#!/usr/bin/env python3
"""
Example: Visual AI QC Headless Operation
Demonstrates how to use the API without the web interface
"""

import requests
import time
import json

# Configuration
API_BASE = "http://localhost:7183"
IMAGE_PATH = "path/to/your/image.jpg"

def headless_analysis_example():
    """Complete example of headless Visual AI QC analysis"""
    
    print("🤖 Visual AI QC - Headless Analysis Example")
    print("=" * 50)
    
    # 1. Get available profiles
    print("\n📋 Step 1: Getting available profiles...")
    response = requests.get(f"{API_BASE}/api/profiles")
    if response.status_code == 200:
        profiles = response.json()
        print(f"✅ Found {len(profiles)} profile categories")
        for category, profile_list in profiles.items():
            print(f"   {category}: {len(profile_list)} profiles")
    else:
        print(f"❌ Error getting profiles: {response.status_code}")
        return
    
    # 2. Get available reference assets
    print("\n📁 Step 2: Getting reference assets...")
    response = requests.get(f"{API_BASE}/api/brand_guidelines")
    if response.status_code == 200:
        guidelines = response.json()
        print(f"✅ Found {len(guidelines.get('files', {}))} reference assets")
        for file_id, file_info in guidelines.get('files', {}).items():
            print(f"   {file_info['brand_name']}: {file_info['original_filename']}")
    
    # 3. Start analysis with async tracking
    print(f"\n🔍 Step 3: Starting analysis...")
    
    with open(IMAGE_PATH, 'rb') as f:
        files = {'file': f}
        data = {
            'profile': 'diageo_key_visual',  # Use Diageo profile
            'mode': 'json',                  # JSON output
            'reference_asset': 'Hellmanns_20250805_113413'  # Use reference asset
        }
        
        response = requests.post(f"{API_BASE}/api/start_analysis", files=files, data=data)
    
    if response.status_code != 200:
        print(f"❌ Error starting analysis: {response.status_code}")
        return
    
    result = response.json()
    session_id = result.get('session_id')
    
    if not session_id:
        print("❌ No session ID returned")
        return
    
    print(f"✅ Analysis started with session ID: {session_id}")
    
    # 4. Poll for progress
    print("\n⏳ Step 4: Monitoring progress...")
    while True:
        response = requests.get(f"{API_BASE}/api/progress/{session_id}")
        if response.status_code != 200:
            print(f"❌ Error getting progress: {response.status_code}")
            break
            
        progress_data = response.json()
        progress = progress_data.get('progress', {})
        
        if progress.get('stage') == 'complete':
            print("✅ Analysis complete!")
            results = progress.get('result', {})
            break
        else:
            current_step = progress.get('current_check_display', 'Processing...')
            percentage = progress.get('percentage', 0)
            completed = progress.get('completed_checks', 0)
            total = progress.get('total_checks', 0)
            
            print(f"   Progress: {percentage}% - {current_step} ({completed}/{total})")
            time.sleep(2)
    
    # 5. Display results
    print("\n📊 Step 5: Analysis Results")
    print("-" * 30)
    
    summary = results.get('summary', {})
    print(f"Overall Score: {summary.get('overall_score', 0)}/100")
    print(f"Grade: {summary.get('grade', 'Unknown')}")
    print(f"Checks Performed: {summary.get('checks_count', 0)}")
    
    # Show individual check results
    qc_results = results.get('qc_analysis', {}).get('check_results', {})
    print(f"\n🔍 Individual Check Results:")
    for check_name, check_result in qc_results.items():
        if check_result.get('status') == 'completed':
            score = check_result.get('score', 0)
            print(f"   {check_name}: {score}/10")
    
    # 6. Get output files
    print("\n📄 Step 6: Generated Files")
    response = requests.get(f"{API_BASE}/api/output_files")
    if response.status_code == 200:
        files = response.json()
        print(f"✅ {len(files)} output files available")
        for file_info in files[:3]:  # Show latest 3
            print(f"   {file_info['filename']} ({file_info['size']})")
    
    print("\n🎉 Headless analysis complete!")

def simple_analysis_example():
    """Simplified headless analysis"""
    
    print("\n🚀 Simple Headless Analysis")
    print("-" * 30)
    
    with open(IMAGE_PATH, 'rb') as f:
        files = {'file': f}
        data = {
            'profile': 'general_key_visual',
            'mode': 'json'
        }
        
        # Direct analysis (may take longer but simpler)
        response = requests.post(f"{API_BASE}/api/analyze", files=files, data=data)
    
    if response.status_code == 200:
        results = response.json()
        summary = results.get('summary', {})
        print(f"✅ Score: {summary.get('overall_score', 0)}/100")
        print(f"   Grade: {summary.get('grade', 'Unknown')}")
    else:
        print(f"❌ Analysis failed: {response.status_code}")

def brand_detection_example():
    """Example of headless brand detection"""
    
    print("\n🏷️ Brand Detection Example")
    print("-" * 30)
    
    with open(IMAGE_PATH, 'rb') as f:
        files = {'file': f}
        response = requests.post(f"{API_BASE}/api/detect_brand", files=files)
    
    if response.status_code == 200:
        result = response.json()
        print(f"✅ Detected Brand: {result.get('brand', 'Unknown')}")
        print(f"   Confidence: {result.get('confidence', 0)}")
    else:
        print(f"❌ Brand detection failed: {response.status_code}")

if __name__ == "__main__":
    # Run examples (update IMAGE_PATH first!)
    try:
        headless_analysis_example()
        simple_analysis_example() 
        brand_detection_example()
    except FileNotFoundError:
        print("❌ Please update IMAGE_PATH with a valid image file path")
    except requests.exceptions.ConnectionError:
        print("❌ Cannot connect to API server. Make sure it's running on localhost:7183")