def _generate_key_points(
        self, source: str, temperature: float = 0.0
    ) -> str:
        """
        Uses chat completion model. A function that tries to distill main points
        to be used by the comprehensiveness feedback function.

         Args:
            source (str): Text corresponding to source material.

        Returns:
            (str) key points of the source text.
        """
        assert self.endpoint is not None, "Endpoint is not set."
        llm_messages = [
            {
                "role": "system",
                "content": feedback_prompts.GENERATE_KEY_POINTS_SYSTEM_PROMPT,
            },
            {
                "role": "user",
                "content": str.format(
                    feedback_prompts.GENERATE_KEY_POINTS_USER_PROMPT,
                    source=source,
                ),
            },
        ]

        return self.endpoint.run_in_pace(
            func=self._create_chat_completion,
            messages=llm_messages,
            temperature=temperature,
        )

        Uses chat completion model. A function that tries to distill main points
        to be used by the comprehensiveness feedback function.

         Args:
            source (str): Text corresponding to source material.

        Returns:
            (str) key points of the source text.
        
src/feedback/trulens/feedback/llm_provider.py