"The default custom credentials (google.auth.credentials.Credentials) to use "
    "when making API calls. If not provided, credentials will be ascertained from "
    "the environment."
    @property
    def _default_params(self) -> Dict[str, Any]:
        base_params = {
            "temperature": self.temperature,
            "max_output_tokens": self.max_output_tokens,
            "top_k": self.top_k,
            "top_p": self.top_p,
        }
        return {**base_params}
    def _predict(
        self, prompt: str, stop: Optional[List[str]] = None, **kwargs: Any
    ) -> str:
        params = {**self._default_params, **kwargs}
        res = self.client.predict(prompt, **params)
        return self._enforce_stop_words(res.text, stop)
    def _enforce_stop_words(self, text: str, stop: Optional[List[str]] = None) -> str:
        if stop is None and self.stop is not None:
            stop = self.stop
        if stop:
            return enforce_stop_tokens(text, stop)
        return text
    @property
    def _llm_type(self) -> str:
        return "vertexai"
    @classmethod
    def _try_init_vertexai(cls, values: Dict) -> None:
        allowed_params = ["project", "location", "credentials"]
        params = {k: v for k, v in values.items() if k in allowed_params}
        init_vertexai(**params)
        return None
[docs]class VertexAI(_VertexAICommon, LLM):
    """Wrapper around Google Vertex AI large language models."""
    model_name: str = "text-bison"
    tuned_model_name: Optional[str] = None
rtdocs_stable/api.python.langchain.com/en/stable/_modules/langchain/llms/vertexai.html