The recommendation system that adapts to your cognitive state and mental energy levels
MindState revolutionizes recommendations by considering not just what you like, but what you can mentally handle right now. When you're stressed, it suggests simple content. When you're energized, it offers complex challenges.
- Cognitive State Detection: Real-time analysis of behavioral patterns
- Content Complexity Analysis: Automated scoring of content difficulty
- State-Aware Recommendations: Matching content to cognitive capacity
- Real-time Adaptation: Updates as your mental state changes
- ML/AI: scikit-learn, PyTorch, transformers
- Backend: FastAPI, WebSockets for real-time streaming
- Frontend: Streamlit for interactive demos
- Data: Pandas, NumPy for processing
- Visualization: Plotly, Matplotlib
mindstate-project/ ├── src │ ├── behavioral_analyzer/ # Cognitive state detection │ ├── content_analyzer/ # Content complexity analysis │ ├── recommendation_engine/ # Core recommendation logic │ ├── api/ # FastAPI endpoints │ └── utils/ # Shared utilities ├── data/ # Datasets and processed data ├── notebooks/ # Jupyter notebooks for exploration ├── tests/ # Unit and integration tests └── frontend/ # Demo interfaces
# Clone and setup
git clone [your-repo-url]
cd mindstate-project
# Create virtual environment
python -m venv mindstate_env
source mindstate_env/bin/activate # or mindstate_env\Scripts\activate on Windows
# Install dependencies
pip install -r requirements.txt
# Run basic demo
python src/demo.py