AI Teaching Assistant

Check it out here: Landing Page

Trying to build a good solution for fixing some educational problems in early university courses.

Being developed by Vansh Sood

Project Structure

.
├── client/             # Next.js frontend application
├── server/             # Python FastAPI backend application
└── docker-compose.yml  # Main Docker compose configuration

Technologies Used

Frontend (client/)

• Next.js with TypeScript
• Tailwind CSS for styling
• Modern React patterns and hooks
• Environment variables for configuration

Backend (server/)

• Python FastAPI
• Firebase integration
• File upload and processing capabilities
• Environment-based configuration

Prerequisites

• Docker and Docker Compose
• Node.js 20+ (for local frontend development)
• Python 3.10+ (for local backend development)
• Firebase account and credentials

Getting Started

1. Clone the repository:

git clone https://github.com/Vansh983/ai-ta.git
cd ai-ta

2. Set up environment variables:

   • Copy .env.example to .env in the server directory
   • Copy .env.local.example to .env.local in the client directory
   • Fill in the required environment variables

3. Start the application using Docker:

docker-compose up --build

The application will be available at:

• Frontend: http://localhost:3000
• Backend: http://localhost:8000

Development Setup

Frontend Development

cd client
yarn install
yarn dev

Backend Development

cd server
python -m venv venv
source venv/bin/activate  # On Windows: .\venv\Scripts\activate
pip install -r requirements.txt
./run_dev.sh

API Documentation

Still working on this

Contributing

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

License

This project is licensed under the Apache License, Version 2.0 - see the LICENSE file for details.