metadatas: Optional[List[dict]] = None,
    ids: Optional[List[str]] = None,
    vector_field: str = "vector_field",
    text_field: str = "text",
    mapping: Optional[Dict] = None,
    max_chunk_bytes: Optional[int] = 1 * 1024 * 1024,
    is_aoss: bool = False,
) -> List[str]:
    """Bulk Ingest Embeddings into given index."""
    if not mapping:
        mapping = dict()
    bulk = _import_bulk()
    not_found_error = _import_not_found_error()
    requests = []
    return_ids = []
    mapping = mapping
    try:
        client.indices.get(index=index_name)
    except not_found_error:
        client.indices.create(index=index_name, body=mapping)
    for i, text in enumerate(texts):
        metadata = metadatas[i] if metadatas else {}
        _id = ids[i] if ids else str(uuid.uuid4())
        request = {
            "_op_type": "index",
            "_index": index_name,
            vector_field: embeddings[i],
            text_field: text,
            "metadata": metadata,
        }
        if is_aoss:
            request["id"] = _id
        else:
            request["_id"] = _id
        requests.append(request)
        return_ids.append(_id)
    bulk(client, requests, max_chunk_bytes=max_chunk_bytes)
    if not is_aoss:
        client.indices.refresh(index=index_name)
    return return_ids
def _default_scripting_text_mapping(
    dim: int,
    vector_field: str = "vector_field",
) -> Dict: