Method optimize_with_feedback

src/agent.py:461–505

Optimize the code based on feedback from the MLLM

(self, section: Section, feedback: VideoFeedback)

            )

    def optimize_with_feedback(self, section: Section, feedback: VideoFeedback) -> bool:
        """Optimize the code based on feedback from the MLLM"""
        if not feedback.has_issues or not feedback.suggested_improvements:
            print(f"✅ {self.learning_topic} {section.id} no optimization needed")
            return True

        # === Step 1: back up original code ===
        original_code_content = self.section_codes[section.id]

        for attempt in range(self.max_feedback_gen_code_tries):
            print(
                f"🎯 {self.learning_topic} MLLM feedback optimization {section.id} code, attempt {attempt + 1}/{self.max_feedback_gen_code_tries}"
            )

            # === Step 2: back up original code and apply improvements ===
            if attempt > 0:
                self.section_codes[section.id] = original_code_content

            # === Step 3: re-generate code with feedback ===
            self.generate_section_code(
                section=section, attempt=attempt + 1, feedback_improvements=feedback.suggested_improvements
            )
            success = self.debug_and_fix_code(section.id, max_fix_attempts=self.max_mllm_fix_bugs_tries)
            if success:
                optimized_output_dir = self.output_dir / "optimized_videos"
                optimized_output_dir.mkdir(exist_ok=True)
                optimized_video_path = optimized_output_dir / f"{section.id}_optimized.mp4"

                if section.id in self.section_videos:
                    original_video_path = Path(self.section_videos[section.id])
                    if original_video_path.exists():
                        original_video_path.rename(optimized_video_path)
                        self.section_videos[section.id] = str(optimized_video_path)
                        print(f"✨ {self.learning_topic} {section.id} optimized video saved: {optimized_video_path}")
                    else:
                        print(f"⚠️ {self.learning_topic} {section.id} original video file not found: {original_video_path}")
                else:
                    print(f"⚠️ {self.learning_topic} {section.id} no optimized video path found")
                return True
            else:
                print(
                    f"❌ {self.learning_topic} {section.id} MLLM optimization failed, attempt {attempt + 1}/{self.max_feedback_gen_code_tries}"
                )

        return False

    def generate_codes(self) -> Dict[str, str]:
        if not self.sections: