langchain

Commit Graph

Author	SHA1	Message	Date
Philippe PRADOS	26cee2e878	partners[patch]: MongoDB vectorstore to return and accept string IDs (#23818 ) The mongdb have some errors. - `add_texts() -> List` returns a list of `ObjectId`, and not a list of string - `delete()` with `id` never remove chunks. --------- Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>	3 months ago
Ikko Eltociear Ashimine	75734fbcf1	community: fix typo in unit tests for test_zenguard.py (#23819 ) enviroment -> environment - [x] PR title: "package: description" - Where "package" is whichever of langchain, community, core, experimental, etc. is being modified. Use "docs: ..." for purely docs changes, "templates: ..." for template changes, "infra: ..." for CI changes. - Example: "community: add foobar LLM"	3 months ago
Bagatur	a0c2281540	infra: update mypy 1.10, ruff 0.5 (#23721 ) ```python """python scripts/update_mypy_ruff.py""" import glob import tomllib from pathlib import Path import toml import subprocess import re ROOT_DIR = Path(__file__).parents[1] def main(): for path in glob.glob(str(ROOT_DIR / "libs/*/pyproject.toml"), recursive=True): print(path) with open(path, "rb") as f: pyproject = tomllib.load(f) try: pyproject["tool"]["poetry"]["group"]["typing"]["dependencies"]["mypy"] = ( "^1.10" ) pyproject["tool"]["poetry"]["group"]["lint"]["dependencies"]["ruff"] = ( "^0.5" ) except KeyError: continue with open(path, "w") as f: toml.dump(pyproject, f) cwd = "/".join(path.split("/")[:-1]) completed = subprocess.run( "poetry lock --no-update; poetry install --with typing; poetry run mypy . --no-color", cwd=cwd, shell=True, capture_output=True, text=True, ) logs = completed.stdout.split("\n") to_ignore = {} for l in logs: if re.match("^(.)\:(\d+)\: error:.\[(.)\]", l): path, line_no, error_type = re.match( "^(.)\:(\d+)\: error:.\[(.*)\]", l ).groups() if (path, line_no) in to_ignore: to_ignore[(path, line_no)].append(error_type) else: to_ignore[(path, line_no)] = [error_type] print(len(to_ignore)) for (error_path, line_no), error_types in to_ignore.items(): all_errors = ", ".join(error_types) full_path = f"{cwd}/{error_path}" try: with open(full_path, "r") as f: file_lines = f.readlines() except FileNotFoundError: continue file_lines[int(line_no) - 1] = ( file_lines[int(line_no) - 1][:-1] + f" # type: ignore[{all_errors}]\n" ) with open(full_path, "w") as f: f.write("".join(file_lines)) subprocess.run( "poetry run ruff format .; poetry run ruff --select I --fix .", cwd=cwd, shell=True, capture_output=True, text=True, ) if __name__ == "__main__": main() ```	3 months ago
William FH	6cd56821dc	[Core] Unify function schema parsing (#23370 ) Use pydantic to infer nested schemas and all that fun. Include bagatur's convenient docstring parser Include annotation support Previously we didn't adequately support many typehints in the bind_tools() method on raw functions (like optionals/unions, nested types, etc.)	3 months ago
Oguz Vuruskaner	2a2c0d1a94	community[deepinfra]: fix tool call parsing. (#23162 ) This PR includes fix for DeepInfra tool call parsing.	3 months ago
maang-h	525109e506	feat: Implement ChatBaichuan asynchronous interface (#23589 ) - Description: Add interface to `ChatBaichuan` to support asynchronous requests - `_agenerate` method - `_astream` method --------- Co-authored-by: ccurme <chester.curme@gmail.com>	3 months ago
Bagatur	8842a0d986	docs: fireworks nit (#23822 )	3 months ago
Leonid Ganeline	716a316654	core: docstrings `indexing` (#23785 ) Added missed docstrings. Formatted docstrings to the consistent form.	3 months ago
Leonid Ganeline	30fdc2dbe7	core: docstrings `messages` (#23788 ) Added missed docstrings. Formatted docstrings to the consistent form.	3 months ago
ccurme	54e730f6e4	fireworks[patch]: read from tool calls attribute (#23820 )	3 months ago
Bagatur	e787249af1	docs: fireworks standard page (#23816 )	3 months ago
