vectorstores

Vector store stores embedded data and performs vector search.

One of the most common ways to store and search over unstructured data is to embed it and store the resulting embedding vectors, and then query the store and retrieve the data that are ‘most similar’ to the embedded query.

Class hierarchy:

VectorStore --> <name>  # Examples: Annoy, FAISS, Milvus

BaseRetriever --> VectorStoreRetriever --> <name>Retriever  # Example: VespaRetriever

Main helpers:

Embeddings, Document

Classes

vectorstores.aerospike.Aerospike(client, ...)	Aerospike vector store.
vectorstores.alibabacloud_opensearch.AlibabaCloudOpenSearch(...)	Alibaba Cloud OpenSearch vector store.
vectorstores.alibabacloud_opensearch.AlibabaCloudOpenSearchSettings(...)	Alibaba Cloud Opensearch` client configuration.
vectorstores.analyticdb.AnalyticDB(...[, ...])	AnalyticDB (distributed PostgreSQL) vector store.
vectorstores.annoy.Annoy(embedding_function, ...)	Annoy vector store.
vectorstores.apache_doris.ApacheDoris(...[, ...])	Apache Doris vector store.
vectorstores.apache_doris.ApacheDorisSettings	Apache Doris client configuration.
vectorstores.aperturedb.ApertureDB(embeddings)	Create a vectorstore backed by ApertureDB
vectorstores.atlas.AtlasDB(name[, ...])	Atlas vector store.
vectorstores.awadb.AwaDB([table_name, ...])	AwaDB vector store.
vectorstores.azure_cosmos_db.AzureCosmosDBVectorSearch(...)	Azure Cosmos DB for MongoDB vCore vector store.
vectorstores.azure_cosmos_db.CosmosDBSimilarityType(value)	Cosmos DB Similarity Type as enumerator.
vectorstores.azure_cosmos_db.CosmosDBVectorSearchType(value)	Cosmos DB Vector Search Type as enumerator.
vectorstores.azure_cosmos_db_no_sql.AzureCosmosDBNoSqlVectorSearch(*, ...)	Azure Cosmos DB for NoSQL vector store.
vectorstores.azure_cosmos_db_no_sql.Condition	Create a new model by parsing and validating input data from keyword arguments.
vectorstores.azure_cosmos_db_no_sql.CosmosDBQueryType(value)	CosmosDB Query Type
vectorstores.azure_cosmos_db_no_sql.PreFilter	Create a new model by parsing and validating input data from keyword arguments.
vectorstores.azuresearch.AzureSearch(...[, ...])	Azure Cognitive Search vector store.
vectorstores.azuresearch.AzureSearchVectorStoreRetriever	Retriever that uses Azure Cognitive Search.
vectorstores.bagel.Bagel([cluster_name, ...])	Bagel.net Inference platform.
vectorstores.baiducloud_vector_search.BESVectorStore(...)	Baidu Elasticsearch vector store.
vectorstores.baiduvectordb.BaiduVectorDB(...)	Baidu VectorDB as a vector store.
vectorstores.baiduvectordb.ConnectionParams(...)	Baidu VectorDB Connection params.
vectorstores.baiduvectordb.TableParams(dimension)	Baidu VectorDB table params.
vectorstores.cassandra.Cassandra(embedding)	Apache Cassandra(R) for vector-store workloads.
vectorstores.clarifai.Clarifai([user_id, ...])	Clarifai AI vector store.
vectorstores.clickhouse.Clickhouse(embedding)	ClickHouse vector store integration.
vectorstores.clickhouse.ClickhouseSettings	ClickHouse client configuration.
vectorstores.dashvector.DashVector(...)	DashVector vector store.
vectorstores.deeplake.DeepLake([...])	Activeloop Deep Lake vector store.
vectorstores.dingo.Dingo(embedding, text_key, *)	Dingo vector store.
vectorstores.docarray.base.DocArrayIndex(...)	Base class for DocArray based vector stores.
