Team Name: Weefy
Problem Statement: Developing an AI-based application for generating questions from a given text document.
Team Leader Email: akilsadik1234@gmail.com
A Brief of the Prototype: The prototype is a Python application that uses the Transformers library to generate questions from a given text document. It reads a DOCX file, extracts the text content, and generates a specified number of questions based on the content. The generated questions are then categorized into 2, 5, and 7 mark questions and saved into a new DOCX file.
UML Diagrams:
Tech Stack:
- Python
- docx library for reading and writing DOCX files
- PyPDF2 library for readinf and writin pdf files
- Transformers library for question generation
- T5Tokenizer and T5ForConditionalGeneration for tokenizing the text and generating the questions
Step-by-Step Code Execution Instructions:
- Install the necessary libraries (docx, transformers).
- Place the input DOCX file in the specified path.
- Run the Python script.
- The script will read the input DOCX file, generate the questions, and save them into a new DOCX file.
What I Learned: While developing this prototype, I learned how to use the Transformers library for question generation. I also learned how to read and write DOCX files using Python. This project helped me understand the practical applications of AI in education, specifically in automating the process of question paper generation. It was a great learning experience working with NLP models and seeing how they can be used to generate meaningful questions from a given text.