250 Commits (95c3e5f85f8ed8026a11e351b57bfae488d654c4)

Author	SHA1	Message	Date
Sky	12d65f17ff	community[patch]: surrealdb provide functions for MMR (Maximal Marginal Relevance) (#21185) ... This PR contains 4 added functions: - max_marginal_relevance_search_by_vector - amax_marginal_relevance_search_by_vector - max_marginal_relevance_search - amax_marginal_relevance_search I'm no langchain expert, but tried do inspect other vectorstore sources like chroma, to build these functions for SurrealDB. If someone has some changes for me, please let me know. Otherwise I would be happy, if these changes are added to the repository, so that I can use the orignal repo and not my local monkey patched version. --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	4 months ago
Bagatur	50186da0a1	infra: rm unused # noqa violations (#22049) ... Updating #21137	4 months ago
Mohammad Mohtashim	16617dd239	community[patch]: AzureSearchVectorStoreRetriever Fixed to account for search_kwargs (#21572) ... - **Description:** Fixed `AzureSearchVectorStoreRetriever` to account for search_kwargs. More explanation is in the mentioned issue. - **Issue:** #21492 --------- Co-authored-by: MAC <mac@MACs-MacBook-Pro.local> Co-authored-by: Massimiliano Pronesti <massimiliano.pronesti@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	4 months ago
CaroFG	6b98140b38	community[patch]: update for compatibility with Meilisearch v1.8 (#21979) ... Thank you for contributing to LangChain! - [x] **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" - [x] **PR message**: ***Delete this entire checklist*** and replace with - **Description:** Updates Meilisearch vectorstore for compatibility with v1.8. Adds [”showRankingScore”: true”](https://www.meilisearch.com/docs/reference/api/search#ranking-score) in the search parameters and replaces `_semanticScore` field with ` _rankingScore` - [ ] **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. - [x] **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, ccurme, vbarda, hwchase17.	4 months ago
Oleksii Pokotylo	98c0b093bb	community[patch]: Extend AzureSearch with `maximal_marginal_relevance`, `from_embeddings` (#21065) ... **Description:** - Extend AzureSearch with `maximal_marginal_relevance` (for vector and hybrid search) - Add construction `from_embeddings` - if the user has already embedded the texts - Add `add_embeddings` - Refactor common parts (`_simple_search`, `_results_to_documents`, `_reorder_results_with_maximal_marginal_relevance`) - Add `vector_search_dimensions` as a parameter to the constructor to avoid extra calls to `embed_query` (most of the time the user applies the same model and knows the dimension) **Issue:** none **Dependencies:** none - [x] **Add tests and docs**: The docstrings have been added to the new functions, and unified for the existing ones. The example notebook is great in illustrating the main usage of AzureSearch, adding the new methods would only dilute the main content. - [x] **Lint and test** --------- Co-authored-by: Oleksii Pokotylo <oleksii.pokotylo@pwc.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	4 months ago
SaschaStoll	709664a079	community[patch]: Performant filter columns option for Hanavector (#21971) ... **Description:** Backwards compatible extension of the initialisation interface of HanaDB to allow the user to specify specific_metadata_columns that are used for metadata storage of selected keys which yields increased filter performance. Any not-mentioned metadata remains in the general metadata column as part of a JSON string. Furthermore switched to executemany for batch inserts into HanaDB. **Issue:** N/A **Dependencies:** no new dependencies added **Twitter handle:** @sapopensource --------- Co-authored-by: Martin Kolb <martin.kolb@sap.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	4 months ago
Eugene Yurtsev	36813d2f00	community[patch]: Fix remaining __inits__ in community (#22037) ... Fixes the __init__ files in community to use __all__ which is statically defined.	4 months ago
Bagatur	72d4a8eeed	community[patch]: AzureSearch dont overwrite default async (#21989)	4 months ago
Jesse S	fc79b372cb	community[minor]: add aerospike vectorstore integration (#21735) ... Please let me know if you see any possible areas of improvement. I would very much appreciate your constructive criticism if time allows. **Description:** - Added a aerospike vector store integration that utilizes [Aerospike-Vector-Search](https://aerospike.com/products/vector-database-search-llm/) add-on. - Added both unit tests and integration tests - Added a docker compose file for spinning up a test environment - Added a notebook **Dependencies:** any dependencies required for this change - aerospike-vector-search **Twitter handle:** - No twitter, you can use my GitHub handle or LinkedIn if you'd like Thanks! --------- Co-authored-by: Jesse Schumacher <jschumacher@aerospike.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	4 months ago
