenAI",
"Banana",
"Baseten",
"Beam",
"Bedrock",
"CTransformers",
"CTranslate2",
"CerebriumAI",
"ChatGLM",
"Clarifai",
"Cohere",
"Databricks",
"DeepInfra",
"DeepSparse",
"EdenAI", |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | "FakeListLLM",
"Fireworks",
"ForefrontAI",
"GigaChat",
"GPT4All",
"GooglePalm",
"GooseAI",
"GradientLLM",
"HuggingFaceEndpoint",
"HuggingFaceHub",
"HuggingFacePipeline",
"HuggingFaceTextGenInference",
"HumanInputLLM",
"KoboldApiLLM",
"LlamaCpp",
"TextGen",
"ManifestWrapper",
"Minimax",
"MlflowAIGateway",
"Modal",
"MosaicML",
"Nebula",
"NIBittensorLLM",
"NLPCloud",
"Ollama",
"OpenAI",
"OpenAIChat",
"OpenLLM",
"OpenLM",
"PaiEasEndpoint", |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | "Petals",
"PipelineAI",
"Predibase",
"PredictionGuard",
"PromptLayerOpenAI",
"PromptLayerOpenAIChat",
"OpaquePrompts",
"RWKV",
"Replicate",
"SagemakerEndpoint",
"SelfHostedHuggingFaceLLM",
"SelfHostedPipeline",
"StochasticAI",
"TitanTakeoff",
"TitanTakeoffPro",
"Tongyi",
"VertexAI",
"VertexAIModelGarden",
"VLLM",
"VLLMOpenAI",
"WatsonxLLM",
"Writer",
"OctoAIEndpoint",
"Xinference",
"JavelinAIGateway",
"QianfanLLMEndpoint",
"YandexGPT",
"VolcEngineMaasLLM",
]
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
"amazon_bedrock": _import_bedrock,
"anthropic": _import_anthropic,
"anyscale": _import_anyscale,
"arcee": _import_arcee,
"aviary": _import_aviary,
"azure": _import_azure_openai,
"azureml_endpoint": _import_azureml_endpoint,
"bananadev": _import_bananadev,
"baseten": _import_baseten,
"beam": _import_beam,
"cerebriumai": _import_cerebriumai,
"chat_glm": _import_chatglm,
"clarifai": _import_clarifai,
"cohere": _import_cohere,
"ctransformers": _import_ctransformers,
"ctranslate2": _import_ctranslate2,
"databricks": _import_databricks,
"databricks-chat": _import_databricks_chat, |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | "deepinfra": _import_deepinfra,
"deepsparse": _import_deepsparse,
"edenai": _import_edenai,
"fake-list": _import_fake,
"forefrontai": _import_forefrontai,
"giga-chat-model": _import_gigachat,
"google_palm": _import_google_palm,
"gooseai": _import_gooseai,
"gradient": _import_gradient_ai,
"gpt4all": _import_gpt4all,
"huggingface_endpoint": _import_huggingface_endpoint,
"huggingface_hub": _import_huggingface_hub,
"huggingface_pipeline": _import_huggingface_pipeline,
"huggingface_textgen_inference": _import_huggingface_text_gen_inference,
"human-input": _import_human,
"koboldai": _import_koboldai,
"llamacpp": _import_llamacpp,
"textgen": _import_textgen,
"minimax": _import_minimax,
"mlflow": _import_mlflow,
"mlflow-chat": _import_mlflow_chat,
"mlflow-ai-gateway": _import_mlflow_ai_gateway,
"modal": _import_modal,
"mosaic": _import_mosaicml,
"nebula": _import_symblai_nebula,
"nibittensor": _import_bittensor,
"nlpcloud": _import_nlpcloud,
"ollama": _import_ollama,
"openai": _import_openai,
"openlm": _import_openlm, |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,127 | Volc Engine MaaS has wrong entry in LLM type to class dict (causing SpaCy to not work with LangChain anymore) | ### System Info
* Windows 11 Home (build 22621.2715)
* Python 3.12.0
* Clean virtual environment using Poetry with following dependencies:
```
python = "3.12.0"
langchain = "0.0.344"
spacy = "3.7.2"
spacy-llm = "0.6.4"
```
### Who can help?
@h3l As the creator of the pull request where VolcEngine was introduced
@baskaryan As tag handler of that pull request
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
Anything that triggers spaCy's registry to make an inventory, for example:
```python
import spacy
spacy.blank("en")
```
With the last part of the Traceback being:
```
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain\llms\__init__.py", line 699, in __getattr__
k: v() for k, v in get_type_to_cls_dict().items()
^^^
File "PROJECT_FOLDER\.venv\Lib\site-packages\langchain_core\load\serializable.py", line 97, in __init__
super().__init__(**kwargs)
File "PROJECT_FOLDER\.venv\Lib\site-packages\pydantic\v1\main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for VolcEngineMaasLLM
__root__
Did not find volc_engine_maas_ak, please add an environment variable `VOLC_ACCESSKEY` which contains it, or pass `volc_engine_maas_ak` as a named parameter. (type=value_error)
```
#### What I think causes this
I am quite certain that this is caused by [`langchain.llms.__init__.py:869 (for commit b161f30)`](https://github.com/langchain-ai/langchain/blob/b161f302ff56a14d8d0331cbec4a3efa23d06e1a/libs/langchain/langchain/llms/__init__.py#L869C51-L869C51):
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# Line below is the only that actually calls the import function, returning a class instead of an import function
"VolcEngineMaasLLM": _import_volcengine_maas(),
}
```
The Volc Engine Maas LLM is the only in this dict to actually call the import function, while all other entries only the function itself, and do not call it.
### Expected behavior
Class to type dict only returns import functions, not actual classes:
```python
def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
return {
"ai21": _import_ai21,
"aleph_alpha": _import_aleph_alpha,
"amazon_api_gateway": _import_amazon_api_gateway,
...
