langchain

Commit Graph

Author	SHA1	Message	Date
Christophe Bornet	8595c3ab59	community[minor]: Add InMemoryVectorStore to module level imports (#19576 )	6 months ago
Anindyadeep	b2a11ce686	community[minor]: Prem AI langchain integration (#19113 ) ### Prem SDK integration in LangChain This PR adds the integration with [PremAI's](https://www.premai.io/) prem-sdk with langchain. User can now access to deployed models (llms/embeddings) and use it with langchain's ecosystem. This PR adds the following: ### This PR adds the following: - [x] Add chat support - [X] Adding embedding support - [X] writing integration tests - [X] writing tests for chat - [X] writing tests for embedding - [X] writing unit tests - [X] writing tests for chat - [X] writing tests for embedding - [X] Adding documentation - [X] writing documentation for chat - [X] writing documentation for embedding - [X] run `make test` - [X] run `make lint`, `make lint_diff` - [X] Final checks (spell check, lint, format and overall testing) --------- Co-authored-by: Anindyadeep Sannigrahi <anindyadeepsannigrahi@Anindyadeeps-MacBook-Pro.local> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Erick Friis <erick@langchain.dev> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
Dmitry Tyumentsev	08b769d539	community[patch]: YandexGPT Use recent yandexcloud sdk version (#19341 ) Fixed inability to work with [yandexcloud SDK](https://pypi.org/project/yandexcloud/) version higher 0.265.0	6 months ago
Mikelarg	dac2e0165a	community[minor]: Added GigaChat Embeddings support + updated previous GigaChat integration (#19516 ) - Description: Added integration with [GigaChat](https://developers.sber.ru/portal/products/gigachat) embeddings. Also added support for extra fields in GigaChat LLM and fixed docs.	6 months ago
Igor Muniz Soares	743f888580	community[minor]: Dappier chat model integration (#19370 ) Description: This PR adds [Dappier](https://dappier.com/) for the chat model. It supports generate, async generate, and batch functionalities. We added unit and integration tests as well as a notebook with more details about our chat model. Dependencies: No extra dependencies are needed.	6 months ago
Hugoberry	96dc180883	community[minor]: Add `DuckDB` as a vectorstore (#18916 ) DuckDB has a cosine similarity function along list and array data types, which can be used as a vector store. - Description: The latest version of DuckDB features a cosine similarity function, which can be used with its support for list or array column types. This PR surfaces this functionality to langchain. - Dependencies: duckdb 0.10.0 - Twitter handle: @igocrite --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
Christophe Bornet	00614f332a	community[minor]: Add InMemoryVectorStore (#19326 ) This is a basic VectorStore implementation using an in-memory dict to store the documents. It doesn't need any extra/optional dependency as it uses numpy which is already a dependency of langchain. This is useful for quick testing, demos, examples. Also it allows to write vendor-neutral tutorials, guides, etc...	6 months ago
Nithish Raghunandanan	7ad0a3f2a7	community: add Couchbase Vector Store (#18994 ) - Description: Added support for Couchbase Vector Search to LangChain. - Dependencies: couchbase>=4.1.12 - Twitter handle: @nithishr --------- Co-authored-by: Nithish Raghunandanan <nithishr@users.noreply.github.com>	6 months ago
gonvee	b82644078e	community: Add `keep_alive` parameter to control how long the model w… (#19005 ) Add `keep_alive` parameter to control how long the model will stay loaded into memory with Ollama。 --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Leonid Ganeline	7de1d9acfd	community: `llms` imports fixes (#18943 ) Classes are missed in __all__ and in different places of __init__.py - BaichuanLLM - ChatDatabricks - ChatMlflow - Llamafile - Mlflow - Together Added classes to __all__. I also sorted __all__ list. --------- Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
fengjial	c922ea36cb	community[minor]: Add Baidu VectorDB as vector store (#17997 ) Co-authored-by: fengjialin <fengjialin@MacBook-Pro.local>	6 months ago
Leonid Ganeline	9c8523b529	community[patch]: flattening imports 3 (#18939 ) @eyurtsev	6 months ago
Virat Singh	cafffe8a21	community: Add PolygonAggregates tool (#18882 ) Description: In this PR, I am adding a `PolygonAggregates` tool, which can be used to get historical stock price data (called aggregates by Polygon) for a given ticker. Polygon [docs](https://polygon.io/docs/stocks/get_v2_aggs_ticker__stocksticker__range__multiplier___timespan___from___to) for this endpoint. Twitter: [@virattt](https://twitter.com/virattt)	6 months ago
Ishani Vyas	2b0cbd65ba	community[patch]: Add Passio Nutrition AI Food Search Tool to Community Package (#18278 ) ## Add Passio Nutrition AI Food Search Tool to Community Package ### Description We propose adding a new tool to the `community` package, enabling integration with Passio Nutrition AI for food search functionality. This tool will provide a simple interface for retrieving nutrition facts through the Passio Nutrition AI API, simplifying user access to nutrition data based on food search queries. ### Implementation Details - Class Structure: Implement `NutritionAI`, extending `BaseTool`. It includes an `_run` method that accepts a query string and, optionally, a `CallbackManagerForToolRun`. - API Integration: Use `NutritionAIAPI` for the API wrapper, encapsulating all interactions with the Passio Nutrition AI and providing a clean API interface. - Error Handling: Implement comprehensive error handling for API request failures. ### Expected Outcome - User Benefits: Enable easy querying of nutrition facts from Passio Nutrition AI, enhancing the utility of the `langchain_community` package for nutrition-related projects. - Functionality: Provide a straightforward method for integrating nutrition information retrieval into users' applications. ### Dependencies - `langchain_core` for base tooling support - `pydantic` for data validation and settings management - Consider `requests` or another HTTP client library if not covered by `NutritionAIAPI`. ### Tests and Documentation - Unit Tests: Include tests that mock network interactions to ensure tool reliability without external API dependency. - Documentation: Create an example notebook in `docs/docs/integrations/tools/passio_nutrition_ai.ipynb` showing usage, setup, and example queries. ### Contribution Guidelines Compliance - Adhere to the project's linting and formatting standards (`make format`, `make lint`, `make test`). - Ensure compliance with LangChain's contribution guidelines, particularly around dependency management and package modifications. ### Additional Notes - Aim for the tool to be a lightweight, focused addition, not introducing significant new dependencies or complexity. - Potential future enhancements could include caching for common queries to improve performance. ### Twitter Handle - Here is our Passio AI [twitter handle](https://twitter.com/@passio_ai) where we announce our products. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, hwchase17.	6 months ago
Christophe Bornet	e54a49b697	community[minor]: Add lazy_table_reflection param to SqlDatabase (#18742 ) For some DBs with lots of tables, reflection of all the tables can take very long. So this change will make the tables be reflected lazily when get_table_info() is called and `lazy_table_reflection` is True.	6 months ago
Tomaz Bratanic	4bfe888717	comunity[patch]: Fix neo4j sanitizing values (#18750 ) Fixing sanitization for when deeply nested lists appear	6 months ago
Yunmo Koo	fee6f983ef	community[minor]: Integration for `Friendli` LLM and `ChatFriendli` ChatModel. (#17913 ) ## Description - Add [Friendli](https://friendli.ai/) integration for `Friendli` LLM and `ChatFriendli` chat model. - Unit tests and integration tests corresponding to this change are added. - Documentations corresponding to this change are added. ## Dependencies - Optional dependency [`friendli-client`](https://pypi.org/project/friendli-client/) package is added only for those who use `Frienldi` or `ChatFriendli` model. ## Twitter handle - https://twitter.com/friendliai	6 months ago
Ian	390ef6abe3	community[minor]: Add Initial Support for TiDB Vector Store (#15796 ) This pull request introduces initial support for the TiDB vector store. The current version is basic, laying the foundation for the vector store integration. While this implementation provides the essential features, we plan to expand and improve the TiDB vector store support with additional enhancements in future updates. Upcoming Enhancements: * Support for Vector Index Creation: To enhance the efficiency and performance of the vector store. * Support for max marginal relevance search. * Customized Table Structure Support: Recognizing the need for flexibility, we plan for more tailored and efficient data store solutions. Simple use case exmaple ```python from typing import List, Tuple from langchain.docstore.document import Document from langchain_community.vectorstores import TiDBVectorStore from langchain_openai import OpenAIEmbeddings db = TiDBVectorStore.from_texts( embedding=embeddings, texts=['Andrew like eating oranges', 'Alexandra is from England', 'Ketanji Brown Jackson is a judge'], table_name="tidb_vector_langchain", connection_string=tidb_connection_url, distance_strategy="cosine", ) query = "Can you tell me about Alexandra?" docs_with_score: List[Tuple[Document, float]] = db.similarity_search_with_score(query) for doc, score in docs_with_score: print("-" * 80) print("Score: ", score) print(doc.page_content) print("-" * 80) ```	6 months ago
Eugene Yurtsev	e188d4ecb0	Add dangerous parameter to requests tool (#18697 ) The tools are already documented as dangerous. Not clear whether adding an opt-in parameter is necessary or not	6 months ago
Erick Friis	1beb84b061	community[patch]: move pdf text tests to integration (#18746 )	6 months ago
Christophe Bornet	4a7d73b39d	community: If load() has been overridden, use it in default lazy_load() (#18690 )	6 months ago
Sam Khano	1b4dcf22f3	community[minor]: Add DocumentDBVectorSearch VectorStore (#17757 ) Description: - Added Amazon DocumentDB Vector Search integration (HNSW index) - Added integration tests - Updated AWS documentation with DocumentDB Vector Search instructions - Added notebook for DocumentDB integration with example usage --------- Co-authored-by: EC2 Default User <ec2-user@ip-172-31-95-226.ec2.internal>	6 months ago
Vittorio Rigamonti	51f3902bc4	community[minor]: Adding support for Infinispan as VectorStore (#17861 ) Description: This integrates Infinispan as a vectorstore. Infinispan is an open-source key-value data grid, it can work as single node as well as distributed. Vector search is supported since release 15.x For more: [Infinispan Home](https://infinispan.org) Integration tests are provided as well as a demo notebook	6 months ago
Djordje	12b4a4d860	community[patch]: Opensearch delete method added - indexing supported (#18522 ) - Description: Added delete method for OpenSearchVectorSearch, therefore indexing supported - Issue: No - Dependencies: No - Twitter handle: stkbmf	6 months ago
Eugene Yurtsev	4c25b49229	community[major]: breaking change in some APIs to force users to opt-in for pickling (#18696 ) This is a PR that adds a dangerous load parameter to force users to opt in to use pickle. This is a PR that's meant to raise user awareness that the pickling module is involved.	6 months ago
Eugene Yurtsev	0e52961562	community[patch]: Patch tdidf retriever (CVE-2024-2057) (#18695 ) This is a patch for `CVE-2024-2057`: https://www.cve.org/CVERecord?id=CVE-2024-2057 This affects users that: * Use the `TFIDFRetriever` * Attempt to de-serialize it from an untrusted source that contains a malicious payload	6 months ago
Christophe Bornet	15b1770326	Merge pull request #18421 * Implement lazy_load() for AssemblyAIAudioTranscriptLoader	6 months ago
Christophe Bornet	bb284eebe4	Merge pull request #18436 * Implement lazy_load() for ConfluenceLoader	6 months ago
Liang Zhang	81985b31e6	community[patch]: Databricks SerDe uses cloudpickle instead of pickle (#18607 ) - Description: Databricks SerDe uses cloudpickle instead of pickle when serializing a user-defined function transform_input_fn since pickle does not support functions defined in `__main__`, and cloudpickle supports this. - Dependencies: cloudpickle>=2.0.0 Added a unit test.	6 months ago
Dounx	ad48f55357	community[minor]: add Yuque document loader (#17924 ) This pull request support loading documents from Yuque with Langchain. Yuque is a professional cloud-based knowledge base for team collaboration in documentation. Website: https://www.yuque.com OpenAPI: https://www.yuque.com/yuque/developer/openapi	6 months ago