缨缨	bd39b2ccdf	community: enable SupabaseVectorStore to support extended table fields (#21762) ... Thank you for contributing to LangChain! - [x] **PR title**: "community: enable SupabaseVectorStore to support extended table fields" - [x] **PR message**: - Added extension fields to the function _add_vectors so that users can add other custom fields when insert a record into the database. eg:  --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	4 months ago
Tomaz Bratanic	d85e46321a	community[patch]: Better error message for neo4j vector when text is null (#21861)	4 months ago
Sen Lin	eb7f07ae36	community[patch]: fix typo in ValueError message in load_local function (#21818) ... **Description:** Corrected an error in the `allow_dangerous_deserialization` message within the `load_local` functions	4 months ago
Massimiliano Pronesti	0c0db7c5db	feat(community): support semantic hybrid score threshold in Azure AI Search (#21527) ... Support semantic hybrid search with a score threshold -- similar to what we do for similarity search and for hybrid search (#20907).	4 months ago
Anush	edd68e4ad4	qdrant: init package (#21146) ... ## Description This PR introduces the new `langchain-qdrant` partner package, intending to deprecate the community package. ## Changes - Moved the Qdrant vector store implementation `/libs/partners/qdrant` with integration tests. - The conditional imports of the client library are now regular with minor implementation improvements. - Added a deprecation warning to `langchain_community.vectorstores.qdrant.Qdrant`. - Replaced references/imports from `langchain_community` with either `langchain_core` or by moving the definitions to the `langchain_qdrant` package itself. - Updated the Qdrant vector store documentation to reflect the changes. ## Testing - `QDRANT_URL` and [`QDRANT_API_KEY`](583e36bf6b) env values need to be set to [run integration tests](d608c93d1f) in the [cloud](https://cloud.qdrant.tech). - If a Qdrant instance is running at `http://localhost:6333`, the integration tests will use it too. - By default, tests use an [`in-memory`](https://github.com/qdrant/qdrant-client?tab=readme-ov-file#local-mode) instance(Not comprehensive). --------- Co-authored-by: Erick Friis <erick@langchain.dev> Co-authored-by: Erick Friis <erickfriis@gmail.com>	4 months ago
Christophe Bornet	66a4da8ad0	community[patch]: Improve Cassandra VectorStore docsctrings (#21620)	4 months ago
Leonid Ganeline	500569da48	community[patch]: `vectorstores` import update (#21169) ... Issue: we have several helper functions to import third-party libraries like lancedb.import_lancedb in [community.vectorstores](https://api.python.langchain.com/en/latest/vectorstores/langchain_community.vectorstores.lancedb.import_lancedb.html#langchain_community.vectorstores.lancedb.import_lancedb). And we have core.utils.utils.guard_import that works exactly for this purpose. The import_<package> functions work inconsistently and rather be private functions. Change: replaced these functions with the guard_import function. Related to #21133	4 months ago
Yash	cb31c3611f	Ndb enterprise (#21233) ... Description: Adds NeuralDBClientVectorStore to the langchain, which is our enterprise client. --------- Co-authored-by: kartikTAI <129414343+kartikTAI@users.noreply.github.com> Co-authored-by: Kartik Sarangmath <kartik@thirdai.com>	4 months ago
Andreas Motl	17e42bbd18	community[patch]: pgvector: Slight refactoring to make code a bit more reusable (#16243) ... - **Description:** Improve [pgvector vector store adapter](https://github.com/langchain-ai/langchain/blob/v0.1.1/libs/community/langchain_community/vectorstores/pgvector.py) to make it reusable by adapters deriving from that. - **Issue:** NA - **Dependencies:** NA - **References:** https://github.com/crate-workbench/langchain/pull/1 - **Addressed to:** @eyurtsev, @cbornet Hi from the CrateDB team, first of all, thanks a stack for conceiving and maintaining LangChain. We are currently [preparing a patch](https://github.com/crate-workbench/langchain/pull/1) for adding [CrateDB](https://github.com/crate/crate) to the list of community adapters. Because CrateDB aims to be compatible with PostgreSQL to some degree, the vector store subsystem in LangChain derives functionality from the corresponding implementation for pgvector. Therefore, in order to make the implementation more reusable, we needed to rename the private methods `__from` and `__query_collection` to the less private counterparts `_from` and `_query_collection`, so they can be overwritten, in order to unlock other adapters deriving from [pgvector](https://github.com/langchain-ai/langchain/blob/v0.1.1/libs/community/langchain_community/vectorstores/pgvector.py). With kind regards, Andreas.	4 months ago
