Adds the embeddings passed in to the vector store and returns it
from_embeddings(
cls: Type[Kinetica],
text_embeddings: List[Tuple[str, List[float]]],
embedding: Embeddings,
metadatas: Optional[List[dict]] = None,
config: KineticaSettings = KineticaSettings(),
dimensions: int = Dimension.OPENAI,
collection_name: str = _LANGCHAIN_DEFAULT_COLLECTION_NAME,
distance_strategy: DistanceStrategy = DEFAULT_DISTANCE_STRATEGY,
ids: Optional[List[str]] = None,
pre_delete_collection: bool = False,
*,
schema_name: str = _LANGCHAIN_DEFAULT_SCHEMA_NAME,
**kwargs: Any = {}
) -> Kinetica| Name | Type | Description |
|---|---|---|
cls* | Type[Kinetica] | Kinetica class |
text_embeddings* | List[Tuple[str, List[float]]] | A list of texts and the embeddings |
embedding* | Embeddings | List of embeddings |
metadatas | Optional[List[dict]] | Default: NoneList of dicts, JSON describing the texts/documents. Defaults to None. |
config | KineticaSettings | Default: KineticaSettings()a |
dimensions | int | Default: Dimension.OPENAIDimension for the vector data, if not passed a default will be used. Defaults to Dimension.OPENAI. |
collection_name | str | Default: _LANGCHAIN_DEFAULT_COLLECTION_NAMEKinetica schema name. Defaults to _LANGCHAIN_DEFAULT_COLLECTION_NAME. |
schema_name | str | Default: _LANGCHAIN_DEFAULT_SCHEMA_NAMEKinetica schema name. Defaults to _LANGCHAIN_DEFAULT_SCHEMA_NAME. |
distance_strategy | DistanceStrategy | Default: DEFAULT_DISTANCE_STRATEGYDistance strategy e.g., l2, cosine etc.. Defaults to DEFAULT_DISTANCE_STRATEGY. |
ids | Optional[List[str]] | Default: NoneA list of UUIDs for each text/document. Defaults to None. |
pre_delete_collection | bool | Default: FalseIndicates whether the Kinetica schema is to be deleted or not. Defaults to False. |