Return docs selected using the maximal marginal relevance.
amax_marginal_relevance_search_by_vector(...)
Return docs selected using the maximal marginal relevance.
as_retriever(**kwargs)
Return VectorStoreRetriever initialized from this VectorStore.
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 most similar to query.
create_table(table_name, **kwargs)
Create a new table.
delete([ids])
Delete the documents which have the specified ids.
from_documents(documents[, embedding, ...])
Create an AwaDB vectorstore from a list of documents.
from_texts(texts[, embedding, metadatas, ...])
Create an AwaDB vectorstore from a raw documents.
get([ids, text_in_page_content, ...])
Return docs according ids.
get_current_table(**kwargs)
Get the current table.
list_tables(**kwargs)
List all the tables created by the client.
load_local(table_name, **kwargs)
Load the local specified table.
max_marginal_relevance_search(query[, k, ...])
Return docs selected using the maximal marginal relevance.
max_marginal_relevance_search_by_vector(...)
Return docs selected using the maximal marginal relevance.
search(query, search_type, **kwargs)
Return docs most similar to query using specified search type.
similarity_search(query[, k, ...])
Return docs most similar to query.
similarity_search_by_vector([embedding, k, ...])