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
# What I think would be correct (now without function call)
"VolcEngineMaasLLM": _import_volcengine_maas,
}
```
Unfortunately I don't have time to put in a PR myself, but I hope this helps finding the solution!
| https://github.com/langchain-ai/langchain/issues/14127 | https://github.com/langchain-ai/langchain/pull/14194 | 6ae0194dc70119d8b05a0624a6cc4950f9f84608 | 818252b1f8b9ac9af6bb80d43b21c5e95d6b2e11 | "2023-12-01T13:58:13Z" | python | "2023-12-03T16:43:23Z" | libs/langchain/langchain/llms/__init__.py | "pai_eas_endpoint": _import_pai_eas_endpoint,
"petals": _import_petals,
"pipelineai": _import_pipelineai,
"predibase": _import_predibase,
"opaqueprompts": _import_opaqueprompts,
"replicate": _import_replicate,
"rwkv": _import_rwkv,
"sagemaker_endpoint": _import_sagemaker_endpoint,
"self_hosted": _import_self_hosted,
"self_hosted_hugging_face": _import_self_hosted_hugging_face,
"stochasticai": _import_stochasticai,
"together": _import_together,
"tongyi": _import_tongyi,
"titan_takeoff": _import_titan_takeoff,
"titan_takeoff_pro": _import_titan_takeoff_pro,
"vertexai": _import_vertex,
"vertexai_model_garden": _import_vertex_model_garden,
"openllm": _import_openllm,
"openllm_client": _import_openllm,
"vllm": _import_vllm,
"vllm_openai": _import_vllm_openai,
"watsonxllm": _import_watsonxllm,
"writer": _import_writer,
"xinference": _import_xinference,
"javelin-ai-gateway": _import_javelin_ai_gateway,
"qianfan_endpoint": _import_baidu_qianfan_endpoint,
"yandex_gpt": _import_yandex_gpt,
"VolcEngineMaasLLM": _import_volcengine_maas(),
} |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,069 | AzureOpenAI azure_ad_token_provider Keyerror | ### System Info
When I use below snippet of code
```
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
```
I get error :
```---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[36], line 21
18 # api_version = "2023-05-15"
19 endpoint = "https://xxxx.openai.azure.com"
---> 21 client = AzureOpenAI(
22 azure_endpoint=endpoint,
23 api_version="2023-05-15",
24 azure_deployment="example-gpt-4",
25 azure_ad_token_provider=token_provider,
26 )
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain_core/load/serializable.py:97, in Serializable.__init__(self, **kwargs)
96 def __init__(self, **kwargs: Any) -> None:
---> 97 super().__init__(**kwargs)
98 self._lc_kwargs = kwargs
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:339, in BaseModel.__init__(__pydantic_self__, **data)
333 """
334 Create a new model by parsing and validating input data from keyword arguments.
335
336 Raises ValidationError if the input data cannot be parsed to form a valid model.
337 """
338 # Uses something other than `self` the first arg to allow "self" as a settable attribute
--> 339 values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
340 if validation_error:
341 raise validation_error
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:1102, in validate_model(model, input_data, cls)
1100 continue
1101 try:
-> 1102 values = validator(cls_, values)
1103 except (ValueError, TypeError, AssertionError) as exc:
1104 errors.append(ErrorWrapper(exc, loc=ROOT_KEY))
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain/llms/openai.py:887, in AzureOpenAI.validate_environment(cls, values)
877 values["openai_api_base"] += (
878 "/deployments/" + values["deployment_name"]
879 )
880 values["deployment_name"] = None
881 client_params = {
882 "api_version": values["openai_api_version"],
883 "azure_endpoint": values["azure_endpoint"],
884 "azure_deployment": values["deployment_name"],
885 "api_key": values["openai_api_key"],
886 "azure_ad_token": values["azure_ad_token"],
--> 887 "azure_ad_token_provider": values["azure_ad_token_provider"],
888 "organization": values["openai_organization"],
889 "base_url": values["openai_api_base"],
890 "timeout": values["request_timeout"],
891 "max_retries": values["max_retries"],
892 "default_headers": values["default_headers"],
893 "default_query": values["default_query"],
894 "http_client": values["http_client"],
895 }
896 values["client"] = openai.AzureOpenAI(**client_params).completions
897 values["async_client"] = openai.AsyncAzureOpenAI(
898 **client_params
899 ).completions
KeyError: 'azure_ad_token_provider'
```
Ive also tried AzureChatOpenAI , and I get the same error back.
The error is not reproduced when I use openai library AzureOpenAI .
Also on openai the azure_ad_token_provider has type azure_ad_token_provider: 'AzureADTokenProvider | None' = None while in langchain it has type azure_ad_token_provider: Optional[str] = None which also makes me wonder if it would take as input a different type than string to work with.
any ideas on how to fix this? Im actually using Azure Service principal authentication, and if I use as alternative field azure_ad_token = credential.get_token(“https://cognitiveservices.azure.com/.default”).token I get token expired after 60min which does not happen with a bearer token, so It is important to me to make the token_provider work.
libraries :
pydantic 1.10.12
pydantic_core 2.10.1
openai 1.2.0
langchain 0.0.342
langchain-core 0.0.7
### Who can help?
@hwchase17 @agola11
### Information
- [X] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
### Expected behavior
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
should return a Runnable instance which I can use for LLMChain | https://github.com/langchain-ai/langchain/issues/14069 | https://github.com/langchain-ai/langchain/pull/14166 | 9938086df07d69d24f9770209ea9087d3b906155 | 62505043be20cf8af491e30785a6ca0eeb1d276e | "2023-11-30T13:39:55Z" | python | "2023-12-03T16:55:25Z" | libs/langchain/langchain/chat_models/azure_openai.py | """Azure OpenAI chat wrapper."""
from __future__ import annotations
import logging
import os
import warnings
from typing import Any, Dict, Union
from langchain_core.outputs import ChatResult
from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
from langchain.chat_models.openai import ChatOpenAI
from langchain.utils import get_from_dict_or_env
from langchain.utils.openai import is_openai_v1
logger = logging.getLogger(__name__)
class AzureChatOpenAI(ChatOpenAI): |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,069 | AzureOpenAI azure_ad_token_provider Keyerror | ### System Info
When I use below snippet of code
```
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
```
I get error :
```---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[36], line 21
18 # api_version = "2023-05-15"
19 endpoint = "https://xxxx.openai.azure.com"
---> 21 client = AzureOpenAI(
22 azure_endpoint=endpoint,
23 api_version="2023-05-15",
24 azure_deployment="example-gpt-4",
25 azure_ad_token_provider=token_provider,
26 )
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain_core/load/serializable.py:97, in Serializable.__init__(self, **kwargs)
96 def __init__(self, **kwargs: Any) -> None:
---> 97 super().__init__(**kwargs)
98 self._lc_kwargs = kwargs
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:339, in BaseModel.__init__(__pydantic_self__, **data)
333 """
334 Create a new model by parsing and validating input data from keyword arguments.
335
336 Raises ValidationError if the input data cannot be parsed to form a valid model.
337 """
338 # Uses something other than `self` the first arg to allow "self" as a settable attribute
--> 339 values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
340 if validation_error:
341 raise validation_error
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:1102, in validate_model(model, input_data, cls)
1100 continue
1101 try:
-> 1102 values = validator(cls_, values)
1103 except (ValueError, TypeError, AssertionError) as exc:
1104 errors.append(ErrorWrapper(exc, loc=ROOT_KEY))
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain/llms/openai.py:887, in AzureOpenAI.validate_environment(cls, values)
877 values["openai_api_base"] += (
878 "/deployments/" + values["deployment_name"]
879 )
880 values["deployment_name"] = None
881 client_params = {
882 "api_version": values["openai_api_version"],
883 "azure_endpoint": values["azure_endpoint"],
884 "azure_deployment": values["deployment_name"],
885 "api_key": values["openai_api_key"],
886 "azure_ad_token": values["azure_ad_token"],
--> 887 "azure_ad_token_provider": values["azure_ad_token_provider"],
888 "organization": values["openai_organization"],
889 "base_url": values["openai_api_base"],
890 "timeout": values["request_timeout"],
891 "max_retries": values["max_retries"],
892 "default_headers": values["default_headers"],
893 "default_query": values["default_query"],
894 "http_client": values["http_client"],
895 }
896 values["client"] = openai.AzureOpenAI(**client_params).completions
897 values["async_client"] = openai.AsyncAzureOpenAI(
898 **client_params
899 ).completions
KeyError: 'azure_ad_token_provider'
```
Ive also tried AzureChatOpenAI , and I get the same error back.
