feat: add storage and training modules for snore detection

- 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.

.gitignore

@@ -0,0 +1,36 @@
+# Python caches and build artifacts
+__pycache__/
+*.py[cod]
+*.pyo
+*.pyd
+*.so
+*.egg-info/
+build/
+dist/
+
+# Virtual environments and local settings
+.venv/
+venv/
+.env
+
+# Test and tooling caches
+.pytest_cache/
+.mypy_cache/
+.coverage
+htmlcov/
+
+# VS Code local workspace settings
+.vscode/*
+!.vscode/extensions.json
+
+# Generated app data
+data/raw/*
+data/spectrograms/*
+data/models/*
+data/meta/*.json
+
+# Keep generated-data folder structure tracked
+!data/raw/.gitkeep
+!data/spectrograms/.gitkeep
+!data/models/.gitkeep
+!data/meta/.gitkeep