41 Commits (5e60d659179d9338259ca3774173d5c649db98f9)

Author	SHA1	Message	Date
Jingpan Xiong	1202017c56	community[minor]: Add relyt vector database (#20316) ... Co-authored-by: kaka <kaka@zbyte-inc.cloud> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: jingsi <jingsi@leadincloud.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	2 months ago
Raghav Dixit	9b7fb381a4	community[patch]: LanceDB integration patch update (#20686) ... Description : - added functionalities - delete, index creation, using existing connection object etc. - updated usage - Added LaceDB cloud OSS support make lint_diff , make test checks done	2 months ago
ccurme	c010ec8b71	patch: deprecate (a)get_relevant_documents (#20477) ... - `.get_relevant_documents(query)` -> `.invoke(query)` - `.get_relevant_documents(query=query)` -> `.invoke(query)` - `.get_relevant_documents(query, callbacks=callbacks)` -> `.invoke(query, config={"callbacks": callbacks})` - `.get_relevant_documents(query, **kwargs)` -> `.invoke(query, **kwargs)` --------- Co-authored-by: Erick Friis <erick@langchain.dev>	2 months ago
sdan	a7c5e41443	community[minor]: Added VLite as VectorStore (#20245) ... Support [VLite](https://github.com/sdan/vlite) as a new VectorStore type. **Description**: vlite is a simple and blazing fast vector database(vdb) made with numpy. It abstracts a lot of the functionality around using a vdb in the retrieval augmented generation(RAG) pipeline such as embeddings generation, chunking, and file processing while still giving developers the functionality to change how they're made/stored. **Before submitting**: Added tests [here](c09c2ebd5c/libs/community/tests/integration_tests/vectorstores/test_vlite.py) Added ipython notebook [here](c09c2ebd5c/docs/docs/integrations/vectorstores/vlite.ipynb) Added simple docs on how to use [here](c09c2ebd5c/docs/docs/integrations/providers/vlite.mdx) **Profiles** Maintainers: @sdan Twitter handles: [@sdand](https://x.com/sdand) --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	3 months ago
Leonid Ganeline	4cb5f4c353	community[patch]: import flattening fix (#20110) ... This PR should make it easier for linters to do type checking and for IDEs to jump to definition of code. See #20050 as a template for this PR. - As a byproduct: Added 3 missed `test_imports`. - Added missed `SolarChat` in to __init___.py Added it into test_import ut. - Added `# type: ignore` to fix linting. It is not clear, why linting errors appear after ^ changes. --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	3 months ago
jeff kit	ac42e96e4c	community[patch], langchain[minor]: Enhance Tencent Cloud VectorDB, langchain: make Tencent Cloud VectorDB self query retrieve compatible (#19651) ... - make Tencent Cloud VectorDB support metadata filtering. - implement delete function for Tencent Cloud VectorDB. - support both Langchain Embedding model and Tencent Cloud VDB embedding model. - Tencent Cloud VectorDB support filter search keyword, compatible with langchain filtering syntax. - add Tencent Cloud VectorDB TranslationVisitor, now work with self query retriever. - more documentations. --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	3 months ago
happy-go-lucky	c6432abdbe	community[patch]: Implement delete method and all async methods in opensearch_vector_search (#17321) ... - **Description:** In order to use index and aindex in libs/langchain/langchain/indexes/_api.py, I implemented delete method and all async methods in opensearch_vector_search - **Dependencies:** No changes	3 months ago
Jan Chorowski	b8b42ccbc5	community[minor]: Pathway vectorstore(#14859) ... - **Description:** Integration with pathway.com data processing pipeline acting as an always updated vectorstore - **Issue:** not applicable - **Dependencies:** optional dependency on [`pathway`](https://pypi.org/project/pathway/) - **Twitter handle:** pathway_com The PR provides and integration with `pathway` to provide an easy to use always updated vector store: ```python import pathway as pw from langchain.embeddings.openai import OpenAIEmbeddings from langchain.text_splitter import CharacterTextSplitter from langchain.vectorstores import PathwayVectorClient, PathwayVectorServer data_sources = [] data_sources.append( pw.io.gdrive.read(object_id="17H4YpBOAKQzEJ93xmC2z170l0bP2npMy", service_user_credentials_file="credentials.json", with_metadata=True)) text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0) embeddings_model = OpenAIEmbeddings(openai_api_key=os.environ["OPENAI_API_KEY"]) vector_server = PathwayVectorServer( *data_sources, embedder=embeddings_model, splitter=text_splitter, ) vector_server.run_server(host="127.0.0.1", port="8765", threaded=True, with_cache=False) client = PathwayVectorClient( host="127.0.0.1", port="8765", ) query = "What is Pathway?" docs = client.similarity_search(query) ``` The `PathwayVectorServer` builds a data processing pipeline which continusly scans documents in a given source connector (google drive, s3, ...) and builds a vector store. The `PathwayVectorClient` implements LangChain's `VectorStore` interface and connects to the server to retrieve documents. --------- Co-authored-by: Mateusz Lewandowski <lewymati@users.noreply.github.com> Co-authored-by: mlewandowski <mlewandowski@MacBook-Pro-mlewandowski.local> Co-authored-by: Berke <berkecanrizai1@gmail.com> Co-authored-by: Adrian Kosowski <adrian@pathway.com> Co-authored-by: mlewandowski <mlewandowski@macbook-pro-mlewandowski.home> Co-authored-by: berkecanrizai <63911408+berkecanrizai@users.noreply.github.com> Co-authored-by: Erick Friis <erick@langchain.dev> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: mlewandowski <mlewandowski@MBPmlewandowski.ht.home> Co-authored-by: Szymon Dudycz <szymond@pathway.com> Co-authored-by: Szymon Dudycz <szymon.dudycz@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	3 months ago
