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feat: configure ML retraining interval in apps.yaml - #5433
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springfall2008 merged 1 commit intoOct 12, 2026
Merged
springfall2008 merged 1 commit into
springfall2008 merged 1 commit into
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Keep the two-hour default and support daily retraining with a 1-48 hour range. Preserve startup training and prediction cadence. Refs springfall2008#5072.
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🟢 Approval recommended
The configuration is correctly wired, bounded, documented, and covered by focused tests.
0 open findings
What changed in this PR
Adds an apps.yaml option for configuring ML retraining from 1–48 hours while retaining the two-hour default.
Changes:
- Wires the interval through configuration and ML scheduling.
- Adds validation and cadence tests.
- Documents daily retraining and unchanged prediction behavior.
| File | Description |
|---|---|
apps/predbat/config.py |
Validates the new setting. |
apps/predbat/components.py |
Passes configuration to the ML component. |
apps/predbat/load_ml_component.py |
Applies the configured retraining interval. |
apps/predbat/tests/test_load_ml.py |
Tests scheduling, defaults, and bounds. |
apps/predbat/tests/test_validate_config.py |
Tests schema validation. |
docs/load-ml.md |
Documents detailed usage. |
docs/components.md |
Updates the component reference. |
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Keep the two-hour default and support daily retraining with a 1-48 hour range. Preserve startup training and prediction cadence.
Refs #5072.
Config in YAML rather than a HAOS entity parameter.
Been running this code for a few days, seems fine.
Changes done by AI.