🔐🤖 Building a Secure AI-Powered Coding Challenge Platform

In the rapidly evolving world of software development, staying sharp with coding skills is essential. I built a secure, AI-powered platform that generates personalized coding challenges using modern web technologies. This project demonstrates how to combine artificial intelligence with robust security practices to create an educational tool that's both powerful and safe.

🚀 FastAPI + ⚡ React + 🔐 Clerk + 🤖 OpenAI = The ultimate secure coding challenge generator with intelligent question generation and enterprise-grade authentication!

Live Demo GitHub Repository Demo Video

🎯 Project Vision

The platform addresses a common challenge in developer education: generating diverse, high-quality coding questions at scale while maintaining user security and preventing abuse. By leveraging AI for content generation and implementing robust authentication, the system provides a personalized learning experience with enterprise-grade security.

Core Problems Solved

Content Scalability: AI generates unlimited unique coding challenges
Security First: JWT-based authentication with webhook verification
Abuse Prevention: Daily quotas and rate limiting
User Experience: Seamless authentication flow with challenge history
Educational Value: Structured questions with detailed explanations

🎬 Live Demo

See the platform in action! This demo showcases the complete user journey from authentication to challenge generation:

🎯 Demo Highlights: - Secure Authentication: Clerk integration with seamless login - AI Challenge Generation: Real-time question creation with OpenAI - Interactive UI: Modern React interface with smooth animations - Quota Management: Daily limits and usage tracking - Challenge History: Personal archive of completed challenges

⚡ Tech Stack Architecture

🏗️ System Architecture

Hover over components to explore the tech stack

🔐 Security-First Architecture

Security isn't an afterthought—it's built into every layer of the application.

Authentication Flow

sequenceDiagram
    participant U as User
    participant F as Frontend
    participant C as Clerk
    participant B as Backend
    participant AI as OpenAI

    U->>F: Access Application
    F->>C: Authenticate User
    C->>F: Return JWT Token
    F->>B: API Request + JWT
    B->>C: Verify Token
    C->>B: Token Valid
    B->>AI: Generate Challenge
    AI->>B: Return Challenge
    B->>F: Secure Response
    F->>U: Display Challenge

Security Layers

JWT Authentication: Clerk-managed tokens with automatic refresh
Webhook Verification: Svix-powered signature validation
Rate Limiting: Daily quotas prevent API abuse
CORS Protection: Configured for secure cross-origin requests
Environment Security: Secure credential management

🤖 AI-Powered Challenge Generation

The heart of the platform lies in its intelligent challenge generation system.

Challenge Structure

interface CodingChallenge {
  question: string;
  options: string[];
  correct_answer: number;
  explanation: string;
  difficulty: 'easy' | 'medium' | 'hard';
  topic: string;
}

AI Prompt Engineering

The system uses carefully crafted prompts to ensure consistent, high-quality output:

def generate_challenge_prompt(difficulty: str, topic: str) -> str:
    return f"""
    Generate a {difficulty} coding challenge about {topic}.

    Requirements:
    - Multiple choice with 4 options
    - One correct answer
    - Detailed explanation
    - Practical, interview-style question

    Return valid JSON matching the schema.
    """

Intelligent Features

Difficulty Scaling: AI adjusts complexity based on user selection
Topic Diversity: Covers algorithms, data structures, system design
Explanation Quality: Detailed reasoning for learning reinforcement
Validation: Pydantic models ensure data integrity

🎯 User Experience Design

Challenge Generation Flow

🔄 Challenge Generation Flow

Watch the process in action

🎯

Select Difficulty

Choose your challenge level

🤖

AI Generation

OpenAI creates your question

💭

Answer Challenge

Test your knowledge

📊

View Results

Learn from explanations

Current Step:

Key UX Features

Instant Feedback: Real-time challenge generation
Progress Tracking: Visual quota indicators
History Management: Personal challenge archive
Responsive Design: Seamless mobile experience
Error Handling: Graceful degradation with fallbacks

📊 Technical Implementation

Backend API Design

@app.post("/api/generate-challenge")
async def generate_challenge(
    request: ChallengeRequest,
    user: User = Depends(get_current_user)
):
    # Check daily quota
    if not await check_user_quota(user.id):
        raise HTTPException(status_code=429, detail="Daily quota exceeded")

    # Generate AI challenge
    challenge = await ai_generator.create_challenge(
        difficulty=request.difficulty,
        topic=request.topic
    )

