langchain

Commit Graph

Author	SHA1	Message	Date
Tomaz Bratanic	8c08cf4619	community: Add support for relationship indexes in neo4j vector (#20657 ) Neo4j has added relationship vector indexes. We can't populate them, but we can use existing indexes for retrieval	5 months ago
Guangdong Liu	e3c2431c5b	comminuty[patch]:Fix Error in apache doris insert (#19989 ) - Issue: #19886	5 months ago
Tomaz Bratanic	27370b679e	community[patch]: Ignore null and invalid embedding values for neo4j metadata filtering (#20558 )	5 months ago
Massimiliano Pronesti	2542a09abc	community[patch]: AzureSearch incorrectly converted to retriever (#20601 ) Closes #20600. Please see the issue for more details.	5 months ago
Christophe Bornet	8f0b5687a3	community[minor]: Add hybrid search to Cassandra VectorStore (#20286 ) Only supported by Astra DB at the moment. Twitter handle: cbornet_	5 months ago
ccurme	c897264b9b	community: (milvus) check for num_shards (#20603 ) @rgupta2508 I believe this change is necessary following https://github.com/langchain-ai/langchain/pull/20318 because of how Milvus handles defaults: `59bf5e811a/pymilvus/client/prepare.py (L82-L85)` ```python num_shards = kwargs[next(iter(same_key))] if not isinstance(num_shards, int): msg = f"invalid num_shards type, got {type(num_shards)}, expected int" raise ParamError(message=msg) req.shards_num = num_shards ``` this way lets Milvus control the default value (instead of maintaining a separate default in Langchain). Let me know if I've got this wrong or you feel it's unnecessary. Thanks.	5 months ago
Rohit Gupta	25c4c24e89	Support to create shards_num in milvus vectorstores (#20318 ) To support number of the shards for the collection to create in milvus vvectorstores. Thank you for contributing to LangChain! - [ ] PR title: "package: description" - Where "package" is whichever of langchain, community, core, experimental, etc. is being modified. Use "docs: ..." for purely docs changes, "templates: ..." for template changes, "infra: ..." for CI changes. - Example: "community: add foobar LLM" - [ ] PR message: *Delete this entire checklist* and replace with - Description: a description of the change - Issue: the issue # it fixes, if applicable - Dependencies: any dependencies required for this change - Twitter handle: if your PR gets announced, and you'd like a mention, we'll gladly shout you out! - [ ] Add tests and docs: If you're adding a new integration, please include 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. - [ ] Lint and test: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, hwchase17.	5 months ago
Christophe Bornet	a22da4315b	community[patch]: Replace function in CassandraVectorStore with simpler lambda (#20323 )	5 months ago
Christophe Bornet	75733c5cc1	community[minor]: Improve CassandraVectorStore from_texts (#20284 )	5 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>	5 months ago
Benito Geordie	57b226532d	community[minor]: Added integrations for ThirdAI's NeuralDB as a Retriever (#17334 ) Description: Adds ThirdAI NeuralDB retriever integration. NeuralDB is a CPU-friendly and fine-tunable text retrieval engine. We previously added a vector store integration but we think that it will be easier for our customers if they can also find us under under langchain-community/retrievers. --------- Co-authored-by: kartikTAI <129414343+kartikTAI@users.noreply.github.com> Co-authored-by: Kartik Sarangmath <kartik@thirdai.com>	5 months ago
Martín Gotelli Ferenaz	b48add4353	community[patch]: Fix pgvector deprecated filter clause usage with OR and AND conditions (#20446 ) Description: Support filter by OR and AND for deprecated PGVector version Issue: #20445 Dependencies: N/A Twitter handle: @martinferenaz	5 months ago
Eugene Yurtsev	c50099161b	community[patch]: Use uuid4 not uuid1 (#20487 ) Using UUID1 is incorrect since it's time dependent, which makes it easy to generate the exact same uuid	5 months ago
Leonid Kuligin	676c68d318	community[patch]: deprecating remaining google_community integrations (#20471 ) Deprecating remaining google community integrations	5 months ago
Leonid Ganeline	7cf2d2759d	community[patch]: docstrings update (#20301 ) Added missed docstrings. Format docstings to the consistent form.	5 months ago
Eugene Yurtsev	22fd844e8a	community[patch]: Add deprecation warnings to postgres implementation (#20222 ) Add deprecation warnings to postgres implementation that are in langchain-postgres.	5 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>	5 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>	5 months ago
Tomaz Bratanic	df25829f33	community[minor]: Add metadata filtering support for neo4j vector (#20001 )	5 months ago
Ben Mitchell	b52b78478f	community[minor]: Implement Async OpenSearch `afrom_texts` & `afrom_embeddings` (#20009 ) - Description: Adds async variants of afrom_texts and afrom_embeddings into `OpenSearchVectorSearch`, which allows for `afrom_documents` to be called. - Issue: I implemented this because my use case involves an async scraper generating documents as and when they're ready to be ingested by Embedding/OpenSearch - Dependencies: None that I'm aware Co-authored-by: Ben Mitchell <b.mitchell@reply.com>	5 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	5 months ago
