PrepEase

PrepEase is an AI-powered learning platform that helps students study smarter and helps teachers create better course content. It combines a React frontend, a Node.js/Express backend, and AI-assisted study tools for chat, quiz generation, assignments, and flashcards.

Overview

The platform is designed around uploaded course materials. Teachers can add learning resources, and students can interact with those materials through an AI study buddy that answers questions using grounded content from the document.

Key Features

• AI study buddy for asking questions about uploaded materials
• Quiz, assignment, and flashcard generation for teachers
• Course enrollment and access control for students
• PDF text extraction and material processing
• React-based dashboard with a responsive UI
• JWT-based authentication and role-based permissions

Project Structure

Prep-Ease/
├── PrepEase/          # React + Vite frontend
├── backend/           # Node.js + Express API
├── ai-service/        # Python AI microservice
└── README.md          # Project overview and setup

Tech Stack

• Frontend: React, Vite, TypeScript, Tailwind CSS
• Backend: Node.js, Express, MongoDB, JWT
• AI Integration: Google Gemini, content-grounded prompts, PDF extraction
• Optional AI Service: FastAPI-based internal AI microservice for semantic retrieval workflows

Requirements

• Node.js 18+
• npm
• Python 3.10+ if you want to run ai-service
• MongoDB connection string
• A valid Gemini API key

Setup

1. Install dependencies

cd PrepEase
npm install

cd ../backend
npm install

cd ../ai-service
pip install -r requirements.txt

2. Configure environment variables

Create or update backend/.env with the required values, including:

MONGODB_URI=your_mongodb_connection_string
JWT_SECRET=your_secret_key
GEMINI_API_KEY=your_gemini_api_key
PORT=5001

If you use the Python AI service, configure its environment variables as needed as well.

3. Start the backend

cd backend
npm run dev

The API usually runs on http://localhost:5001.

4. Start the frontend

cd PrepEase
npm run dev

The frontend usually runs on http://localhost:5173.

5. Optional: start the AI service

cd ai-service
uvicorn main:app --host 0.0.0.0 --port 8000 --reload

Common Workflow

1. A teacher uploads a PDF or learning resource.
2. The backend extracts and stores the content.
3. AI features become available for the material.
4. Students open Study Buddy to ask grounded questions.
5. Teachers generate quizzes, assignments, or flashcards from the same material.

Troubleshooting

• If Gemini requests fail, verify that GEMINI_API_KEY is correct and restart the backend.
• If the frontend cannot connect, confirm the backend is running on port 5001.
• If MongoDB is unavailable, verify the MONGODB_URI value in backend/.env.
• If AI features are unavailable, ensure the uploaded material finished processing successfully.

Useful References

• QUICK_START.md for a fast local setup
• backend/GEMINI_INTEGRATION_SUMMARY.md for AI configuration details
• backend/FLASHCARD_IMPLEMENTATION.md for flashcard workflow details
• backend/00_START_HERE.md for implementation status and API overview

License

No license has been specified in this repository.