Kazuki Maeda	60c5d964a8	community[minor]: use jq schema for content_key in json_loader (#18003 ) ### Description Changed the value specified for `content_key` in JSONLoader from a single key to a value based on jq schema. I created [similar PR](https://github.com/langchain-ai/langchain/pull/11255) before, but it has several conflicts because of the architectural change associated stable version release, so I re-create this PR to fit new architecture. ### Why For json data like the following, specify `.data[].attributes.message` for page_content and `.data[].attributes.id` or `.data[].attributes.attributes. tags`, etc., the `content_key` must also parse the json structure. <details> <summary>sample json data</summary> ```json { "data": [ { "attributes": { "message": "message1", "tags": [ "tag1" ] }, "id": "1" }, { "attributes": { "message": "message2", "tags": [ "tag2" ] }, "id": "2" } ] } ``` </details> <details> <summary>sample code</summary> ```python def metadata_func(record: dict, metadata: dict) -> dict: metadata["source"] = None metadata["id"] = record.get("id") metadata["tags"] = record["attributes"].get("tags") return metadata sample_file = "sample1.json" loader = JSONLoader( file_path=sample_file, jq_schema=".data[]", content_key=".attributes.message", ## content_key is parsable into jq schema is_content_key_jq_parsable=True, ## this is added parameter metadata_func=metadata_func ) data = loader.load() data ``` </details> ### Dependencies none ### Twitter handle [kzk_maeda](https://twitter.com/kzk_maeda)	6 months ago
Erick Friis	e1924b3e93	core[patch]: deprecate hwchase17/langchain-hub, address path traversal (#18600 ) Deprecates the old langchain-hub repository. Does not deprecate the new https://smith.langchain.com/hub @PinkDraconian has correctly raised that in the event someone is loading unsanitized user input into the `try_load_from_hub` function, they have the ability to load files from other locations in github than the hwchase17/langchain-hub repository. This PR adds some more path checking to that function and deprecates the functionality in favor of the hub built into LangSmith.	6 months ago
Scott Nath	b051bba1a9	community: Add you.com tool, add async to retriever, add async testing, add You tool doc (#18032 ) - Description: finishes adding the you.com functionality including: - add async functions to utility and retriever - add the You.com Tool - add async testing for utility, retriever, and tool - add a tool integration notebook page - Dependencies: any dependencies required for this change - Twitter handle: @scottnath	6 months ago
Kate Silverstein	b7c71e2e07	community[minor]: llamafile embeddings support (#17976 ) * Description: adds `LlamafileEmbeddings` class implementation for generating embeddings using [llamafile](https://github.com/Mozilla-Ocho/llamafile)-based models. Includes related unit tests and notebook showing example usage. * Issue: N/A * Dependencies: N/A	6 months ago
Petteri Johansson	6c1989d292	community[minor], langchain[minor], docs: Gremlin Graph Store and QA Chain (#17683 ) - Description: New feature: Gremlin graph-store and QA chain (including docs). Compatible with Azure CosmosDB. - Dependencies: no changes	6 months ago
Ather Fawaz	a5ccf5d33c	community[minor]: Add support for Perplexity chat model(#17024 ) - Description: This PR adds support for [Perplexity AI APIs](https://blog.perplexity.ai/blog/introducing-pplx-api). - Issues: None - Dependencies: None - Twitter handle: [@atherfawaz](https://twitter.com/AtherFawaz) --------- Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
Rodrigo Nogueira	3438d2cbcc	community[minor]: add maritalk chat (#17675 ) Description: Adds the MariTalk chat that is based on a LLM specially trained for Portuguese. Twitter handle: @MaritacaAI	6 months ago
RadhikaBansal97	8bafd2df5e	community[patch]: Change github endpoint in GithubLoader (#17622 ) Description- - Changed the GitHub endpoint as existing was not working and giving 404 not found error - Also the existing function was failing if file_filter is not passed as the tree api return all paths including directory as well, and when get_file_content was iterating over these path, the function was failing for directory as the api was returning list of files inside the directory, so added a condition to ignore the paths if it a directory - Fixes this issue - https://github.com/langchain-ai/langchain/issues/17453 Co-authored-by: Radhika Bansal <Radhika.Bansal@veritas.com>	6 months ago
Eugene Yurtsev	51b661cfe8	community[patch]: BaseLoader load method should just delegate to lazy_load (#18289 ) load() should just reference lazy_load()	7 months ago
Erick Friis	040271f33a	community[patch]: remove llmlingua extended tests (#18344 )	7 months ago
Virat Singh	cd926ac3dd	community: Add PolygonFinancials Tool (#18324 ) Description: In this PR, I am adding a `PolygonFinancials` tool, which can be used to get financials data for a given ticker. The financials data is the fundamental data that is found in income statements, balance sheets, and cash flow statements of public US companies. Twitter: [@virattt](https://twitter.com/virattt)	7 months ago
Eugene Yurtsev	cd52433ba0	community[minor]: Add `SQLDatabaseLoader` document loader (#18281 ) - Description: A generic document loader adapter for SQLAlchemy on top of LangChain's `SQLDatabaseLoader`. - Needed by: https://github.com/crate-workbench/langchain/pull/1 - Depends on: GH-16655 - Addressed to: @baskaryan, @cbornet, @eyurtsev Hi from CrateDB again, in the same spirit like GH-16243 and GH-16244, this patch breaks out another commit from https://github.com/crate-workbench/langchain/pull/1, in order to reduce the size of this patch before submitting it, and to separate concerns. To accompany the SQLAlchemy adapter implementation, the patch includes integration tests for both SQLite and PostgreSQL. Let me know if corresponding utility resources should be added at different spots. With kind regards, Andreas. ### Software Tests ```console docker compose --file libs/community/tests/integration_tests/document_loaders/docker-compose/postgresql.yml up ``` ```console cd libs/community pip install psycopg2-binary pytest -vvv tests/integration_tests -k sqldatabase ``` ``` 14 passed ``` ![image](https://github.com/langchain-ai/langchain/assets/453543/42be233c-eb37-4c76-a830-474276e01436) --------- Co-authored-by: Andreas Motl <andreas.motl@crate.io>	7 months ago
David Ruan	af35e2525a	community[minor]: add hugging_face_model document loader (#17323 ) - Description: add hugging_face_model document loader, - Issue: NA, - Dependencies: NA, --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	7 months ago
