Quizcraft

Introduction

This project aims to create a tool that automatically generates Multiple Choice Questions (MCQs) from given text or PDF documents. It leverages the power of Natural Language Processing (NLP) to extract relevant information and formulate potential questions.

Features

• Input Formats: Accepts both text and PDF files as input.
• NLP Processing: Employs spaCy for text preprocessing, entity recognition, and dependency parsing.
• Question Generation: Creates MCQs based on extracted information, including factual, inferential, and application-based questions.
• Accuracy: Strives to generate accurate and relevant MCQs.

upload pdf or text file and choose number of questions

Requirements

• Python (version 3.6 or later)
• spaCy

Limitations

• Accuracy might be affected by the complexity of the input text.
• Currently supports English language only.
• Question types are limited.

Future Improvements

• Expand supported file formats (e.g., Word, HTML).
• Enhance question generation techniques.
• Implement answer generation.
• Provide options for customizing question difficulty and type.
• Incorporate feedback mechanisms to improve accuracy.