📚 SAMMY: System for Automated Multi-modal Quiz Mastering and Yielding 🤖

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⚡️ Revolutionizing Quiz Automation: AI-Powered and OS-Controlled with SAMMY! ⚡️

SAMMY (System for Automated Multi-modal Quiz Mastering and Yielding) is an advanced, multi-modal AI bot designed to autonomously attend and complete quizzes by interacting directly with the operating system. Leveraging state-of-the-art models and Python libraries, SAMMY can read, listen, and click through quizzes with minimal human intervention—perfect for friendly quizzes where efficiency and accuracy matter!

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🚀 Features

• Multi-Modal Interaction: Handles text, image, and audio-based questions with ease.
• OS-Level Control: Uses PyAutoGUI for full control over the OS, bypassing the limitations of browser-based automation.
• Smart Decision Making: Implements lightweight, efficient models for accurate answer prediction.
• Human-in-the-Loop: Seamless integration for manual captcha handling when needed.
• Customizable & Extensible: Easily fine-tune models and integrate new features as required.

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🎯 Use Cases

• Friendly Quizzes: Automate quiz-taking for educational or recreational purposes.
• Practice Sessions: Efficiently go through practice quizzes with minimal input.
• AI/ML Demonstrations: Show off the power of multi-modal AI in real-world applications.

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📂 Project Structure

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├── data/                   # Data folder for training/testing models
├── models/                 # Pre-trained or fine-tuned models
├── scripts/                # Core bot scripts
├── notebooks/              # Jupyter notebooks for experiments and demos
├── docs/                   # Documentation and resources
├── tests/                  # Unit and integration tests
├── README.md               # This very file
└── setup.py                # Setup script for package installation

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🔧 Setup & Installation

Requirements

• Python 3.8+
• Pipenv or Virtualenv (Recommended for environment management)
• CUDA (If using a GPU)

Installation Steps

1. Clone the Repository

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

2. Set Up the Virtual Environment

   pip install pipenv
   pipenv install --dev

3. Install Dependencies

   pipenv install

4. Run Initial Setup

   python setup.py install

5. Download Pre-trained Models

   Download the necessary models from Model Zoo and place them in the models/ directory.

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🚀 Getting Started

1. Initial Configuration

• Configure your environment variables in a .env file:

  QUIZ_MODE="friendly"
  CAPTCHA_ENABLED="True"

2. Running the Bot

• Start SAMMY with:

  python scripts/quiz_bot.py --config configs/default.yaml

• Demo Mode: Try out the demo with a sample quiz:

  python scripts/demo_quiz.py

3. Training & Fine-Tuning

• Use provided Jupyter notebooks in the notebooks/ folder to experiment and fine-tune models:

  jupyter notebook notebooks/Training.ipynb

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🧠 Models & Techniques

Text Recognition

• OCR: Tesseract for efficient text extraction.

Image Classification

• MobileNetV2: Lightweight image classification for quick inference.

Audio Transcription

• Wav2Vec 2.0: State-of-the-art model for real-time audio-to-text transcription.

Answer Prediction

• DistilBERT: NLP model for understanding and predicting answers based on text.

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🔍 Example Screenshots

1. Text-Based Quiz Interaction

2. Image-Based Question Handling

3. Audio Question Processing

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🛠️ Contributing

We welcome contributions! Please check out our Contributing Guide for more details.

1. Fork the Repository
2. Create a Feature Branch
3. Submit a Pull Request

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🐛 Issue Reporting

Found a bug? Have a feature request? Please open an issue here.

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📜 License

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

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🙌 Acknowledgements

• Thanks to the open-source community for providing the building blocks for this project!
• Special thanks to contributors and supporters.

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🌟 Star This Project

If you find this project helpful or interesting, please consider giving it a star 🌟 on GitHub to show your support!

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Happy Quiz Automation with SAMMY! 🎉

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💡 Future Enhancements

• Advanced AI Integration: Experiment with GPT-based models for complex quizzes.
• Real-time Data Analysis: Implement dashboards to track quiz performance.
• Cross-Platform Support: Extend support to other operating systems.

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