Ayo Ayibiowu	ac1d7d9de8	community[feat]: Adds LLMLingua as a document compressor (#17711 ) Description: This PR adds support for using the [LLMLingua project ](https://github.com/microsoft/LLMLingua) especially the LongLLMLingua (Enhancing Large Language Model Inference via Prompt Compression) as a document compressor / transformer. The LLMLingua project is an interesting project that can greatly improve RAG system by compressing prompts and contexts while keeping their semantic relevance. Issue: https://github.com/microsoft/LLMLingua/issues/31 Dependencies: [llmlingua](https://pypi.org/project/llmlingua/) @baskaryan --------- Co-authored-by: Ayodeji Ayibiowu <ayodeji.ayibiowu@getinge.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	7 months ago
am-kinetica	9b8f6455b1	Langchain vectorstore integration with Kinetica (#18102 ) - Description: New vectorstore integration with the Kinetica database - Issue: - Dependencies: the Kinetica Python API `pip install gpudb==7.2.0.1`, - Tag maintainer: @baskaryan, @hwchase17 - Twitter handle: --------- Co-authored-by: Chad Juliano <cjuliano@kinetica.com>	7 months ago
Dan Stambler	69344a0661	community: Add Laser Embedding Integration (#18111 ) - Description: Added Integration with Meta AI's LASER Language-Agnostic SEntence Representations embedding library, which supports multilingual embedding for any of the languages listed here: https://github.com/facebookresearch/flores/blob/main/flores200/README.md#languages-in-flores-200, including several low resource languages - Dependencies: laser_encoders	7 months ago
Barun Amalkumar Halder	cc69976860	community[minor] : adds callback handler for Fiddler AI (#17708 ) Description: Callback handler to integrate fiddler with langchain. This PR adds the following - 1. `FiddlerCallbackHandler` implementation into langchain/community 2. Example notebook `fiddler.ipynb` for usage documentation [Internal Tracker : FDL-14305] Issue: NA Dependencies: - Installation of langchain-community is unaffected. - Usage of FiddlerCallbackHandler requires installation of latest fiddler-client (2.5+) Twitter handle: @fiddlerlabs @behalder Co-authored-by: Barun Halder <barun@fiddler.ai>	7 months ago
Chad Juliano	50ba3c68bb	community[minor]: add Kinetica LLM wrapper (#17879 ) Description: Initial pull request for Kinetica LLM wrapper Issue: N/A Dependencies: No new dependencies for unit tests. Integration tests require gpudb, typeguard, and faker Twitter handle: @chad_juliano Note: There is another pull request for Kinetica vectorstore. Ultimately we would like to make a partner package but we are starting with a community contribution.	7 months ago
Brad Erickson	ecd72d26cf	community: Bugfix - correct Ollama API path to avoid HTTP 307 (#17895 ) Sets the correct /api/generate path, without ending /, to reduce HTTP requests. Reference: https://github.com/ollama/ollama/blob/efe040f8/docs/api.md#generate-request-streaming Before: DEBUG: Starting new HTTP connection (1): localhost:11434 DEBUG: http://localhost:11434 "POST /api/generate/ HTTP/1.1" 307 0 DEBUG: http://localhost:11434 "POST /api/generate HTTP/1.1" 200 None After: DEBUG: Starting new HTTP connection (1): localhost:11434 DEBUG: http://localhost:11434 "POST /api/generate HTTP/1.1" 200 None	7 months ago
Ian	3019a594b7	community[minor]: Add tidb loader support (#17788 ) This pull request support loading data from TiDB database with Langchain. A simple usage: ``` from langchain_community.document_loaders import TiDBLoader CONNECTION_STRING = "mysql+pymysql://root@127.0.0.1:4000/test" QUERY = "select id, name, description from items;" loader = TiDBLoader( connection_string=CONNECTION_STRING, query=QUERY, page_content_columns=["name", "description"], metadata_columns=["id"], ) documents = loader.load() print(documents) ```	7 months ago
Michael Feil	242981b8f0	community[minor]: infinity embedding local option (#17671 ) drop-in-replacement for sentence-transformers inference. https://github.com/langchain-ai/langchain/discussions/17670 tldr from the discussion above -> around a 4x-22x speedup over using SentenceTransformers / huggingface embeddings. For more info: https://github.com/michaelfeil/infinity (pure-python dependency) --------- Co-authored-by: Erick Friis <erick@langchain.dev>	7 months ago
Zachary Toliver	29ee0496b6	community[patch]: Allow override of 'fetch_schema_from_transport' in the GraphQL tool (#17649 ) - Description: In order to override the bool value of "fetch_schema_from_transport" in the GraphQLAPIWrapper, a "fetch_schema_from_transport" value needed to be added to the "_EXTRA_OPTIONAL_TOOLS" dictionary in load_tools in the "graphql" key. The parameter "fetch_schema_from_transport" must also be passed in to the GraphQLAPIWrapper to allow reading of the value when creating the client. Passing as an optional parameter is probably best to avoid breaking changes. This change is necessary to support GraphQL instances that do not support fetching schema, such as TigerGraph. More info here: [TigerGraph GraphQL Schema Docs](https://docs.tigergraph.com/graphql/current/schema) - Threads handle: @zacharytoliver --------- Co-authored-by: Zachary Toliver <zt10191991@hotmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Guangdong Liu	47b1b7092d	community[minor]: Add SparkLLM to community (#17702 )	7 months ago
Guangdong Liu	3ba1cb8650	community[minor]: Add SparkLLM Text Embedding Model and SparkLLM introduction (#17573 )	7 months ago
Virat Singh	92e52e89ca	community: Add PolygonTickerNews Tool (#17808 ) Description: In this PR, I am adding a PolygonTickerNews Tool, which can be used to get the latest news for a given ticker / stock. Twitter handle: [@virattt](https://twitter.com/virattt)	7 months ago
CogniJT	919ebcc596	community[minor]: CogniSwitch Agent Toolkit for LangChain (#17312 ) Description: CogniSwitch focusses on making GenAI usage more reliable. It abstracts out the complexity & decision making required for tuning processing, storage & retrieval. Using simple APIs documents / URLs can be processed into a Knowledge Graph that can then be used to answer questions. Dependencies: No dependencies. Just network calls & API key required Tag maintainer: @hwchase17 Twitter handle: https://github.com/CogniSwitch Documentation: Please check `docs/docs/integrations/toolkits/cogniswitch.ipynb` Tests: The usual tool & toolkits tests using `test_imports.py` PR has passed linting and testing before this submission. --------- Co-authored-by: Saicharan Sridhara <145636106+saiCogniswitch@users.noreply.github.com>	7 months ago
Guangdong Liu	73edf17b4e	community[minor]: Add Apache Doris as vector store (#17527 ) --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Nejc Habjan	b4fa847a90	community[minor]: add exclude parameter to DirectoryLoader (#17316 ) - Description: adds an `exclude` parameter to the DirectoryLoader class, based on similar behavior in GenericLoader - Issue: discussed in https://github.com/langchain-ai/langchain/discussions/9059 and I think in some other issues that I cannot find at the moment 🙇 - Dependencies: None - Twitter handle: don't have one sorry! Just https://github/nejch --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	7 months ago
