Protégé is an AI-powered platform designed to enhance learning through teaching. Users create lessons on various topics and explain them to the AI, which provides real-time feedback and suggestions for improvement. This interactive approach reinforces understanding and deepens knowledge retention.
Inspired by the protégé effect, where teaching others strengthens one's own understanding, Protégé aims to empower users to actively learn by explaining concepts to an AI model.
- Lesson Creation: Users can prompt the model to generate lessons based on topics.
- Teaching Mode: Users "teach" the AI by explaining concepts verbally.
- Real-Time Feedback: The AI evaluates responses and provides constructive suggestions.
- Personalized Learning Paths: Future versions will offer customized lesson plans based on user performance.
- Front-End: Built using the Reflex framework for a seamless user experience.
- Back-End: Integrated AI models for lesson generation and evaluation.
- Speech Recognition: Utilizes Deepgram for accurate real-time speech-to-text conversion.
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Clone the repository:
git clone https://github.com/yourusername/protege.git -
Navigate to the project directory:
cd protege -
Install Reflex: If you haven't installed Reflex yet, follow the instructions from the Reflex documentation.
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Install Python dependencies: Ensure you have Python installed, then run:
pip install -r requirements.txt -
Start the application:
reflex run
- Ensuring seamless integration between the AI model and front-end.
- Achieving accurate real-time speech-to-text functionality.
- Developed a responsive platform for real-time interaction with the AI.
- Successfully integrated Deepgram for speech recognition, enhancing user experience.
- Introduce personalized lesson plans based on user performance.
- Expand subject coverage for broader educational content.
- Add gamification elements to motivate users.
- Develop community features for collaborative learning.
- Create a mobile version for accessibility on the go.