langchain

Commit Graph

Author	SHA1	Message	Date
Erick Friis	adc008407e	exa: init pkg (#16553 )	7 months ago
Rave Harpaz	c4e9c9ca29	community[minor]: Add OCI Generative AI integration (#16548 ) <!-- Thank you for contributing to LangChain! Please title your PR "<package>: <description>", where <package> is whichever of langchain, community, core, experimental, etc. is being modified. Replace this entire comment with: - Description: Adding Oracle Cloud Infrastructure Generative AI integration. Oracle Cloud Infrastructure (OCI) Generative AI is a fully managed service that provides a set of state-of-the-art, customizable large language models (LLMs) that cover a wide range of use cases, and which is available through a single API. Using the OCI Generative AI service you can access ready-to-use pretrained models, or create and host your own fine-tuned custom models based on your own data on dedicated AI clusters. https://docs.oracle.com/en-us/iaas/Content/generative-ai/home.htm - Issue: None, - Dependencies: OCI Python SDK, - Twitter handle: we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` from the root of the package you've modified to check this locally. Passed See contribution guidelines for more information on how to write/run tests, lint, etc: https://python.langchain.com/docs/contributing/ 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. we provide unit tests. However, we cannot provide integration tests due to Oracle policies that prohibit public sharing of api keys. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> --------- Co-authored-by: Arthur Cheng <arthur.cheng@oracle.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Harel Gal	a91181fe6d	community[minor]: add support for Guardrails for Amazon Bedrock (#15099 ) Added support for optionally supplying 'Guardrails for Amazon Bedrock' on both types of model invocations (batch/regular and streaming) and for all models supported by the Amazon Bedrock service. @baskaryan @hwchase17 ```python llm = Bedrock(model_id="<model_id>", client=bedrock, model_kwargs={}, guardrails={"id": " <guardrail_id>", "version": "<guardrail_version>", "trace": True}, callbacks=[BedrockAsyncCallbackHandler()]) class BedrockAsyncCallbackHandler(AsyncCallbackHandler): """Async callback handler that can be used to handle callbacks from langchain.""" async def on_llm_error( self, error: BaseException, **kwargs: Any, ) -> Any: reason = kwargs.get("reason") if reason == "GUARDRAIL_INTERVENED": # kwargs contains additional trace information sent by 'Guardrails for Bedrock' service. print(f"""Guardrails: {kwargs}""") # streaming llm = Bedrock(model_id="<model_id>", client=bedrock, model_kwargs={}, streaming=True, guardrails={"id": "<guardrail_id>", "version": "<guardrail_version>"}) ``` --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Martin Kolb	04651f0248	community[minor]: VectorStore integration for SAP HANA Cloud Vector Engine (#16514 ) - Description: This PR adds a VectorStore integration for SAP HANA Cloud Vector Engine, which is an upcoming feature in the SAP HANA Cloud database (https://blogs.sap.com/2023/11/02/sap-hana-clouds-vector-engine-announcement/). - Issue: N/A - Dependencies: [SAP HANA Python Client](https://pypi.org/project/hdbcli/) - Twitter handle: @sapopensource Implementation of the integration: `libs/community/langchain_community/vectorstores/hanavector.py` Unit tests: `libs/community/tests/unit_tests/vectorstores/test_hanavector.py` Integration tests: `libs/community/tests/integration_tests/vectorstores/test_hanavector.py` Example notebook: `docs/docs/integrations/vectorstores/hanavector.ipynb` Access credentials for execution of the integration tests can be provided to the maintainers. --------- Co-authored-by: sascha <sascha.stoll@sap.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Unai Garay Maestre	fdbfa6b2c8	Adds progress bar to VertexAIEmbeddings (#14542 ) - Description: Adds progress bar to VertexAIEmbeddings - Issue: related issue https://github.com/langchain-ai/langchain/issues/13637 Signed-off-by: ugm2 <unaigaraymaestre@gmail.com> --------- Signed-off-by: ugm2 <unaigaraymaestre@gmail.com>	7 months ago
