ML INTERACTIVE PREDICTION¶
Loads a previously trained ML model file (single .pkl, comma-separated .pkl list, or per-target CSV manifest) and interrogates it via LucyML to surface model metadata — including inputs, targets, training data schema, and configuration — without requiring new prediction data. Use this worker to inspect or pass model context downstream in a workflow before or instead of running a full prediction.
When to use¶
Tagged: info, lucy, lucyml, ml, model inspection, model metadata, per-target, pkl.
Inputs¶
| Label | ID | Type | Default | Required | Description |
|---|---|---|---|---|---|
| Saved Model File | mfile | text | — | ✓ | Path, numeric mathmodel ID, or inline per-target CSV manifest pointing to the saved model file (.pkl) produced by a prior training worker; also accepts a comma-separated list of .pkl paths for multi-target models. |
Outputs¶
| Label | ID | Type | Description |
|---|---|---|---|
| Model File | mfile | text | Resolved filesystem path(s) to the loaded model file(s); comma-separated when multiple per-target models were processed. |
| Lucy JSON | lucy_json | json | Raw LucyML JSON envelope (dataType: lucy_ml_json) returned by the model-info call, containing the full payload of all responses from the Python backend. |
| Independents | inputs | scalar | Scalar list of independent (feature) variable names registered in the model. |
| Targets | targets | scalar | Scalar list of target (response) variable names the model was trained to predict; also surfaced as a dataset containing the original training target values. |
| Training Data | targets | dataset | Scalar list of target (response) variable names the model was trained to predict; also surfaced as a dataset containing the original training target values. |
| Schema | schema | dataset | Dataset describing the model’s feature schema — column names, types, and any preprocessing metadata — as extracted from the saved model file. |
| Config Parameters | config | keyvalue | Key-value map of configuration parameters (hyperparameters, algorithm settings, etc.) stored inside the model at training time. |
Disciplines¶
- ai_ml.model_selection
- ai_ml.supervised.classification
- ai_ml.supervised.regression
- ai_ml.surrogate
Auto-generated from platform schema. Worker id: ml_predict_info. Schema hash: b4d8d70e9ba8. Hand-curated docs in workerexamples/ override this page when present.