"""
Legacy Inference Module - Backward Compatibility Interface.

This module provides a simplified interface that maintains backward compatibility
with the original inference.py while leveraging the new modular architecture.

For new development, use the specific modules directly:
- video.py: Video classification and play analysis
- audio.py: Audio transcription and NFL corrections
- config.py: Configuration and constants

This module is maintained for:
1. Backward compatibility with existing scripts
2. Simple single-clip processing interface
3. Legacy CLI functionality
"""

import os
import sys
import json
from typing import List, Tuple

# Import from new modular structure
from video import predict_clip, analyze_play_state, detect_play_boundaries
from audio import transcribe_clip, load_audio, apply_sports_corrections, fuzzy_sports_corrections
from config import DEFAULT_DATA_DIR

# Re-export all functions for backward compatibility
__all__ = [
    'predict_clip',
    'analyze_play_state', 
    'detect_play_boundaries',
    'transcribe_clip',
    'load_audio',
    'apply_sports_corrections',
    'fuzzy_sports_corrections'
]


def main():
    """
    CLI interface for single clip processing (backward compatibility).
    
    Usage:
        python inference.py path/to/clip.mov
    """
    if len(sys.argv) < 2:
        print("Usage: python inference.py <path_to_video_clip>")
        print(f"Example: python inference.py {DEFAULT_DATA_DIR}/segment_001.mov")
        sys.exit(1)
    
    clip_path = sys.argv[1]
    
    if not os.path.exists(clip_path):
        print(f"Error: File '{clip_path}' not found")
        sys.exit(1)
    
    print(f"Processing: {clip_path}")
    print("=" * 50)
    
    # Video classification
    print("🎬 Video Classification:")
    predictions = predict_clip(clip_path)
    
    if predictions:
        print(f"\nTop-5 labels for {clip_path}:")
        for label, score in predictions:
            print(f"{label:>30s} : {score:.3f}")
        
        # Save classification results
        clip_name = os.path.basename(clip_path)
        with open("classification.json", "w") as f:
            json.dump({clip_name: predictions}, f, indent=2)
        print(f"\n✓ Classification saved to classification.json")
    else:
        print("❌ Video classification failed")
    
    # Audio transcription
    print("\n🎙️ Audio Transcription:")
    transcript = transcribe_clip(clip_path)
    
    if transcript:
        print(f"Transcript: {transcript}")
        
        # Save transcript results
        clip_name = os.path.basename(clip_path)
        with open("transcripts.json", "w") as f:
            json.dump({clip_name: transcript}, f, indent=2)
        print(f"✓ Transcript saved to transcripts.json")
    else:
        print("ℹ️ No audio content detected or transcription failed")
    
    print("\n🏁 Processing complete!")


if __name__ == "__main__":
    main()