feat: add storage and training modules for snore detection

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- Implemented `storage.py` for managing metadata storage, including sample addition, retrieval, and review state management.
- Created `training.py` for training a local model using Random Forest, including functions for training and predicting samples.
- Developed a web interface in `app.js` for capturing audio samples, managing labels, and training the model.
- Added HTML structure in `index.html` for the SnoreStopper control room with sections for sample capture, overnight gathering, training, and status display.
- Styled the application with `styles.css` to enhance user experience and interface aesthetics.

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spencer

2026-03-12 13:35:17 -04:00

commit 28012e70e0

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