Jacob Lee	27aa4d38bf	docs[patch]: Update structured output docs to have more discussion (#23786 ) CC @agola11 @ccurme	3 months ago
Bagatur	ebb404527f	anthropic[patch]: Release 0.1.19 (#23783 )	3 months ago
Bagatur	6168c846b2	openai[patch]: Release 0.1.14 (#23782 )	3 months ago
Bagatur	cb9812593f	openai[patch]: expose model request payload (#23287 ) ![Screenshot 2024-06-21 at 3 12 12 PM](https://github.com/langchain-ai/langchain/assets/22008038/6243a01f-1ef6-4085-9160-2844d9f2b683)	3 months ago
Bagatur	ed200bf2c4	anthropic[patch]: expose payload (#23291 ) ![Screenshot 2024-06-21 at 4 56 02 PM](https://github.com/langchain-ai/langchain/assets/22008038/a2c6224f-3741-4502-9607-1a726a0551c9)	3 months ago
Bagatur	7a3d8e5a99	core[patch]: Release 0.2.11 (#23780 )	3 months ago
Bagatur	d677dadf5f	core[patch]: mark RemoveMessage beta (#23656 )	3 months ago
ccurme	1d54ac93bb	ai21[patch]: release 0.1.7 (#23781 )	3 months ago
Asaf Joseph Gardin	320dc31822	partners: AI21 Labs Jamba Streaming Support (#23538 ) Thank you for contributing to LangChain! - [x] PR title: "package: description" - [x] PR message: *Delete this entire checklist* and replace with - Description: Added support for streaming in AI21 Jamba Model - Twitter handle: https://github.com/AI21Labs - [x] Add tests and docs: If you're adding a new integration, please include - [x] Lint and test: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. --------- Co-authored-by: Asaf Gardin <asafg@ai21.com> Co-authored-by: Erick Friis <erick@langchain.dev> Co-authored-by: Chester Curme <chester.curme@gmail.com>	3 months ago
Qingchuan Hao	5cd4083457	community: make bing web search as the only option (#23523 ) This PR make bing web search as the option for BingSearchAPIWrapper to facilitate and simply the user interface on Langchain. This is a follow-up work of https://github.com/langchain-ai/langchain/pull/23306.	3 months ago
William W Wang	76e7e4e9e6	Update docs: LangChain agent memory (#23673 ) Thank you for contributing to LangChain! - [x] PR title: "package: description" - Where "package" is whichever of langchain, community, core, experimental, etc. is being modified. Use "docs: ..." for purely docs changes, "templates: ..." for template changes, "infra: ..." for CI changes. - Example: "community: add foobar LLM" Description: Update docs content on agent memory If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.	3 months ago
ccurme	7c1cddf1b7	anthropic[patch]: release 0.1.18 (#23778 )	3 months ago
ccurme	c9dac59008	anthropic[patch]: fix model name in some integration tests (#23779 )	3 months ago
Bagatur	7a6c06cadd	anthropic[patch]: tool output parser fix (#23647 )	3 months ago
ccurme	46cbf0e4aa	anthropic[patch]: use core output parsers for structured output (#23776 ) Also add to standard tests for structured output.	3 months ago
kiarina	dc396835ed	langchain_anthropic: add stop_reason in ChatAnthropic stream result (#23689 ) `ChatAnthropic` can get `stop_reason` from the resulting `AIMessage` in `invoke` and `ainvoke`, but not in `stream` and `astream`. This is a different behavior from `ChatOpenAI`. It is possible to get `stop_reason` from `stream` as well, since it is needed to determine the next action after the LLM call. This would be easier to handle in situations where only `stop_reason` is needed. - Issue: NA - Dependencies: NA - Twitter handle: https://x.com/kiarina37	3 months ago
Bagatur	27ce58f86e	docs: google genai standard page (#23766 ) Part of #22296	3 months ago
maang-h	e4e28a6ff5	community[patch]: Fix MiniMaxChat validate_environment error (#23770 ) - Description: Fix some issues in MiniMaxChat - Fix `minimax_api_host` not in `values` error - Remove `minimax_group_id` from reading environment variables, the `minimax_group_id` no longer use in MiniMaxChat - Invoke callback prior to yielding token, the issus #16913	3 months ago
