langchain

Commit Graph

Author	SHA1	Message	Date
wulixuan	0e0030f494	community[patch]: fix yuan2 chat model errors while invoke. (#19015 ) 1. fix yuan2 chat model errors while invoke. 2. update related tests. 3. fix some deprecationWarning.	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
Eugene Yurtsev	6cdca4355d	community[minor]: Revamp PGVector Filtering (#18992 ) This PR makes the following updates in the pgvector database: 1. Use JSONB field for metadata instead of JSON 2. Update operator syntax to include required `$` prefix before the operators (otherwise there will be name collisions with fields) 3. The change is non-breaking, old functionality is still the default, but it will emit a deprecation warning 4. Previous functionality has bugs associated with comparisons due to casting to text (so lexical ordering is used incorrectly for numeric fields) 5. Adds an a GIN index on the JSONB field for more efficient querying	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
Joshua Carroll	ddaf9de169	community: Fix bug with StreamlitChatMessageHistory (#18834 ) - Description: Fix Streamlit bug which was introduced by https://github.com/langchain-ai/langchain/pull/18250, update integration test - Issue: https://github.com/langchain-ai/langchain/issues/18684 - Dependencies: None	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
Eugene Yurtsev	1f50274df7	community[patch]: Add pgvector to docker compose and update settings used in integration test (#18815 )	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
Tomaz Bratanic	ea51cdaede	Remove neo4j bloom labels from graph schema (#18564 ) Neo4j tools use particular node labels and relationship types to store metadata, but are irrelevant for text2cypher or graph generation, so we want to ignore them in the schema representation.	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
Aayush Kataria	7c2f3f6f95	community[minor]: Adding Azure Cosmos Mongo vCore Vector DB Cache (#16856 ) Description: This pull request introduces several enhancements for Azure Cosmos Vector DB, primarily focused on improving caching and search capabilities using Azure Cosmos MongoDB vCore Vector DB. Here's a summary of the changes: - AzureCosmosDBSemanticCache: Added a new cache implementation called AzureCosmosDBSemanticCache, which utilizes Azure Cosmos MongoDB vCore Vector DB for efficient caching of semantic data. Added comprehensive test cases for AzureCosmosDBSemanticCache to ensure its correctness and robustness. These tests cover various scenarios and edge cases to validate the cache's behavior. - HNSW Vector Search: Added HNSW vector search functionality in the CosmosDB Vector Search module. This enhancement enables more efficient and accurate vector searches by utilizing the HNSW (Hierarchical Navigable Small World) algorithm. Added corresponding test cases to validate the HNSW vector search functionality in both AzureCosmosDBSemanticCache and AzureCosmosDBVectorSearch. These tests ensure the correctness and performance of the HNSW search algorithm. - LLM Caching Notebook - The notebook now includes a comprehensive example showcasing the usage of the AzureCosmosDBSemanticCache. This example highlights how the cache can be employed to efficiently store and retrieve semantic data. Additionally, the example provides default values for all parameters used within the AzureCosmosDBSemanticCache, ensuring clarity and ease of understanding for users who are new to the cache implementation. @hwchase17,@baskaryan, @eyurtsev,	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
Tomaz Bratanic	f6bfb969ba	community[patch]: Add an option for indexed generic label when import neo4j graph documents (#18122 ) Current implementation doesn't have an indexed property that would optimize the import. I have added a `baseEntityLabel` parameter that allows you to add a secondary node label, which has an indexed id `property`. By default, the behaviour is identical to previous version. Since multi-labeled nodes are terrible for text2cypher, I removed the secondary label from schema representation object and string, which is used in text2cypher.	7 months ago
Arun Sathiya	4adac20d7b	community[patch]: Make cohere_api_key a SecretStr (#12188 ) This PR makes `cohere_api_key` in `llms/cohere` a SecretStr, so that the API Key is not leaked when `Cohere.cohere_api_key` is represented as a string. --------- Signed-off-by: Arun <arun@arun.blog> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	7 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	7 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>	7 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	7 months ago
Yujie Qian	cbb65741a7	community[patch]: Voyage AI updates default model and batch size (#17655 ) - Description: update the default model and batch size in VoyageEmbeddings - Issue: N/A - Dependencies: N/A - Twitter handle: N/A --------- Co-authored-by: fodizoltan <zoltan@conway.expert>	7 months ago
Shengsheng Huang	ae471a7dcb	community[minor]: add BigDL-LLM integrations (#17953 ) - Description: [`bigdl-llm`](https://github.com/intel-analytics/BigDL) is a library for running LLM on Intel XPU (from Laptop to GPU to Cloud) using INT4/FP4/INT8/FP8 with very low latency (for any PyTorch model). This PR adds bigdl-llm integrations to langchain. - Issue: NA - Dependencies: `bigdl-llm` library - Contribution maintainer: @shane-huang Examples added: - docs/docs/integrations/llms/bigdl.ipynb	7 months ago
Ethan Yang	f61cb8d407	community[minor]: Add openvino backend support (#11591 ) - Description: add openvino backend support by HuggingFace Optimum Intel, - Dependencies: “optimum[openvino]”, --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 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>	7 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
Kai Kugler	df234fb171	community[patch]: Fixing embedchain document mapping (#18255 ) - Description: The current embedchain implementation seems to handle document metadata differently than done in the current implementation of langchain and a KeyError is thrown. I would love for someone else to test this... --------- Co-authored-by: KKUGLER <kai.kugler@mercedes-benz.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Deshraj Yadav <deshraj@gatech.edu>	7 months ago
Erick Friis	040271f33a	community[patch]: remove llmlingua extended tests (#18344 )	7 months ago
Tomaz Bratanic	5999c4a240	Add support for parameters in neo4j retrieval query (#18310 ) Sometimes, you want to use various parameters in the retrieval query of Neo4j Vector to personalize/customize results. Before, when there were only predefined chains, it didn't really make sense. Now that it's all about custom chains and LCEL, it is worth adding since users can inject any params they wish at query time. Isn't prone to SQL injection-type attacks since we use parameters and not concatenating strings.	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

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