MindArc — AI-Powered Quiz Generation Platform

Built by Engineers. Designed for Educators.

MindArc eliminates the gap between great content and great assessment. Feed it a YouTube video, a PDF, or an image — it extracts the content, runs it through an LLM pipeline, and generates ready-to-deploy quizzes. Educators create. Students learn. The platform handles everything in between.

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How It Works

Input (YouTube URL / PDF / Image)
        ↓
Content Extraction
  ├── YouTube → youtube-transcript-api
  ├── PDF     → pdfplumber / PyPDF2
  └── Image   → Tesseract OCR
        ↓
LLM Pipeline (Groq API · Llama 3.1 8B Instant)
        ↓
Structured Quiz (MCQ, adaptive delivery)
        ↓
Student Attempt → Performance Report

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Features

• Multi-Source Quiz Generation — YouTube transcripts, PDFs, and scanned images
• LLM-Powered Questions — Groq API with Llama 3.1 8B Instant for fast, accurate generation
• Role-Based Access — Separate flows for Teachers and Students
• Attempt Tracking — Per-student attempt history with scoring
• Performance Analytics — Detailed reports per quiz and per student
• JWT Authentication — Secure, token-based auth with role-based authorization
• Responsive UI — Built with React + Tailwind CSS

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Tech Stack

Backend

Layer	Technology
Framework	Django 6.0.1 + Django REST Framework 3.16.1
Auth	JWT (djangorestframework-simplejwt)
Database	PostgreSQL
LLM	Groq API (Llama 3.1 8B Instant)
PDF Parsing	pdfplumber, PyPDF2, pdf2image
OCR	Tesseract via ocrmypdf
Transcript	youtube-transcript-api
PDF Export	fpdf2

Frontend

Layer	Technology
Framework	React 19.1.1
Build	Vite 7.1.7
Styling	Tailwind CSS 3.4.17
Routing	React Router DOM 7.9.3
HTTP	Axios 1.12.2
Animations	Framer Motion 12.25.0

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Project Structure

MindArc/
├── backend/
│   ├── accounts/          # Auth & user management
│   ├── ai_quiz/           # LLM quiz generation service
│   ├── attempts/          # Attempt tracking
│   ├── quiz/              # Quiz models & CRUD
│   ├── reports/           # Analytics & exports
│   ├── backend/           # Django settings & URLs
│   ├── manage.py
│   └── requirements.txt
├── frontend/
│   ├── src/
│   │   ├── components/    # Reusable UI components
│   │   ├── pages/         # Route-level pages
│   │   ├── services/      # Axios API layer
│   │   └── utils/
│   ├── vite.config.js
│   └── tailwind.config.js
└── requirements.txt

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Getting Started

Prerequisites

• Python 3.8+
• Node.js 16+ and npm
• PostgreSQL
• Groq API key (get one here)

Backend Setup

cd backend

# Create and activate virtual environment
python3 -m venv venv
source venv/bin/activate          # Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Configure environment variables
cp .env.example .env              # Add your DB credentials and Groq API key

# Run migrations
python manage.py migrate

# Start server
python manage.py runserver        # http://localhost:8000

Frontend Setup

cd frontend

npm install
npm run dev                       # http://localhost:5173

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API Reference

Authentication

Method	Endpoint	Description
POST	/api/accounts/register/	Register new user
POST	/api/accounts/login/	Login, returns JWT tokens
POST	/api/accounts/refresh/	Refresh access token

Quizzes

Method	Endpoint	Access
GET	/api/quiz/	All users
POST	/api/quiz/	Teacher only
GET	/api/quiz/{id}/	All users
PUT	/api/quiz/{id}/	Teacher only
DELETE	/api/quiz/{id}/	Teacher only

Attempts & Reports

Method	Endpoint	Description
GET	/api/attempts/	List user attempts
POST	/api/attempts/	Start a new attempt
PUT	/api/attempts/{id}/	Submit attempt
GET	/api/reports/	Performance overview
GET	/api/reports/{id}/	Detailed report

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User Roles

Teacher

• Create quizzes from YouTube, PDF, or image sources
• Monitor student attempts and scores
• Export performance reports

Student

• Browse and attempt assigned quizzes
• View attempt history and scores
• Track learning progress

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Deployment

# Build frontend
cd frontend && npm run build      # Output: frontend/dist/

# Backend
python manage.py collectstatic --noinput
gunicorn backend.wsgi:application

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Known Limitations

• YouTube transcript extraction depends on video having auto-generated or manual captions enabled
• OCR accuracy on low-resolution or handwritten images may vary
• Groq API rate limits apply on the free tier

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License

MIT