The error is not reproduced when I use openai library AzureOpenAI .
Also on openai the azure_ad_token_provider has type azure_ad_token_provider: 'AzureADTokenProvider | None' = None while in langchain it has type azure_ad_token_provider: Optional[str] = None which also makes me wonder if it would take as input a different type than string to work with.
any ideas on how to fix this? Im actually using Azure Service principal authentication, and if I use as alternative field azure_ad_token = credential.get_token(“https://cognitiveservices.azure.com/.default”).token I get token expired after 60min which does not happen with a bearer token, so It is important to me to make the token_provider work.
libraries :
pydantic 1.10.12
pydantic_core 2.10.1
openai 1.2.0
langchain 0.0.342
langchain-core 0.0.7
### Who can help?
@hwchase17 @agola11
### Information
- [X] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
### Expected behavior
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
should return a Runnable instance which I can use for LLMChain | https://github.com/langchain-ai/langchain/issues/14069 | https://github.com/langchain-ai/langchain/pull/14166 | 9938086df07d69d24f9770209ea9087d3b906155 | 62505043be20cf8af491e30785a6ca0eeb1d276e | "2023-11-30T13:39:55Z" | python | "2023-12-03T16:55:25Z" | libs/langchain/langchain/chat_models/azure_openai.py | """`Azure OpenAI` Chat Completion API.
To use this class you
must have a deployed model on Azure OpenAI. Use `deployment_name` in the
constructor to refer to the "Model deployment name" in the Azure portal.
In addition, you should have the ``openai`` python package installed, and the
following environment variables set or passed in constructor in lower case:
- ``AZURE_OPENAI_API_KEY``
- ``AZURE_OPENAI_API_ENDPOINT``
- ``AZURE_OPENAI_AD_TOKEN``
- ``OPENAI_API_VERSION``
- ``OPENAI_PROXY``
For example, if you have `gpt-35-turbo` deployed, with the deployment name
`35-turbo-dev`, the constructor should look like:
.. code-block:: python
AzureChatOpenAI(
azure_deployment="35-turbo-dev",
openai_api_version="2023-05-15",
)
Be aware the API version may change.
You can also specify the version of the model using ``model_version`` constructor
parameter, as Azure OpenAI doesn't return model version with the response.
Default is empty. When you specify the version, it will be appended to the |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,069 | AzureOpenAI azure_ad_token_provider Keyerror | ### System Info
When I use below snippet of code
```
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
```
I get error :
```---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[36], line 21
18 # api_version = "2023-05-15"
19 endpoint = "https://xxxx.openai.azure.com"
---> 21 client = AzureOpenAI(
22 azure_endpoint=endpoint,
23 api_version="2023-05-15",
24 azure_deployment="example-gpt-4",
25 azure_ad_token_provider=token_provider,
26 )
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain_core/load/serializable.py:97, in Serializable.__init__(self, **kwargs)
96 def __init__(self, **kwargs: Any) -> None:
---> 97 super().__init__(**kwargs)
98 self._lc_kwargs = kwargs
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:339, in BaseModel.__init__(__pydantic_self__, **data)
333 """
334 Create a new model by parsing and validating input data from keyword arguments.
335
336 Raises ValidationError if the input data cannot be parsed to form a valid model.
337 """
338 # Uses something other than `self` the first arg to allow "self" as a settable attribute
--> 339 values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
340 if validation_error:
341 raise validation_error
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:1102, in validate_model(model, input_data, cls)
1100 continue
1101 try:
-> 1102 values = validator(cls_, values)
1103 except (ValueError, TypeError, AssertionError) as exc:
1104 errors.append(ErrorWrapper(exc, loc=ROOT_KEY))
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain/llms/openai.py:887, in AzureOpenAI.validate_environment(cls, values)
877 values["openai_api_base"] += (
878 "/deployments/" + values["deployment_name"]
879 )
880 values["deployment_name"] = None
881 client_params = {
882 "api_version": values["openai_api_version"],
883 "azure_endpoint": values["azure_endpoint"],
884 "azure_deployment": values["deployment_name"],
885 "api_key": values["openai_api_key"],
886 "azure_ad_token": values["azure_ad_token"],
--> 887 "azure_ad_token_provider": values["azure_ad_token_provider"],
888 "organization": values["openai_organization"],
889 "base_url": values["openai_api_base"],
890 "timeout": values["request_timeout"],
891 "max_retries": values["max_retries"],
892 "default_headers": values["default_headers"],
893 "default_query": values["default_query"],
894 "http_client": values["http_client"],
895 }
896 values["client"] = openai.AzureOpenAI(**client_params).completions
897 values["async_client"] = openai.AsyncAzureOpenAI(
898 **client_params
899 ).completions
KeyError: 'azure_ad_token_provider'
```
Ive also tried AzureChatOpenAI , and I get the same error back.
The error is not reproduced when I use openai library AzureOpenAI .
Also on openai the azure_ad_token_provider has type azure_ad_token_provider: 'AzureADTokenProvider | None' = None while in langchain it has type azure_ad_token_provider: Optional[str] = None which also makes me wonder if it would take as input a different type than string to work with.
any ideas on how to fix this? Im actually using Azure Service principal authentication, and if I use as alternative field azure_ad_token = credential.get_token(“https://cognitiveservices.azure.com/.default”).token I get token expired after 60min which does not happen with a bearer token, so It is important to me to make the token_provider work.
libraries :
pydantic 1.10.12
pydantic_core 2.10.1
openai 1.2.0
langchain 0.0.342
langchain-core 0.0.7
### Who can help?
@hwchase17 @agola11
### Information
- [X] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
### Expected behavior
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
should return a Runnable instance which I can use for LLMChain | https://github.com/langchain-ai/langchain/issues/14069 | https://github.com/langchain-ai/langchain/pull/14166 | 9938086df07d69d24f9770209ea9087d3b906155 | 62505043be20cf8af491e30785a6ca0eeb1d276e | "2023-11-30T13:39:55Z" | python | "2023-12-03T16:55:25Z" | libs/langchain/langchain/chat_models/azure_openai.py | model name in the response. Setting correct version will help you to calculate the
cost properly. Model version is not validated, so make sure you set it correctly
to get the correct cost.
