Interface for vector store.
VectorStore()Run more texts through the embeddings and add to the VectorStore.
Delete by vector ID or other criteria.
Get documents by their IDs.
The returned documents are expected to have the ID field set to the ID of the document in the vector store.
Fewer documents may be returned than requested if some IDs are not found or if there are duplicated IDs.
Users should not assume that the order of the returned documents matches the order of the input IDs. Instead, users should rely on the ID field of the returned documents.
This method should NOT raise exceptions if no documents are found for some IDs.
Async get documents by their IDs.
The returned documents are expected to have the ID field set to the ID of the document in the vector store.
Fewer documents may be returned than requested if some IDs are not found or if there are duplicated IDs.
Users should not assume that the order of the returned documents matches the order of the input IDs. Instead, users should rely on the ID field of the returned documents.
This method should NOT raise exceptions if no documents are found for some IDs.
Async delete by vector ID or other criteria.
Async run more texts through the embeddings and add to the VectorStore.
Add or update documents in the VectorStore.
Async run more documents through the embeddings and add to the VectorStore.
Return docs most similar to query using a specified search type.
Async return docs most similar to query using a specified search type.
Return docs most similar to query.
Run similarity search with distance.
Async run similarity search with distance.
Return docs and relevance scores in the range [0, 1].
0 is dissimilar, 1 is most similar.
Async return docs and relevance scores in the range [0, 1].
0 is dissimilar, 1 is most similar.
Async return docs most similar to query.
Return docs most similar to embedding vector.
Async return docs most similar to embedding vector.
Return docs selected using the maximal marginal relevance.
Maximal marginal relevance optimizes for similarity to query AND diversity among selected documents.
Async return docs selected using the maximal marginal relevance.
Maximal marginal relevance optimizes for similarity to query AND diversity among selected documents.
Return docs selected using the maximal marginal relevance.
Maximal marginal relevance optimizes for similarity to query AND diversity among selected documents.
Async return docs selected using the maximal marginal relevance.
Maximal marginal relevance optimizes for similarity to query AND diversity among selected documents.
Return VectorStore initialized from documents and embeddings.
Async return VectorStore initialized from documents and embeddings.
Return VectorStore initialized from texts and embeddings.
Async return VectorStore initialized from texts and embeddings.
Return VectorStoreRetriever initialized from this VectorStore.