fields = item["fields"]
                query_result_list.append(
                    Document(
                        page_content=fields[self.config.field_name_mapping["document"]],
                        metadata=self.create_inverse_metadata(fields),
                    )
                )
        return query_result_list
[docs]    def create_inverse_metadata(self, fields: Dict[str, Any]) -> Dict[str, Any]:
        """Create metadata from fields.
        Args:
            fields: The fields of the document. The fields must be a dict.
        Returns:
            metadata: The metadata of the document. The metadata must be a dict.
        """
        metadata: Dict[str, Any] = {}
        for key, value in fields.items():
            if key == "id" or key == "document" or key == "embedding":
                continue
            metadata[self.config.inverse_field_name_mapping[key]] = value
        return metadata
[docs]    def create_results_with_score(
        self, json_result: Dict[str, Any]
    ) -> List[Tuple[Document, float]]:
        """Parsing the returned results with scores.
        Args:
            json_result: Results from OpenSearch query.
        Returns:
            query_result_list: Results with scores.
        """
        items = json_result["result"]
        query_result_list: List[Tuple[Document, float]] = []
        for item in items:
            fields = item["fields"]
            query_result_list.append(
                (
                    Document(
                        page_content=fields[self.config.field_name_mapping["document"]],
                        metadata=self.create_inverse_metadata(fields),
                    ),
                    float(item["score"]),
                )
            )
        return query_result_list
[docs]    def delete_documents_with_texts(self, texts: List[str]) -> bool: