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App README

WhartonAI

WhartonAI-Thon project

WhartonAI - Lecture Notes Assistant

An AI-powered tool that helps you better understand and retain your lecture materials by creating summaries, generating quizzes, and providing detailed performance reviews.

Features

1. PDF Processing

  • —Upload your lecture notes in PDF format
  • —Automatic text extraction and processing
  • —Support for various PDF layouts and formats

2. AI-Powered Summary

  • —Concise summary of lecture content
  • —Key points and main concepts highlighted
  • —Easy to understand format
  • —Citations to original lecture sections

3. Interactive Quiz

  • —Multiple-choice questions generated from lecture content
  • —Questions test understanding of key concepts
  • —Immediate feedback on answers
  • —Step-by-step solutions for incorrect answers
  • —Progress tracking throughout the quiz

4. Performance Review

  • —Detailed analysis of quiz performance
  • —Personalized feedback on areas for improvement
  • —Topic-specific study recommendations
  • —Actionable learning strategies
  • —List of questions to review with:
  • —Correct answers
  • —Key concepts
  • —Relevant lecture sections

5. Study Tools

  • —Question regeneration for additional practice
  • —Performance tracking across attempts
  • —Citation-based learning
  • —Concept-focused review

How to Use

  1. 1.Upload Your Notes
  2. 2.Click the file upload button
  3. 3.Select your lecture notes PDF
  4. 4.Wait for processing to complete
  1. 1.Review the Summary
  2. 2.Read the AI-generated summary
  3. 3.Note key concepts and main points
  4. 4.Use citations to reference original content
  1. 1.Take the Quiz
  2. 2.Answer multiple-choice questions
  3. 3.Get immediate feedback
  4. 4.View solutions for incorrect answers
  5. 5.Track your progress
  1. 1.Review Your Performance
  2. 2.Get detailed feedback on your performance
  3. 3.Identify areas for improvement
  4. 4.Access personalized study recommendations
  5. 5.Review questions you got wrong
  1. 1.Practice More
  2. 2.Regenerate questions for additional practice
  3. 3.Focus on specific topics
  4. 4.Track improvement over time

Technical Details

  • —Built with Python and Gradio
  • —Uses OpenAI's GPT models for content generation
  • —PDF processing with PyPDF2
  • —Efficient text chunking for better context management
  • —Streaming responses for real-time feedback

Requirements

  • —Python 3.8+
  • —OpenAI API key
  • —Required Python packages (see requirements.txt)

Installation

  1. 1.Clone the repository:
bash
git clone https://github.com/kgampol/WhartonAI.git
cd WhartonAI
  1. 1.Install dependencies:
bash
pip install -r requirements.txt
  1. 1.Set up your OpenAI API key:
bash
export OPENAI_API_KEY='your-api-key-here'
  1. 1.Run the application:
bash
python app.py

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

  • —OpenAI for providing the GPT-3.5-turbo API
  • —Gradio team for the excellent UI framework
  • —All contributors who have helped improve this project

Last updated: March 2024