return values
    @property
    def _identifying_params(self) -> Mapping[str, Any]:
        """Get the identifying parameters."""
        _model_kwargs = self.model_kwargs or {}
        return {
            "nebula_service_url": self.nebula_service_url,
            "nebula_service_path": self.nebula_service_path,
            **{"model_kwargs": _model_kwargs},
            "conversation": self.conversation,
        }
    @property
    def _llm_type(self) -> str:
        """Return type of llm."""
        return "nebula"
    def _call(
        self,
        prompt: str,
        stop: Optional[List[str]] = None,
        run_manager: Optional[CallbackManagerForLLMRun] = None,
        **kwargs: Any,
    ) -> str:
        """Call out to Nebula Service endpoint.
        Args:
            prompt: The prompt to pass into the model.
            stop: Optional list of stop words to use when generating.
        Returns:
            The string generated by the model.
        Example:
            .. code-block:: python
                response = nebula("Tell me a joke.")
        """
        _model_kwargs = self.model_kwargs or {}
        nebula_service_endpoint = f"{self.nebula_service_url}{self.nebula_service_path}"
        headers = {
            "Content-Type": "application/json",
            "ApiKey": f"{self.nebula_api_key}",
        }
        body = {
            "prompt": {
                "instruction": prompt,
                "conversation": {"text": f"{self.conversation}"},
            },
            "return_scores": self.return_scores,
            "max_new_tokens": self.max_new_tokens,