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| # 🤝 Contributing to Classroom AI Assistant | |
| Thanks for your interest in helping improve the Classroom AI Assistant! | |
| This project, built under Intel Unnati by Team Bitbots, showcases a fully local emotion-aware AI system—no external LLM APIs used. | |
| ## 🚀 What You Can Help With | |
| - Improving frontend responsiveness and UI interactions | |
| - Optimizing FastAPI backend and WebSocket performance | |
| - Enhancing emotion-label mappings and voice synthesis | |
| - Fixing bugs or suggesting new features | |
| ## 🧰 Tech Stack | |
| - Frontend: HTML, TailwindCSS, JavaScript | |
| - Backend: FastAPI, WebSockets, DeepFace | |
| - AI: Locally hosted LLaMA 3.1 3B (8-bit), Speech & Emotion modules | |
| ## 🔧 Getting Started | |
| 1. Fork the repo and clone your branch | |
| 2. Set up local model files and install dependencies | |
| 3. Make your changes and submit a pull request with a clear description | |
| 🧱 All contributions must keep LLM inference fully local and support async handling. | |
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| We appreciate every issue, PR, and star—thank you for helping build emotionally intelligent AI! 🌟 | |