Method invoke

ReportEngine/llms/base.py:69–100

以非流式方式调用LLM，并返回一次性完成的完整响应。 Args: system_prompt: 系统角色提示 user_prompt: 用户高优先级指令 **kwargs: 允许透传temperature/top_p等采样参数 Returns: 去除首尾空白后的LLM响应文本

(self, system_prompt: str, user_prompt: str, **kwargs)

    @with_retry(LLM_RETRY_CONFIG)
    def invoke(self, system_prompt: str, user_prompt: str, **kwargs) -> str:
        """
        以非流式方式调用LLM，并返回一次性完成的完整响应。

        Args:
            system_prompt: 系统角色提示
            user_prompt: 用户高优先级指令
            **kwargs: 允许透传temperature/top_p等采样参数

        Returns:
            去除首尾空白后的LLM响应文本
        """
        messages = [
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": user_prompt},
        ]

        allowed_keys = {"temperature", "top_p", "presence_penalty", "frequency_penalty", "stream"}
        extra_params = {key: value for key, value in kwargs.items() if key in allowed_keys and value is not None}

        timeout = kwargs.pop("timeout", self.timeout)

        response = self.client.chat.completions.create(
            model=self.model_name,
            messages=messages,
            timeout=timeout,
            **extra_params,
        )

        if response.choices and response.choices[0].message:
            return self.validate_response(response.choices[0].message.content)
        return ""

    def stream_invoke(self, system_prompt: str, user_prompt: str, **kwargs) -> Generator[str, None, None]:
        """