Bagatur	8f14234afb	infra: ignore flakey lua test (#17618 )	7 months ago
Moshe Berchansky	20a56fe0a2	community[minor]: Add QuantizedEmbedders (#17391 ) Description: * adding Quantized embedders using optimum-intel and intel-extension-for-pytorch. * added mdx documentation and example notebooks * added embedding import testing. Dependencies: optimum = {extras = ["neural-compressor"], version = "^1.14.0", optional = true} intel_extension_for_pytorch = {version = "^2.2.0", optional = true} Dependencies have been added to pyproject.toml for the community lib. Twitter handle: @peter_izsak --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
nvpranak	91bcc9c5c9	community[minor]: Nemo embeddings(#16206 ) This PR is adding support for NVIDIA NeMo embeddings issue #16095. --------- Co-authored-by: Praveen Nakshatrala <pnakshatrala@gmail.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
wulixuan	c776cfc599	community[minor]: integrate with model Yuan2.0 (#15411 ) 1. integrate with [`Yuan2.0`](https://github.com/IEIT-Yuan/Yuan-2.0/blob/main/README-EN.md) 2. update `langchain.llms` 3. add a new doc for [Yuan2.0 integration](docs/docs/integrations/llms/yuan2.ipynb) --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Kate Silverstein	0bc4a9b3fc	community[minor]: Adds Llamafile as an LLM (#17431 ) * Description: Adds a simple LLM implementation for interacting with [llamafile](https://github.com/Mozilla-Ocho/llamafile)-based models. * Dependencies: N/A * Issue: N/A Detail [llamafile](https://github.com/Mozilla-Ocho/llamafile) lets you run LLMs locally from a single file on most computers without installing any dependencies. To use the llamafile LLM implementation, the user needs to: 1. Download a llamafile e.g. https://huggingface.co/jartine/TinyLlama-1.1B-Chat-v1.0-GGUF/resolve/main/TinyLlama-1.1B-Chat-v1.0.Q5_K_M.llamafile?download=true 2. Make the file executable. 3. Run the llamafile in 'server mode'. (All llamafiles come packaged with a lightweight server; by default, the server listens at `http://localhost:8080`.) ```bash wget https://url/of/model.llamafile chmod +x model.llamafile ./model.llamafile --server --nobrowser ``` Now, the user can invoke the LLM via the LangChain client: ```python from langchain_community.llms.llamafile import Llamafile llm = Llamafile() llm.invoke("Tell me a joke.") ```	7 months ago
Qihui Xie	5738143d4b	add mongodb_store (#13801 ) # Add MongoDB storage - Description: Add MongoDB Storage as an option for large doc store. Example usage: ```Python # Instantiate the MongodbStore with a MongoDB connection from langchain.storage import MongodbStore mongo_conn_str = "mongodb://localhost:27017/" mongodb_store = MongodbStore(mongo_conn_str, db_name="test-db", collection_name="test-collection") # Set values for keys doc1 = Document(page_content='test1') doc2 = Document(page_content='test2') mongodb_store.mset([("key1", doc1), ("key2", doc2)]) # Get values for keys values = mongodb_store.mget(["key1", "key2"]) # [doc1, doc2] # Iterate over keys for key in mongodb_store.yield_keys(): print(key) # Delete keys mongodb_store.mdelete(["key1", "key2"]) ``` - Dependencies: Use `mongomock` for integration test. --------- Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	7 months ago
wulixuan	5d06797905	community[minor]: integrate chat models with Yuan2.0 (#16575 ) 1. integrate chat models with [`Yuan2.0`](https://github.com/IEIT-Yuan/Yuan-2.0/blob/main/README-EN.md) 2. add a new doc for [Yuan2.0 integration](docs/docs/integrations/llms/yuan2.ipynb) Yuan2.0 is a new generation Fundamental Large Language Model developed by IEIT System. We have published all three models, Yuan 2.0-102B, Yuan 2.0-51B, and Yuan 2.0-2B. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Ian Gregory	e5472b5eb8	Framework for supporting more languages in LanguageParser (#13318 ) ## Description I am submitting this for a school project as part of a team of 5. Other team members are @LeilaChr, @maazh10, @Megabear137, @jelalalamy. This PR also has contributions from community members @Harrolee and @Mario928. Initial context is in the issue we opened (#11229). This pull request adds: - Generic framework for expanding the languages that `LanguageParser` can handle, using the [tree-sitter](https://github.com/tree-sitter/py-tree-sitter#py-tree-sitter) parsing library and existing language-specific parsers written for it - Support for the following additional languages in `LanguageParser`: - C - C++ - C# - Go - Java (contributed by @Mario928 https://github.com/ThatsJustCheesy/langchain/pull/2) - Kotlin - Lua - Perl - Ruby - Rust - Scala - TypeScript (contributed by @Harrolee https://github.com/ThatsJustCheesy/langchain/pull/1) Here is the [design document](https://docs.google.com/document/d/17dB14cKCWAaiTeSeBtxHpoVPGKrsPye8W0o_WClz2kk) if curious, but no need to read it. ## Issues - Closes #11229 - Closes #10996 - Closes #8405 ## Dependencies `tree_sitter` and `tree_sitter_languages` on PyPI. We have tried to add these as optional dependencies. ## Documentation We have updated the list of supported languages, and also added a section to `source_code.ipynb` detailing how to add support for additional languages using our framework. ## Maintainer - @hwchase17 (previously reviewed https://github.com/langchain-ai/langchain/pull/6486) Thanks!! ## Git commits We will gladly squash any/all of our commits (esp merge commits) if necessary. Let us know if this is desirable, or if you will be squash-merging anyway. <!-- Thank you for contributing to LangChain! Replace this entire comment with: - Description: a description of the change, - Issue: the issue # it fixes (if applicable), - Dependencies: any dependencies required for this change, - Tag maintainer: for a quicker response, tag the relevant maintainer (see below), - 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` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md 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/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> --------- Co-authored-by: Maaz Hashmi <mhashmi373@gmail.com> Co-authored-by: LeilaChr <87657694+LeilaChr@users.noreply.github.com> Co-authored-by: Jeremy La <jeremylai511@gmail.com> Co-authored-by: Megabear137 <zubair.alnoor27@gmail.com> Co-authored-by: Lee Harrold <lhharrold@sep.com> Co-authored-by: Mario928 <88029051+Mario928@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	7 months ago
