d = {
            "max_tokens_to_sample": self.max_tokens_to_sample,
            "model": self.model,
        }
        if self.temperature is not None:
            d["temperature"] = self.temperature
        if self.top_k is not None:
            d["top_k"] = self.top_k
        if self.top_p is not None:
            d["top_p"] = self.top_p
        return d
    @property
    def _identifying_params(self) -> Mapping[str, Any]:
        """Get the identifying parameters."""
        return {**{}, **self._default_params}
    def _get_anthropic_stop(self, stop: Optional[List[str]] = None) -> List[str]:
        if not self.HUMAN_PROMPT or not self.AI_PROMPT:
            raise NameError("Please ensure the anthropic package is loaded")
        if stop is None:
            stop = []
        # Never want model to invent new turns of Human / Assistant dialog.
        stop.extend([self.HUMAN_PROMPT])
        return stop
[docs]class Anthropic(LLM, _AnthropicCommon):
    """Anthropic large language models.
    To use, you should have the ``anthropic`` python package installed, and the
    environment variable ``ANTHROPIC_API_KEY`` set with your API key, or pass
    it as a named parameter to the constructor.
    Example:
        .. code-block:: python
            import anthropic
            from langchain.llms import Anthropic
            model = Anthropic(model="<model_name>", anthropic_api_key="my-api-key")
            # Simplest invocation, automatically wrapped with HUMAN_PROMPT
            # and AI_PROMPT.
            response = model("What are the biggest risks facing humanity?")