KGampol/MasterMind-AI-Mobile
1
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
- Upload Your Notes
- Click the file upload button
- Select your lecture notes PDF
- Wait for processing to complete
- Review the Summary
- Read the AI-generated summary
- Note key concepts and main points
- Use citations to reference original content
- Take the Quiz
- Answer multiple-choice questions
- Get immediate feedback
- View solutions for incorrect answers
- Track your progress
- Review Your Performance
- Get detailed feedback on your performance
- Identify areas for improvement
- Access personalized study recommendations
- Review questions you got wrong
- Practice More
- Regenerate questions for additional practice
- Focus on specific topics
- 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
- Clone the repository:
git clone https://github.com/kgampol/WhartonAI.git
cd WhartonAI- Install dependencies:
pip install -r requirements.txt- Set up your OpenAI API key:
export OPENAI_API_KEY='your-api-key-here'- Run the application:
python app.pyContributing
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