Jeremi Joslin	9e95699277	community[patch]: Fix error message when litellm is not installed (#16316 ) The error message was mentioning the wrong package. I updated it to the correct one.	7 months ago
bachr	b3ed98dec0	community[patch]: avoid KeyError when language not in LANGUAGE_SEGMENTERS (#15212 ) Description: Handle unsupported languages in same way as when none is provided Issue: The following line will throw a KeyError if the language is not supported. ```python self.Segmenter = LANGUAGE_SEGMENTERS[language] ``` E.g. when using `Language.CPP` we would get `KeyError: <Language.CPP: 'cpp'>` --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
chyroc	61da2ff24c	community[patch]: use SecretStr for yandex model secrets (#15463 )	7 months ago
Alessio Serra	d628a80a5d	community[patch]: added 'conversational' as a valid task for hugginface endopoint models (#15761 ) - Description: added the conversational task to hugginFace endpoint in order to use models designed for chatbot programming. - Dependencies: None --------- Co-authored-by: Alessio Serra (ext.) <alessio.serra@partner.bmw.de> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Karim Lalani	4c7755778d	community[patch]: SurrealDB fix for asyncio (#16092 ) Code fix for asyncio	7 months ago
Raunak	476bf8b763	community[patch]: Load list of files using UnstructuredFileLoader (#16216 ) - Description: Updated `_get_elements()` function of `UnstructuredFileLoader `class to check if the argument self.file_path is a file or list of files. If it is a list of files then it iterates over the list of file paths, calls the partition function for each one, and appends the results to the elements list. If self.file_path is not a list, it calls the partition function as before. - Issue: Fixed #15607, - Dependencies: NA - Twitter handle: NA Co-authored-by: H161961 <Raunak.Raunak@Honeywell.com>	7 months ago
Xudong Sun	019b6ebe8d	community[minor]: Add iFlyTek Spark LLM chat model support (#13389 ) - Description: This PR enables LangChain to access the iFlyTek's Spark LLM via the chat_models wrapper. - Dependencies: websocket-client ^1.6.1 - Tag maintainer: @baskaryan ### SparkLLM chat model usage Get SparkLLM's app_id, api_key and api_secret from [iFlyTek SparkLLM API Console](https://console.xfyun.cn/services/bm3) (for more info, see [iFlyTek SparkLLM Intro](https://xinghuo.xfyun.cn/sparkapi) ), then set environment variables `IFLYTEK_SPARK_APP_ID`, `IFLYTEK_SPARK_API_KEY` and `IFLYTEK_SPARK_API_SECRET` or pass parameters when using it like the demo below: ```python3 from langchain.chat_models.sparkllm import ChatSparkLLM client = ChatSparkLLM( spark_app_id="<app_id>", spark_api_key="<api_key>", spark_api_secret="<api_secret>" ) ```	7 months ago
Serena Ruan	5c6e123757	community[patch]: Fix MlflowCallback with none artifacts_dir (#16487 )	7 months ago
bu2kx	ff3163297b	community[minor]: Add KDBAI vector store (#12797 ) Addition of KDBAI vector store (https://kdb.ai). Dependencies: `kdbai_client` v0.1.2 Python package. Sample notebook: `docs/docs/integrations/vectorstores/kdbai.ipynb` Tag maintainer: @bu2kx Twitter handle: @kxsystems	7 months ago
Shivani Modi	4e160540ff	community[minor]: Adding Konko Completion endpoint (#15570 ) This PR introduces update to Konko Integration with LangChain. 1. New Endpoint Addition: Integration of a new endpoint to utilize completion models hosted on Konko. 2. Chat Model Updates for Backward Compatibility: We have updated the chat models to ensure backward compatibility with previous OpenAI versions. 4. Updated Documentation: Comprehensive documentation has been updated to reflect these new changes, providing clear guidance on utilizing the new features and ensuring seamless integration. Thank you to the LangChain team for their exceptional work and for considering this PR. Please let me know if any additional information is needed. --------- Co-authored-by: Shivani Modi <shivanimodi@Shivanis-MacBook-Pro.local> Co-authored-by: Shivani Modi <shivanimodi@Shivanis-MBP.lan>	7 months ago