vectorstores.docarray.hnsw.DocArrayHnswSearch(...)	HnswLib storage using DocArray package.
vectorstores.docarray.in_memory.DocArrayInMemorySearch(...)	In-memory DocArray storage for exact search.
vectorstores.documentdb.DocumentDBSimilarityType(value)	DocumentDB Similarity Type as enumerator.
vectorstores.documentdb.DocumentDBVectorSearch(...)	Amazon DocumentDB (with MongoDB compatibility) vector store.
vectorstores.duckdb.DuckDB(*[, connection, ...])	DuckDB vector store.
vectorstores.ecloud_vector_search.EcloudESVectorStore(...)	ecloud Elasticsearch vector store.
vectorstores.elasticsearch.BaseRetrievalStrategy()	Base class for Elasticsearch retrieval strategies.
vectorstores.epsilla.Epsilla(client, embeddings)	Wrapper around Epsilla vector database.
vectorstores.faiss.FAISS(embedding_function, ...)	FAISS vector store integration.
vectorstores.falkordb_vector.FalkorDBVector(...)	FalkorDB vector index.
vectorstores.falkordb_vector.IndexType(value)	Enumerator of the index types.
vectorstores.falkordb_vector.SearchType(value)	Enumerator for different search strategies in FalkorDB VectorStore.
vectorstores.hanavector.HanaDB(connection, ...)	SAP HANA Cloud Vector Engine
vectorstores.hippo.Hippo(embedding_function)	Hippo vector store.
vectorstores.hologres.Hologres(...[, ndims, ...])	Hologres API vector store.
vectorstores.infinispanvs.Infinispan([...])	Helper class for Infinispan REST interface.
vectorstores.infinispanvs.InfinispanVS([...])	Infinispan VectorStore interface.
vectorstores.jaguar.Jaguar(pod, store, ...)	Jaguar API vector store.
vectorstores.kdbai.KDBAI(table, embedding[, ...])	KDB.AI vector store.
vectorstores.kinetica.Dimension(value[, ...])	Some default dimensions for known embeddings.
vectorstores.kinetica.DistanceStrategy(value)	Enumerator of the Distance strategies.
vectorstores.kinetica.Kinetica(config, ...)	Kinetica vector store.
vectorstores.kinetica.KineticaSettings	Kinetica client configuration.
vectorstores.lancedb.LanceDB([connection, ...])	LanceDB vector store.
vectorstores.lantern.BaseEmbeddingStore()	Base class for the Lantern embedding store.
vectorstores.lantern.DistanceStrategy(value)	Enumerator of the Distance strategies.
vectorstores.lantern.Lantern(...[, ...])	Postgres with the lantern extension as a vector store.
vectorstores.lantern.QueryResult()	Result from a query.
vectorstores.llm_rails.LLMRails([...])	Implementation of Vector Store using LLMRails.
vectorstores.llm_rails.LLMRailsRetriever	Retriever for LLMRails.
vectorstores.manticore_search.ManticoreSearch(...)	ManticoreSearch Engine vector store.
vectorstores.manticore_search.ManticoreSearchSettings	Create a new model by parsing and validating input data from keyword arguments.
vectorstores.marqo.Marqo(client, index_name)	Marqo vector store.
vectorstores.meilisearch.Meilisearch(embedding)	Meilisearch vector store.
vectorstores.momento_vector_index.MomentoVectorIndex(...)	Momento Vector Index (MVI) vector store.
vectorstores.myscale.MyScale(embedding[, config])	MyScale vector store.
vectorstores.myscale.MyScaleSettings	MyScale client configuration.
vectorstores.myscale.MyScaleWithoutJSON(...)	MyScale vector store without metadata column
vectorstores.nucliadb.NucliaDB(...[, ...])	NucliaDB vector store.
vectorstores.opensearch_vector_search.OpenSearchVectorSearch(...)	Amazon OpenSearch Vector Engine vector store.
vectorstores.oraclevs.OracleVS(client, ...)	OracleVS vector store.
