AI Study Assistant 📚

An intelligent study companion powered by Google's Gemini AI that helps students master complex topics through interactive learning. The application provides detailed explanations, generates practice questions, and offers topic-specific guidance.

Features ✨

• Topic Understanding: Get detailed, easy-to-understand explanations of complex topics
• Practice Questions: Generate subject-specific practice questions with solutions
• Interactive Learning: Engage with concepts through an interactive Q&A interface
• Subject-Specific Focus: Tailored explanations based on the academic subject
• Animated UI: Modern, responsive interface with smooth animations

Tech Stack 🛠️

• Frontend: HTML, CSS (Tailwind CSS), JavaScript
• Backend: Flask (Python)
• AI Integration: Google Gemini API
• Deployment: Gunicorn
• Styling: Tailwind CSS

Prerequisites 📋

• Python 3.8 or higher
• Google Gemini API key
• Modern web browser
• Internet connection

Installation 💻

1. Clone the repository

git clone https://github.com/prabOG7/ai-study-assistant.git
cd ai-study-assistant

2. Install dependencies

pip install flask google-generativeai flask-cors gunicorn

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

GOOGLE_API_KEY=your_gemini_api_key_here

4. Run the application

python app.py

The application will be available at http://localhost:8000

Deployment 🚀

Deploying to Render

1. Create a Render account at render.com
2. Create a new Web Service
3. Connect your GitHub repository
4. Configure the service:
   • Environment: Python 3
   • Build Command: pip install -r requirements.txt
   • Start Command: gunicorn app:app
5. Add your GOOGLE_API_KEY to environment variables
6. Deploy!

Usage 📝

1. Open the application in your web browser
2. Enter your study topic or concept
3. Choose the type of help you need:
   • Detailed explanation
   • Practice questions
   • Interactive learning
4. Review the AI-generated content and engage with the interactive elements

Project Structure 📁

ai-study-assistant/
├── app.py                 # Flask application
├── templates/
│   └── index.html        # Main HTML template
├── requirements.txt      # Python dependencies
└── README.md            # Documentation

Contributing 🤝

1. Fork the repository
2. Create a new branch (git checkout -b feature/improvement)
3. Make your changes
4. Commit your changes (git commit -am 'Add new feature')
5. Push to the branch (git push origin feature/improvement)
6. Create a Pull Request

Environment Variables 🔑

• GOOGLE_API_KEY: Your Google Gemini API key

License 📄

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

Acknowledgments 🙏

• Google Gemini API for powering the AI capabilities
• Flask framework for the backend
• Tailwind CSS for the styling
• All contributors and users of this application

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Made with ❤️ for students everywhere @prabOG7