langchain/vectorstores/vectara.py/Vectara/from_texts
class Vectara:    def from_texts(
        cls: Type[Vectara],
        texts: List[str],
        embedding: Optional[Embeddings] = None,
        metadatas: Optional[List[dict]] = None,
        **kwargs: Any,
    ) -> Vectara:
        """Construct Vectara wrapper from raw documents.
        This is intended to be a quick way to get started.
        Example:
            .. code-block:: python

                from langchain import Vectara
                vectara = Vectara.from_texts(
                    texts,
                    vectara_customer_id=customer_id,
                    vectara_corpus_id=corpus_id,
                    vectara_api_key=api_key,
                )
        """
        # Note: Vectara generates its own embeddings, so we ignore the provided
        # embeddings (required by interface)
        vectara = cls(**kwargs)
        vectara.add_texts(texts, metadatas)
        return vectara