    # Save to database
    await save_challenge(user.id, challenge)

    # Update quota
    await update_user_quota(user.id)

    return challenge

Frontend State Management

const useChallenge = () => {
  return useQuery({
    queryKey: ['challenge', difficulty],
    queryFn: async () => {
      const response = await fetch('/api/generate-challenge', {
        method: 'POST',
        headers: {
          'Authorization': `Bearer ${await getToken()}`,
          'Content-Type': 'application/json'
        },
        body: JSON.stringify({ difficulty, topic })
      });
      return response.json();
    },
    staleTime: 0 // Always fresh challenges
  });
};

Database Schema

-- Users managed by Clerk
CREATE TABLE challenges (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    user_id TEXT NOT NULL,
    question TEXT NOT NULL,
    options JSON NOT NULL,
    correct_answer INTEGER NOT NULL,
    explanation TEXT NOT NULL,
    difficulty TEXT NOT NULL,
    topic TEXT NOT NULL,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

CREATE TABLE user_quotas (
    user_id TEXT PRIMARY KEY,
    daily_count INTEGER DEFAULT 0,
    last_reset DATE DEFAULT CURRENT_DATE
);

🚀 Performance Optimizations

Frontend Optimizations

Code Splitting: Route-based lazy loading
React Query: Intelligent caching and background updates
Vite + SWC: Lightning-fast development builds
Bundle Analysis: Optimized chunk sizes

Backend Optimizations

UV Package Manager: 10-100x faster than pip
SQLAlchemy 2.0: Async database operations
Connection Pooling: Efficient database connections
Response Caching: Reduced API latency

AI Integration Optimizations

Prompt Caching: Reuse optimized prompts
Fallback Strategies: Graceful degradation
Rate Limiting: Prevent API quota exhaustion
Response Validation: Ensure data quality

🔮 Advanced Features

Quota Management System

async def reset_daily_quotas():
    """Reset quotas for all users daily"""
    await database.execute("""
        UPDATE user_quotas 
        SET daily_count = 0, last_reset = CURRENT_DATE
        WHERE last_reset < CURRENT_DATE
    """)

Webhook Security

@app.post("/webhooks/clerk")
async def handle_clerk_webhook(request: Request):
    # Verify webhook signature
    payload = await request.body()
    headers = request.headers

    try:
        event = svix.Webhook(clerk_webhook_secret).verify(
            payload, headers
        )
    except Exception:
        raise HTTPException(status_code=400, detail="Invalid signature")

    # Process user events
    if event["type"] == "user.created":
        await create_user_quota(event["data"]["id"])

    return {"status": "success"}

📈 Real-World Impact

Educational Benefits

Skill Assessment: Evaluate programming knowledge
Interview Preparation: Practice with realistic questions
Continuous Learning: Daily challenge routine
Progress Tracking: Monitor improvement over time

Technical Benefits

Scalable Architecture: Handle thousands of users
Security Best Practices: Enterprise-grade protection
Modern Stack: Latest web technologies
Developer Experience: Fast development workflow

🔧 Development Workflow

Local Development Setup

# Backend setup
cd backend
uv sync
uv run server.py

# Frontend setup
cd frontend
npm install
npm run dev

# Ngrok for webhooks
ngrok http 8000 --domain=your-domain.ngrok-free.app

Environment Configuration

# Required Environment Variables
OPENAI_API_KEY=your_openai_key
CLERK_SECRET_KEY=your_clerk_secret
NGROK_AUTHTOKEN=your_ngrok_token
NGROK_DOMAIN=your-domain.ngrok-free.app
DATABASE_URL=sqlite:///./challenges.db

💡 Key Learnings

Building this platform taught me valuable lessons about modern web development:

Security First: Authentication should be built-in, not bolted-on
AI Integration: Structured outputs are more reliable than free-form text
User Experience: Real-time feedback improves engagement
Performance: Modern tools like UV and Vite dramatically improve DX
Architecture: Clean separation of concerns enables scalability

🎉 Conclusion

This secure AI-powered coding challenge platform demonstrates how to build modern, scalable applications that prioritize both user experience and security. By combining cutting-edge AI capabilities with robust authentication and thoughtful architecture, we can create educational tools that are both powerful and safe.

The project showcases the potential of AI in education while maintaining the security standards required for production applications. As AI continues to evolve, platforms like this will play a crucial role in developer education and skill assessment.

Ready to test your coding skills? Try the platform and see how AI can personalize your learning journey while keeping your data secure!

🏷️ Tags

#AI #Security #FastAPI #React #Authentication #OpenAI #Webhooks #Education #FullStack #ModernWeb