utils.utils.mock_now(dt_value)
Context manager for mocking out datetime.now() in unit tests.
utils.utils.raise_for_status_with_text(response)
Raise an error with the response text.
utils.utils.xor_args(*arg_groups)
Validate specified keyword args are mutually exclusive.
langchain.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.atlas.AtlasDB(name[, ...])
Atlas vector store.
vectorstores.awadb.AwaDB([table_name, ...])
AwaDB vector store.
vectorstores.azuresearch.AzureSearch(...[, ...])
Azure Cognitive Search vector store.
vectorstores.azuresearch.AzureSearchVectorStoreRetriever
Retriever that uses Azure Cognitive Search.
vectorstores.bageldb.Bagel([cluster_name, ...])
BagelDB.ai vector store.