TurbopufferVectorStore

Embeddings interface for generating vector embeddings from text queries, enabling vector-based similarity searches.

Returns a string representing the type of vector store, which subclasses must implement to identify their specific vector storage type.

Add documents to the store.

Add vectors and their associated documents to the store.

Creates a VectorStoreRetriever instance with flexible configuration options.

Delete documents by ID or delete all documents in the namespace.

Return documents selected using the maximal marginal relevance. Maximal marginal relevance optimizes for similarity to the query AND diversity among selected documents.

Searches for documents similar to a text query by embedding the query and performing a similarity search on the resulting vector.

Search for documents similar to the query vector.

Searches for documents similar to a text query by embedding the query, and returns results with similarity scores.

Create a TurbopufferVectorStore from documents.

Create a TurbopufferVectorStore from text strings.

The name of the serializable. Override to provide an alias or to preserve the serialized module name in minified environments.

Implemented as a static method to support loading logic.