# Entry point for the mknotes audio transcription and note enhancement tool

import os
from tqdm import tqdm

from src.cli import parse_args
from src.utils import find_audio_files, ensure_directory_exists, convert_wav_to_mp3
from src.transcriber import transcribe_audio
from src.enhancer import enhance_note

def main():
    args = parse_args()
    input_dir = args.input_dir
    output_dir = args.output_dir
    model_size = args.model_size

    ensure_directory_exists(output_dir)

    audio_files = find_audio_files(input_dir)
    if not audio_files:
        print(f"No audio files found in {input_dir}.")
        return

    print(f"Found {len(audio_files)} audio files. Starting transcription and enhancement...")

    for audio_path in tqdm(audio_files, desc="Processing files"):
        base_name = os.path.splitext(os.path.basename(audio_path))[0]
        txt_path = os.path.join(output_dir, base_name + ".txt")
        md_path = os.path.join(output_dir, base_name + ".md")
        
        # Skip if enhanced note already exists (unless force flag is set)
        if os.path.exists(md_path) and not args.force:
            print(f"Skipping {audio_path} - enhanced note already exists at {md_path}")
            continue

        # Check if transcription exists
        if os.path.exists(txt_path) and not args.force:
            print(f"Using existing transcription for {audio_path}")
            with open(txt_path, "r", encoding="utf-8") as f:
                transcription = f.read()
        else:
            # Convert WAV to MP3 if needed
            path_to_transcribe = audio_path
            
            if audio_path.lower().endswith(".wav"):
                print(f"Processing WAV file: {audio_path}")
                mp3_path = convert_wav_to_mp3(audio_path)
                if mp3_path:
                    path_to_transcribe = mp3_path
                else:
                    print(f"Warning: Failed to convert {audio_path}. Will attempt to transcribe the WAV file directly.")
            
            # Transcribe audio
            transcription = transcribe_audio(
                path_to_transcribe,
                txt_path,
                model_size=model_size,
                turbo=args.turbo
            )

        # Enhance note (only if md file doesn't exist or force flag is set)
        if not os.path.exists(md_path) or args.force:
            try:
                enhanced_note = enhance_note(transcription)
                with open(md_path, "w", encoding="utf-8") as f:
                    f.write(enhanced_note)
            except Exception as e:
                print(f"Error enhancing note for {audio_path}: {e}")

    print(f"Processing complete. Output saved to: {output_dir}")

if __name__ == "__main__":
    main()