WeaviateVectorStore

Upload texts with metadata (properties) to Weaviate.

Return docs most similar to query.

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 list of documents most similar to the query text and cosine distance in float for each.

Lower score represents more similarity.

Return docs selected using the similarity search by vector.

Construct Weaviate wrapper from raw documents.

This is a user-friendly interface that:

1. Embeds documents.
2. Creates a new index for the embeddings in the Weaviate instance.
3. Adds the documents to the newly created Weaviate index.

This is intended to be a quick way to get started.

Delete by vector IDs.

Add texts to Weaviate asynchronously.

Return docs most similar to query asynchronously.

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 list of documents most similar to the query text and cosine distance in float for each. Lower score represents more similarity.

Return docs most similar to embedding vector asynchronously.

Construct Weaviate wrapper from raw documents asynchronously.