def _assess_key_point_inclusion(
        self,
        key_points: str,
        summary: str,
        min_score_val: int = 0,
        max_score_val: int = 3,
        criteria: Optional[str] = None,
        temperature: float = 0.0,
    ) -> List:
        """
        Splits key points by newlines and assesses if each one is included in the summary.

        Args:
            key_points (str): Key points separated by newlines.
            summary (str): The summary text to check for inclusion of key points.

        Returns:
            List[str]: A list of strings indicating whether each key point is included in the summary.
        """
        assert self.endpoint is not None, "Endpoint is not set."
        key_points_list = [
            point.strip() for point in key_points.split("\n") if point.strip()
        ]

        output_space = self._determine_output_space(
            min_score_val, max_score_val
        )

        system_prompt = feedback_v2.Comprehensiveness.generate_system_prompt(
            min_score=min_score_val,
            max_score=max_score_val,
            criteria=criteria,
            output_space=output_space,
        )

        inclusion_assessments = []
        for key_point in key_points_list:
            user_prompt = str.format(
                feedback_prompts.COMPREHENSIVENESS_USER_PROMPT,
                key_point=key_point,
                summary=summary,
            )

            llm_messages = [
                {"role": "system", "content": system_prompt},
                {"role": "user", "content": user_prompt},
            ]

            inclusion_assessment = self.endpoint.run_in_pace(
                func=self._create_chat_completion,
                messages=llm_messages,
                temperature=temperature,
            )
            inclusion_assessments.append(inclusion_assessment)

        return inclusion_assessments

        Splits key points by newlines and assesses if each one is included in the summary.

        Args:
            key_points (str): Key points separated by newlines.
            summary (str): The summary text to check for inclusion of key points.

        Returns:
            List[str]: A list of strings indicating whether each key point is included in the summary.
        
src/feedback/trulens/feedback/llm_provider.py