ConvexVectorStore

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

Type that defines the filter used in the similaritySearchVectorWithScore and maxMarginalRelevanceSearch methods. It includes limit, filter and a flag to include embeddings.

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

Add documents to the Convex table. It first converts the documents to vectors using the embeddings and then calls the addVectors method.

Add vectors and their corresponding documents to the Convex table.

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.

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

Similarity search on the vectors stored in the Convex table. It returns a list of documents and their corresponding similarity scores.

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

Static method to create an instance of ConvexVectorStore from a list of documents. It first converts the documents to vectors and then adds them to the Convex table.

Static method to create an instance of ConvexVectorStore from a list of texts. It first converts the texts to vectors and then adds them to the Convex table.

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.