SN	acc457f645	core[patch]: fix nested sections for mustache templating (#23747 ) The prompt template variable detection only worked for singly-nested sections because we just kept track of whether we were in a section and then set that to false as soon as we encountered an end block. i.e. the following: ``` {{#outerSection}} {{variableThatShouldntShowUp}} {{#nestedSection}} {{nestedVal}} {{/nestedSection}} {{anotherVariableThatShouldntShowUp}} {{/outerSection}} ``` Would yield `['outerSection', 'anotherVariableThatShouldntShowUp']` as input_variables (whereas it should just yield `['outerSection']`). This fixes that by keeping track of the current depth and using a stack.	3 months ago
Karim Lalani	acc8fb3ead	docs[patch]: Update OllamaFunctions docs to match chat model integration template (#23179 ) Added Tool Calling Agent Example with langgraph to OllamaFunctions documentation	3 months ago
Bagatur	79c07a8ade	docs: standardize bedrock page (#23738 ) Part of #22296	3 months ago
Teja Hara	a77a263e24	Added langchain-community installation (#23741 ) PR title: Docs enhancement - Description: Adding installation instructions for integrations requiring langchain-community package since 0.2 - Issue: https://github.com/langchain-ai/langchain/issues/22005 --------- Co-authored-by: ccurme <chester.curme@gmail.com>	3 months ago
Eugene Yurtsev	46ff0f7a3c	community[patch]: Update @root_validators to use explicit pre=True or pre=False (#23737 )	3 months ago
Igor Drozdov	b664dbcc36	feat(community): add support for tool_calls response (#23765 ) When `model_kwargs={"tools": tools}` are passed to `ChatLiteLLM`, they are executed, but the response is not recognized correctly Let's add `tool_calls` to the `additional_kwargs` Thank you for contributing to LangChain! ## ChatAnthropic I used the following example to verify the output of llm with tools: ```python from langchain_core.pydantic_v1 import BaseModel, Field from langchain_anthropic import ChatAnthropic class GetWeather(BaseModel): '''Get the current weather in a given location''' location: str = Field(..., description="The city and state, e.g. San Francisco, CA") class GetPopulation(BaseModel): '''Get the current population in a given location''' location: str = Field(..., description="The city and state, e.g. San Francisco, CA") llm = ChatAnthropic(model="claude-3-sonnet-20240229") llm_with_tools = llm.bind_tools([GetWeather, GetPopulation]) ai_msg = llm_with_tools.invoke("Which city is hotter today and which is bigger: LA or NY?") print(ai_msg.tool_calls) ``` I get the following response: ```json [{'name': 'GetWeather', 'args': {'location': 'Los Angeles, CA'}, 'id': 'toolu_01UfDA89knrhw3vFV9X47neT'}, {'name': 'GetWeather', 'args': {'location': 'New York, NY'}, 'id': 'toolu_01NrYVRYae7m7z7tBgyPb3Gd'}, {'name': 'GetPopulation', 'args': {'location': 'Los Angeles, CA'}, 'id': 'toolu_01EPFEpDgzL6vV2dTpD9SVP5'}, {'name': 'GetPopulation', 'args': {'location': 'New York, NY'}, 'id': 'toolu_01B5J6tPJXgwwfhQX9BHP2dt'}] ``` ## LiteLLM Based on https://litellm.vercel.app/docs/completion/function_call ```python from langchain_core.pydantic_v1 import BaseModel, Field from langchain_core.utils.function_calling import convert_to_openai_tool import litellm class GetWeather(BaseModel): '''Get the current weather in a given location''' location: str = Field(..., description="The city and state, e.g. San Francisco, CA") class GetPopulation(BaseModel): '''Get the current population in a given location''' location: str = Field(..., description="The city and state, e.g. San Francisco, CA") prompt = "Which city is hotter today and which is bigger: LA or NY?" tools = [convert_to_openai_tool(GetWeather), convert_to_openai_tool(GetPopulation)] response = litellm.completion(model="claude-3-sonnet-20240229", messages=[{'role': 'user', 'content': prompt}], tools=tools) print(response.choices[0].message.tool_calls) ``` ```python [ChatCompletionMessageToolCall(function=Function(arguments='{"location": "Los