#!/usr/bin/env python3
"""Test Gemini directly using the models endpoint."""

import requests
import json

def test_direct_gemini():
    """Test Gemini directly through the models endpoint."""
    
    print("🎯 Direct Gemini Test")
    print("=" * 40)
    
    # Simple test transcript
    test_transcript = """
    This is a comprehensive video about artificial intelligence and machine learning. 
    The speaker discusses the evolution of neural networks, from simple perceptrons to 
    complex deep learning architectures. Key topics covered include convolutional neural 
    networks for computer vision, recurrent neural networks for sequence processing, 
    and transformer architectures that have revolutionized natural language processing. 
    The video also explores practical applications in healthcare, autonomous vehicles, 
    and recommendation systems. The presenter emphasizes the importance of ethical AI 
    development and responsible deployment of machine learning systems in production 
    environments.
    """.strip()
    
    request_data = {
        "model": "gemini-1.5-pro",  # Explicitly request Gemini
        "transcript": test_transcript,
        "options": {
            "length": "brief",
            "focus_areas": ["AI", "machine learning", "neural networks"]
        }
    }
    
    try:
        print("📤 Testing direct Gemini summarization...")
        response = requests.post(
            "http://localhost:8000/api/models/summarize",
            json=request_data,
            headers={"Content-Type": "application/json"},
            timeout=60
        )
        
        print(f"📨 Response status: {response.status_code}")
        
        if response.status_code == 200:
            result = response.json()
            print("✅ SUCCESS! Gemini summarization worked!")
            
            # Display results
            if 'summary' in result:
                summary = result['summary']
                print(f"\n📋 Summary: {summary}")
            
            if 'key_points' in result:
                key_points = result.get('key_points', [])
                print(f"\n🔑 Key Points ({len(key_points)} found):")
                for i, point in enumerate(key_points, 1):
                    print(f"  {i}. {point}")
            
            if 'cost_data' in result:
                cost_data = result['cost_data']
                cost = cost_data.get('total_cost_usd', 0)
                input_tokens = cost_data.get('input_tokens', 0)
                output_tokens = cost_data.get('output_tokens', 0)
                print(f"\n💰 Cost: ${cost:.4f}")
                print(f"📄 Input tokens: {input_tokens:,}")
                print(f"📝 Output tokens: {output_tokens:,}")
            
            if 'processing_metadata' in result:
                metadata = result['processing_metadata']
                model_used = metadata.get('model_used', 'N/A')
                processing_time = metadata.get('processing_time_seconds', 0)
                print(f"\n🤖 Model: {model_used}")
                print(f"⚡ Time: {processing_time:.2f}s")
                
                if 'large_context_advantage' in metadata:
                    advantage = metadata['large_context_advantage']
                    print(f"🚀 Context advantage: {advantage}")
            
            return True
            
        else:
            print(f"❌ Failed with status {response.status_code}")
            try:
                error = response.json()
                print(f"Error: {error}")
            except:
                print(f"Error text: {response.text}")
            
            return False
            
    except Exception as e:
        print(f"❌ Exception: {e}")
        return False

def test_health_check():
    """Quick health check."""
    print("\n=== Health Check ===")
    
    try:
        response = requests.get("http://localhost:8000/health")
        if response.status_code == 200:
            print("✅ Backend is healthy")
            return True
        else:
            print(f"❌ Health check failed: {response.status_code}")
            return False
    except Exception as e:
        print(f"❌ Health check error: {e}")
        return False

if __name__ == "__main__":
    if test_health_check():
        success = test_direct_gemini()
        
        if success:
            print("\n🎉 ✅ GEMINI DIRECT TEST PASSED!")
            print("✅ Gemini 1.5 Pro is working correctly")
            print("✅ Ready for YouTube video processing")
        else:
            print("\n❌ Direct Gemini test failed")
    else:
        print("❌ Backend not available")
        
    print("\n" + "=" * 40)