SmartQraft - AI-Powered Question Generator

SmartQraft is an AI-driven question generation tool that helps educators, students, and self-learners to create quizzes and assessments from any text-based content. Built with Flask and powered by the T5 transformer model, SmartQraft generates relevant questions from input text, making it a versatile tool for reinforcing learning and enhancing study materials.

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Features

• AI-Generated Questions: Generate insightful and contextually relevant questions from any input text.
• Regenerate Capability: Refine your questions by regenerating from the same text for variety.
• Data Collection for Improvement: Stores user-generated questions and input text for potential fine-tuning and improvement of the model.
• User-Friendly Interface: Simple, clean, and intuitive UI built with HTML and Bootstrap for easy navigation.

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How It Works

SmartQraft leverages the T5 (Text-To-Text Transfer Transformer) model to convert educational or informative content into a question-answer format. By parsing the input text, SmartQraft identifies key concepts and generates questions that encourage deeper understanding and retention.

1. Input Text: Users provide a passage or paragraph of text.
2. Question Generation: The T5 model generates questions related to the key points in the text.
3. Data Storage: Each session's data (input text and generated questions) is saved in a CSV file for potential future fine-tuning.
4. Regeneration Option: Users can regenerate questions to receive different phrasing or new questions based on the same input.

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Getting Started

Prerequisites

• Python 3.7+
• pip (Python package manager)

Installation

1. Clone the Repository:

   git clone https://github.com/yourusername/SmartQraft.git
   cd SmartQraft
   

2. Set Up a Virtual Environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install Dependencies:

   pip install -r requirements.txt
   

4. Download spaCy Model (for text segmentation):

   python -m spacy download en_core_web_sm
   

Running the Application

To start the Flask app, run:

python app.py

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Usage

1. Navigate to the Home Page: Enter the text you wish to generate questions from.
2. Generate Questions: Click the "Generate Questions" button to see AI-generated questions based on the input text.
3. Regenerate Questions: Use the "Regenerate" option to create a new set of questions from the same text.
4. View and Download: Generated questions are displayed on the results page, allowing for easy review and saving.

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Project Structure

SmartQraft/
├── app.py                  # Main Flask application with routes and data handling
├── question_generator.py    # Question generation logic using T5 model
├── requirements.txt         # Project dependencies
├── static/                  # Static files (CSS, images, etc.)
├── templates/               # HTML templates for the front end
└── user_data.csv            # CSV file for storing user input and generated questions (ignored in .gitignore)

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Technologies Used

• Flask: Backend framework to handle routing and server operations.
• Hugging Face Transformers: T5 model for question generation.
• spaCy: For text segmentation and pre-processing.
• Bootstrap: Front-end styling for a clean and responsive interface.
• Pandas: For efficient CSV handling and data storage.

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Future Enhancements

• Fine-Tuning: Use stored user data for fine-tuning the T5 model to improve question quality.
• Custom NER Integration: Integrate custom Named Entity Recognition (NER) for enhanced entity-based question generation.
• Export Options: Allow users to export questions in PDF or DOCX formats for easy sharing and printing.
• User Authentication: Add login functionality to let users save and track generated questions.

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Contact

For any questions or feedback, please contact us at:

• Email: [email protected]
• GitHub Issues: Report an Issue