Method mutual_consistency

optillm/rstar.py:205–212

(self, trajectory: List[Node])

        return trajectories

    def mutual_consistency(self, trajectory: List[Node]) -> bool:
        split_index = random.randint(1, len(trajectory) - 1)
        partial_trajectory = trajectory[:split_index]
        prompt = self.create_discriminator_prompt(partial_trajectory)
        completion = self.generate_response(prompt)
        is_consistent = self.compare_completions(completion, trajectory[split_index:])
        logger.debug(f"Mutual consistency check: {'Passed' if is_consistent else 'Failed'}")
        return is_consistent

    def select_final_trajectory(self, trajectories: List[List[Node]]) -> List[Node]:
        logger.debug("Selecting final trajectory")