def _delete(
        self,
        ids: Optional[List[str]] = None,
        **kwargs: Any,
    ) -> None:
        """
        Delete the documents which have the specified ids.

        Args:
            ids: The ids of the embedding vectors.
            **kwargs: Other keyword arguments that subclasses might use.

        Returns:
            Optional[bool]: True if deletion is successful.
            False otherwise, None if not implemented.

        """
        if ids is None or len(ids) == 0:
            return
        for _id in ids:
            queries = {
                "query": {
                    "filter": [{"term": {"ref_doc_id": [_id], "operator": "and"}}]
                },
                "size": 10000,
            }
            self._vearch.delete_by_query(
                self, self.using_db_name, self.using_table_name, queries
            )

        Delete the documents which have the specified ids.

        Args:
            ids: The ids of the embedding vectors.
            **kwargs: Other keyword arguments that subclasses might use.

        Returns:
            Optional[bool]: True if deletion is successful.
            False otherwise, None if not implemented.

        
llama-index-integrations/vector_stores/llama-index-vector-stores-vearch/llama_index/vector_stores/vearch/base.py