Noah Stapp	e135e5257c	community[patch]: Include scores in MongoDB Atlas QA chain results (#14666 ) Adds the ability to return similarity scores when using `RetrievalQA.from_chain_type` with `MongoDBAtlasVectorSearch`. Requires that `return_source_documents=True` is set. Example use: ``` vector_search = MongoDBAtlasVectorSearch.from_documents(...) qa = RetrievalQA.from_chain_type( llm=OpenAI(), chain_type="stuff", retriever=vector_search.as_retriever(search_kwargs={"additional": ["similarity_score"]}), return_source_documents=True ) ... docs = qa({"query": "..."}) docs["source_documents"][0].metadata["score"] # score will be here ``` I've tested this feature locally, using a MongoDB Atlas Cluster with a vector search index.	7 months ago
Serena Ruan	90f5a1c40e	community[minor]: Improve mlflow callback (#15691 ) - Description: Allow passing run_id to MLflowCallbackHandler to resume a run instead of creating a new run. Support recording retriever relevant metrics. Refactor the code to fix some bugs. --------- Signed-off-by: Serena Ruan <serena.rxy@gmail.com>	7 months ago
Facundo Santiago	92e6a641fd	feat: adding paygo api support for Azure ML / Azure AI Studio (#14560 ) - Description: Introducing support for LLMs and Chat models running in Azure AI studio and Azure ML using the new deployment mode pay-as-you-go (model as a service). - Issue: NA - Dependencies: None. - Tag maintainer: @prakharg-msft @gdyre - Twitter handle: @santiagofacundo Examples added: * [docs/docs/integrations/llms/azure_ml.ipynb](https://github.com/santiagxf/langchain/blob/santiagxf/azureml-endpoints-paygo-community/docs/docs/integrations/chat/azureml_endpoint.ipynb) * [docs/docs/integrations/chat/azureml_chat_endpoint.ipynb](https://github.com/santiagxf/langchain/blob/santiagxf/azureml-endpoints-paygo-community/docs/docs/integrations/chat/azureml_chat_endpoint.ipynb) --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	7 months ago
Davide Menini	9ce177580a	community: normalize bedrock embeddings (#15103 ) In this PR I added a post-processing function to normalize the embeddings. This happens only if the new `normalize` flag is `True`. --------- Co-authored-by: taamedag <Davide.Menini@swisscom.com>	7 months ago
baichuan-assistant	20fcd49348	community: Fix Baichuan Chat. (#15207 ) - Description: Baichuan Chat (with both Baichuan-Turbo and Baichuan-Turbo-192K models) has updated their APIs. There are breaking changes. For example, BAICHUAN_SECRET_KEY is removed in the latest API but is still required in Langchain. Baichuan's Langchain integration needs to be updated to the latest version. - Issue: #15206 - Dependencies: None, - Twitter handle: None @hwchase17. Co-authored-by: BaiChuanHelper <wintergyc@WinterGYCs-MacBook-Pro.local>	7 months ago
gcheron	cfc225ecb3	community: SQLStrStore/SQLDocStore provide an easy SQL alternative to `InMemoryStore` to persist data remotely in a SQL storage (#15909 ) Description: - Implement `SQLStrStore` and `SQLDocStore` classes that inherits from `BaseStore` to allow to persist data remotely on a SQL server. - SQL is widely used and sometimes we do not want to install a caching solution like Redis. - Multiple issues/comments complain that there is no easy remote and persistent solution that are not in memory (users want to replace InMemoryStore), e.g., https://github.com/langchain-ai/langchain/issues/14267, https://github.com/langchain-ai/langchain/issues/15633, https://github.com/langchain-ai/langchain/issues/14643, https://stackoverflow.com/questions/77385587/persist-parentdocumentretriever-of-langchain - This is particularly painful when wanting to use `ParentDocumentRetriever ` - This implementation is particularly useful when: * it's expensive to construct an InMemoryDocstore/dict * you want to retrieve documents from remote sources * you just want to reuse existing objects - This implementation integrates well with PGVector, indeed, when using PGVector, you already have a SQL instance running. `SQLDocStore` is a convenient way of using this instance to store documents associated to vectors. An integration example with ParentDocumentRetriever and PGVector is provided in docs/docs/integrations/stores/sql.ipynb or [here](https://github.com/gcheron/langchain/blob/sql-store/docs/docs/integrations/stores/sql.ipynb). - It persists `str` and `Document` objects but can be easily extended. Issue: Provide an easy SQL alternative to `InMemoryStore`. --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	7 months ago
Massimiliano Pronesti	e529939c54	feat(llms): support more tasks in HuggingFaceHub LLM and remove deprecated dep (#14406 ) - Description: this PR upgrades the `HuggingFaceHub` LLM: * support more tasks (`translation` and `conversational`) * replaced the deprecated `InferenceApi` with `InferenceClient` * adjusted the overall logic to use the "recommended" model for each task when no model is provided, and vice-versa. - Tag mainter(s): @baskaryan @hwchase17	7 months ago
Bagatur	54149292f8	community[patch]: Release 0.0.15 (#16474 )	7 months ago
Tomaz Bratanic	d0a8082188	Fix neo4j sanitize (#16439 ) Fix the sanitization bug and add an integration test	7 months ago
Florian MOREL	4b7969efc5	community[minor]: New documents loader for visio files (with extension .vsdx) (#16171 ) Description : New documents loader for visio files (with extension .vsdx) A [visio file](https://fr.wikipedia.org/wiki/Microsoft_Visio) (with extension .vsdx) is associated with Microsoft Visio, a diagram creation software. It stores information about the structure, layout, and graphical elements of a diagram. This format facilitates the creation and sharing of visualizations in areas such as business, engineering, and computer science. A Visio file can contain multiple pages. Some of them may serve as the background for others, and this can occur across multiple layers. This loader extracts the textual content from each page and its associated pages, enabling the extraction of all visible text from each page, similar to what an OCR algorithm would do. Dependencies : xmltodict package	7 months ago
Boris Feld	404abf139a	community: Add CometLLM tracing context var (#15765 ) I also added LANGCHAIN_COMET_TRACING to enable the CometLLM tracing integration similar to other tracing integrations. This is easier for end-users to enable it rather than importing the callback and pass it manually. (This is the same content as https://github.com/langchain-ai/langchain/pull/14650 but rebased and squashed as something seems to confuse Github Action).	7 months ago
DL	b9e7f6f38a	community[minor]: Bedrock async methods (#12477 ) Description: Added support for asynchronous streaming in the Bedrock class and corresponding tests. Primarily: async def aprepare_output_stream async def _aprepare_input_and_invoke_stream async def _astream async def _acall I've ensured that the code adheres to the project's linting and formatting standards by running make format, make lint, and make test. Issue: #12054, #11589 Dependencies: None Tag maintainer: @baskaryan Twitter handle: @dominic_lovric --------- Co-authored-by: Piyush Jain <piyushjain@duck.com>	7 months ago
Frank995	5694728816	community[patch]: Implement vector length definition at init time in PGVector for indexing (#16133 ) Replace this entire comment with: - Description: allow user to define tVector length in PGVector when creating the embedding store, this allows for later indexing - Issue: #16132 - Dependencies: None	7 months ago
parkererickson-tg	b26a22f307	community[minor]: add TigerGraph support (#16280 ) Description: Add support for querying TigerGraph databases through the InquiryAI service. Issue: N/A Dependencies: N/A Twitter handle: @TigerGraphDB	7 months ago
Alireza Kashani	d1b4ead87c	community[patch]: Update grobid.py (#16298 ) there is a case where "coords" does not exist in the "sentence" therefore, the "split(";")" will lead to error. we can fix that by adding "if sentence.get("coords") is not None:" the resulting empty "sbboxes" from this scenario will raise error at "sbboxes[0]["page"]" because sbboxes are empty. the PDF from https://pubmed.ncbi.nlm.nih.gov/23970373/ can replicate those errors.	7 months ago
