"""**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:** .. code-block:: VectorStore --> # Examples: Annoy, FAISS, Milvus BaseRetriever --> VectorStoreRetriever --> Retriever # Example: VespaRetriever **Main helpers:** .. code-block:: Embeddings, Document """ # noqa: E501 import importlib from typing import Any _module_lookup = { "AlibabaCloudOpenSearch": "langchain_community.vectorstores.alibabacloud_opensearch", # noqa: E501 "AlibabaCloudOpenSearchSettings": "langchain_community.vectorstores.alibabacloud_opensearch", # noqa: E501 "AnalyticDB": "langchain_community.vectorstores.analyticdb", "Annoy": "langchain_community.vectorstores.annoy", "ApacheDoris": "langchain_community.vectorstores.apache_doris", "AstraDB": "langchain_community.vectorstores.astradb", "AtlasDB": "langchain_community.vectorstores.atlas", "AwaDB": "langchain_community.vectorstores.awadb", "AzureCosmosDBVectorSearch": "langchain_community.vectorstores.azure_cosmos_db", "AzureSearch": "langchain_community.vectorstores.azuresearch", "BaiduVectorDB": "langchain_community.vectorstores.baiduvectordb", "BESVectorStore": "langchain_community.vectorstores.baiducloud_vector_search", "Bagel": "langchain_community.vectorstores.bageldb", "BigQueryVectorSearch": "langchain_community.vectorstores.bigquery_vector_search", "Cassandra": "langchain_community.vectorstores.cassandra", "Chroma": "langchain_community.vectorstores.chroma", "Clarifai": "langchain_community.vectorstores.clarifai", "Clickhouse": "langchain_community.vectorstores.clickhouse", "ClickhouseSettings": "langchain_community.vectorstores.clickhouse", "CouchbaseVectorStore": "langchain_community.vectorstores.couchbase", "DashVector": "langchain_community.vectorstores.dashvector", "DatabricksVectorSearch": "langchain_community.vectorstores.databricks_vector_search", # noqa: E501 "DeepLake": "langchain_community.vectorstores.deeplake", "Dingo": "langchain_community.vectorstores.dingo", "DistanceStrategy": "langchain_community.vectorstores.kinetica", "DocArrayHnswSearch": "langchain_community.vectorstores.docarray", "DocArrayInMemorySearch": "langchain_community.vectorstores.docarray", "DocumentDBVectorSearch": "langchain_community.vectorstores.documentdb", "DuckDB": "langchain_community.vectorstores.duckdb", "EcloudESVectorStore": "langchain_community.vectorstores.ecloud_vector_search", "ElasticKnnSearch": "langchain_community.vectorstores.elastic_vector_search", "ElasticVectorSearch": "langchain_community.vectorstores.elastic_vector_search", "ElasticsearchStore": "langchain_community.vectorstores.elasticsearch", "Epsilla": "langchain_community.vectorstores.epsilla", "FAISS": "langchain_community.vectorstores.faiss", "HanaDB": "langchain_community.vectorstores.hanavector", "Hologres": "langchain_community.vectorstores.hologres", "InfinispanVS": "langchain_community.vectorstores.infinispanvs", "InMemoryVectorStore": "langchain_community.vectorstores.inmemory", "KDBAI": "langchain_community.vectorstores.kdbai", "Kinetica": "langchain_community.vectorstores.kinetica", "KineticaSettings": "langchain_community.vectorstores.kinetica", "LLMRails": "langchain_community.vectorstores.llm_rails", "LanceDB": "langchain_community.vectorstores.lancedb", "Lantern": "langchain_community.vectorstores.lantern", "Marqo": "langchain_community.vectorstores.marqo", "MatchingEngine": "langchain_community.vectorstores.matching_engine", "Meilisearch": "langchain_community.vectorstores.meilisearch", "Milvus": "langchain_community.vectorstores.milvus", "MomentoVectorIndex": "langchain_community.vectorstores.momento_vector_index", "MongoDBAtlasVectorSearch": "langchain_community.vectorstores.mongodb_atlas", "MyScale": "langchain_community.vectorstores.myscale", "MyScaleSettings": "langchain_community.vectorstores.myscale", "Neo4jVector": "langchain_community.vectorstores.neo4j_vector", "NeuralDBVectorStore": "langchain_community.vectorstores.thirdai_neuraldb", "OpenSearchVectorSearch": "langchain_community.vectorstores.opensearch_vector_search", # noqa: E501 "PGEmbedding": "langchain_community.vectorstores.pgembedding", "PGVector": "langchain_community.vectorstores.pgvector", "Pinecone": "langchain_community.vectorstores.pinecone", "Qdrant": "langchain_community.vectorstores.qdrant", "Redis": "langchain_community.vectorstores.redis", "Rockset": "langchain_community.vectorstores.rocksetdb", "SKLearnVectorStore": "langchain_community.vectorstores.sklearn", "SQLiteVSS": "langchain_community.vectorstores.sqlitevss", "ScaNN": "langchain_community.vectorstores.scann", "SemaDB": "langchain_community.vectorstores.semadb", "SingleStoreDB": "langchain_community.vectorstores.singlestoredb", "StarRocks": "langchain_community.vectorstores.starrocks", "SupabaseVectorStore": "langchain_community.vectorstores.supabase", "SurrealDBStore": "langchain_community.vectorstores.surrealdb", "Tair": "langchain_community.vectorstores.tair", "TencentVectorDB": "langchain_community.vectorstores.tencentvectordb", "TiDBVectorStore": "langchain_community.vectorstores.tidb_vector", "Tigris": "langchain_community.vectorstores.tigris", "TileDB": "langchain_community.vectorstores.tiledb", "TimescaleVector": "langchain_community.vectorstores.timescalevector", "Typesense": "langchain_community.vectorstores.typesense", "USearch": "langchain_community.vectorstores.usearch", "Vald": "langchain_community.vectorstores.vald", "VDMS": "langchain_community.vectorstores.vdms", "Vearch": "langchain_community.vectorstores.vearch", "Vectara": "langchain_community.vectorstores.vectara", "VectorStore": "langchain_core.vectorstores", "VespaStore": "langchain_community.vectorstores.vespa", "Weaviate": "langchain_community.vectorstores.weaviate", "Yellowbrick": "langchain_community.vectorstores.yellowbrick", "ZepVectorStore": "langchain_community.vectorstores.zep", "Zilliz": "langchain_community.vectorstores.zilliz", } def __getattr__(name: str) -> Any: if name in _module_lookup: module = importlib.import_module(_module_lookup[name]) return getattr(module, name) raise AttributeError(f"module {__name__} has no attribute {name}") __all__ = list(_module_lookup.keys())