Sridhar Ramaswamy	9f1cbbc6ed	community[minor]: Add pebblo safe document loader (#16862 ) - Description: Pebblo opensource project enables developers to safely load data to their Gen AI apps. It identifies semantic topics and entities found in the loaded data and summarizes them in a developer-friendly report. - Dependencies: none - Twitter handle: srics @hwchase17	7 months ago
mhavey	1bbb64d956	community[minor], langchian[minor]: Add Neptune Rdf graph and chain (#16650 ) Description: This PR adds a chain for Amazon Neptune graph database RDF format. It complements the existing Neptune Cypher chain. The PR also includes a Neptune RDF graph class to connect to, introspect, and query a Neptune RDF graph database from the chain. A sample notebook is provided under docs that demonstrates the overall effect: invoking the chain to make natural language queries against Neptune using an LLM. Issue: This is a new feature Dependencies: The RDF graph class depends on the AWS boto3 library if using IAM authentication to connect to the Neptune database. --------- Co-authored-by: Piyush Jain <piyushjain@duck.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Andreas Motl	1fdd9bd980	community/SQLDatabase: Generalize and trim software tests (#16659 ) - Description: Improve test cases for `SQLDatabase` adapter component, see [suggestion](https://github.com/langchain-ai/langchain/pull/16655#pullrequestreview-1846749474). - Depends on: GH-16655 - Addressed to: @baskaryan, @cbornet, @eyurtsev _Remark: This PR is stacked upon GH-16655, so that one will need to go in first._ Edit: Thank you for bringing in GH-17191, @eyurtsev. This is a little aftermath, improving/streamlining the corresponding test cases.	7 months ago
morgana	722aae4fd1	community: add delete method to rocksetdb vectorstore to support recordmanager (#17030 ) - Description: This adds a delete method so that rocksetdb can be used with `RecordManager`. - Issue: N/A - Dependencies: N/A - Twitter handle: `@_morgan_adams_` --------- Co-authored-by: Rockset API Bot <admin@rockset.io>	7 months ago
Spencer Kelly	54fa78c887	community[patch]: fixed vector similarity filtering (#16967 ) Description: changed filtering so that failed filter doesn't add document to results. Currently filtering is entirely broken and all documents are returned whether or not they pass the filter. fixes issue introduced in https://github.com/langchain-ai/langchain/pull/16190	7 months ago
Abhijeeth Padarthi	584b647b96	community[minor]: AWS Athena Document Loader (#15625 ) - Description: Adds the document loader for [AWS Athena](https://aws.amazon.com/athena/), a serverless and interactive analytics service. - Dependencies: Added boto3 as a dependency	7 months ago
david-tempelmann	93da18b667	community[minor]: Add mmr and similarity_score_threshold retrieval to DatabricksVectorSearch (#16829 ) - Description: This PR adds support for `search_types="mmr"` and `search_type="similarity_score_threshold"` to retrievers using `DatabricksVectorSearch`, - Issue: - Dependencies: - Twitter handle: --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Erick Friis	3a2eb6e12b	infra: add print rule to ruff (#16221 ) Added noqa for existing prints. Can slowly remove / will prevent more being intro'd	7 months ago
kYLe	c9999557bf	community[patch]: Modify LLMs/Anyscale work with OpenAI API v1 (#14206 ) <!-- Thank you for contributing to LangChain! Replace this entire comment with: - Description: a description of the change, - Issue: the issue # it fixes (if applicable), - Dependencies: any dependencies required for this change, - Tag maintainer: for a quicker response, tag the relevant maintainer (see below), - 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` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md 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/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> - Description: 1. Modify LLMs/Anyscale to work with OAI v1 2. Get rid of openai_ prefixed variables in Chat_model/ChatAnyscale 3. Modify `anyscale_api_base` to `anyscale_base_url` to follow OAI name convention (reverted) --------- Co-authored-by: Erick Friis <erick@langchain.dev>	7 months ago
Bagatur	65e97c9b53	infra: mv SQLDatabase tests to community (#17276 )	7 months ago
Scott Nath	a32798abd7	community: Add you.com utility, update you retriever integration docs (#17014 ) <!-- 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: a description of the change, - Issue: the issue # it fixes if applicable, - Dependencies: any dependencies required for this change, - 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. 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. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> - Description: changes to you.com files - general cleanup - adds community/utilities/you.py, moving bulk of code from retriever -> utility - removes `snippet` as endpoint - adds `news` as endpoint - adds more tests <s>Description: update community MAKE file - adds `integration_tests` - adds `coverage`</s> - Issue: the issue # it fixes if applicable, - [For New Contributors: Update Integration Documentation](https://github.com/langchain-ai/langchain/issues/15664#issuecomment-1920099868) - Dependencies: n/a - Twitter handle: @scottnath - Mastodon handle: scottnath@mastodon.social --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Liang Zhang	7306600e2f	community[patch]: Support SerDe transform functions in Databricks LLM (#16752 ) Description: Databricks LLM does not support SerDe the transform_input_fn and transform_output_fn. After saving and loading, the LLM will be broken. This PR serialize these functions into a hex string using pickle, and saving the hex string in the yaml file. Using pickle to serialize a function can be flaky, but this is a simple workaround that unblocks many use cases. If more sophisticated SerDe is needed, we can improve it later. Test: Added a simple unit test. I did manual test on Databricks and it works well. The saved yaml looks like: ``` llm: _type: databricks cluster_driver_port: null cluster_id: null databricks_uri: databricks endpoint_name: databricks-mixtral-8x7b-instruct extra_params: {} host: e2-dogfood.staging.cloud.databricks.com max_tokens: null model_kwargs: null n: 1 stop: null task: null temperature: 0.0 transform_input_fn: 80049520000000000000008c085f5f6d61696e5f5f948c0f7472616e73666f726d5f696e7075749493942e transform_output_fn: null ``` @baskaryan ```python from langchain_community.embeddings import DatabricksEmbeddings from langchain_community.llms