)
        is_appx_search = _get_kwargs_value(kwargs, "is_appx_search", True)
        vector_field = _get_kwargs_value(kwargs, "vector_field", "vector_field")
        text_field = _get_kwargs_value(kwargs, "text_field", "text")
        max_chunk_bytes = _get_kwargs_value(kwargs, "max_chunk_bytes", 1 * 1024 * 1024)
        http_auth = _get_kwargs_value(kwargs, "http_auth", None)
        is_aoss = _is_aoss_enabled(http_auth=http_auth)
        engine = None
        if is_aoss and not is_appx_search:
            raise ValueError(
                "Amazon OpenSearch Service Serverless only "
                "supports `approximate_search`"
            )
        if is_appx_search:
            engine = _get_kwargs_value(kwargs, "engine", "nmslib")
            space_type = _get_kwargs_value(kwargs, "space_type", "l2")
            ef_search = _get_kwargs_value(kwargs, "ef_search", 512)
            ef_construction = _get_kwargs_value(kwargs, "ef_construction", 512)
            m = _get_kwargs_value(kwargs, "m", 16)
            _validate_aoss_with_engines(is_aoss, engine)
            mapping = _default_text_mapping(
                dim, engine, space_type, ef_search, ef_construction, m, vector_field
            )
        else:
            mapping = _default_scripting_text_mapping(dim)
        [kwargs.pop(key, None) for key in keys_list]
        client = _get_opensearch_client(opensearch_url, **kwargs)
        _bulk_ingest_embeddings(
            client,
            index_name,
            embeddings,
            texts,
            ids=ids,