def _get_embedding(self, text: str) -> List[float]:
        """
        Generate an embedding for a single query text.

        Args:
            text (str): The query text to generate an embedding for.

        Returns:
            List[float]: The embedding for the input query text.

        """
        response = self._client.infer_trained_model(
            model_id=self.model_id,
            docs=[{self.input_field: text}],
        )

        return response["inference_results"][0]["predicted_value"]

        Generate an embedding for a single query text.

        Args:
            text (str): The query text to generate an embedding for.

        Returns:
            List[float]: The embedding for the input query text.

        
llama-index-integrations/embeddings/llama-index-embeddings-elasticsearch/llama_index/embeddings/elasticsearch/base.py