#!/usr/bin/env python3
"""
Handle Telegram voice messages - download and transcribe
Usage: telegram_voice_handler.py <bot_token> <file_id> [--model MODEL]
"""

import argparse
import os
import sys
import json
import urllib.request
import tempfile

def download_voice_file(bot_token, file_id, output_path):
    """Download voice file from Telegram"""
    
    # Step 1: Get file path from Telegram
    file_info_url = f"https://api.telegram.org/bot{bot_token}/getFile?file_id={file_id}"
    
    try:
        with urllib.request.urlopen(file_info_url) as response:
            data = json.loads(response.read().decode())
            if not data.get("ok"):
                print(f"Error getting file info: {data}", file=sys.stderr)
                sys.exit(1)
            
            file_path = data["result"]["file_path"]
    except Exception as e:
        print(f"Error fetching file info: {e}", file=sys.stderr)
        sys.exit(1)
    
    # Step 2: Download the actual file
    download_url = f"https://api.telegram.org/file/bot{bot_token}/{file_path}"
    
    try:
        urllib.request.urlretrieve(download_url, output_path)
        return output_path
    except Exception as e:
        print(f"Error downloading file: {e}", file=sys.stderr)
        sys.exit(1)

def transcribe_with_whisper(audio_path, model_size="base"):
    """Transcribe using local Faster-Whisper"""
    
    from faster_whisper import WhisperModel
    
    # Load model (cached after first use)
    model = WhisperModel(model_size, device="cpu", compute_type="int8")
    
    # Transcribe
    segments, info = model.transcribe(audio_path, beam_size=5)
    
    # Collect text
    full_text = []
    for segment in segments:
        full_text.append(segment.text.strip())
    
    return {
        "text": " ".join(full_text),
        "language": info.language,
        "language_probability": info.language_probability
    }

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Download and transcribe Telegram voice message")
    parser.add_argument("bot_token", help="Telegram bot token")
    parser.add_argument("file_id", help="Telegram voice file_id")
    parser.add_argument("--model", default="base",
                       choices=["tiny", "base", "small", "medium", "large"],
                       help="Whisper model size (default: base)")
    
    args = parser.parse_args()
    
    # Allow override from environment
    model = os.environ.get("WHISPER_MODEL", args.model)
    
    # Create temp file for download
    with tempfile.NamedTemporaryFile(suffix=".ogg", delete=False) as tmp:
        temp_path = tmp.name
    
    try:
        # Download
        print(f"Downloading voice file...", file=sys.stderr)
        download_voice_file(args.bot_token, args.file_id, temp_path)
        
        # Transcribe
        print(f"Transcribing with {model} model...", file=sys.stderr)
        result = transcribe_with_whisper(temp_path, model)
        
        # Output result
        print(json.dumps(result))
        
    finally:
        # Cleanup
        if os.path.exists(temp_path):
            os.remove(temp_path)