#!/usr/bin/env python3
"""
Launch script for Clinical Trial Matching Pipeline

Checks dependencies and provides helpful startup information.
"""

import sys
import subprocess
import importlib.util

def check_package(package_name, display_name=None):
    """Check if a package is installed."""
    if display_name is None:
        display_name = package_name
    
    spec = importlib.util.find_spec(package_name)
    if spec is None:
        return False, display_name
    return True, display_name

def check_dependencies():
    """Check if all required dependencies are installed."""
    
    required_packages = [
        ('gradio', 'gradio'),
        ('pandas', 'pandas'),
        ('numpy', 'numpy'),
        ('torch', 'PyTorch'),
        ('transformers', 'transformers'),
        ('sentence_transformers', 'sentence-transformers'),
    ]
    
    optional_packages = [
        ('vllm', 'vLLM (for faster LLM inference)'),
    ]
    
    print("Checking dependencies...\n")
    
    missing = []
    for package, display in required_packages:
        installed, name = check_package(package, display)
        status = "✓" if installed else "✗"
        print(f"  {status} {name}")
        if not installed:
            missing.append(package)
    
    print("\nOptional packages:")
    for package, display in optional_packages:
        installed, name = check_package(package, display)
        status = "✓" if installed else "○"
        print(f"  {status} {name}")
    
    if missing:
        print(f"\n❌ Missing required packages: {', '.join(missing)}")
        print("\nInstall with:")
        print(f"  pip install {' '.join(missing)}")
        print("\nOr install all requirements:")
        print("  pip install -r requirements.txt")
        return False
    
    print("\n✓ All required dependencies installed!")
    return True

def check_cuda():
    """Check CUDA availability."""
    try:
        import torch
        if torch.cuda.is_available():
            print(f"\n🚀 CUDA available!")
            print(f"   GPU count: {torch.cuda.device_count()}")
            for i in range(torch.cuda.device_count()):
                print(f"   GPU {i}: {torch.cuda.get_device_name(i)}")
            return True
        else:
            print("\n⚠️  CUDA not available - running on CPU")
            print("   For better performance, install PyTorch with CUDA:")
            print("   pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121")
            return False
    except ImportError:
        return False

def print_startup_info():
    """Print helpful startup information."""
    print("\n" + "="*70)
    print("Clinical Trial Matching Pipeline")
    print("="*70)
    print("\nStarting Gradio web interface...")
    print("\nOnce started, the interface will be available at:")
    print("  Local:   http://localhost:7860")
    print("  Network: http://0.0.0.0:7860")
    print("\nPress Ctrl+C to stop the server.")
    print("\n" + "="*70 + "\n")

def main():
    """Main launch function."""
    
    # Check dependencies
    if not check_dependencies():
        sys.exit(1)
    
    # Check CUDA
    check_cuda()
    
    # Print startup info
    print_startup_info()
    
    # Launch the app
    try:
        import trial_matching_app
        # The app will launch automatically when imported
    except KeyboardInterrupt:
        print("\n\nShutting down gracefully...")
        sys.exit(0)
    except Exception as e:
        print(f"\n❌ Error launching application: {e}")
        import traceback
        traceback.print_exc()
        sys.exit(1)

if __name__ == "__main__":
    main()