@validator("http_client", always=True, allow_reuse=True)
    @classmethod
    def validate_client(cls, field_value: Any, values: Dict) -> AzureMLEndpointClient:
        """Validate that api key and python package exists in environment."""
        endpoint_key = get_from_dict_or_env(
            values, "endpoint_api_key", "AZUREML_ENDPOINT_API_KEY"
        )
        endpoint_url = get_from_dict_or_env(
            values, "endpoint_url", "AZUREML_ENDPOINT_URL"
        )
        deployment_name = get_from_dict_or_env(
            values, "deployment_name", "AZUREML_DEPLOYMENT_NAME", ""
        )
        http_client = AzureMLEndpointClient(endpoint_url, endpoint_key, deployment_name)
        return http_client
    @property
    def _identifying_params(self) -> Mapping[str, Any]:
        """Get the identifying parameters."""
        _model_kwargs = self.model_kwargs or {}
        return {
            **{"deployment_name": self.deployment_name},
            **{"model_kwargs": _model_kwargs},
        }
    @property
    def _llm_type(self) -> str:
        """Return type of llm."""
        return "azureml_endpoint"
    def _call(
        self,
        prompt: str,
        stop: Optional[List[str]] = None,
        run_manager: Optional[CallbackManagerForLLMRun] = None,
        **kwargs: Any,
    ) -> str:
        """Call out to an AzureML Managed Online 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