May 2024 - Software Engineering Project (Group 13)

IIT Madras Software Engineering Group Project - May 2024

Padh.ai : Learning Management System with AI Integration

Project Overview

This project is a Learning Management System (LMS) with integrated generative AI capabilities. It's designed to provide a comprehensive learning platform for students, enhanced with AI-powered features for a more engaging & enriching study experience.

Features

• User authentication and authorization
• Support for video lectures
• Assignment handling:
  • Multiple-choice questions (MCQ) based Assignments
  • Programming assignments with automatic evaluation
• AI-powered chat system for student support
• AI-powered lecture summaries for a concise overview
• Support for creating and editing notes
• Progress tracking and grading system
• RESTful API for easy integration with front-end applications

Technologies Used

• Backend: Python with Flask framework
• Database: SQLite with SQLAlchemy ORM
• API: Flask-RestX for RESTful API development
• Authentication: Flask-JWT-Extended for JSON Web Token authentication
• Code Execution: Piston API for remote code execution and evaluation
• AI Integration: Gemini Flash 1.5
• Frontend: Vue.js, vuelidate, axios, vue-ace-editor, bootstrap, vue-router

Project Folder Structure

├── backend/
│   ├── app/
│   │   ├── __init__.py
│   │   ├── models/
│   │   ├── routes/
│   │   ├── services/
│   │   └── utils/
│   ├── config.py
│   ├── instance
│   │   ├── db.sqlite3
│   │   └── test_db.sqlite3
│   ├── pytest.ini
│   ├── requirements.txt
│   ├── run.py
│   └── tests/
├── frontend/
│   └── padh.ai/
│       ├── eslintrc.cjs
│       ├── index.html
│       ├── jsconfig.json
│       ├── package.json
│       ├── package-lock.json
│       ├── prettierrc.json
│       ├── public/
│       │   └── favicon.ico
│       ├── README.md
│       ├── src/
│       │   ├── App.vue
│       │   ├── assets/
│       │   ├── components/
│       │   ├── main.js
│       │   ├── router/
│       │   └── views/
│       └── vite.config.js
├── package-lock.json
└── README.md

Setup and Installation

1. Clone the repository:

   git clone https://github.com/gagneetkaur04/soft-engg-project-may-2024-se-may-13.git
   cd soft-engg-project-may-2024-se-may-13

2. Set up a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables: Create a .env file in the root of the backend directory and add the following variables:

   GEMINI_API_KET=your_gemini_key

5. Run the application:

   python3 run.py

   The API should now be running on http://localhost:5000.

6. Setup and Installation of npm packages for frontend.

   cd frontend/padh.ai/
   npm install

7. Run the following command to start the frontend server in dev mode

   npm run dev

API Documentation

Once the application is running, you can access the Swagger UI documentation at http://localhost:5000/docs. This provides a comprehensive overview of all available endpoints and allows for easy testing.

Testing

We use pytest for testing in our project. To run the test suite, make sure you're in the backend directory and run:

pytest -v

This will give you the status of all the test cases in the project.