mitus/meetus/cache_manager.py

"""
Manage caching for frames, transcripts, and analysis results.
"""
from pathlib import Path
import json
import logging
from typing import List, Tuple, Dict, Optional

logger = logging.getLogger(__name__)


class CacheManager:
    """Manage caching of intermediate processing results."""

    def __init__(self, output_dir: Path, frames_dir: Path, video_name: str, use_cache: bool = True,
                 skip_cache_frames: bool = False, skip_cache_whisper: bool = False,
                 skip_cache_analysis: bool = False):
        """
        Initialize cache manager.

        Args:
            output_dir: Output directory for cached files
            frames_dir: Directory for cached frames
            video_name: Name of the video (stem)
            use_cache: Whether to use caching globally
            skip_cache_frames: Skip cached frames specifically
            skip_cache_whisper: Skip cached whisper specifically
            skip_cache_analysis: Skip cached analysis specifically
        """
        self.output_dir = output_dir
        self.frames_dir = frames_dir
        self.video_name = video_name
        self.use_cache = use_cache
        self.skip_cache_frames = skip_cache_frames
        self.skip_cache_whisper = skip_cache_whisper
        self.skip_cache_analysis = skip_cache_analysis

    def get_whisper_cache(self) -> Optional[Path]:
        """
        Check for cached Whisper transcript.

        Returns:
            Path to cached transcript or None
        """
        if not self.use_cache or self.skip_cache_whisper:
            return None

        cache_path = self.output_dir / f"{self.video_name}.json"
        if cache_path.exists():
            logger.info(f"✓ Found cached Whisper transcript: {cache_path.name}")

            # Debug: Show cached transcript info
            try:
                import json
                with open(cache_path, 'r', encoding='utf-8') as f:
                    data = json.load(f)
                if 'segments' in data:
                    logger.debug(f"Cached transcript has {len(data['segments'])} segments")
            except Exception as e:
                logger.debug(f"Could not parse cached whisper for debug: {e}")

            return cache_path

        return None

    def get_frames_cache(self) -> Optional[List[Tuple[str, float]]]:
        """
        Check for cached frames.

        Returns:
            List of (frame_path, timestamp) tuples or None
        """
        if not self.use_cache or self.skip_cache_frames or not self.frames_dir.exists():
            return None

        existing_frames = list(self.frames_dir.glob("frame_*.jpg"))

        if not existing_frames:
            return None

        logger.info(f"✓ Found {len(existing_frames)} cached frames in {self.frames_dir.name}/")
        logger.debug(f"Frame filenames: {[f.name for f in sorted(existing_frames)[:3]]}...")

        # Build frames_info from existing files
        frames_info = []
        for frame_path in sorted(existing_frames):
            # Try to extract timestamp from filename (e.g., frame_00001_12.34s.jpg)
            try:
                timestamp_str = frame_path.stem.split('_')[-1].rstrip('s')
                timestamp = float(timestamp_str)
            except:
                timestamp = 0.0
            frames_info.append((str(frame_path), timestamp))

        return frames_info

    def get_analysis_cache(self, analysis_type: str) -> Optional[List[Dict]]:
        """
        Check for cached analysis results.

        Args:
            analysis_type: 'vision' or 'ocr'

        Returns:
            List of analysis results or None
        """
        if not self.use_cache or self.skip_cache_analysis:
            return None

        cache_path = self.output_dir / f"{self.video_name}_{analysis_type}.json"

        if cache_path.exists():
            logger.info(f"✓ Found cached {analysis_type} analysis: {cache_path.name}")
            with open(cache_path, 'r', encoding='utf-8') as f:
                results = json.load(f)
            logger.info(f"✓ Loaded {len(results)} analyzed frames from cache")

            # Debug: Show first cached result
            if results:
                logger.debug(f"First cached result: timestamp={results[0].get('timestamp')}, text_length={len(results[0].get('text', ''))}")

            return results

        return None

    def save_analysis(self, analysis_type: str, results: List[Dict]):
        """
        Save analysis results to cache.

        Args:
            analysis_type: 'vision' or 'ocr'
            results: Analysis results to save
        """
        cache_path = self.output_dir / f"{self.video_name}_{analysis_type}.json"

        with open(cache_path, 'w', encoding='utf-8') as f:
            json.dump(results, f, indent=2, ensure_ascii=False)

        logger.info(f"✓ Saved {analysis_type} analysis to: {cache_path.name}")

    def cache_exists(self, analysis_type: Optional[str] = None) -> Dict[str, bool]:
        """
        Check what caches exist.

        Args:
            analysis_type: Optional specific analysis type to check

        Returns:
            Dictionary of cache status
        """
        status = {
            "whisper": (self.output_dir / f"{self.video_name}.json").exists(),
            "frames": len(list(self.frames_dir.glob("frame_*.jpg"))) > 0 if self.frames_dir.exists() else False,
        }

        if analysis_type:
            status[analysis_type] = (self.output_dir / f"{self.video_name}_{analysis_type}.json").exists()
        else:
            status["vision"] = (self.output_dir / f"{self.video_name}_vision.json").exists()
            status["ocr"] = (self.output_dir / f"{self.video_name}_ocr.json").exists()

        return status