vectorstores.pathway.PathwayVectorClient([...])	VectorStore connecting to Pathway Vector Store.
vectorstores.pgembedding.BaseModel(**kwargs)	Base model for all SQL stores.
vectorstores.pgembedding.CollectionStore(...)	Collection store.
vectorstores.pgembedding.EmbeddingStore(**kwargs)	Embedding store.
vectorstores.pgembedding.PGEmbedding(...[, ...])	Postgres with the pg_embedding extension as a vector store.
vectorstores.pgembedding.QueryResult()	Result from a query.
vectorstores.pgvecto_rs.PGVecto_rs(...[, ...])	VectorStore backed by pgvecto_rs.
vectorstores.pgvector.BaseModel(**kwargs)	Base model for the SQL stores.
vectorstores.pgvector.DistanceStrategy(value)	Enumerator of the Distance strategies.
vectorstores.qdrant.QdrantException	Qdrant related exceptions.
vectorstores.redis.base.RedisVectorStoreRetriever	Retriever for Redis VectorStore.
vectorstores.redis.filters.RedisFilter()	Collection of RedisFilterFields.
vectorstores.redis.filters.RedisFilterExpression([...])	Logical expression of RedisFilterFields.
vectorstores.redis.filters.RedisFilterField(field)	Base class for RedisFilterFields.
vectorstores.redis.filters.RedisFilterOperator(value)	RedisFilterOperator enumerator is used to create RedisFilterExpressions.
vectorstores.redis.filters.RedisNum(field)	RedisFilterField representing a numeric field in a Redis index.
vectorstores.redis.filters.RedisTag(field)	RedisFilterField representing a tag in a Redis index.
vectorstores.redis.filters.RedisText(field)	RedisFilterField representing a text field in a Redis index.
vectorstores.redis.schema.FlatVectorField	Schema for flat vector fields in Redis.
vectorstores.redis.schema.HNSWVectorField	Schema for HNSW vector fields in Redis.
vectorstores.redis.schema.NumericFieldSchema	Schema for numeric fields in Redis.
vectorstores.redis.schema.RedisDistanceMetric(value)	Distance metrics for Redis vector fields.
vectorstores.redis.schema.RedisField	Base class for Redis fields.
vectorstores.redis.schema.RedisModel	Schema for Redis index.
vectorstores.redis.schema.RedisVectorField	Base class for Redis vector fields.
vectorstores.redis.schema.TagFieldSchema	Schema for tag fields in Redis.
vectorstores.redis.schema.TextFieldSchema	Schema for text fields in Redis.
vectorstores.relyt.Relyt(connection_string, ...)	Relyt (distributed PostgreSQL) vector store.
vectorstores.rocksetdb.Rockset(client, ...)	Rockset vector store.
vectorstores.scann.ScaNN(embedding, index, ...)	ScaNN vector store.
vectorstores.semadb.SemaDB(collection_name, ...)	SemaDB vector store.
vectorstores.singlestoredb.SingleStoreDB(...)	SingleStore DB vector store.
vectorstores.sklearn.BaseSerializer(persist_path)	Base class for serializing data.
vectorstores.sklearn.BsonSerializer(persist_path)	Serialize data in Binary JSON using the bson python package.
vectorstores.sklearn.JsonSerializer(persist_path)	Serialize data in JSON using the json package from python standard library.
vectorstores.sklearn.ParquetSerializer(...)	Serialize data in Apache Parquet format using the pyarrow package.
vectorstores.sklearn.SKLearnVectorStore(...)	Simple in-memory vector store based on the scikit-learn library NearestNeighbors.
vectorstores.sklearn.SKLearnVectorStoreException	Exception raised by SKLearnVectorStore.
vectorstores.sqlitevec.SQLiteVec(table, ...)	SQLite with Vec extension as a vector database.
vectorstores.sqlitevss.SQLiteVSS(table, ...)	SQLite with VSS extension as a vector database.
vectorstores.starrocks.StarRocks(embedding)	StarRocks vector store.
vectorstores.starrocks.StarRocksSettings	StarRocks client configuration.
vectorstores.supabase.SupabaseVectorStore(...)	Supabase Postgres vector store.
vectorstores.surrealdb.SurrealDBStore(...)	SurrealDB as Vector Store.
vectorstores.tablestore.TablestoreVectorStore(...)	Tablestore vector store.
vectorstores.tair.Tair(embedding_function, ...)	Tair vector store.
vectorstores.tencentvectordb.ConnectionParams(...)	Tencent vector DB Connection params.
vectorstores.tencentvectordb.IndexParams(...)	Tencent vector DB Index params.
vectorstores.tencentvectordb.MetaField	MetaData Field for Tencent vector DB.
vectorstores.tencentvectordb.TencentVectorDB(...)	Tencent VectorDB as a vector store.
vectorstores.thirdai_neuraldb.NeuralDBClientVectorStore(db)	Vectorstore that uses ThirdAI's NeuralDB Enterprise Python Client for NeuralDBs.
vectorstores.thirdai_neuraldb.NeuralDBVectorStore(db)	Vectorstore that uses ThirdAI's NeuralDB.
vectorstores.tidb_vector.TiDBVectorStore(...)	TiDB Vector Store.
vectorstores.tigris.Tigris(client, ...)	Tigris vector store.
vectorstores.tiledb.TileDB(embedding, ...[, ...])	TileDB vector store.
vectorstores.timescalevector.TimescaleVector(...)	Timescale Postgres vector store
vectorstores.typesense.Typesense(...[, ...])	Typesense vector store.
vectorstores.upstash.UpstashVectorStore([...])	Upstash Vector vector store
vectorstores.usearch.USearch(embedding, ...)	USearch vector store.
vectorstores.utils.DistanceStrategy(value[, ...])	Enumerator of the Distance strategies for calculating distances between vectors.
vectorstores.vald.Vald(embedding[, host, ...])	Vald vector database.
vectorstores.vdms.VDMS(client, *[, ...])	Intel Lab's VDMS for vector-store workloads.
vectorstores.vearch.Vearch(embedding_function)	Initialize vearch vector store flag 1 for cluster,0 for standalone
vectorstores.vectara.MMRConfig([is_enabled, ...])	Configuration for Maximal Marginal Relevance (MMR) search.
vectorstores.vectara.RerankConfig([...])	Configuration for Reranker.
vectorstores.vectara.SummaryConfig([...])	Configuration for summary generation.
vectorstores.vectara.Vectara([...])	Vectara API vector store.
vectorstores.vectara.VectaraQueryConfig([k, ...])	Configuration for Vectara query.
vectorstores.vectara.VectaraRAG(vectara, config)	Vectara RAG runnable.
vectorstores.vectara.VectaraRetriever	Vectara Retriever class.
vectorstores.vespa.VespaStore(app[, ...])	Vespa vector store.
vectorstores.vikingdb.VikingDB(...[, ...])	vikingdb as a vector store
vectorstores.vikingdb.VikingDBConfig([host, ...])	vikingdb connection config
vectorstores.vlite.VLite(embedding_function)	VLite is a simple and fast vector database for semantic search.
vectorstores.weaviate.Weaviate(client, ...)	Weaviate vector store.
vectorstores.xata.XataVectorStore(api_key, ...)	Xata vector store.
vectorstores.yellowbrick.Yellowbrick(...[, ...])	Yellowbrick as a vector database.
vectorstores.zep.CollectionConfig(name, ...)	Configuration for a Zep Collection.
vectorstores.zep.ZepVectorStore(...[, ...])	Zep vector store.
vectorstores.zep_cloud.ZepCloudVectorStore(...)	Zep vector store.
vectorstores.zilliz.Zilliz(embedding_function)	Zilliz vector store.

