CodeMentor AI

Track your coding progress, generate study plans, execute code online, and accelerate your learning journey — all in one platform.

---

📌 About the Project

CodeMentor AI is an advanced web-based coding assistant and progress tracker built using Flask + Python.
It provides developers with:

• AI-Powered Tutoring: Ask concepts, get explanations, and walk through coding paradigms dynamically.
• Spaced Repetition Flashcards: Automatically generate revision decks on any topic using Google Gemini/OpenAI, and schedule them using a SuperMemo algorithm.
• Code Execution Sandbox: Safe, cross-platform isolated sandbox supporting real-time Python/C++ code compilation and automated test case runner.
• Collaborative Study Groups: Matches you with peers based on your target companies, goals, and coding progress.
• Competitive Contests: Admin-created coding challenges with leaderboards, runtime scoring, and visual podiums.

---

📸 Screenshots

📊 CodeMentor AI Dashboard

---

🗂️ Project Structure

The project follows a standard Flask application factory architecture:

CodeMentor AI/
│
├── app/
│   ├── __init__.py             # Flask application factory & database setup
│   ├── models.py               # Unified database models
│   ├── routes.py               # Controller routes (auth, dashboards, contests)
│   ├── ai/                     # AI abstraction layer (Gemini, Claude, OpenAI, DeepSeek)
│   ├── services/               # Core business services (code execution, notifications)
│   ├── static/                 # Front-end assets (consolidated CSS, JavaScript)
│   └── templates/              # HTML Templates
│
├── tests/                      # Testing package (34 tests with 80%+ coverage)
├── Dockerfile                  # Production container definition
├── docker-compose.yml          # Container configuration for local environments
├── .env.example                # Default configuration environment variables
├── Procfile                    # Production startup commands
├── render.yaml                 # Infrastructure-as-code deployment settings
├── main.py                     # Entrypoint script
└── README.md

---

🛠️ Installation & Setup

1️⃣ Clone the repository

git clone https://github.com/manojk909/CODE-TRACK-PRO.git
cd CODE-TRACK-PRO

2️⃣ Create & activate virtual environment

python -m venv venv
source venv/bin/activate        # macOS/Linux
venv\Scripts\activate           # Windows

3️⃣ Install dependencies

pip install -r render_requirements.txt

4️⃣ Set up environment variables

Copy the template configuration:

cp .env.example .env

Open .env and fill in your custom keys (e.g., GEMINI_API_KEY, OPENAI_API_KEY).

5️⃣ Seed local database

Create tables and populate sample problems:

python seed_db.py

6️⃣ Run the application

python main.py

Open http://localhost:5000 in your browser.

---

📊 Future Roadmap

• Voice AI tutor
• Resume analyzer
• Interview simulator
• Competitive coding arena
• AI coding agent
• Mobile application
• Learning recommendation engine

---

🤝 Contributing

Contributions are welcome.

Fork → Create Branch → Commit → Push → Pull Request

---