Tomaz Bratanic	dec00d3050	community[patch]: Add the ability to pass maps to neo4j retrieval query (#19758) ... Makes it easier to flatten complex values to text, so you don't have to use a lot of Cypher to do it.	3 months ago
Chaunte W. Lacewell	a31f692f4e	community[minor]: Add VDMS vectorstore (#19551) ... - **Description:** Add support for Intel Lab's [Visual Data Management System (VDMS)](https://github.com/IntelLabs/vdms) as a vector store - **Dependencies:** `vdms` library which requires protobuf = "4.24.2". There is a conflict with dashvector in `langchain` package but conflict is resolved in `community`. - **Contribution maintainer:** [@cwlacewe](https://github.com/cwlacewe) - **Added tests:** libs/community/tests/integration_tests/vectorstores/test_vdms.py - **Added docs:** docs/docs/integrations/vectorstores/vdms.ipynb - **Added cookbook:** cookbook/multi_modal_RAG_vdms.ipynb --------- Co-authored-by: Eugene Yurtsev <eugene@langchain.dev> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	3 months ago
yongheng.liu	7e29b6061f	community[minor]: integrate China Mobile Ecloud vector search (#15298) ... - **Description:** integrate China Mobile Ecloud vector search, - **Dependencies:** elasticsearch==7.10.1 Co-authored-by: liuyongheng <liuyongheng@cmss.chinamobile.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	3 months ago
Christophe Bornet	8595c3ab59	community[minor]: Add InMemoryVectorStore to module level imports (#19576)	3 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>	3 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...	3 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>	3 months ago
fengjial	c922ea36cb	community[minor]: Add Baidu VectorDB as vector store (#17997) ... Co-authored-by: fengjialin <fengjialin@MacBook-Pro.local>	4 months ago
Leonid Ganeline	9c8523b529	community[patch]: flattening imports 3 (#18939) ... @eyurtsev	4 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) ```	4 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>	4 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	4 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	4 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.	4 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>	4 months ago
Guangdong Liu	73edf17b4e	community[minor]: Add Apache Doris as vector store (#17527) ... --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	4 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>	5 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	5 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>	5 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.	5 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>	5 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>	5 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.	5 months ago
Bagatur	5df8ab574e	infra: move indexing documentation test (#16595)	5 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>	5 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	5 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>	5 months ago
Carey	021b0484a8	community[patch]: add skipped test for inner product normalization (#14989) ... --------- Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
Varik Matevosyan	efe6cfafe2	community: Added Lantern as VectorStore (#12951) ... Support [Lantern](https://github.com/lanterndata/lantern) as a new VectorStore type. - Added Lantern as VectorStore. It will support 3 distance functions `l2 squared`, `cosine` and `hamming` and will use `HNSW` index. - Added tests - Added example notebook	6 months ago
Diego Rani Mazine	ec72225265	refactor: enable connection pool usage in PGVector (#11514) ... - **Description:** `PGVector` refactored to use connection pool. - **Issue:** #11433, - **Tag maintainer:** @hwchase17 @eyurtsev, --------- Co-authored-by: Diego Rani Mazine <diego.mazine@mercadolivre.com> Co-authored-by: Nuno Campos <nuno@langchain.dev>	6 months ago
Karim Lalani	a0064330b1	community[minor]: Add SurrealDB vectorstore (#13331) ... **Description:** Vectorstore implementation around [SurrealDB](https://www.surrealdb.com) --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Tomaz Bratanic	ea2616ae23	Fix RRF and lucene escape characters for neo4j vector store (#14646) ... * Remove Lucene special characters (fixes https://github.com/langchain-ai/langchain/issues/14232) * Fixes RRF normalization for hybrid search	7 months ago
Bagatur	ed58eeb9c5	community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463) ... Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes	7 months ago