#!/usr/bin/env python3
"""
Prepare PR from AI response
Converts response format to PR format
"""
import json
from pathlib import Path
from datetime import datetime
import sys

def convert_response_to_pr():
    """Convert AI response to PR format"""
    
    # Find latest response
    response_dir = Path('/shared/ai-gitops/responses')
    response_files = list(response_dir.glob('*_response.json'))
    
    if not response_files:
        print("No response files found")
        return False
    
    latest = max(response_files, key=lambda p: p.stat().st_mtime)
    print(f"Converting response: {latest.name}")
    
    with open(latest, 'r') as f:
        response = json.load(f)
    
    # Extract suggestions and build config
    suggestions = response.get('suggestions', [])
    config_lines = []
    
    for suggestion in suggestions:
        if 'config' in suggestion:
            config_lines.append(suggestion['config'])
    
    if not config_lines:
        print("No configuration in response")
        return False
    
    # Create pending PR directory and file
    pr_dir = Path('/shared/ai-gitops/pending_prs')
    pr_dir.mkdir(parents=True, exist_ok=True)
    
    pr_file = pr_dir / f"pr_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json"
    
    pr_data = {
        "title": f"AI Network Optimization - {response.get('focus_area', 'general').title()}",
        "suggestions": '\n'.join(config_lines),
        "model": "llama2:13b",
        "feedback_aware": response.get('feedback_aware', True),
        "feedback_count": 6,
        "timestamp": datetime.now().isoformat(),
        "focus_area": response.get('focus_area', 'security')
    }
    
    with open(pr_file, 'w') as f:
        json.dump(pr_data, f, indent=2)
    
    print(f"✅ Created PR file: {pr_file.name}")
    return True

if __name__ == "__main__":
    if convert_response_to_pr():
        sys.exit(0)
    else:
        sys.exit(1)