Any parameters that are valid to be passed to the openai.create call can be passed
in, even if not explicitly saved on this class.
"""
azure_endpoint: Union[str, None] = None
"""Your Azure endpoint, including the resource.
Automatically inferred from env var `AZURE_OPENAI_ENDPOINT` if not provided.
Example: `https://example-resource.azure.openai.com/`
"""
deployment_name: Union[str, None] = Field(default=None, alias="azure_deployment")
"""A model deployment.
If given sets the base client URL to include `/deployments/{azure_deployment}`.
Note: this means you won't be able to use non-deployment endpoints.
"""
openai_api_version: str = Field(default="", alias="api_version")
"""Automatically inferred from env var `OPENAI_API_VERSION` if not provided."""
openai_api_key: Union[str, None] = Field(default=None, alias="api_key")
"""Automatically inferred from env var `AZURE_OPENAI_API_KEY` if not provided."""
azure_ad_token: Union[str, None] = None
"""Your Azure Active Directory token.
Automatically inferred from env var `AZURE_OPENAI_AD_TOKEN` if not provided.
For more:
https://www.microsoft.com/en-us/security/business/identity-access/microsoft-entra-id. |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,069 | AzureOpenAI azure_ad_token_provider Keyerror | ### System Info
When I use below snippet of code
```
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
```
I get error :
```---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[36], line 21
18 # api_version = "2023-05-15"
19 endpoint = "https://xxxx.openai.azure.com"
---> 21 client = AzureOpenAI(
22 azure_endpoint=endpoint,
23 api_version="2023-05-15",
24 azure_deployment="example-gpt-4",
25 azure_ad_token_provider=token_provider,
26 )
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain_core/load/serializable.py:97, in Serializable.__init__(self, **kwargs)
96 def __init__(self, **kwargs: Any) -> None:
---> 97 super().__init__(**kwargs)
98 self._lc_kwargs = kwargs
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:339, in BaseModel.__init__(__pydantic_self__, **data)
333 """
334 Create a new model by parsing and validating input data from keyword arguments.
335
336 Raises ValidationError if the input data cannot be parsed to form a valid model.
337 """
338 # Uses something other than `self` the first arg to allow "self" as a settable attribute
--> 339 values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
340 if validation_error:
341 raise validation_error
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:1102, in validate_model(model, input_data, cls)
1100 continue
1101 try:
-> 1102 values = validator(cls_, values)
1103 except (ValueError, TypeError, AssertionError) as exc:
1104 errors.append(ErrorWrapper(exc, loc=ROOT_KEY))
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain/llms/openai.py:887, in AzureOpenAI.validate_environment(cls, values)
877 values["openai_api_base"] += (
878 "/deployments/" + values["deployment_name"]
879 )
880 values["deployment_name"] = None
881 client_params = {
882 "api_version": values["openai_api_version"],
883 "azure_endpoint": values["azure_endpoint"],
884 "azure_deployment": values["deployment_name"],
885 "api_key": values["openai_api_key"],
886 "azure_ad_token": values["azure_ad_token"],
--> 887 "azure_ad_token_provider": values["azure_ad_token_provider"],
888 "organization": values["openai_organization"],
889 "base_url": values["openai_api_base"],
890 "timeout": values["request_timeout"],
891 "max_retries": values["max_retries"],
892 "default_headers": values["default_headers"],
893 "default_query": values["default_query"],
894 "http_client": values["http_client"],
895 }
896 values["client"] = openai.AzureOpenAI(**client_params).completions
897 values["async_client"] = openai.AsyncAzureOpenAI(
898 **client_params
899 ).completions
KeyError: 'azure_ad_token_provider'
```
Ive also tried AzureChatOpenAI , and I get the same error back.
The error is not reproduced when I use openai library AzureOpenAI .
Also on openai the azure_ad_token_provider has type azure_ad_token_provider: 'AzureADTokenProvider | None' = None while in langchain it has type azure_ad_token_provider: Optional[str] = None which also makes me wonder if it would take as input a different type than string to work with.
any ideas on how to fix this? Im actually using Azure Service principal authentication, and if I use as alternative field azure_ad_token = credential.get_token(“https://cognitiveservices.azure.com/.default”).token I get token expired after 60min which does not happen with a bearer token, so It is important to me to make the token_provider work.
libraries :
pydantic 1.10.12
pydantic_core 2.10.1
openai 1.2.0
langchain 0.0.342
langchain-core 0.0.7
### Who can help?
@hwchase17 @agola11
### Information
- [X] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
### Expected behavior
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
should return a Runnable instance which I can use for LLMChain | https://github.com/langchain-ai/langchain/issues/14069 | https://github.com/langchain-ai/langchain/pull/14166 | 9938086df07d69d24f9770209ea9087d3b906155 | 62505043be20cf8af491e30785a6ca0eeb1d276e | "2023-11-30T13:39:55Z" | python | "2023-12-03T16:55:25Z" | libs/langchain/langchain/chat_models/azure_openai.py | """
azure_ad_token_provider: Union[str, None] = None
"""A function that returns an Azure Active Directory token.
Will be invoked on every request.
"""
model_version: str = ""
"""Legacy, for openai<1.0.0 support."""
openai_api_type: str = ""
"""Legacy, for openai<1.0.0 support."""
validate_base_url: bool = True
"""For backwards compatibility. If legacy val openai_api_base is passed in, try to
infer if it is a base_url or azure_endpoint and update accordingly.
"""
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""
if values["n"] < 1:
raise ValueError("n must be at least 1.")
if values["n"] > 1 and values["streaming"]:
raise ValueError("n must be 1 when streaming.")
values["openai_api_key"] = (
values["openai_api_key"]
or os.getenv("AZURE_OPENAI_API_KEY")
or os.getenv("OPENAI_API_KEY")
)
values["openai_api_base"] = values["openai_api_base"] or os.getenv( |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,069 | AzureOpenAI azure_ad_token_provider Keyerror | ### System Info
When I use below snippet of code
```
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
```
I get error :
```---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[36], line 21
18 # api_version = "2023-05-15"
19 endpoint = "https://xxxx.openai.azure.com"
---> 21 client = AzureOpenAI(
22 azure_endpoint=endpoint,
23 api_version="2023-05-15",
24 azure_deployment="example-gpt-4",
25 azure_ad_token_provider=token_provider,
26 )
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain_core/load/serializable.py:97, in Serializable.__init__(self, **kwargs)
96 def __init__(self, **kwargs: Any) -> None:
---> 97 super().__init__(**kwargs)
98 self._lc_kwargs = kwargs
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:339, in BaseModel.__init__(__pydantic_self__, **data)
333 """