Angeles, CA"}', name='GetWeather'), id='toolu_01HeDWV5vP7BDFfytH5FJsja', type='function'), ChatCompletionMessageToolCall(function=Function(arguments='{"location": "New York, NY"}', name='GetWeather'), id='toolu_01EiLesUSEr3YK1DaE2jxsQv', type='function'), ChatCompletionMessageToolCall(function=Function(arguments='{"location": "Los Angeles, CA"}', name='GetPopulation'), id='toolu_01Xz26zvkBDRxEUEWm9pX6xa', type='function'), ChatCompletionMessageToolCall(function=Function(arguments='{"location": "New York, NY"}', name='GetPopulation'), id='toolu_01SDqKnsLjvUXuBsgAZdEEpp', type='function')] ``` ## ChatLiteLLM When I try the following ```python from langchain_core.pydantic_v1 import BaseModel, Field from langchain_core.utils.function_calling import convert_to_openai_tool from langchain_community.chat_models import ChatLiteLLM class GetWeather(BaseModel): '''Get the current weather in a given location''' location: str = Field(..., description="The city and state, e.g. San Francisco, CA") class GetPopulation(BaseModel): '''Get the current population in a given location''' location: str = Field(..., description="The city and state, e.g. San Francisco, CA") prompt = "Which city is hotter today and which is bigger: LA or NY?" tools = [convert_to_openai_tool(GetWeather), convert_to_openai_tool(GetPopulation)] llm = ChatLiteLLM(model="claude-3-sonnet-20240229", model_kwargs={"tools": tools}) ai_msg = llm.invoke(prompt) print(ai_msg) print(ai_msg.tool_calls) ``` ```python content="Okay, let's find out the current weather and populations for Los Angeles and New York City:" response_metadata={'token_usage': Usage(prompt_tokens=329, completion_tokens=193, total_tokens=522), 'model': 'claude-3-sonnet-20240229', 'finish_reason': 'tool_calls'} id='run-748b7a84-84f4-497e-bba1-320bd4823937-0' [] ``` --- When I apply the changes of this PR, the output is ```json [{'name': 'GetWeather', 'args': {'location': 'Los Angeles, CA'}, 'id': 'toolu_017D2tGjiaiakB1HadsEFZ4e'}, {'name': 'GetWeather', 'args': {'location': 'New York, NY'}, 'id': 'toolu_01WrDpJfVqLkPejWzonPCbLW'}, {'name': 'GetPopulation', 'args': {'location': 'Los Angeles, CA'}, 'id': 'toolu_016UKyYrVAV9Pz99iZGgGU7V'}, {'name': 'GetPopulation', 'args': {'location': 'New York, NY'}, 'id': 'toolu_01Sgv1imExFX1oiR1Cw88zKy'}] ``` If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17. Co-authored-by: Igor Drozdov <idrozdov@gitlab.com>	3 months ago
Eugene Yurtsev	338cef35b4	community[patch]: update @root_validator in utilities namespace (#23768 ) Update all utilities to use `pre=True` or `pre=False` https://github.com/langchain-ai/langchain/issues/22819	3 months ago
wenngong	ee5eedfa04	partners: support reading HuggingFace params from env (#23309 ) Description: 1. partners/HuggingFace module support reading params from env. Not adjust langchain_community/.../huggingfaceXX modules since they are deprecated. 2. pydantic 2 @root_validator migration. Issue: #22448 #22819 --------- Co-authored-by: gongwn1 <gongwn1@lenovo.com>	3 months ago
antonpibm	ffde8a6a09	Milvus vectorstore: fix pass ids as argument after upsert (#23761 ) Description: Milvus vectorstore supports both `add_documents` via the base class and `upsert` method which deletes and re-adds documents based on their ids Issue: Due to mismatch in the interfaces the ids used by `upsert` are neglected in `add_documents`, as `ids` are passed as argument in `upsert` but via `kwargs` is `add_documents` This caused exceptions and inconsistency in the DB, tested with `auto_id=False` Fix: pass `ids` via `kwargs` to `add_documents`	3 months ago
Eugene Yurtsev	d084172b63	community[patch]: root validator set explicit pre=False or pre=True (#23764 ) See issue: https://github.com/langchain-ai/langchain/issues/22819	3 months ago
