"""OCTOAI API Token"""
    class Config:
        """Configuration for this pydantic object."""
        extra = Extra.forbid
    @root_validator(allow_reuse=True)
    def validate_environment(cls, values: Dict) -> Dict:
        """Validate that api key and python package exists in environment."""
        octoai_api_token = get_from_dict_or_env(
            values, "octoai_api_token", "OCTOAI_API_TOKEN"
        )
        values["endpoint_url"] = get_from_dict_or_env(
            values, "endpoint_url", "ENDPOINT_URL"
        )
        values["octoai_api_token"] = octoai_api_token
        return values
    @property
    def _identifying_params(self) -> Mapping[str, Any]:
        """Get the identifying parameters."""
        _model_kwargs = self.model_kwargs or {}
        return {
            **{"endpoint_url": self.endpoint_url},
            **{"model_kwargs": _model_kwargs},
        }
    @property
    def _llm_type(self) -> str:
        """Return type of llm."""
        return "octoai_endpoint"
    def _call(
        self,
        prompt: str,
        stop: Optional[List[str]] = None,
        run_manager: Optional[CallbackManagerForLLMRun] = None,
        **kwargs: Any,
    ) -> str:
        """Call out to OctoAI's inference 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.
        """
        _model_kwargs = self.model_kwargs or {}
        # Prepare the payload JSON