/Q---Genie

A powerful tool for generating multiple-choice questions from text using advanced NLP models. Ideal for educators and trainers, this project includes a user-friendly Streamlit app, customizable Python scripts, and comprehensive tutorials to enhance assessment creation.

Primary LanguageJupyter NotebookMIT LicenseMIT

MCQ Question Generator

Welcome to the MCQ Question Generator! This project leverages advanced NLP models to automatically generate multiple-choice questions (MCQs) from text data, making it an invaluable resource for educators, trainers, and content creators.

APP:

Project Screenshot

Table of Contents

  • Introduction
  • Features
  • Installation
  • Usage
  • Files Overview
  • Contributing
  • License
  • Contact

Introduction

The MCQ Question Generator is designed to automate the creation of multiple-choice questions from textual content. This tool saves time and effort by harnessing the power of natural language processing (NLP) while ensuring diverse and challenging questions for quizzes, exams, and learning assessments.

Features

  • Automatic MCQ Generation: Generates questions from any text input.
  • Advanced NLP Models: Utilizes state-of-the-art language models for accurate and meaningful question creation.
  • Streamlit App: Easy-to-use interface for generating questions and visualizing outputs.
  • Customization: Python scripts allow for customization of question difficulty and types.
  • Comprehensive Tutorials: Step-by-step guides to help you understand and extend the model's capabilities.

Installation

To get started with the MCQ Question Generator, follow these steps:

  • Install in terminal one by one
  • pip install flask-bootstrap
  • pip install flask
  • pip install spacy
  • pip install PyPDF2
  • pandas
  • NumPy
  • sci-kit-learn
  • transformers
  • torch
  • nltk
  • spacy
  • sentence-transformers
  • openai
  • jupyter

Usage

Generating Questions:

  • Open the Flask app in your web browser.
  • Upload a text file or enter text directly into the provided input box.
  • Click the "Generate Questions" button to see the generated MCQs.
  • Customizing the Model: You can modify the Python scripts to adjust the difficulty level of the questions or change the question generation logic.

Files Overview

  • app.py: Streamlit app script for the user interface.
  • MCQ Question Generator My Model.ipynb: Jupyter notebook for the main model and question generation logic.
  • Question MCQs Generator Tutorials.ipynb: Tutorials to help understand the code and model workings.
  • README.md: This file, provides an overview and guide for the project.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Contact

For questions or suggestions, feel free to reach out:

Your Name - dhruvsharma4054@gmail.com GitHub - testgithubrittttttt requirements.txt: List of Python dependencies required to run the project.