AstraDB

Empty the collection of all its stored entries.

Empty the collection of all its stored entries.

Remove a single document from the store, given its document ID.

Remove a single document from the store, given its document ID.

Delete by vector ids.

Delete by vector ids.

Completely delete the collection from the database (as opposed to :meth:~clear, which empties it only). Stored data is lost and unrecoverable, resources are freed. Use with caution.

Completely delete the collection from the database (as opposed to :meth:~aclear, which empties it only). Stored data is lost and unrecoverable, resources are freed. Use with caution.

Run texts through the embeddings and add them to the vectorstore.

If passing explicit ids, those entries whose id is in the store already will be replaced.

Run texts through the embeddings and add them to the vectorstore.

If passing explicit ids, those entries whose id is in the store already will be replaced.

Return docs most similar to embedding vector with score and id.

Return docs most similar to embedding vector with score and id.

Return docs most similar to the query with score and id.

Return docs most similar to the query with score and id.

Return docs most similar to embedding vector with score.

Return docs most similar to embedding vector with score.

Return docs most similar to query.

Return docs most similar to query.

Return docs most similar to embedding vector.

Return docs most similar to embedding vector.

Return docs most similar to query with score.

Return docs most similar to query with score.

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.

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.

Create an Astra DB vectorstore from raw texts.

Create an Astra DB vectorstore from raw texts.

Create an Astra DB vectorstore from a document list.

Utility method that defers to 'from_texts' (see that one).