s-g-1	fbe592a5ce	community[patch]: fix typo in pgvecto_rs debug msg (#16318 ) fixes typo in pip install message for the pgvecto_rs community vector store no issues found mentioning this no dependents changed	7 months ago
Ian	b9f5104e6c	communty[minor]: Store Message History to TiDB Database (#16304 ) This pull request integrates the TiDB database into LangChain for storing message history, marking one of several steps towards a comprehensive integration of TiDB with LangChain. A simple usage ```python from datetime import datetime from langchain_community.chat_message_histories import TiDBChatMessageHistory history = TiDBChatMessageHistory( connection_string="mysql+pymysql://<host>:<PASSWORD>@<host>:4000/<db>?ssl_ca=/etc/ssl/cert.pem&ssl_verify_cert=true&ssl_verify_identity=true", session_id="code_gen", earliest_time=datetime.utcnow(), # Optional to set earliest_time to load messages after this time point. ) history.add_user_message("hi! How's feature going?") history.add_ai_message("It's almot done") ```	7 months ago
Erick Friis	cfe95ab085	multiple: update langsmith dep (#16407 )	7 months ago
Eli Lucherini	6b2a57161a	community[patch]: allow additional kwargs in MlflowEmbeddings for compatibility with Cohere API (#15242 ) - Description: add support for kwargs in`MlflowEmbeddings` `embed_document()` and `embed_query()` so that all the arguments required by Cohere API (and others?) can be passed down to the server. - Issue: #15234 - Dependencies: MLflow with MLflow Deployments (`pip install mlflow[genai]`) Tests Now this code [adapted from the docs](https://python.langchain.com/docs/integrations/providers/mlflow#embeddings-example) for the Cohere API works locally. ```python """ Setup ----- export COHERE_API_KEY=... mlflow deployments start-server --config-path examples/deployments/cohere/config.yaml Run --- python /path/to/this/file.py """ embeddings = MlflowCohereEmbeddings(target_uri="http://127.0.0.1:5000", endpoint="embeddings") print(embeddings.embed_query("hello")[:3]) print(embeddings.embed_documents(["hello", "world"])[0][:3]) ``` Output ``` [0.060455322, 0.028793335, -0.025848389] [0.031707764, 0.021057129, -0.009361267] ```	7 months ago
Guillem Orellana Trullols	aad2aa7188	community[patch]: BedrockChat -> Support Titan express as chat model (#15408 ) Titan Express model was not supported as a chat model because LangChain messages were not "translated" to a text prompt. Co-authored-by: Guillem Orellana Trullols <guillem.orellana_trullols@siemens.com>	7 months ago
Katarina Supe	01c2f27ffa	community[patch]: Update Memgraph support (#16360 ) - Description: I removed two queries to the database and left just one whose results were formatted afterward into other type of schema (avoided two calls to DB) - Issue: / - Dependencies: / - Twitter handle: @supe_katarina	7 months ago
Max Jakob	8569b8f680	community[patch]: ElasticsearchStore enable max inner product (#16393 ) Enable max inner product for approximate retrieval strategy. For exact strategy we lack the necessary `maxInnerProduct` function in the Painless scripting language, this is why we do not add it there. Similarity docs: https://www.elastic.co/guide/en/elasticsearch/reference/current/dense-vector.html#dense-vector-params --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Joe McElroy <joseph.mcelroy@elastic.co>	7 months ago
Iskren Ivov Chernev	fc196cab12	community[minor]: DeepInfra support for chat models (#16380 ) Add deepinfra chat models support. This is https://github.com/langchain-ai/langchain/pull/14234 re-opened from my branch (so maintainers can edit).	7 months ago
Bagatur	85e8423312	community[patch]: Update bing results tool name (#16395 ) Make BingSearchResults tool name OpenAI functions compatible (can't have spaces). Fixes #16368	7 months ago