Shailendra Mishra	aa966b6161	Replaced bind variable in SQL with formatted string for compatibility with sql syntax. (#21439) ... 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.	4 months ago
Eugene Yurtsev	6a1d61dbf1	community[patch]: Fix in memory vectorstore to take into account ids when adding docs (#21384) ... Should respect `ids` if passed	4 months ago
Jan Soubusta	d9a61c0fa9	fix: respect table_name argument when calling from_texts (#21252) ... valid for from_documents() as well fixes #21251	4 months ago
Mark Cusack	060987d755	community[minor]: Add indexing via locality sensitive hashing to the Yellowbrick vector store (#20856) ... - **Description:** Add LSH-based indexing to the Yellowbrick vector store module - **Twitter handle:** @markcusack --------- Co-authored-by: markcusack <markcusack@markcusacksmac.lan> Co-authored-by: markcusack <markcusack@Mark-Cusack-sMac.local> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	4 months ago
Christophe Bornet	484a009012	community[minor]: Relax constraints on Cassandra VectorStore constructors (#21209) ... If Session and/or keyspace are not provided, they are resolved from cassio's context. So they are not required. This change is fully backward compatible.	4 months ago
Rohan Aggarwal	8021d2a2ab	community[minor]: Oraclevs integration (#21123) ... Thank you for contributing to LangChain! - Oracle AI Vector Search Oracle AI Vector Search is designed for Artificial Intelligence (AI) workloads that allows you to query data based on semantics, rather than keywords. One of the biggest benefit of Oracle AI Vector Search is that semantic search on unstructured data can be combined with relational search on business data in one single system. This is not only powerful but also significantly more effective because you don't need to add a specialized vector database, eliminating the pain of data fragmentation between multiple systems. - Oracle AI Vector Search is designed for Artificial Intelligence (AI) workloads that allows you to query data based on semantics, rather than keywords. One of the biggest benefit of Oracle AI Vector Search is that semantic search on unstructured data can be combined with relational search on business data in one single system. This is not only powerful but also significantly more effective because you don't need to add a specialized vector database, eliminating the pain of data fragmentation between multiple systems. This Pull Requests Adds the following functionalities Oracle AI Vector Search : Vector Store Oracle AI Vector Search : Document Loader Oracle AI Vector Search : Document Splitter Oracle AI Vector Search : Summary Oracle AI Vector Search : Oracle Embeddings - We have added unit tests and have our own local unit test suite which verifies all the code is correct. We have made sure to add guides for each of the components and one end to end guide that shows how the entire thing runs. - We have made sure that make format and make lint run clean. 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. --------- Co-authored-by: skmishraoracle <shailendra.mishra@oracle.com> Co-authored-by: hroyofc <harichandan.roy@oracle.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	4 months ago
ccurme	6da3d92b42	(all): update removal in deprecation warnings from 0.2 to 0.3 (#21265) ... We are pushing out the removal of these to 0.3. `find . -type f -name "*.py" -exec sed -i '' 's/removal="0\.2/removal="0.3/g' {} +`	4 months ago
Raghav Dixit	7d451d0041	community[patch]: Update lancedb.py (#21192) ... very minor update in LanceDB integration, 'metric' argument was missing.	4 months ago