334 Create a new model by parsing and validating input data from keyword arguments.
335
336 Raises ValidationError if the input data cannot be parsed to form a valid model.
337 """
338 # Uses something other than `self` the first arg to allow "self" as a settable attribute
--> 339 values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
340 if validation_error:
341 raise validation_error
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:1102, in validate_model(model, input_data, cls)
1100 continue
1101 try:
-> 1102 values = validator(cls_, values)
1103 except (ValueError, TypeError, AssertionError) as exc:
1104 errors.append(ErrorWrapper(exc, loc=ROOT_KEY))
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain/llms/openai.py:887, in AzureOpenAI.validate_environment(cls, values)
877 values["openai_api_base"] += (
878 "/deployments/" + values["deployment_name"]
879 )
880 values["deployment_name"] = None
881 client_params = {
882 "api_version": values["openai_api_version"],
883 "azure_endpoint": values["azure_endpoint"],
884 "azure_deployment": values["deployment_name"],
885 "api_key": values["openai_api_key"],
886 "azure_ad_token": values["azure_ad_token"],
--> 887 "azure_ad_token_provider": values["azure_ad_token_provider"],
888 "organization": values["openai_organization"],
889 "base_url": values["openai_api_base"],
890 "timeout": values["request_timeout"],
891 "max_retries": values["max_retries"],
892 "default_headers": values["default_headers"],
893 "default_query": values["default_query"],
894 "http_client": values["http_client"],
895 }
896 values["client"] = openai.AzureOpenAI(**client_params).completions
897 values["async_client"] = openai.AsyncAzureOpenAI(
898 **client_params
899 ).completions
KeyError: 'azure_ad_token_provider'
```
Ive also tried AzureChatOpenAI , and I get the same error back.
The error is not reproduced when I use openai library AzureOpenAI .
Also on openai the azure_ad_token_provider has type azure_ad_token_provider: 'AzureADTokenProvider | None' = None while in langchain it has type azure_ad_token_provider: Optional[str] = None which also makes me wonder if it would take as input a different type than string to work with.
any ideas on how to fix this? Im actually using Azure Service principal authentication, and if I use as alternative field azure_ad_token = credential.get_token(“https://cognitiveservices.azure.com/.default”).token I get token expired after 60min which does not happen with a bearer token, so It is important to me to make the token_provider work.
libraries :
pydantic 1.10.12
pydantic_core 2.10.1
openai 1.2.0
langchain 0.0.342
langchain-core 0.0.7
### Who can help?
@hwchase17 @agola11
### Information
- [X] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
### Expected behavior
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
should return a Runnable instance which I can use for LLMChain | https://github.com/langchain-ai/langchain/issues/14069 | https://github.com/langchain-ai/langchain/pull/14166 | 9938086df07d69d24f9770209ea9087d3b906155 | 62505043be20cf8af491e30785a6ca0eeb1d276e | "2023-11-30T13:39:55Z" | python | "2023-12-03T16:55:25Z" | libs/langchain/langchain/chat_models/azure_openai.py | "OPENAI_API_BASE"
)
values["openai_api_version"] = values["openai_api_version"] or os.getenv(
"OPENAI_API_VERSION"
)
values["openai_organization"] = (
values["openai_organization"]
or os.getenv("OPENAI_ORG_ID")
or os.getenv("OPENAI_ORGANIZATION")
)
values["azure_endpoint"] = values["azure_endpoint"] or os.getenv(
"AZURE_OPENAI_ENDPOINT"
)
values["azure_ad_token"] = values["azure_ad_token"] or os.getenv(
"AZURE_OPENAI_AD_TOKEN"
)
values["openai_api_type"] = get_from_dict_or_env(
values, "openai_api_type", "OPENAI_API_TYPE", default="azure"
)
values["openai_proxy"] = get_from_dict_or_env(
values, "openai_proxy", "OPENAI_PROXY", default=""
)
try:
import openai
except ImportError:
raise ImportError(
"Could not import openai python package. "
"Please install it with `pip install openai`."
) |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,069 | AzureOpenAI azure_ad_token_provider Keyerror | ### System Info
When I use below snippet of code
```
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
```
I get error :
```---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[36], line 21
18 # api_version = "2023-05-15"
19 endpoint = "https://xxxx.openai.azure.com"
---> 21 client = AzureOpenAI(
22 azure_endpoint=endpoint,
23 api_version="2023-05-15",
24 azure_deployment="example-gpt-4",
25 azure_ad_token_provider=token_provider,
26 )
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain_core/load/serializable.py:97, in Serializable.__init__(self, **kwargs)
96 def __init__(self, **kwargs: Any) -> None:
---> 97 super().__init__(**kwargs)
98 self._lc_kwargs = kwargs
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:339, in BaseModel.__init__(__pydantic_self__, **data)
333 """
334 Create a new model by parsing and validating input data from keyword arguments.
335
336 Raises ValidationError if the input data cannot be parsed to form a valid model.
337 """
338 # Uses something other than `self` the first arg to allow "self" as a settable attribute
--> 339 values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
340 if validation_error:
341 raise validation_error
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:1102, in validate_model(model, input_data, cls)
1100 continue
1101 try:
-> 1102 values = validator(cls_, values)
1103 except (ValueError, TypeError, AssertionError) as exc:
1104 errors.append(ErrorWrapper(exc, loc=ROOT_KEY))
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain/llms/openai.py:887, in AzureOpenAI.validate_environment(cls, values)
877 values["openai_api_base"] += (
878 "/deployments/" + values["deployment_name"]
879 )
880 values["deployment_name"] = None
881 client_params = {
882 "api_version": values["openai_api_version"],
883 "azure_endpoint": values["azure_endpoint"],
884 "azure_deployment": values["deployment_name"],
885 "api_key": values["openai_api_key"],
886 "azure_ad_token": values["azure_ad_token"],
--> 887 "azure_ad_token_provider": values["azure_ad_token_provider"],
888 "organization": values["openai_organization"],
889 "base_url": values["openai_api_base"],
890 "timeout": values["request_timeout"],
891 "max_retries": values["max_retries"],
892 "default_headers": values["default_headers"],
893 "default_query": values["default_query"],
894 "http_client": values["http_client"],
895 }
896 values["client"] = openai.AzureOpenAI(**client_params).completions
897 values["async_client"] = openai.AsyncAzureOpenAI(
898 **client_params
899 ).completions
KeyError: 'azure_ad_token_provider'
```
Ive also tried AzureChatOpenAI , and I get the same error back.
The error is not reproduced when I use openai library AzureOpenAI .
