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candle-annotator/openspec/changes/archive/2026-02-18-ml-ui-connection/specs/model-selector/spec.md
Marko Djordjevic c0f5654450 sync: ml-ui-connection delta specs to main specs
2026-02-18 10:21:05 +01:00

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ADDED Requirements

Requirement: Model selector dropdown

The system SHALL display a model selector dropdown in the prediction panel area. The dropdown SHALL list all completed training runs from the backend, showing model type, date, and key metric (F1 macro) for each entry. The currently loaded model SHALL be indicated with a checkmark or "active" badge.

Scenario: Display available models

  • WHEN the user opens the model selector dropdown
  • THEN completed training runs are listed with model type, training date, and F1 score

Scenario: No models available

  • WHEN no completed training runs exist
  • THEN the dropdown shows "No trained models available"

Scenario: Current model indicated

  • WHEN a model is currently loaded
  • THEN the corresponding entry in the dropdown shows an "active" indicator

Requirement: Model switching

The system SHALL load a different model when the user selects a training run from the model selector. The system SHALL send the run_id to POST /api/model/load and update the prediction panel to reflect the newly loaded model's info. Existing cached predictions SHALL be cleared on model switch.

Scenario: Switch model

  • WHEN the user selects a different model from the dropdown
  • THEN the system sends POST /api/model/load with the run_id, shows a loading indicator, and upon success updates the model info display and clears prediction cache

Scenario: Model load failure

  • WHEN model loading fails (e.g., model artifact not found)
  • THEN the system shows an error message and keeps the previously loaded model active

Scenario: Prediction cache cleared

  • WHEN a new model is successfully loaded
  • THEN all cached predictions are invalidated and the chart clears any displayed predictions

Requirement: Model info refresh on switch

The system SHALL refresh the model info display (name, version, type, per-class metrics) after a successful model switch. The prediction panel SHALL reflect the new model's capabilities and labels.

Scenario: Model info updates after switch

  • WHEN a new model is loaded successfully
  • THEN the prediction panel refreshes to show the new model's name, type, version, and per-class metrics