asearch(query, search_type, **kwargs)
Return docs most similar to query using specified search type.
asimilarity_search(query[, k])
Return docs most similar to query.
asimilarity_search_by_vector(embedding[, k])
Return docs most similar to embedding vector.
asimilarity_search_with_relevance_scores(query)
Return docs and relevance scores in the range [0, 1], asynchronously.
asimilarity_search_with_score(*args, **kwargs)
Run similarity search with distance asynchronously.
clear()
Empty the collection of all its stored entries.
delete([ids, concurrency])
Delete by vector ids.
delete_by_document_id(document_id)
Remove a single document from the store, given its document_id (str).
delete_collection()
Completely delete the collection from the database (as opposed to 'clear()', which empties it only).
from_documents(documents, embedding, **kwargs)
Create an Astra DB vectorstore from a document list.
from_texts(texts, embedding[, metadatas, ids])
Create an Astra DB vectorstore from raw texts.
max_marginal_relevance_search(query[, k, ...])