self, topic: str, now: Optional[datetime] = None
    ) -> List[str]:
        """Generate 'insights' on a topic of reflection, based on pertinent memories."""
        prompt = PromptTemplate.from_template(
            "Statements relevant to: '{topic}'\n"
            "---\n"
            "{related_statements}\n"
            "---\n"
            "What 5 high-level novel insights can you infer from the above statements "
            "that are relevant for answering the following question?\n"
            "Do not include any insights that are not relevant to the question.\n"
            "Do not repeat any insights that have already been made.\n\n"
            "Question: {topic}\n\n"
            "(example format: insight (because of 1, 5, 3))\n"
        )
        related_memories = self.fetch_memories(topic, now=now)
        related_statements = "\n".join(
            [
                self._format_memory_detail(memory, prefix=f"{i+1}. ")
                for i, memory in enumerate(related_memories)
            ]
        )
        result = self.chain(prompt).run(
            topic=topic, related_statements=related_statements
        )
        # TODO: Parse the connections between memories and insights
        return self._parse_list(result)
[docs]    def pause_to_reflect(self, now: Optional[datetime] = None) -> List[str]:
        """Reflect on recent observations and generate 'insights'."""
        if self.verbose:
            logger.info("Character is reflecting")
        new_insights = []
        topics = self._get_topics_of_reflection()
        for topic in topics:
            insights = self._get_insights_on_topic(topic, now=now)