Construct BESVectorStore wrapper from raw documents.
from_texts(
cls,
texts: List[str],
embedding: Optional[Embeddings] = None,
metadatas: Optional[List[Dict[str, Any]]] = None,
**kwargs: Any = {}
) -> BESVectorStore| Name | Type | Description |
|---|---|---|
texts* | List[str] | List of texts to add to the Elasticsearch index. |
embedding | Optional[Embeddings] | Default: NoneEmbedding function to use to embed the texts. |
metadatas | Optional[List[Dict[str, Any]]] | Default: NoneOptional list of metadatas associated with the texts. |
index_name* | unknown | Name of the Elasticsearch index to create. |
kwargs | Any | Default: {}create index key words arguments |