Row-wise cosine similarity between two equal-width matrices.
utils.math.cosine_similarity_top_k(X, Y[, ...])
Row-wise cosine similarity with optional top-k and score threshold filtering.
utils.openai.is_openai_v1()
utils.openai_functions.convert_pydantic_to_openai_function(...)
Converts a Pydantic model to a function description for the OpenAI API.
utils.openai_functions.convert_pydantic_to_openai_tool(...)
Converts a Pydantic model to a function description for the OpenAI API.
langchain_community.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.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.astradb.AstraDB(*, embedding, ...)
Wrapper around DataStax Astra DB for vector-store workloads.
vectorstores.atlas.AtlasDB(name[, ...])
Atlas vector store.