LanceDB

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

Defines the filter type used in search and delete operations. Can be an object for structured conditions or a string for simpler filtering.

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

Adds documents to the database.

Adds vectors and their corresponding documents to the database.

Creates a VectorStoreRetriever instance with flexible configuration options.

Deletes documents from the vector store based on the specified parameters.

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

Performs a similarity search in the database and returns the documents.

Performs a similarity search on the vectors in the database and returns the documents and their scores.

Performs a similarity search in the database and returns the documents and their scores.

Creates a new instance of LanceDB from documents.

Creates a new instance of LanceDB from texts.

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.