CodePath AI - An AI-Assisted Beginner Coding Platform

🌍 Live Website

https://codepath-ai-frontend.onrender.com/

🎯 Overview

CodePath AI is a production-ready web application designed to help beginners learn programming through:

• Micro-Lessons: Bite-sized lessons covering programming fundamentals
• Hands-On Coding: In-browser code editor with real-time execution
• AI-Guided Hints: Intelligent mentoring that guides without giving solutions
• Progress Tracking: Streaks, badges, and leaderboards to keep you motivated

⚠️ Core Philosophy

The AI Mentor NEVER provides complete solutions. Instead, it offers:

• Conceptual explanations
• Logical hints and guiding questions
• Error reasoning and debugging guidance
• Optimization suggestions and best practices

This approach ensures learners develop problem-solving skills rather than just copying code.

🚀 Learning Tracks

1. Java with DSA - Java fundamentals and Data Structures & Algorithms
2. Data Science - Python, NumPy, Pandas, and data analysis
3. AI Engineer - Machine learning concepts and implementations

🛠️ Tech Stack

Backend

• FastAPI - Modern Python web framework
• MongoDB - NoSQL database with Motor async driver
• JWT - Secure authentication with access & refresh tokens
• Piston API - Safe code execution in isolated containers

Frontend

• React 18 - UI library with hooks
• Vite - Lightning-fast build tool
• Tailwind CSS - Utility-first styling
• Monaco Editor - VS Code's editor in the browser
• Zustand - Lightweight state management
• React Router v6 - Client-side routing

📁 Project Structure

🧩 Team Module Architecture (4 Modules)

Project ownership is divided into these modules:

1. User Management & Authentication
2. Learning Content & Micro-Lessons
3. Coding Practice & AI Guidance
4. Progress Tracking & Recommendation

The backend now registers routes through module entrypoints in backend/modules/, and the frontend route wiring imports module entrypoints from frontend/src/modules/.

For full file ownership mapping and push order, see MODULE_SPLIT.md.

codepath-ai/
├── backend/
│   ├── main.py                 # FastAPI application entry
│   ├── config/
│   │   ├── database.py         # MongoDB connection
│   │   └── settings.py         # Environment settings
│   ├── models/
│   │   ├── user.py             # User model
│   │   ├── lesson.py           # Lesson model
│   │   ├── problem.py          # Problem model
│   │   ├── progress.py         # Progress model
│   │   └── ai_hint.py          # AI hint model
│   ├── routes/
│   │   ├── auth.py             # Authentication endpoints
│   │   ├── lessons.py          # Lesson CRUD
│   │   ├── practice.py         # Problem solving
│   │   ├── progress.py         # Progress tracking
│   │   └── ai_mentor.py        # AI hint endpoints
│   ├── services/
│   │   ├── auth_service.py     # Auth business logic
│   │   ├── lesson_service.py   # Lesson operations
│   │   ├── problem_service.py  # Problem operations
│   │   ├── code_execution_service.py  # Piston API
│   │   ├── progress_service.py # Stats & badges
│   │   └── ai_mentor_service.py # AI mentoring
│   ├── ai/
│   │   └── prompts.py          # AI prompt templates
│   └── utils/
│       └── security.py         # JWT & password utils
├── frontend/
│   ├── src/
│   │   ├── main.jsx            # React entry
│   │   ├── App.jsx             # Routes & layouts
│   │   ├── components/
│   │   │   ├── layouts/        # MainLayout, AuthLayout
│   │   │   └── editor/         # CodeEditor, OutputPanel, AIHintPanel
│   │   ├── pages/
│   │   │   ├── HomePage.jsx
│   │   │   ├── DashboardPage.jsx
│   │   │   ├── LessonsPage.jsx
│   │   │   ├── ProblemsPage.jsx
│   │   │   ├── ProblemSolvePage.jsx
│   │   │   ├── ProgressPage.jsx
│   │   │   ├── ProfilePage.jsx
│   │   │   └── auth/
│   │   ├── services/           # API service layer
│   │   └── stores/             # Zustand stores
│   ├── package.json
│   ├── vite.config.js
│   └── tailwind.config.js
├── requirements.txt
├── Dockerfile
├── .env.example
└── README.md