Also on openai the azure_ad_token_provider has type azure_ad_token_provider: 'AzureADTokenProvider | None' = None while in langchain it has type azure_ad_token_provider: Optional[str] = None which also makes me wonder if it would take as input a different type than string to work with.
any ideas on how to fix this? Im actually using Azure Service principal authentication, and if I use as alternative field azure_ad_token = credential.get_token(“https://cognitiveservices.azure.com/.default”).token I get token expired after 60min which does not happen with a bearer token, so It is important to me to make the token_provider work.
libraries :
pydantic 1.10.12
pydantic_core 2.10.1
openai 1.2.0
langchain 0.0.342
langchain-core 0.0.7
### Who can help?
@hwchase17 @agola11
### Information
- [X] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
### Expected behavior
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
should return a Runnable instance which I can use for LLMChain | https://github.com/langchain-ai/langchain/issues/14069 | https://github.com/langchain-ai/langchain/pull/14166 | 9938086df07d69d24f9770209ea9087d3b906155 | 62505043be20cf8af491e30785a6ca0eeb1d276e | "2023-11-30T13:39:55Z" | python | "2023-12-03T16:55:25Z" | libs/langchain/langchain/chat_models/azure_openai.py | if is_openai_v1():
openai_api_base = values["openai_api_base"]
if openai_api_base and values["validate_base_url"]:
if "/openai" not in openai_api_base:
values["openai_api_base"] = (
values["openai_api_base"].rstrip("/") + "/openai"
)
warnings.warn(
"As of openai>=1.0.0, Azure endpoints should be specified via "
f"the `azure_endpoint` param not `openai_api_base` "
f"(or alias `base_url`). Updating `openai_api_base` from "
f"{openai_api_base} to {values['openai_api_base']}."
)
if values["deployment_name"]:
warnings.warn(
"As of openai>=1.0.0, if `deployment_name` (or alias "
"`azure_deployment`) is specified then "
"`openai_api_base` (or alias `base_url`) should not be. "
"Instead use `deployment_name` (or alias `azure_deployment`) "
"and `azure_endpoint`."
)
if values["deployment_name"] not in values["openai_api_base"]:
warnings.warn(
"As of openai>=1.0.0, if `openai_api_base` "
"(or alias `base_url`) is specified it is expected to be "
"of the form "
"https://example-resource.azure.openai.com/openai/deployments/example-deployment. "
f"Updating {openai_api_base} to " |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,069 | AzureOpenAI azure_ad_token_provider Keyerror | ### System Info
When I use below snippet of code
```
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
```
I get error :
```---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[36], line 21
18 # api_version = "2023-05-15"
19 endpoint = "https://xxxx.openai.azure.com"
---> 21 client = AzureOpenAI(
22 azure_endpoint=endpoint,
23 api_version="2023-05-15",
24 azure_deployment="example-gpt-4",
25 azure_ad_token_provider=token_provider,
26 )
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain_core/load/serializable.py:97, in Serializable.__init__(self, **kwargs)
96 def __init__(self, **kwargs: Any) -> None:
---> 97 super().__init__(**kwargs)
98 self._lc_kwargs = kwargs
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:339, in BaseModel.__init__(__pydantic_self__, **data)
333 """
334 Create a new model by parsing and validating input data from keyword arguments.
335
336 Raises ValidationError if the input data cannot be parsed to form a valid model.
337 """
338 # Uses something other than `self` the first arg to allow "self" as a settable attribute
--> 339 values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
340 if validation_error:
341 raise validation_error
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:1102, in validate_model(model, input_data, cls)
1100 continue
1101 try:
-> 1102 values = validator(cls_, values)
1103 except (ValueError, TypeError, AssertionError) as exc:
1104 errors.append(ErrorWrapper(exc, loc=ROOT_KEY))
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain/llms/openai.py:887, in AzureOpenAI.validate_environment(cls, values)
877 values["openai_api_base"] += (
878 "/deployments/" + values["deployment_name"]
879 )
880 values["deployment_name"] = None
881 client_params = {
882 "api_version": values["openai_api_version"],
883 "azure_endpoint": values["azure_endpoint"],
884 "azure_deployment": values["deployment_name"],
885 "api_key": values["openai_api_key"],
886 "azure_ad_token": values["azure_ad_token"],
--> 887 "azure_ad_token_provider": values["azure_ad_token_provider"],
888 "organization": values["openai_organization"],
889 "base_url": values["openai_api_base"],
890 "timeout": values["request_timeout"],
891 "max_retries": values["max_retries"],
892 "default_headers": values["default_headers"],
893 "default_query": values["default_query"],
894 "http_client": values["http_client"],
895 }
896 values["client"] = openai.AzureOpenAI(**client_params).completions
897 values["async_client"] = openai.AsyncAzureOpenAI(
898 **client_params
899 ).completions
KeyError: 'azure_ad_token_provider'
```
Ive also tried AzureChatOpenAI , and I get the same error back.
The error is not reproduced when I use openai library AzureOpenAI .
Also on openai the azure_ad_token_provider has type azure_ad_token_provider: 'AzureADTokenProvider | None' = None while in langchain it has type azure_ad_token_provider: Optional[str] = None which also makes me wonder if it would take as input a different type than string to work with.
any ideas on how to fix this? Im actually using Azure Service principal authentication, and if I use as alternative field azure_ad_token = credential.get_token(“https://cognitiveservices.azure.com/.default”).token I get token expired after 60min which does not happen with a bearer token, so It is important to me to make the token_provider work.
libraries :
pydantic 1.10.12
pydantic_core 2.10.1
openai 1.2.0
langchain 0.0.342
langchain-core 0.0.7
### Who can help?
@hwchase17 @agola11
### Information
- [X] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
### Expected behavior
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
should return a Runnable instance which I can use for LLMChain | https://github.com/langchain-ai/langchain/issues/14069 | https://github.com/langchain-ai/langchain/pull/14166 | 9938086df07d69d24f9770209ea9087d3b906155 | 62505043be20cf8af491e30785a6ca0eeb1d276e | "2023-11-30T13:39:55Z" | python | "2023-12-03T16:55:25Z" | libs/langchain/langchain/chat_models/azure_openai.py | f"{values['openai_api_base']}."