import Databricks from langchain.chains import RetrievalQA from langchain.document_loaders import TextLoader from langchain.text_splitter import CharacterTextSplitter from langchain.vectorstores import FAISS import mlflow embeddings = DatabricksEmbeddings(endpoint="databricks-bge-large-en") def transform_input(**request): request["messages"] = [ { "role": "user", "content": request["prompt"] } ] del request["prompt"] return request llm = Databricks(endpoint_name="databricks-mixtral-8x7b-instruct", transform_input_fn=transform_input) persist_dir = "faiss_databricks_embedding" # Create the vector db, persist the db to a local fs folder loader = TextLoader("state_of_the_union.txt") documents = loader.load() text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0) docs = text_splitter.split_documents(documents) db = FAISS.from_documents(docs, embeddings) db.save_local(persist_dir) def load_retriever(persist_directory): embeddings = DatabricksEmbeddings(endpoint="databricks-bge-large-en") vectorstore = FAISS.load_local(persist_directory, embeddings) return vectorstore.as_retriever() retriever = load_retriever(persist_dir) retrievalQA = RetrievalQA.from_llm(llm=llm, retriever=retriever) with mlflow.start_run() as run: logged_model = mlflow.langchain.log_model( retrievalQA, artifact_path="retrieval_qa", loader_fn=load_retriever, persist_dir=persist_dir, ) # Load the retrievalQA chain loaded_model = mlflow.pyfunc.load_model(logged_model.model_uri) print(loaded_model.predict([{"query": "What did the president say about Ketanji Brown Jackson"}])) ```	7 months ago
ByeongUk Choi	b88329e9a5	community[patch]: Implement Unique ID Enforcement in FAISS (#17244 ) Description: Implemented unique ID validation in the FAISS component to ensure all document IDs are distinct. This update resolves issues related to non-unique IDs, such as inconsistent behavior during deletion processes.	7 months ago
Luiz Ferreira	34d2daffb3	community[patch]: Fix chat openai unit test (#17124 ) - Description: Actually the test named `test_openai_apredict` isn't testing the apredict method from ChatOpenAI. - Twitter handle: https://twitter.com/OAlmofadas	7 months ago
Frank	ef082c77b1	community[minor]: add github file loader to load any github file content b… (#15305 ) ### Description support load any github file content based on file extension. Why not use [git loader](https://python.langchain.com/docs/integrations/document_loaders/git#load-existing-repository-from-disk) ? git loader clones the whole repo even only interested part of files, that's too heavy. This GithubFileLoader only downloads that you are interested files. ### Twitter handle my twitter: @shufanhaotop --------- Co-authored-by: Hao Fan <h_fan@apple.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Ryan Kraus	f027696b5f	community: Added new Utility runnables for NVIDIA Riva. (#15966 ) Please tag this issue with `nvidia_genai` - Description: Added new Runnables for integration NVIDIA Riva into LCEL chains for Automatic Speech Recognition (ASR) and Text To Speech (TTS). - Issue: N/A - Dependencies: To use these runnables, the NVIDIA Riva client libraries are required. It they are not installed, an error will be raised instructing how to install them. The Runnables can be safely imported without the riva client libraries. - Twitter handle: N/A All of the Riva Runnables are inside a single folder in the Utilities module. In this folder are four files: - common.py - Contains all code that is common to both TTS and ASR - stream.py - Contains a class representing an audio stream that allows the end user to put data into the stream like a queue. - asr.py - Contains the RivaASR runnable - tts.py - Contains the RivaTTS runnable The following Python function is an example of creating a chain that makes use of both of these Runnables: ```python def create( config: Configuration, audio_encoding: RivaAudioEncoding, sample_rate: int, audio_channels: int = 1, ) -> Runnable[ASRInputType, TTSOutputType]: """Create a new instance of the chain.""" _LOGGER.info("Instantiating the chain.") # create the riva asr client riva_asr = RivaASR( url=str(config.riva_asr.service.url), ssl_cert=config.riva_asr.service.ssl_cert, encoding=audio_encoding, audio_channel_count=audio_channels, sample_rate_hertz=sample_rate, profanity_filter=config.riva_asr.profanity_filter, enable_automatic_punctuation=config.riva_asr.enable_automatic_punctuation, language_code=config.riva_asr.language_code, ) # create the prompt template prompt = PromptTemplate.from_template("{user_input}") # model = ChatOpenAI() model = ChatNVIDIA(model="mixtral_8x7b") # type: ignore # create the riva tts client riva_tts = RivaTTS( url=str(config.riva_asr.service.url), ssl_cert=config.riva_asr.service.ssl_cert, output_directory=config.riva_tts.output_directory, language_code=config.riva_tts.language_code, voice_name=config.riva_tts.voice_name, ) # construct and return the chain return {"user_input": riva_asr} \| prompt \| model \| riva_tts # type: ignore ``` The following code is an example of creating a new audio stream for Riva: ```python input_stream = AudioStream(maxsize=1000) # Send bytes into the stream for chunk in audio_chunks: await input_stream.aput(chunk) input_stream.close() ``` The following code is an example of how to execute the chain with RivaASR and RivaTTS ```python output_stream = asyncio.Queue() while not input_stream.complete: async for chunk in chain.astream(input_stream): output_stream.put(chunk) ``` Everything should be async safe and thread safe. Audio data can be put into the input stream while the chain is running without interruptions. --------- Co-authored-by: Hayden Wolff <hwolff@nvidia.com> Co-authored-by: Hayden Wolff <hwolff@Haydens-Laptop.local> Co-authored-by: Hayden Wolff <haydenwolff99@gmail.com> Co-authored-by: Erick Friis <erick@langchain.dev>	7 months ago
Alex Boury	334b6ebdf3	community[minor]: Breebs docs retriever (#16578 ) - Description: Implementation of breeb retriever with integration tests -> libs/community/tests/integration_tests/retrievers/test_breebs.py and documentation (notebook) -> docs/docs/integrations/retrievers/breebs.ipynb. - Dependencies: None	7 months ago
Harrison Chase	4eda647fdd	infra: add -p to mkdir in lint steps (#17013 ) Previously, if this did not find a mypy cache then it wouldnt run this makes it always run adding mypy ignore comments with existing uncaught issues to unblock other prs --------- Co-authored-by: Erick Friis <erick@langchain.dev> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	7 months ago
