StudyNest

Welcome to StudyNest, a comprehensive platform designed for seamless collaboration between teachers and students. This application integrates modern technologies to provide features like class management, note sharing, quiz generation, and real-time communication.

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Table of Contents

1. Features
2. Workflow Diagram
3. Technologies Used
4. Frontend Overview
5. Backend Overview
6. Setup Instructions
7. Environment Variables
8. Endpoints
9. Running the Application
10. Notes

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Features

• User authentication (teacher and student roles).
• Class creation and management.
• Notes upload and retrieval (text and PDF).
• Quiz generation based on uploaded notes.
• Real-time chat functionality for classes.

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Workflow Diagram

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Technologies Used

Frontend

• Framework: Next.js
• Styling: Tailwind CSS
• State Management: React Context API
• Real-time Communication: WebSocket integration

Backend

• Framework: Flask
• Database: MongoDB
• Authentication: JWT
• File Storage: GridFS
• Real-time Communication: Flask-SocketIO
• AI Integration: Google Generative AI (Gemini API)

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Frontend Overview

The frontend is built using Next.js, providing a fast and responsive user interface. Key features include:

• Dynamic routing for pages.
• Integration with the backend for seamless data exchange.
• Real-time updates using WebSocket.

To start the frontend:

cd frontend
npm install
npm run dev

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Backend Overview

The backend is powered by Flask, offering robust APIs for managing classes, notes, quizzes, and chat functionality. It also integrates AI for quiz generation.

DB Diagram

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Setup Instructions

Clone the repository:

git clone <repository-url>
cd StudyNest

Install dependencies:

Frontend:

cd frontend
npm install

Backend:

cd backend
pip install -r requirements.txt

Set up the environment variables:

Create a .env file in the backend directory and add the following:

GEMINI_API_KEY=<your-gemini-api-key>
JWT_SECRET_KEY=<your-jwt-secret-key>
MONGO_URI=mongodb://localhost:27017

Start the MongoDB server:

mongod

Run the application:

Frontend:

npm run dev

Backend:

python backend/app.py

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Environment Variables

Variable	Description
GEMINI_API_KEY	API key for Google Generative AI.
JWT_SECRET_KEY	Secret key for JWT authentication.
MONGO_URI	MongoDB connection URI.

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Endpoints

Authentication

Method	Endpoint	Description
POST	/auth/signup	Register a new user.
POST	/auth/login	Log in and get a JWT token.

Classes

Method	Endpoint	Description
POST	/classes/	Create a new class (teacher).
POST	/classes/join	Join a class using a code.
GET	/classes/teacher	Get all classes for a teacher.
GET	/classes/student	Get all classes for a student.

Notes

Method	Endpoint	Description
POST	/notes/	Upload notes (text or PDF).
GET	/notes/class/<class_id>	Get all notes for a class.
GET	/notes/<note_id>/download	Download a PDF note.

Quizzes

Method	Endpoint	Description
POST	/quizzes/generate	Generate a quiz (teacher only).
GET	/quizzes/<quiz_id>	Get a student's personalized quiz.
POST	/quizzes/<quiz_id>/submit	Submit a quiz (student only).
GET	/quizzes/assignments/<quiz_id>/scores	Get quiz scores (teacher).

Chat

Method	Endpoint	Description
POST	/chat/messages	Post a message in a class chat.
GET	/chat/messages/<class_id>	Get all messages for a class chat.

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Running the Application

1. Ensure MongoDB is running locally.
2. Start the Flask backend:

   python backend/app.py

3. Start the Next.js frontend:

   npm run dev

4. Access the application at http://127.0.0.1:5000.

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Notes

• Ensure you have the required API keys and environment variables set up before running the application.
• Use tools like Postman or cURL to test the endpoints.
• For real-time chat, use a WebSocket client to connect to the /chat namespace.