Initialize a Vector Store backed by Momento Vector Index.
Parameters
embedding (Embeddings) – The embedding function to use.
configuration (VectorIndexConfiguration) – The configuration to initialize
the Vector Index with.
credential_provider (CredentialProvider) – The credential provider to
authenticate the Vector Index with.
index_name (str, optional) – The name of the index to store the documents in.
Defaults to “default”.
distance_strategy (DistanceStrategy, optional) – The distance strategy to
use. If you select DistanceStrategy.EUCLIDEAN_DISTANCE, Momento uses
the squared Euclidean distance. Defaults to DistanceStrategy.COSINE.
text_field (str, optional) – The name of the metadata field to store the
original text in. Defaults to “text”.
ensure_index_exists (bool, optional) – Whether to ensure that the index
exists before adding documents to it. Defaults to True.
async aadd_documents(documents: List[Document], **kwargs: Any) → List[str]¶
Run more documents through the embeddings and add to the vectorstore.
Parameters
(List[Document] (documents) – Documents to add to the vectorstore.
Returns
List of IDs of the added texts.
Return type
List[str]
async aadd_texts(texts: Iterable[str], metadatas: Optional[List[dict]] = None, **kwargs: Any) → List[str]¶
Run more texts through the embeddings and add to the vectorstore.
add_documents(documents: List[Document], **kwargs: Any) → List[str]¶
Run more documents through the embeddings and add to the vectorstore.
Parameters
(List[Document] (documents) – Documents to add to the vectorstore.
Returns
List of IDs of the added texts.
Return type
List[str]