Bagatur	d62e84c4f5	community[patch]: Revert " Fix the bug that Chroma does not specify `e… (#19866 ) …mbedding_function` (#19277)" This reverts commit `7042934b5f`. Fixes #19848	5 months ago
Dt22	6dbf1a2de0	community[patch]: fix redis input type for index_schema field (#16874 ) ### Subject: Fix Type Misdeclaration for index_schema in redis/base.py I noticed a type misdeclaration for the index_schema column in the redis/base.py file. When following the instructions outlined in [Redis Custom Metadata Indexing](https://python.langchain.com/docs/integrations/vectorstores/redis) to create our own index_schema, it leads to a Pylance type error. <br/> The error message indicates that Dict[str, list[Dict[str, str]]] is incompatible with the type Optional[Union[Dict[str, str], str, os.PathLike]]. ``` index_schema = { "tag": [{"name": "credit_score"}], "text": [{"name": "user"}, {"name": "job"}], "numeric": [{"name": "age"}], } rds, keys = Redis.from_texts_return_keys( texts, embeddings, metadatas=metadata, redis_url="redis://localhost:6379", index_name="users_modified", index_schema=index_schema, ) ``` Therefore, I have created this pull request to rectify the type declaration problem. --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
morgana	074ad5095f	community[patch]: mmr search for Rockset vectorstore integration (#16908 ) - Description: Adding support for mmr search in the Rockset vectorstore integration. - Issue: N/A - Dependencies: N/A - Twitter handle: `@_morgan_adams_` --------- Co-authored-by: Rockset API Bot <admin@rockset.io> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 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>	6 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.	6 months ago
Marcus Virginia	69bb96c80f	community[patch]: surrealdb handle for empty metadata and allow collection names with complex characters (#17374 ) - Description: Handle for empty metadata and allow collection names with complex characters - Issue: #17057 - Dependencies: `surrealdb` --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
高远	688ca48019	community[patch]: Adding validation when vector does not exist (#19698 ) Adding validation when vector does not exist Co-authored-by: gaoyuan <gaoyuan.20001218@bytedance.com>	6 months ago
Chaunte W. Lacewell	4a49fc5a95	community[patch]: Fix bug in vdms (#19728 ) Description: Fix embedding check in vdms Contribution maintainer: [@cwlacewe](https://github.com/cwlacewe)	6 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>	6 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>	6 months ago
CaroFG	cf96060ab7	community[patch]: update for compatibility with latest Meilisearch version (#18970 ) - Description: Updates Meilisearch vectorstore for compatibility with v1.6 and above. Adds embedders settings and embedder_name which are now required. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Guangdong Liu	7042934b5f	community[patch]: Fix the bug that Chroma does not specify `embedding_function` (#19277 ) - Issue: close #18291 - @baskaryan, @eyurtsev PTAL	6 months ago
Adam Law	aeb7b6b11d	community[patch]: use semantic_configurations in AzureSearch (#19347 ) - Description: Currently the semantic_configurations are not used when creating an AzureSearch instance, instead creating a new one with default values. This PR changes the behavior to use the passed semantic_configurations if it is present, and the existing default configuration if not. --------- Co-authored-by: Adam Law <adamlaw@microsoft.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Adrian Valente	2763d8cbe5	community: add len() implementation to Chroma (#19419 ) Thank you for contributing to LangChain! - [x] Add len() implementation to Chroma: "package: community" - [x] PR message: - Description: add an implementation of the __len__() method for the Chroma vectostore, for convenience. - Issue: no exposed method to know the size of a Chroma vectorstore - Dependencies: None - Twitter handle: lowrank_adrian - [x] Add tests and docs - [x] Lint and test --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
Christophe Bornet	8595c3ab59	community[minor]: Add InMemoryVectorStore to module level imports (#19576 )	6 months ago
Aayush Kataria	03c38005cb	community[patch]: Fixing some caching issues for AzureCosmosDBSemanticCache (#18884 ) Fixing some issues for AzureCosmosDBSemanticCache - Added the entry for "AzureCosmosDBSemanticCache" which was missing in langchain/cache.py - Added application name when creating the MongoClient for the AzureCosmosDBVectorSearch, for tracking purposes. @baskaryan, can you please review this PR, we need this to go in asap. These are just small fixes which we found today in our testing.	6 months ago
