MLH Quizzet
This is a smart Quiz Generator that generates a dynamic quiz from any uploaded text/PDF document using NLP. This can be used for self-analysis, question paper generation, and evaluation, thus reducing human effort.
Features
- implements automatic question generation (AQG) techniques
Automatic question generation (AQG) is concerned with the construction of algorithms for producing questions from knowledge sources, which can be either structured (e.g. knowledge bases (KBs) or unstructured (e.g. text))
- helps in resource saving(time, money and human effort)
- enables the enrichment of the teaching process, adapt learning to student knowledge and needs, as well as drill and practice exercises
- presents an automatic mechanism to assemble exams or to adaptively select questions from a question bank
WorkFlow
Demo Video
Technology Stack:
- Frontend: HTML, CSS, Vanilla JS
- Backend: Flask
- IDE: VS Code
- Design: Canva
- Version Control: Git and GitHub
- Database: Sqllite3
How to Get Started?
GitHub Repository Structure
| S.No. | Branch Name | Purpose |
|---|---|---|
| 1. | master | contains the main code |
| 2. | nlp | contains all machine learning code |
| 3. | webapp | contains all frontend/backend code |
Setup
- Fork and Clone the repo using
$ git clone https://github.com/PragatiVerma18/Fantastic-Falcons-1.0.git
$ cd Fantastic-Falcons-1.0
- Change Branch to
webappusing
$ git checkout webapp
- Setup Virtual environment
$ python3 -m venv env
- Activate the virtual environment
$ source env/bin/activate
- Install dependencies using
$ pip install -r requirements.txt
- Run Flask server using
$ python app.py
Browser Support
- Firefox: version 4 and up
- Chrome: any version
- Safari: version 5.2 and up
- Internet Explorer/Edge: version 8 and up
- Opera: version 9 and up
Note: Support for modern mobile browsers is experimental. The website is not responsive in mobile devices until now.
MLH Fellowship( Fall 2020)
This is a hackathon project made by MLH Fellows(Fall 2020) - Pod 1.0.0 i.e. Fantastic Falcons
Team:
"Alone we can do so little; together we can do so much."
| S.No. | Name | Role | GitHub Username |
|---|---|---|---|
| 1. | Pragati Verma | Frontend Developer | @PragatiVerma18 |
| 2. | Kshitij Kotasthane | Backend Developer | @kshitij86 |
| 3. | Vignesh S | ML | @telescopic |
Contributors ✨
Thanks goes to these wonderful people (emoji key):
 Pragati Verma |
 Kshitij Kotasthane |
 Vignesh S |
This project follows the all-contributors specification. Contributions of any kind welcome!
