ZepCloudVectorStore

The ZepClient instance used to interact with Zep's API.

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 collection. The documents are first embedded into vectors using the provided embedding model.

Adds precomputed vectors and corresponding documents to the vector store.

Creates a VectorStoreRetriever instance with flexible configuration options.

Deletes documents from the collection.

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 on the Zep collection.

Performs a similarity search using a vector query and returns results along with their similarity scores.

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

Creates a new ZepVectorStore instance from an array of Documents. Each Document is added to a Zep collection.

Creates a new ZepVectorStore instance from an array of texts. Each text is converted into a Document and added to the collection.

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.