Max Jakob	de209af533	community[patch]: ElasticsearchStore: add relevance function selector (#16378 ) Implement similarity function selector for ElasticsearchStore. The scores coming back from Elasticsearch are already similarities (not distances) and they are already normalized (see [docs](https://www.elastic.co/guide/en/elasticsearch/reference/current/dense-vector.html#dense-vector-params)). Hence we leave the scores untouched and just forward them. This fixes #11539. However, in hybrid mode (when keyword search and vector search are involved) Elasticsearch currently returns no scores. This PR adds an error message around this fact. We need to think a bit more to come up with a solution for this case. This PR also corrects a small error in the Elasticsearch integration test. --------- Co-authored-by: Erick Friis <erick@langchain.dev>	7 months ago
Tom Jorquera	1445ac95e8	community[patch]: Enable streaming for GPT4all (#16392 ) `streaming` param was never passed to model	7 months ago
Bagatur	8779013847	community[patch]: Release 0.0.14 (#16384 )	7 months ago
Bagatur	1dc6c1ce06	core[patch], community[patch], langchain[patch], docs: Update SQL chains/agents/docs (#16168 ) Revamp SQL use cases docs. In the process update SQL chains and agents.	7 months ago
Luke	5396604ef4	community: Handling missing key in Google Trends API response. (#15864 ) - Description: Handing response where _interest_over_time_ is missing. - Issue: #15859 - Dependencies: None	7 months ago
Virat Singh	c2a614eddc	community: Add PolygonLastQuote Tool and Toolkit (#15990 ) Description: In this PR, I am adding a `PolygonLastQuote` Tool, which can be used to get the latest price quote for a given ticker / stock. Additionally, I've added a Polygon Toolkit, which we can use to encapsulate future tools that we build for Polygon. Twitter handle: [@virattt](https://twitter.com/virattt) --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	7 months ago
Ofer Mendelevitch	ffae98d371	template: Update Vectara templates (#15363 ) fixed multi-query template for Vectara added self-query template for Vectara Also added prompt_name parameter to summarization CC @efriis Twitter handle: @ofermend	7 months ago
Carey	021b0484a8	community[patch]: add skipped test for inner product normalization (#14989 ) --------- Co-authored-by: Erick Friis <erick@langchain.dev>	7 months ago
Christophe Bornet	3ccbe11363	community[minor]: Add Cassandra document loader (#16215 ) - Description: document loader for Apache Cassandra - Twitter handle: cbornet_	7 months ago
mikeFore4	9d32af72ce	community[patch]: huggingface hub character removal bug fix (#16233 ) - Description: Some text-generation models on huggingface repeat the prompt in their generated response, but not all do! The tests use "gpt2" which DOES repeat the prompt and as such, the HuggingFaceHub class is hardcoded to remove the first few characters of the response (to match the len(prompt)). However, if you are using a model (such as the very popular "meta-llama/Llama-2-7b-chat-hf") that DOES NOT repeat the prompt in it's generated text, then the beginning of the generated text will be cut off. This code change fixes that bug by first checking whether the prompt is repeated in the generated response and removing it conditionally. - Issue: #16232 - Dependencies: N/A - Twitter handle: N/A	7 months ago
Andreas Motl	3613d8a2ad	community[patch]: Use SQLAlchemy's `bulk_save_objects` method to improve insert performance (#16244 ) - Description: Improve [pgvector vector store adapter](https://github.com/langchain-ai/langchain/blob/v0.1.1/libs/community/langchain_community/vectorstores/pgvector.py) to save embeddings in batches, to improve its performance. - Issue: NA - Dependencies: NA - References: https://github.com/crate-workbench/langchain/pull/1 Hi again from the CrateDB team, following up on GH-16243, this is another minor patch to the pgvector vector store adapter. Inserting embeddings in batches, using [SQLAlchemy's `bulk_save_objects`](https://docs.sqlalchemy.org/en/20/orm/session_api.html#sqlalchemy.orm.Session.bulk_save_objects) method, can deliver substantial performance gains. With kind regards, Andreas. NB: As I am seeing just now that this method is a legacy feature of SA 2.0, it will need to be reworked on a future iteration. However, it is not deprecated yet, and I haven't been able to come up with a different implementation, yet.	7 months ago

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281 Commits (e510cfaa23b90662ed88d54115f0f8c0726213b8)