Erick Friis	b1a847366c	community: revert SQL Stores (#16912 ) This reverts commit `cfc225ecb3`. https://github.com/langchain-ai/langchain/pull/15909#issuecomment-1922418097 These will have existed in langchain-community 0.0.16 and 0.0.17.	7 months ago
Christophe Bornet	af8c5c185b	langchain[minor],community[minor]: Add async methods in BaseLoader (#16634 ) Adds: * methods `aload()` and `alazy_load()` to interface `BaseLoader` * implementation for class `MergedDataLoader ` * support for class `BaseLoader` in async function `aindex()` with unit tests Note: this is compatible with existing `aload()` methods that some loaders already had. Twitter handle: @cbornet_ --------- Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>	7 months ago
thiswillbeyourgithub	1d082359ee	community: add support for callable filters in FAISS (#16190 ) - Description: Filtering in a FAISS vectorstores is very inflexible and doesn't allow that many use case. I think supporting callable like this enables a lot: regular expressions, condition on multiple keys etc. Note I had to manually alter a test. I don't understand if it was falty to begin with or if there is something funky going on. - Issue: None - Dependencies: None - Twitter handle: None Signed-off-by: thiswillbeyourgithub <26625900+thiswillbeyourgithub@users.noreply.github.com>	8 months ago
Volodymyr Machula	32c5be8b73	community[minor]: Connery Tool and Toolkit (#14506 ) ## Summary This PR implements the "Connery Action Tool" and "Connery Toolkit". Using them, you can integrate Connery actions into your LangChain agents and chains. Connery is an open-source plugin infrastructure for AI. With Connery, you can easily create a custom plugin with a set of actions and seamlessly integrate them into your LangChain agents and chains. Connery will handle the rest: runtime, authorization, secret management, access management, audit logs, and other vital features. Additionally, Connery and our community offer a wide range of ready-to-use open-source plugins for your convenience. Learn more about Connery: - GitHub: https://github.com/connery-io/connery-platform - Documentation: https://docs.connery.io - Twitter: https://twitter.com/connery_io ## TODOs - [x] API wrapper - [x] Integration tests - [x] Connery Action Tool - [x] Docs - [x] Example - [x] Integration tests - [x] Connery Toolkit - [x] Docs - [x] Example - [x] Formatting (`make format`) - [x] Linting (`make lint`) - [x] Testing (`make test`)	8 months ago
Neli Hateva	c95facc293	langchain[minor], community[minor]: Implement Ontotext GraphDB QA Chain (#16019 ) - Description: Implement Ontotext GraphDB QA Chain - Issue: N/A - Dependencies: N/A - Twitter handle: @OntotextGraphDB	8 months ago
Jael Gu	a1aa3a657c	community[patch]: Milvus supports add & delete texts by ids (#16256 ) # Description To support [langchain indexing](https://python.langchain.com/docs/modules/data_connection/indexing) as requested by users, vectorstore Milvus needs to support: - document addition by id (`add_documents` method with `ids` argument) - delete by id (`delete` method with `ids` argument) Example usage: ```python from langchain.indexes import SQLRecordManager, index from langchain.schema import Document from langchain_community.vectorstores import Milvus from langchain_openai import OpenAIEmbeddings collection_name = "test_index" embedding = OpenAIEmbeddings() vectorstore = Milvus(embedding_function=embedding, collection_name=collection_name) namespace = f"milvus/{collection_name}" record_manager = SQLRecordManager( namespace, db_url="sqlite:///record_manager_cache.sql" ) record_manager.create_schema() doc1 = Document(page_content="kitty", metadata={"source": "kitty.txt"}) doc2 = Document(page_content="doggy", metadata={"source": "doggy.txt"}) index( [doc1, doc1, doc2], record_manager, vectorstore, cleanup="incremental", # None, "incremental", or "full" source_id_key="source", ) ``` # Fix issues Fix https://github.com/milvus-io/milvus/issues/30112 --------- Signed-off-by: Jael Gu <mengjia.gu@zilliz.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	8 months ago
Benito Geordie	f3fdc5c5da	community: Added integrations for ThirdAI's NeuralDB with Retriever and VectorStore frameworks (#15280 ) Description: Adds ThirdAI NeuralDB retriever and vectorstore integration. NeuralDB is a CPU-friendly and fine-tunable text retrieval engine.	8 months ago
Christophe Bornet	4915c3cd86	[Fix] Fix Cassandra Document loader default page content mapper (#16273 ) We can't use `json.dumps` by default as many types returned by the cassandra driver are not serializable. It's safer to use `str` and let users define their own custom `page_content_mapper` if needed.	8 months ago
Micah Parker	6543e585a5	community[patch]: Added support for Ollama's num_predict option in ChatOllama (#16633 ) Just a simple default addition to the options payload for a ollama generate call to support a max_new_tokens parameter. Should fix issue: https://github.com/langchain-ai/langchain/issues/14715	8 months ago
baichuan-assistant	70ff54eace	community[minor]: Add Baichuan Text Embedding Model and Baichuan Inc introduction (#16568 ) - Description: Adding Baichuan Text Embedding Model and Baichuan Inc introduction. Baichuan Text Embedding ranks #1 in C-MTEB leaderboard: https://huggingface.co/spaces/mteb/leaderboard Co-authored-by: BaiChuanHelper <wintergyc@WinterGYCs-MacBook-Pro.local>	8 months ago
Ghani	e30c6662df	Langchain-community : EdenAI chat integration. (#16377 ) - Description: This PR adds [EdenAI](https://edenai.co/) for the chat model (already available in LLM & Embeddings). It supports all [ChatModel] functionality: generate, async generate, stream, astream and batch. A detailed notebook was added. - Dependencies: No dependencies are added as we call a rest API. --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	8 months ago
Bagatur	5df8ab574e	infra: move indexing documentation test (#16595 )	8 months ago
Brian Burgin	148347e858	community[minor]: Add LiteLLM Router Integration (#15588 ) community: - Description: - Add new ChatLiteLLMRouter class that allows a client to use a LiteLLM Router as a LangChain chat model. - Note: The existing ChatLiteLLM integration did not cover the LiteLLM Router class. - Add tests and Jupyter notebook. - Issue: None - Dependencies: Relies on existing ChatLiteLLM integration - Twitter handle: @bburgin_0 --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	8 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>	8 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>	8 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>" ) ```	8 months ago

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