# "transform_output_fn": self.transform_output_fn,
        }
    @property
    def _identifying_params(self) -> Mapping[str, Any]:
        return self._default_params
    @property
    def _llm_type(self) -> str:
        """Return type of llm."""
        return "databricks"
    def _call(
        self,
        prompt: str,
        stop: Optional[List[str]] = None,
        run_manager: Optional[CallbackManagerForLLMRun] = None,
        **kwargs: Any,
    ) -> str:
        """Queries the LLM endpoint with the given prompt and stop sequence."""
        # TODO: support callbacks
        request: Dict[str, Any] = {"prompt": prompt}
        if self._client.llm:
            request.update(self._llm_params)
        request.update(self.model_kwargs or self.extra_params)
        request.update(kwargs)
        if stop:
            request["stop"] = stop
        if self.transform_input_fn:
            request = self.transform_input_fn(**request)
        return self._client.post(request, transform_output_fn=self.transform_output_fn)