Raises
ValueError – If no UUIDs are provided.
classmethod from_documents(documents: List[Document], embedding: Embeddings, **kwargs: Any) → VST¶
Return VectorStore initialized from documents and embeddings.
classmethod from_texts(texts: List[str], embedding: Optional[Embeddings] = None, metadatas: Optional[List[dict]] = None, collection_name: str = '', api_url: str = '', api_key: Optional[str] = None, config: Optional[CollectionConfig] = None, **kwargs: Any) → ZepVectorStore[source]¶
Class method that returns a ZepVectorStore instance initialized from texts.
If the collection does not exist, it will be created.
Parameters
texts (List[str]) – The list of texts to add to the vectorstore.
embedding (Optional[Embeddings]) – Optional embedding function to use to
embed the texts.
metadatas (Optional[List[Dict[str, Any]]]) – Optional list of metadata
associated with the texts.
collection_name (str) – The name of the collection in the Zep store.
api_url (str) – The URL of the Zep API.
api_key (Optional[str]) – The API key for the Zep API.
config (Optional[CollectionConfig]) – The configuration for the collection.
**kwargs – Additional parameters specific to the vectorstore.
Returns
An instance of ZepVectorStore.
Return type
ZepVectorStore
max_marginal_relevance_search(query: str, k: int = 4, fetch_k: int = 20, lambda_mult: float = 0.5, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → List[Document][source]¶
Return docs selected using the maximal marginal relevance.
Maximal marginal relevance optimizes for similarity to query AND diversity