Ismail Hossain Polas	1fdf63fa6c	community[patch]: update package name to bagelML (#19948) ... **Description** This pull request updates the Bagel Network package name from "betabageldb" to "bagelML" to align with the latest changes made by the Bagel Network team. The following modifications have been made: - Updated all references to the old package name ("betabageldb") with the new package name ("bagelML") throughout the codebase. - Modified the documentation, and any relevant scripts to reflect the package name change. - Tested the changes to ensure that the functionality remains intact and no breaking changes were introduced. By merging this pull request, our project will stay up to date with the latest Bagel Network package naming convention, ensuring compatibility and smooth integration with their updated library. Please review the changes and provide any feedback or suggestions. Thank you!	4 months ago
tianzedavid	5a8909440b	docs: remove repetitive words (#21058) ... remove repetitive words Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	4 months ago
MacanPN	0f7f448603	community[patch]: add delete() method to AzureSearch vector store (#21127) ... **Issue:** Currently `AzureSearch` vector store does not implement `delete` method. This PR implements it. This also makes it compatible with LangChain indexer. **Dependencies:** None **Twitter handle:** @martintriska1 --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	4 months ago
Charlie Marsh	8f38b7a725	multiple: Remove unnecessary Ruff suppression comments (#21050) ... ## Summary I ran `ruff check --extend-select RUF100 -n` to identify `# noqa` comments that weren't having any effect in Ruff, and then `ruff check --extend-select RUF100 -n --fix` on select files to remove all of the unnecessary `# noqa: F401` violations. It's possible that these were needed at some point in the past, but they're not necessary in Ruff v0.1.15 (used by LangChain) or in the latest release. Co-authored-by: Erick Friis <erick@langchain.dev>	4 months ago
高远	a7a4630bf4	community[patch]: Modify the text field type and add new exception handling (#20116) ... Co-authored-by: gaoyuan <gaoyuan.20001218@bytedance.com>	4 months ago
Leonid Ganeline	85094cbb3a	docs: community docstring updates (#21040) ... Added missed docstrings. Updated docstrings to consistent format.	4 months ago
Cahid Arda Öz	cc6191cb90	community[minor]: Add support for Upstash Vector (#20824) ... ## Description Adding `UpstashVectorStore` to utilize [Upstash Vector](https://upstash.com/docs/vector/overall/getstarted)! #17012 was opened to add Upstash Vector to langchain but was closed to wait for filtering. Now filtering is added to Upstash vector and we open a new PR. Additionally, [embedding feature](https://upstash.com/docs/vector/features/embeddingmodels) was added and we add this to our vectorstore aswell. ## Dependencies [upstash-vector](https://pypi.org/project/upstash-vector/) should be installed to use `UpstashVectorStore`. Didn't update dependencies because of [this comment in the previous PR](https://github.com/langchain-ai/langchain/pull/17012#pullrequestreview-1876522450). ## Tests Tests are added and they pass. Tests are naturally network bound since Upstash Vector is offered through an API. There was [a discussion in the previous PR about mocking the unittests](https://github.com/langchain-ai/langchain/pull/17012#pullrequestreview-1891820567). We didn't make changes to this end yet. We can update the tests if you can explain how the tests should be mocked. --------- Co-authored-by: ytkimirti <yusuftaha9@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	4 months ago
Massimiliano Pronesti	ce89b34fc0	community[patch]: support hybrid search with threshold in Azure AI Search Retriever (#20907) ... Support hybrid search with a score threshold -- similar to what we do for similarity search.	4 months ago
Leonid Ganeline	dc7c06bc07	community[minor]: import fix (#20995) ... Issue: When the third-party package is not installed, whenever we need to `pip install <package>` the ImportError is raised. But sometimes, the `ValueError` or `ModuleNotFoundError` is raised. It is bad for consistency. Change: replaced the `ValueError` or `ModuleNotFoundError` with `ImportError` when we raise an error with the `pip install <package>` message. Note: Ideally, we replace all `try: import... except... raise ... `with helper functions like `import_aim` or just use the existing [langchain_core.utils.utils.guard_import](https://api.python.langchain.com/en/latest/utils/langchain_core.utils.utils.guard_import.html#langchain_core.utils.utils.guard_import) But it would be much bigger refactoring. @baskaryan Please, advice on this.	4 months ago
Naveen Tatikonda	8bbdb4f6a0	community[patch]: Add OpenSearch as semantic cache (#20254) ... ### Description Use OpenSearch vector store as Semantic Cache. ### Twitter Handle **@OpenSearchProj** --------- Signed-off-by: Naveen Tatikonda <navtat@amazon.com> Co-authored-by: Harish Tatikonda <harishtatikonda@Harishs-MacBook-Air.local> Co-authored-by: EC2 Default User <ec2-user@ip-172-31-31-155.ec2.internal> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