Functions

vectorstores.alibabacloud_opensearch.create_metadata(fields)	Create metadata from fields.
vectorstores.annoy.dependable_annoy_import()	Import annoy if available, otherwise raise error.
vectorstores.clickhouse.has_mul_sub_str(s, *args)	Check if a string contains multiple substrings.
vectorstores.faiss.dependable_faiss_import([...])	Import faiss if available, otherwise raise error.
vectorstores.falkordb_vector.construct_metadata_filter([...])	Construct a metadata filter by directly injecting the filter values into the query.
vectorstores.falkordb_vector.dict_to_yaml_str(...)	Convert a dictionary to a YAML-like string without using external libraries.
vectorstores.falkordb_vector.generate_random_string(length)
vectorstores.falkordb_vector.process_index_data(data)	Processes a nested list of entity data to extract information about labels, entity types, properties, index types, and index details (if applicable).
vectorstores.lancedb.import_lancedb()	Import lancedb package.
vectorstores.lancedb.to_lance_filter(filter)	Converts a dict filter to a LanceDB filter string.
vectorstores.lantern.get_embedding_store(...)	Get the embedding store class.
vectorstores.myscale.has_mul_sub_str(s, *args)	Check if a string contains multiple substrings.
vectorstores.oraclevs.create_index(client, ...)	Create an index on the vector store.
vectorstores.oraclevs.drop_index_if_exists(...)	Drop an index if it exists.
vectorstores.oraclevs.drop_table_purge(...)	Drop a table and purge it from the database.
vectorstores.qdrant.sync_call_fallback(method)	Decorator to call the synchronous method of the class if the async method is not implemented.
vectorstores.redis.base.check_index_exists(...)	Check if Redis index exists.
vectorstores.redis.filters.check_operator_misuse(func)	Decorator to check for misuse of equality operators.
vectorstores.redis.schema.read_schema(...)	Read in the index schema from a dict or yaml file.
vectorstores.scann.dependable_scann_import()	Import scann if available, otherwise raise error.
vectorstores.scann.normalize(x)	Normalize vectors to unit length.
vectorstores.sqlitevec.serialize_f32(vector)	Serializes a list of floats into a compact "raw bytes" format
vectorstores.starrocks.debug_output(s)	Print a debug message if DEBUG is True.
vectorstores.starrocks.get_named_result(...)	Get a named result from a query.
vectorstores.starrocks.has_mul_sub_str(s, *args)	Check if a string has multiple substrings.
vectorstores.tencentvectordb.translate_filter(...)	Translate LangChain filter to Tencent VectorDB filter.
vectorstores.tiledb.dependable_tiledb_import()	Import tiledb-vector-search if available, otherwise raise error.
vectorstores.tiledb.get_documents_array_uri(uri)	Get the URI of the documents array.
vectorstores.tiledb.get_documents_array_uri_from_group(group)	Get the URI of the documents array from group.
vectorstores.tiledb.get_vector_index_uri(uri)	Get the URI of the vector index.
vectorstores.tiledb.get_vector_index_uri_from_group(group)	Get the URI of the vector index.
vectorstores.usearch.dependable_usearch_import()	Import usearch if available, otherwise raise error.
vectorstores.utils.filter_complex_metadata(...)	Filter out metadata types that are not supported for a vector store.
vectorstores.utils.maximal_marginal_relevance(...)	Calculate maximal marginal relevance.
vectorstores.vdms.VDMS_Client([host, port])	VDMS client for the VDMS server.
vectorstores.vdms.embedding2bytes(embedding)	Convert embedding to bytes.

Deprecated classes

vectorstores.astradb.AstraDB(*, embedding, ...)
vectorstores.bigquery_vector_search.BigQueryVectorSearch(...)
vectorstores.chroma.Chroma([...])
vectorstores.couchbase.CouchbaseVectorStore(...)
vectorstores.databricks_vector_search.DatabricksVectorSearch(...)
vectorstores.elastic_vector_search.ElasticKnnSearch(...)
vectorstores.elastic_vector_search.ElasticVectorSearch(...)
vectorstores.elasticsearch.ApproxRetrievalStrategy([...])
vectorstores.elasticsearch.ElasticsearchStore(...)
vectorstores.elasticsearch.ExactRetrievalStrategy(...)
vectorstores.elasticsearch.SparseRetrievalStrategy([...])
vectorstores.matching_engine.MatchingEngine(...)
vectorstores.milvus.Milvus(embedding_function)
vectorstores.mongodb_atlas.MongoDBAtlasVectorSearch(...)
vectorstores.neo4j_vector.IndexType(value[, ...])
vectorstores.neo4j_vector.Neo4jVector(...[, ...])
vectorstores.neo4j_vector.SearchType(value)
vectorstores.pgvector.PGVector(...[, ...])
vectorstores.pinecone.Pinecone(index, ...[, ...])
vectorstores.qdrant.Qdrant(client, ...[, ...])
vectorstores.redis.base.Redis(redis_url, ...)

Deprecated functions

vectorstores.neo4j_vector.check_if_not_null(...)
vectorstores.neo4j_vector.collect_params(...)
vectorstores.neo4j_vector.combine_queries(...)
vectorstores.neo4j_vector.construct_metadata_filter(filter)
vectorstores.neo4j_vector.dict_to_yaml_str(...)
vectorstores.neo4j_vector.remove_lucene_chars(text)
vectorstores.neo4j_vector.sort_by_index_name(...)