🔧 Installation & Setup

Prerequisites

• Python 3.11+
• Node.js 18+
• MongoDB (local or Atlas)
• OpenAI or Anthropic API key

Backend Setup

1. Clone the repository

   git clone https://github.com/yourusername/codepath-ai.git
   cd codepath-ai

2. Create virtual environment

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies

   pip install -r requirements.txt

4. Configure environment

   cp .env.example .env
   # Edit .env with your settings

5. Run the backend

   cd backend
   uvicorn main:app --reload --host 0.0.0.0 --port 8000

Frontend Setup

1. Install dependencies

   cd frontend
   npm install

2. Start development server

   npm run dev

3. Build for production

   npm run build

🔐 Environment Variables

Create a .env file with the following:

# MongoDB
MONGODB_URL=mongodb://localhost:27017
DATABASE_NAME=codepath_ai

# JWT
JWT_SECRET_KEY=your-super-secret-key-min-32-chars
JWT_ALGORITHM=HS256
ACCESS_TOKEN_EXPIRE_MINUTES=30
REFRESH_TOKEN_EXPIRE_DAYS=7

# AI Provider (choose one)
OPENAI_API_KEY=sk-your-openai-key
# OR
ANTHROPIC_API_KEY=your-anthropic-key

# Piston API
PISTON_API_URL=https://emkc.org/api/v2/piston

# Frontend URL (for CORS)
FRONTEND_URL=http://localhost:5173

# Environment
ENVIRONMENT=development

🌐 API Endpoints

Authentication

Method	Endpoint	Description
POST	/api/auth/register	Register new user
POST	/api/auth/login	Login user
POST	/api/auth/refresh	Refresh access token
POST	/api/auth/change-password	Change password
GET	/api/auth/me	Get current user
PUT	/api/auth/profile	Update profile

Lessons

Method	Endpoint	Description
GET	/api/lessons	List lessons
GET	/api/lessons/{id}	Get lesson details
GET	/api/lessons/tracks	Get learning tracks
POST	/api/lessons/{id}/complete	Mark as complete

Practice

Method	Endpoint	Description
GET	/api/practice/problems	List problems
GET	/api/practice/problems/{id}	Get problem
POST	/api/practice/problems/{id}/run	Run code
POST	/api/practice/problems/{id}/submit	Submit solution

AI Mentor

Method	Endpoint	Description
POST	/api/ai/hint	Get AI hint
POST	/api/ai/analyze-error	Analyze code error
POST	/api/ai/ask	Ask AI question

Progress

Method	Endpoint	Description
GET	/api/progress/stats	Get user stats
GET	/api/progress/badges	Get earned badges
GET	/api/progress/leaderboard	Get leaderboard

🐳 Docker Deployment

# Build the image
docker build -t codepath-ai .

# Run the container
docker run -d -p 8000:8000 \
  -e MONGODB_URL=your-mongo-url \
  -e JWT_SECRET_KEY=your-secret \
  -e OPENAI_API_KEY=your-key \
  codepath-ai

🚀 Deployment on Render

1. Create a new Web Service on Render
2. Connect your GitHub repository
3. Set build command: pip install -r requirements.txt
4. Set start command: cd backend && uvicorn main:app --host 0.0.0.0 --port $PORT
5. Add environment variables in Render dashboard

🧪 Testing

# Backend tests
cd backend
pytest

# Frontend tests
cd frontend
npm test

🎨 Features

For Learners

• 📚 Structured micro-lessons by track
• 💻 In-browser code editor with syntax highlighting
• 🤖 AI mentor for guidance (never gives solutions!)
• 📊 Progress tracking with streaks and badges
• 🏆 Leaderboard to compete with others

For Admins

• Create and manage lessons
• Add coding problems with test cases
• Configure AI prompt settings
• View user analytics

🤖 AI Mentoring Rules

The AI strictly follows these guidelines:

1. NEVER provide complete code solutions
2. NEVER write the function body or implementation
3. ALWAYS guide with questions and hints
4. FOCUS on teaching concepts and problem-solving

Example AI response:

"I notice you're trying to find the maximum element. Think about this: what happens when you compare two numbers? How could you use that comparison as you go through each element?"

🤝 Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📧 Support

For questions or issues, please open a GitHub issue or contact the team.

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