QuickQuiz

Specialized Essay - AI-powered automated quiz creation and evaluation system.

Features

• Extract text from documents (OCR)
• Automated document content summarization
• Create quizzes from documents
• Assignment assessment, grading, and detailed explanations
• RAG chatbot answers questions from documents
• User Management and Authentication (IAM)
• Interactive user interface

Demo

• Click image below to watch the demo video.

Architecture

The system is built according to the Microservices architecture:

• Frontend: ReactJS (Port 3000)
• API Gateway: Django (Port 8007) - Primary Communication Gateway
• IAM Service: Django (Port 8001) - Authentication Manager
• Quiz Generator: Python (Port 8002) - Question Generator
• Quiz Evaluator: Python (Port 8003) - Scoring
• OCR Service: FastAPI (Port 8004) - Image/PDF Processing
• Summary Service: FastAPI (Port 8005)
• RAG Chatbot: Python (Port 8006) - Virtual Assistant

Tech Stack

• Client: React, TypeScript, TailwindCSS
• Server: Django, FastAPI, Python
• Database: SQLite (Each service has its own database)
• AI/LLM: Gemini, Qwen-VL, ViT5, RAG

Installation

Prerequisites

Hardware:

• Window 10 or later
• RTX 1650 graphics card or higher Software:
• Python 3.8+
• Node.js & npm
• Vs Code (recommended)

Setup

1. Clone the project

git clone https://github.com/SweetLove1643/QuickQuiz.git
cd QuickQuiz

2. Create the environment and install the necessary libraries

python -m venv .venv
.venv\Scripts\activate
pip install -r ./requirements.txt

3. Create and configure the .env file

# Services
GEMINI_API_KEY =<your api key here>

GEMINI_MODEL=gemini-2.5-flash

# Django Gateway Configuration
DEBUG=True
DJANGO_SECRET_KEY=<your Django key here>
ALLOWED_HOSTS=localhost,127.0.0.1

# Logging
LOG_LEVEL=INFO

Contributing

Contributions are always welcome!

See Contributing.md for ways to get started.

Support

For support, please email to us.

License

This repo is under MIT license.

Authors

• @SweetLove1643
• @TrinhHuuTho