Khelan Modi	4457e64e13	Update azure_cosmos_db for mongodb documentation (#23740 ) added pre-filtering documentation Thank you for contributing to LangChain! - [x] PR title: "package: description" - Where "package" is whichever of langchain, community, core, experimental, etc. is being modified. Use "docs: ..." for purely docs changes, "templates: ..." for template changes, "infra: ..." for CI changes. - Example: "community: add foobar LLM" - [x] PR message: - Description: added filter vector search - Issue: N/A - Dependencies: N/A - Twitter handle:: n/a - [x] Add tests and docs: If you're adding a new integration, please include - No need for tests, just a simple doc update 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. - [x] Lint and test: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.	3 months ago
panwg3	bc98f90ba3	update wrong words (#23749 ) Thank you for contributing to LangChain! - [ ] PR title: "package: description" - Where "package" is whichever of langchain, community, core, experimental, etc. is being modified. Use "docs: ..." for purely docs changes, "templates: ..." for template changes, "infra: ..." for CI changes. - Example: "community: add foobar LLM" - [ ] PR message: *Delete this entire checklist* and replace with - Description: a description of the change - Issue: the issue # it fixes, if applicable - Dependencies: any dependencies required for this change - Twitter handle: if your PR gets announced, and you'd like a mention, we'll gladly shout you out! - [ ] Add tests and docs: If you're adding a new integration, please include 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. - [ ] Lint and test: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.	3 months ago
mattthomps1	cc55823486	docs: updated PPLX model (#23723 ) Description: updated pplx docs to reference a currently [supported model](https://docs.perplexity.ai/docs/model-cards). pplx-70b-online ->llama-3-sonar-small-32k-online --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>	3 months ago
Bagatur	aa165539f6	docs: standardize cohere page (#23739 ) Part of #22296	3 months ago
Jacob Lee	7791d92711	community[patch]: Fix requests alias for load_tools (#23734 ) CC @baskaryan	3 months ago
Eugene Yurtsev	f24e38876a	community[patch]: Update root_validators to use explicit pre=True or pre=False (#23736 )	3 months ago
Yannick Stephan	5b1de2ae93	mistralai: Fixed streaming in MistralAI with ainvoke and callbacks (#22000 ) # Fix streaming in mistral with ainvoke - [x] PR title - [x] PR message - [x] Add tests and docs: 1. [x] Added a test for the fixed integration. 2. [x] An example notebook showing its use. It lives in `docs/docs/integrations` directory. - [x] Lint and test: Ran `make format`, `make lint` and `make test` from the root of the package(s) I've modified. Hello * I Identified an issue in the mistral package where the callback streaming (see on_llm_new_token) was not functioning correctly when the streaming parameter was set to True and call with `ainvoke`. * The root cause of the problem was the streaming not taking into account. ( I think it's an oversight ) * To resolve the issue, I added the `streaming` attribut. * Now, the callback with streaming works as expected when the streaming parameter is set to True. ## How to reproduce ``` from langchain_mistralai.chat_models import ChatMistralAI chain = ChatMistralAI(streaming=True) # Add a callback chain.ainvoke(..) # Oberve on_llm_new_token # Now, the callback is given as streaming tokens, before it was in grouped format. ``` Co-authored-by: Erick Friis <erick@langchain.dev>	3 months ago
Jacob Lee	f4b2e553e7	docs[patch]: Update Unstructured loader notebooks and install instructions (#23726 ) CC @baskaryan @MthwRobinson	3 months ago
Eugene Yurtsev	5d2262af34	community[patch]: Update root_validators to use pre=True or pre=False (#23731 ) Update root_validators in preparation for pydantic 2 migration.	3 months ago
Erick Friis	6019147b66	infra: filter template check (#23727 )	3 months ago
Eugene Yurtsev	ebcee4f610	core[patch]: Add versionadded to get_by_ids (#23728 )	3 months ago

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