Clément Tamines	a6cbb755a7	community[patch]: fix semantic answer bug in AzureSearch vector store (#18938 ) - Description: The `semantic_hybrid_search_with_score_and_rerank` method of `AzureSearch` contains a hardcoded field name "metadata" for the document metadata in the Azure AI Search Index. Adding such a field is optional when creating an Azure AI Search Index, as other snippets from `AzureSearch` test for the existence of this field before trying to access it. Furthermore, the metadata field name shouldn't be hardcoded as "metadata" and use the `FIELDS_METADATA` variable that defines this field name instead. In the current implementation, any index without a metadata field named "metadata" will yield an error if a semantic answer is returned by the search in `semantic_hybrid_search_with_score_and_rerank`. - Issue: https://github.com/langchain-ai/langchain/issues/18731 - Prior fix to this bug: This bug was fixed in this PR https://github.com/langchain-ai/langchain/pull/15642 by adding a check for the existence of the metadata field named `FIELDS_METADATA` and retrieving a value for the key called "key" in that metadata if it exists. If the field named `FIELDS_METADATA` was not present, an empty string was returned. This fix was removed in this PR https://github.com/langchain-ai/langchain/pull/15659 (see `ed1ffca911`#). @lz-chen: could you confirm this wasn't intentional? - New fix to this bug: I believe there was an oversight in the logic of the fix from [#1564](https://github.com/langchain-ai/langchain/pull/15642) which I explain below. The `semantic_hybrid_search_with_score_and_rerank` method creates a dictionary `semantic_answers_dict` with semantic answers returned by the search as follows. `5c2f7e6b2b/libs/community/langchain_community/vectorstores/azuresearch.py (L574-L581)` The keys in this dictionary are the unique document ids in the index, if I understand the [documentation of semantic answers](https://learn.microsoft.com/en-us/azure/search/semantic-answers) in Azure AI Search correctly. When the method transforms a search result into a `Document` object, an "answer" key is added to the document's metadata. The value for this "answer" key should be the semantic answer returned by the search from this document, if such an answer is returned. The match between a `Document` object and the semantic answers returned by the search should be done through the unique document id, which is used as a key for the `semantic_answers_dict` dictionary. This id is defined in the search result's field named `FIELDS_ID`. I added a check to avoid any error in case no field named `FIELDS_ID` exists in a search result (which shouldn't happen in theory). A benefit of this approach is that this fix should work whether or not the Azure AI Search Index contains a metadata field. @levalencia could you confirm my analysis and test the fix? @raunakshrivastava7 do you agree with the fix? Thanks for the help!	6 months ago
Souhail Hanfi	cbec43afa9	community[patch]: avoid creating extension PGvector while using readOnly Databases (#19268 ) - Description: PgVector class always runs "create extension" on init and this statement crashes on ReadOnly databases (read only replicas). but wierdly the next create collection etc work even in readOnly databases - Dependencies: no new dependencies - Twitter handle: @VenOmaX666 Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
JSDu	6e090280fd	community[patch]: milvus will autoflush, manual flush is slowly (#19300 ) reference: https://milvus.io/docs/configure_quota_limits.md#quotaAndLimitsflushRateenabled https://github.com/milvus-io/milvus/issues/31407 Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
mackong	e65dc4b95b	community[patch]: clean warning when delete by ids (#19301 ) * Description: rearrange to avoid variable overwrite, which cause warning always. * Issue: N/A * Dependencies: N/A	6 months ago
FinTech秋田	03ba1d4731	community[patch]: Add Support for GPU Index Types in Milvus 2.4 (#19468 ) - Description: This commit introduces support for the newly available GPU index types introduced in Milvus 2.4 within the LangChain project's `milvus.py`. With the release of Milvus 2.4, a range of GPU-accelerated index types have been added, offering enhanced search capabilities and performance optimizations for vector search operations. This update ensures LangChain users can fully utilize the new performance benefits for vector search operations. - Reference: https://milvus.io/docs/gpu_index.md Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
Martin Kolb	e5bdb26f76	community[patch]: More flexible handling for entity names in vector store "HANA Cloud" (#19523 ) - Description: Added support for lower-case and mixed-case names The names for tables and columns previouly had to be UPPER_CASE. With this enhancement, also lower_case and MixedCase are supported, - Issue: N/A - Dependencies: no new dependecies added - Twitter handle: @sapopensource	6 months ago
ccurme	82de8fd6c9	add kwargs (#19519 ) `HanaDB.add_texts` is missing **kwargs.	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
fengjial	3b52ee05d1	community[patch]: fix bugs in baiduvectordb as vectorstore (#19380 ) fix small bugs in vectorstore/baiduvectordb	6 months ago
Tarun Jain	ef6d3d66d6	community[patch]: docarray requires hnsw installation (#19416 ) I have a small dataset, and I tried to use docarray: ``DocArrayHnswSearch ``. But when I execute, it returns: ```bash raise ImportError( ImportError: Could not import docarray python package. Please install it with `pip install "langchain[docarray]"`. ``` Instead of docarray it needs to be ```bash docarray[hnswlib] ``` 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
Vittorio Rigamonti	9b2f9ee952	community: VectorStore Infinispan, adding autoconfiguration (#18967 ) Description: this PR enable VectorStore autoconfiguration for Infinispan: if metadatas are only of basic types, protobuf config will be automatically generated for the user.	6 months ago

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203 Commits (e5f5d9ff563b6f71bb3ebbccac729c10fb851b3a)