Mayank Solanki	8c085fc697	community[patch]: Added a function `from_existing_collection` in `Qdrant` vector database. (#20779) ... Issue: #20514 The current implementation of `construct_instance` expects a `texts: List[str]` that will call the embedding function. This might not be needed when we already have a client with collection and `path, you don't want to add any text. This PR adds a class method that returns a qdrant instance with an existing client. Here everytime cb6e5e56c2/libs/community/langchain_community/vectorstores/qdrant.py (L1592) `construct_instance` is called, this line sends some text for embedding generation. --------- Co-authored-by: Anush <anushshetty90@gmail.com>	5 months ago
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>	5 months ago
Andres Algaba	05ae8ca7d4	community[patch]: deprecate persist method in Chroma (#20855) ... Thank you for contributing to LangChain! - [x] **PR title** - [x] **PR message**: - **Description:** Deprecate persist method in Chroma no longer exists in Chroma 0.4.x - **Issue:** #20851 - **Dependencies:** None - **Twitter handle:** AndresAlgaba1 - [x] **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. - [x] **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/ --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	5 months ago
Tomaz Bratanic	520972fd0f	community[patch]: Support passing graph object to Neo4j integrations (#20876) ... For driver connection reusage, we introduce passing the graph object to neo4j integrations	5 months ago
Bagatur	5b83130855	core[minor], langchain[patch], community[patch]: mv StructuredQuery (#20849) ... mv StructuredQuery to core	5 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	5 months ago
volodymyr-memsql	493afe4d8d	community[patch]: add hybrid search to singlestoredb vectorstore (#20793) ... Implemented the ability to enable full-text search within the SingleStore vector store, offering users a versatile range of search strategies. This enhancement allows users to seamlessly combine full-text search with vector search, enabling the following search strategies: * Search solely by vector similarity. * Conduct searches exclusively based on text similarity, utilizing Lucene internally. * Filter search results by text similarity score, with the option to specify a threshold, followed by a search based on vector similarity. * Filter results by vector similarity score before conducting a search based on text similarity. * Perform searches using a weighted sum of vector and text similarity scores. Additionally, integration tests have been added to comprehensively cover all scenarios. Updated notebook with examples. CC: @baskaryan, @hwchase17 --------- Co-authored-by: Volodymyr Tkachuk <vtkachuk-ua@singlestore.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
Martin Kolb	0186e4e633	community[patch]: Advanced filtering for HANA Cloud Vector Engine (#20821) ... - **Description:** This PR adds support for advanced filtering to the integration of HANA Vector Engine. The newly supported filtering operators are: $eq, $ne, $gt, $gte, $lt, $lte, $between, $in, $nin, $like, $and, $or - **Issue:** N/A - **Dependencies:** no new dependencies added Added integration tests to: `libs/community/tests/integration_tests/vectorstores/test_hanavector.py` Description of the new capabilities in notebook: `docs/docs/integrations/vectorstores/hanavector.ipynb`	5 months ago
Massimiliano Pronesti	8d1167b32f	community[patch]: add support for similarity_score_threshold search in… (#20852) ... See https://github.com/langchain-ai/langchain/issues/20600#issuecomment-2075569338 for details. @chrislrobert	5 months ago
Mark Needham	ce23f8293a	Community patch clickhouse make it possible to not specify index (#20460) ... Vector indexes in ClickHouse are experimental at the moment and can sometimes break/change behaviour. So this PR makes it possible to say that you don't want to specify an index type. Any queries against the embedding column will be brute force/linear scan, but that gives reasonable performance for small-medium dataset sizes. --------- Co-authored-by: Erick Friis <erick@langchain.dev> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	5 months ago
Christophe Bornet	c909ae0152	community[minor]: Add async methods to CassandraVectorStore (#20602) ... Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	5 months ago
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