langchain/vectorstores/docarray/hnsw.py/DocArrayHnswSearch/from_texts
class DocArrayHnswSearch:    def from_texts(
        cls,
        texts: List[str],
        embedding: Embeddings,
        metadatas: Optional[List[dict]] = None,
        work_dir: Optional[str] = None,
        n_dim: Optional[int] = None,
        **kwargs: Any,
    ) -> DocArrayHnswSearch:
        """Create an DocArrayHnswSearch store and insert data.


        Args:
            texts (List[str]): Text data.
            embedding (Embeddings): Embedding function.
            metadatas (Optional[List[dict]]): Metadata for each text if it exists.
                Defaults to None.
            work_dir (str): path to the location where all the data will be stored.
            n_dim (int): dimension of an embedding.
            **kwargs: Other keyword arguments to be passed to the __init__ method.

        Returns:
            DocArrayHnswSearch Vector Store
        """
        if work_dir is None:
            raise ValueError("`work_dir` parameter has not been set.")
        if n_dim is None:
            raise ValueError("`n_dim` parameter has not been set.")

        store = cls.from_params(embedding, work_dir, n_dim, **kwargs)
        store.add_texts(texts=texts, metadatas=metadatas)
        return store