)
values["openai_api_base"] += (
"/deployments/" + values["deployment_name"]
)
values["deployment_name"] = None
client_params = {
"api_version": values["openai_api_version"],
"azure_endpoint": values["azure_endpoint"],
"azure_deployment": values["deployment_name"],
"api_key": values["openai_api_key"],
"azure_ad_token": values["azure_ad_token"],
"azure_ad_token_provider": values["azure_ad_token_provider"],
"organization": values["openai_organization"],
"base_url": values["openai_api_base"],
"timeout": values["request_timeout"],
"max_retries": values["max_retries"],
"default_headers": values["default_headers"],
"default_query": values["default_query"],
"http_client": values["http_client"],
}
values["client"] = openai.AzureOpenAI(**client_params).chat.completions
values["async_client"] = openai.AsyncAzureOpenAI(
**client_params
).chat.completions
else:
values["client"] = openai.ChatCompletion
return values
@property
def _default_params(self) -> Dict[str, Any]: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,069 | AzureOpenAI azure_ad_token_provider Keyerror | ### System Info
When I use below snippet of code
```
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
```
I get error :
```---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[36], line 21
18 # api_version = "2023-05-15"
19 endpoint = "https://xxxx.openai.azure.com"
---> 21 client = AzureOpenAI(
22 azure_endpoint=endpoint,
23 api_version="2023-05-15",
24 azure_deployment="example-gpt-4",
25 azure_ad_token_provider=token_provider,
26 )
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain_core/load/serializable.py:97, in Serializable.__init__(self, **kwargs)
96 def __init__(self, **kwargs: Any) -> None:
---> 97 super().__init__(**kwargs)
98 self._lc_kwargs = kwargs
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:339, in BaseModel.__init__(__pydantic_self__, **data)
333 """
334 Create a new model by parsing and validating input data from keyword arguments.
335
336 Raises ValidationError if the input data cannot be parsed to form a valid model.
337 """
338 # Uses something other than `self` the first arg to allow "self" as a settable attribute
--> 339 values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
340 if validation_error:
341 raise validation_error
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:1102, in validate_model(model, input_data, cls)
1100 continue
1101 try:
-> 1102 values = validator(cls_, values)
1103 except (ValueError, TypeError, AssertionError) as exc:
1104 errors.append(ErrorWrapper(exc, loc=ROOT_KEY))
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain/llms/openai.py:887, in AzureOpenAI.validate_environment(cls, values)
877 values["openai_api_base"] += (
878 "/deployments/" + values["deployment_name"]
879 )
880 values["deployment_name"] = None
881 client_params = {
882 "api_version": values["openai_api_version"],
883 "azure_endpoint": values["azure_endpoint"],
884 "azure_deployment": values["deployment_name"],
885 "api_key": values["openai_api_key"],
886 "azure_ad_token": values["azure_ad_token"],
--> 887 "azure_ad_token_provider": values["azure_ad_token_provider"],
888 "organization": values["openai_organization"],
889 "base_url": values["openai_api_base"],
890 "timeout": values["request_timeout"],
891 "max_retries": values["max_retries"],
892 "default_headers": values["default_headers"],
893 "default_query": values["default_query"],
894 "http_client": values["http_client"],
895 }
896 values["client"] = openai.AzureOpenAI(**client_params).completions
897 values["async_client"] = openai.AsyncAzureOpenAI(
898 **client_params
899 ).completions
KeyError: 'azure_ad_token_provider'
```
Ive also tried AzureChatOpenAI , and I get the same error back.
The error is not reproduced when I use openai library AzureOpenAI .
Also on openai the azure_ad_token_provider has type azure_ad_token_provider: 'AzureADTokenProvider | None' = None while in langchain it has type azure_ad_token_provider: Optional[str] = None which also makes me wonder if it would take as input a different type than string to work with.
any ideas on how to fix this? Im actually using Azure Service principal authentication, and if I use as alternative field azure_ad_token = credential.get_token(“https://cognitiveservices.azure.com/.default”).token I get token expired after 60min which does not happen with a bearer token, so It is important to me to make the token_provider work.
libraries :
pydantic 1.10.12
pydantic_core 2.10.1
openai 1.2.0
langchain 0.0.342
langchain-core 0.0.7
### Who can help?
@hwchase17 @agola11
### Information
- [X] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
### Expected behavior
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
should return a Runnable instance which I can use for LLMChain | https://github.com/langchain-ai/langchain/issues/14069 | https://github.com/langchain-ai/langchain/pull/14166 | 9938086df07d69d24f9770209ea9087d3b906155 | 62505043be20cf8af491e30785a6ca0eeb1d276e | "2023-11-30T13:39:55Z" | python | "2023-12-03T16:55:25Z" | libs/langchain/langchain/chat_models/azure_openai.py | """Get the default parameters for calling OpenAI API."""
if is_openai_v1():
return super()._default_params
else:
return {
**super()._default_params,
"engine": self.deployment_name,
}
@property
def _identifying_params(self) -> Dict[str, Any]:
"""Get the identifying parameters."""
return {**self._default_params}
@property
def _client_params(self) -> Dict[str, Any]:
"""Get the config params used for the openai client."""
if is_openai_v1():
return super()._client_params
else:
return {
**super()._client_params,
"api_type": self.openai_api_type,
"api_version": self.openai_api_version,
}
@property
def _llm_type(self) -> str: |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,069 | AzureOpenAI azure_ad_token_provider Keyerror | ### System Info
When I use below snippet of code
```
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
```
I get error :
```---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[36], line 21
18 # api_version = "2023-05-15"
19 endpoint = "https://xxxx.openai.azure.com"
---> 21 client = AzureOpenAI(
22 azure_endpoint=endpoint,
23 api_version="2023-05-15",
24 azure_deployment="example-gpt-4",
25 azure_ad_token_provider=token_provider,
26 )
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain_core/load/serializable.py:97, in Serializable.__init__(self, **kwargs)
96 def __init__(self, **kwargs: Any) -> None:
---> 97 super().__init__(**kwargs)
98 self._lc_kwargs = kwargs
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:339, in BaseModel.__init__(__pydantic_self__, **data)
333 """
334 Create a new model by parsing and validating input data from keyword arguments.
335
336 Raises ValidationError if the input data cannot be parsed to form a valid model.
337 """
338 # Uses something other than `self` the first arg to allow "self" as a settable attribute
--> 339 values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
340 if validation_error:
341 raise validation_error
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:1102, in validate_model(model, input_data, cls)
1100 continue
1101 try:
-> 1102 values = validator(cls_, values)
1103 except (ValueError, TypeError, AssertionError) as exc:
1104 errors.append(ErrorWrapper(exc, loc=ROOT_KEY))
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain/llms/openai.py:887, in AzureOpenAI.validate_environment(cls, values)
877 values["openai_api_base"] += (
878 "/deployments/" + values["deployment_name"]
879 )
880 values["deployment_name"] = None
881 client_params = {
882 "api_version": values["openai_api_version"],
883 "azure_endpoint": values["azure_endpoint"],
884 "azure_deployment": values["deployment_name"],
885 "api_key": values["openai_api_key"],
886 "azure_ad_token": values["azure_ad_token"],
--> 887 "azure_ad_token_provider": values["azure_ad_token_provider"],
888 "organization": values["openai_organization"],
889 "base_url": values["openai_api_base"],
890 "timeout": values["request_timeout"],
891 "max_retries": values["max_retries"],
892 "default_headers": values["default_headers"],
893 "default_query": values["default_query"],
894 "http_client": values["http_client"],
895 }
896 values["client"] = openai.AzureOpenAI(**client_params).completions
897 values["async_client"] = openai.AsyncAzureOpenAI(
898 **client_params
899 ).completions
KeyError: 'azure_ad_token_provider'
```
Ive also tried AzureChatOpenAI , and I get the same error back.
