ScholarMate - AI-Powered Learning Companion

If you find this project helpful, please consider ⭐ starring the repository!

---

ScholarMate is a fully stack AI project and intelligent tutoring platform that leverages advanced AI technology to provide personalized learning experiences across various subjects and educational levels. Powered by the DeepSeek-R1 model, it delivers high-quality, contextual responses optimized for educational purposes.

---

📸 Screenshots

---

✨ Features

• Advanced AI Model: Utilizes DeepSeek-R1 with optimized parameters
• Multi-Subject Support: Mathematics, Physics, Chemistry, Computer Science
• Curriculum Alignment: Supports General, IB, AP, Cambridge
• Grade Level Adaptation: From Pre-School to Post-Doctoral
• Interactive Sessions: Real-time Q&A with detailed explanations
• Progress Tracking: Visual analytics of learning progress
• Session History: Comprehensive record of past learning interactions
• Personalized Learning: Adapts to individual learning styles and pace
• Modern UI: Clean, responsive dark-mode interface
• Accessibility: ARIA-compliant navigation
• Mobile-Friendly: Optimized for all screen sizes
• File Upload Support: Easy attachment sharing for questions

---

🛠️ Tech Stack

• Backend: Flask 3.0.2, SQLAlchemy 2.0.41 (SQLite), Flask-Login, Flask-Migrate, WTForms, Bcrypt, Python-dotenv
• Frontend: Jinja2, TailwindCSS, FontAwesome, Vanilla JS (ES6+), Responsive Design, Dark Mode
• AI Integration: DeepSeek-R1, Markdown with LaTeX support, custom parameter tuning
• Development & Deployment: Gunicorn, Git, Python 3.8+, PEP 8, Markdown docs, venv

---

🚀 Installation

1. Clone the repository:

   git clone https://github.com/yourusername/scholarmate.git
   cd scholarmate

2. Create and activate a virtual environment:

   python -m venv venv
   # Windows
   venv\Scripts\activate
   # Unix/MacOS
   source venv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables: Create a .env file in the root directory with:

   SECRET_KEY=your_secret_key_here
   DATABASE_URL=sqlite:///scholarmate.db
   

5. Initialize the database:

   flask db upgrade

6. Run the application:

   python app.py

   The application will be available at http://localhost:5000

---

📂 Project Structure

scholarmate/
├── app.py              # Main application file
├── templates/          # HTML templates
│   ├── base.html
│   ├── about.html
│   ├── contact.html
│   ├── dashboard.html
│   └── ... (other templates)
├── static/             # Static files
│   └── css/
├── migrations/         # Database migrations
└── requirements.txt    # Project dependencies

---

🧠 Features in Detail

AI Tutoring

• Model: DeepSeek-R1
• Parameters:
  • Temperature: 0.5 (for consistent, focused responses)
  • Max Tokens: 1536 (optimal length for educational content)
  • Top P: 0.9 (balanced creativity and accuracy)
  • Frequency Penalty: 0.3 (reduces repetition)
  • Presence Penalty: 0.3 (maintains topic relevance)
• Step-by-step explanations with LaTeX support
• Real-time response generation

User Management

• Secure authentication system
• Profile customization
• Grade level and curriculum selection
• Progress tracking and analytics

Support System

• Comprehensive help center
• Feedback submission with file attachments
• Priority-based support tickets
• Contact form with response tracking

---

🤝 Contributing

1. Fork the repository
2. Create a 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

---

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

---