deploy_to_huggingface.py

#!/usr/bin/env python3
"""
Script to deploy the Patient Evaluation App to Hugging Face Spaces for permanent hosting.
This will give you a permanent URL that doesn't expire.
"""

import os
import subprocess
import sys

def check_requirements():
    """Check if required packages are installed"""
    try:
        import gradio
        print("✅ Gradio is installed")
    except ImportError:
        print("❌ Gradio not found. Please install with: pip install gradio")
        return False
    
    try:
        subprocess.run(["huggingface-cli", "--help"], capture_output=True, check=True)
        print("✅ Hugging Face CLI is available")
    except (subprocess.CalledProcessError, FileNotFoundError):
        print("❌ Hugging Face CLI not found. Please install with: pip install huggingface_hub[cli]")
        return False
    
    return True

def check_login():
    """Check if user is logged into Hugging Face"""
    try:
        result = subprocess.run(["huggingface-cli", "whoami"], capture_output=True, text=True)
        if result.returncode == 0:
            print(f"✅ Logged in as: {result.stdout.strip()}")
            return True
        else:
            print("❌ Not logged into Hugging Face")
            return False
    except Exception as e:
        print(f"❌ Error checking login status: {e}")
        return False

def create_space_config():
    """Create the space configuration file"""
    config_content = """---
title: Patient Evaluation System
emoji: 🏥
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 3.50.2
app_file: chatgpt.py
pinned: false
license: mit
---

# Patient Evaluation System

A comprehensive system for medical experts to evaluate AI-generated patient summaries.

## Features
- Multi-admission patient data evaluation
- Simplified comment system
- Google Drive integration for data backup
- Real-time statistics and analytics
- CSV/JSON data export

## Usage
1. Select a patient sample from the evaluation tab
2. Review the AI-generated summary against the original data
3. Provide ratings and feedback
4. Submit evaluation for analysis

## Setup
The application will guide you through any necessary setup steps.
"""
    
    with open("README.md", "w") as f:
        f.write(config_content)
    print("✅ Created README.md for Hugging Face Space")

def deploy():
    """Deploy to Hugging Face Spaces"""
    if not check_requirements():
        return False
    
    if not check_login():
        print("\n🔑 Please login to Hugging Face first:")
        print("Run: huggingface-cli login")
        print("Then run this script again.")
        return False
    
    print("\n🚀 Starting deployment to Hugging Face Spaces...")
    
    # Create space config
    create_space_config()
    
    try:
        # Deploy using gradio
        print("📤 Deploying application...")
        result = subprocess.run(["gradio", "deploy", "--hf-token"], 
                              input="y\n", text=True, capture_output=True)
        
        if result.returncode == 0:
            print("✅ Deployment successful!")
            print("\n🌐 Your permanent URL will be:")
            print("https://your-username-patient-evaluation.hf.space")
            print("\n💡 Tips:")
            print("- The URL will be permanent and won't expire")
            print("- You can update the app by running this script again")
            print("- Your Google Drive data will be preserved")
            return True
        else:
            print(f"❌ Deployment failed: {result.stderr}")
            return False
            
    except Exception as e:
        print(f"❌ Error during deployment: {e}")
        return False

def main():
    print("🏥 Patient Evaluation System - Hugging Face Deployment")
    print("=" * 60)
    
    print("\n📋 This script will deploy your app to Hugging Face Spaces")
    print("Benefits:")
    print("- ✅ Permanent URL (no 72-hour expiry)")
    print("- ✅ Free hosting")
    print("- ✅ HTTPS security")
    print("- ✅ Easy updates")
    
    answer = input("\n❓ Do you want to proceed? (y/n): ").lower().strip()
    
    if answer in ['y', 'yes']:
        if deploy():
            print("\n🎉 Deployment completed successfully!")
        else:
            print("\n😞 Deployment failed. Please check the errors above.")
    else:
        print("👋 Deployment cancelled.")

if __name__ == "__main__":
    main()