24f3001764/llm_code_deployment-1

LLM Code Deployment API

Automated web application generation and deployment system for TDS 2025 Term 3 Project 1.

🎯 Overview

This API receives task requests, generates web applications using LLM, deploys them to GitHub Pages, and notifies evaluation endpoints.

📡 API Endpoints

Health Check

GET /

Returns API status and version.

Submit Task

POST /request

Request Body:

{
  "email": "student@example.com",
  "secret": "your-secret-key",
  "task": "task-id",
  "round": 1,
  "nonce": "unique-nonce",
  "brief": "Task description",
  "checks": ["requirement1", "requirement2"],
  "evaluation_url": "https://evaluation-endpoint.com",
  "attachments": []
}

Response:

{
  "status": "accepted",
  "message": "Task accepted for processing",
  "task": "task-id",
  "round": 1
}

Check Status

GET /status/{task_id}

Returns processing status for a task.

🔧 Configuration

Required environment variables (set in Space Settings → Repository Secrets):

• —STUDENT_SECRET - Your unique authentication secret
• —OPENAI_API_KEY - OpenAI API key for LLM generation
• —GITHUB_TOKEN - GitHub Personal Access Token (repo + workflow scopes)
• —GITHUB_USERNAME - Your GitHub username

🚀 How It Works

1. 1.Receive Request - API receives task via POST /request
2. 2.Immediate Response - Returns 200 OK immediately
3. 3.Background Processing:
4. 4.Decode attachments
5. 5.Generate app using LLM
6. 6.Create GitHub repository
7. 7.Deploy to GitHub Pages
8. 8.Notify - Send completion notification to evaluation URL

📦 Features

• —✅ Async background task processing
• —✅ Automatic GitHub repo creation
• —✅ GitHub Pages deployment
• —✅ Retry logic with exponential backoff
• —✅ Comprehensive logging
• —✅ Error handling
• —✅ Automated security scanning for secrets
• —✅ Multi-round support (Round 1, 2, N)
• —✅ Real-time status tracking
• —✅ Interactive test client
• —✅ One-command startup with validation

🔒 Security

• —✅ Secret-based authentication
• —✅ Environment variable configuration
• —✅ No hardcoded credentials
• —✅ Automated secret scanning (15+ patterns)
• —✅ Pattern detection for API keys, tokens, passwords
• —✅ Masked logging for sensitive data
• —✅ Pre-deployment security checks

📚 Documentation

For detailed setup and usage instructions, see the documentation files in the root directory:

• —`PROJECT_SUMMARY.md` - Complete project overview and status
• —`QUICKSTART.md` - Quick start guide (5 minutes)
• —`SETUP.md` - Detailed local setup instructions
• —`USAGE_GUIDE.md` - API usage and troubleshooting
• —`ARCHITECTURE.md` - System design and components
• —`DEPLOYMENT_CHECKLIST.md` - Deployment guide

🚀 Quick Start

# 1. Install dependencies
pip install -r requirements.txt

# 2. Configure environment
cp .env.example .env
# Edit .env with your credentials

# 3. Validate setup
python validate_setup.py

# 4. Start server
python start.py
# Or on Windows: start.bat

# 5. Test API
python test/test_client.py
# Or on Windows: run_tests.bat

🐛 Troubleshooting

API not responding?

• —Check Space logs in Hugging Face
• —Verify all environment variables are set
• —Ensure GitHub token has correct permissions

GitHub deployment failing?

• —Verify GitHub token is valid
• —Check GitHub username is correct
• —Ensure repo doesn't already exist

LLM generation failing?

• —Verify OpenAI API key is valid
• —Check API credits/quota
• —Review logs for specific errors

📞 Support

• —Hugging Face Spaces Documentation
• —FastAPI Documentation
• —GitHub API Documentation

Version: 1.0.0 Last Updated: 2025-10-11