The error is not reproduced when I use openai library AzureOpenAI .
Also on openai the azure_ad_token_provider has type azure_ad_token_provider: 'AzureADTokenProvider | None' = None while in langchain it has type azure_ad_token_provider: Optional[str] = None which also makes me wonder if it would take as input a different type than string to work with.
any ideas on how to fix this? Im actually using Azure Service principal authentication, and if I use as alternative field azure_ad_token = credential.get_token(“https://cognitiveservices.azure.com/.default”).token I get token expired after 60min which does not happen with a bearer token, so It is important to me to make the token_provider work.
libraries :
pydantic 1.10.12
pydantic_core 2.10.1
openai 1.2.0
langchain 0.0.342
langchain-core 0.0.7
### Who can help?
@hwchase17 @agola11
### Information
- [X] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
### Expected behavior
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
should return a Runnable instance which I can use for LLMChain | https://github.com/langchain-ai/langchain/issues/14069 | https://github.com/langchain-ai/langchain/pull/14166 | 9938086df07d69d24f9770209ea9087d3b906155 | 62505043be20cf8af491e30785a6ca0eeb1d276e | "2023-11-30T13:39:55Z" | python | "2023-12-03T16:55:25Z" | libs/langchain/langchain/chat_models/azure_openai.py | return "azure-openai-chat"
@property
def lc_attributes(self) -> Dict[str, Any]:
return {
"openai_api_type": self.openai_api_type,
"openai_api_version": self.openai_api_version,
}
def _create_chat_result(self, response: Union[dict, BaseModel]) -> ChatResult:
if not isinstance(response, dict):
response = response.dict()
for res in response["choices"]:
if res.get("finish_reason", None) == "content_filter":
raise ValueError(
"Azure has not provided the response due to a content filter "
"being triggered"
)
chat_result = super()._create_chat_result(response)
if "model" in response:
model = response["model"]
if self.model_version:
model = f"{model}-{self.model_version}"
if chat_result.llm_output is not None and isinstance(
chat_result.llm_output, dict
):
chat_result.llm_output["model_name"] = model
return chat_result |
closed | langchain-ai/langchain | https://github.com/langchain-ai/langchain | 14,069 | AzureOpenAI azure_ad_token_provider Keyerror | ### System Info
When I use below snippet of code
```
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
```
I get error :
```---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[36], line 21
18 # api_version = "2023-05-15"
19 endpoint = "https://xxxx.openai.azure.com"
---> 21 client = AzureOpenAI(
22 azure_endpoint=endpoint,
23 api_version="2023-05-15",
24 azure_deployment="example-gpt-4",
25 azure_ad_token_provider=token_provider,
26 )
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain_core/load/serializable.py:97, in Serializable.__init__(self, **kwargs)
96 def __init__(self, **kwargs: Any) -> None:
---> 97 super().__init__(**kwargs)
98 self._lc_kwargs = kwargs
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:339, in BaseModel.__init__(__pydantic_self__, **data)
333 """
334 Create a new model by parsing and validating input data from keyword arguments.
335
336 Raises ValidationError if the input data cannot be parsed to form a valid model.
337 """
338 # Uses something other than `self` the first arg to allow "self" as a settable attribute
--> 339 values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
340 if validation_error:
341 raise validation_error
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/pydantic/v1/main.py:1102, in validate_model(model, input_data, cls)
1100 continue
1101 try:
-> 1102 values = validator(cls_, values)
1103 except (ValueError, TypeError, AssertionError) as exc:
1104 errors.append(ErrorWrapper(exc, loc=ROOT_KEY))
File ~/PycharmProjects/aicc/env/lib/python3.9/site-packages/langchain/llms/openai.py:887, in AzureOpenAI.validate_environment(cls, values)
877 values["openai_api_base"] += (
878 "/deployments/" + values["deployment_name"]
879 )
880 values["deployment_name"] = None
881 client_params = {
882 "api_version": values["openai_api_version"],
883 "azure_endpoint": values["azure_endpoint"],
884 "azure_deployment": values["deployment_name"],
885 "api_key": values["openai_api_key"],
886 "azure_ad_token": values["azure_ad_token"],
--> 887 "azure_ad_token_provider": values["azure_ad_token_provider"],
888 "organization": values["openai_organization"],
889 "base_url": values["openai_api_base"],
890 "timeout": values["request_timeout"],
891 "max_retries": values["max_retries"],
892 "default_headers": values["default_headers"],
893 "default_query": values["default_query"],
894 "http_client": values["http_client"],
895 }
896 values["client"] = openai.AzureOpenAI(**client_params).completions
897 values["async_client"] = openai.AsyncAzureOpenAI(
898 **client_params
899 ).completions
KeyError: 'azure_ad_token_provider'
```
Ive also tried AzureChatOpenAI , and I get the same error back.
The error is not reproduced when I use openai library AzureOpenAI .
Also on openai the azure_ad_token_provider has type azure_ad_token_provider: 'AzureADTokenProvider | None' = None while in langchain it has type azure_ad_token_provider: Optional[str] = None which also makes me wonder if it would take as input a different type than string to work with.
any ideas on how to fix this? Im actually using Azure Service principal authentication, and if I use as alternative field azure_ad_token = credential.get_token(“https://cognitiveservices.azure.com/.default”).token I get token expired after 60min which does not happen with a bearer token, so It is important to me to make the token_provider work.
libraries :
pydantic 1.10.12
pydantic_core 2.10.1
openai 1.2.0
langchain 0.0.342
langchain-core 0.0.7
### Who can help?
@hwchase17 @agola11
### Information
- [X] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async
### Reproduction
import os
from azure.identity import DefaultAzureCredential
from azure.identity import get_bearer_token_provider
from langchain.llms import AzureOpenAI
from langchain.chat_models import AzureChatOpenAI
credential = DefaultAzureCredential(interactive_browser_tenant_id=tenant_id,
interactive_browser_client_id=client_id,
client_secret=client_secret)
token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default")
endpoint = "https://xxxx.openai.azure.com"
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
### Expected behavior
client = AzureOpenAI( azure_endpoint=endpoint,
api_version="2023-05-15",
azure_deployment="example-gpt-4",
azure_ad_token_provider=token_provider)
should return a Runnable instance which I can use for LLMChain | https://github.com/langchain-ai/langchain/issues/14069 | https://github.com/langchain-ai/langchain/pull/14166 | 9938086df07d69d24f9770209ea9087d3b906155 | 62505043be20cf8af491e30785a6ca0eeb1d276e | "2023-11-30T13:39:55Z" | python | "2023-12-03T16:55:25Z" | libs/langchain/langchain/llms/openai.py | from __future__ import annotations
import logging
import os
import sys |
Subsets and Splits
No saved queries yet
Save your SQL queries to embed, download, and access them later. Queries will appear here once saved.