Update Model Metadata

Update model metadata (name, description).

PATCH /models/{model_id}

Update Model Metadata

cURL

curl --request PATCH \
  --url https://api.woodwide.ai/models/{model_id} \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "<string>",
  "description": "<string>"
}
'

200

{
  "model_id": "b2c3d4e5-0000-0000-0000-000000000001",
  "model_type": "prediction",
  "status": "ready",
  "current_metrics": {
    "accuracy": 0.98
  },
  "current_version": {
    "version_id": "b2c3d4e5-0000-0000-0000-000000000002",
    "version": 1,
    "status": "ready",
    "metrics": {
      "accuracy": 0.98
    }
  },
  "training_dataset_id": "a1b2c3d4-0000-0000-0000-000000000001",
  "training_dataset_name": "retention_customers",
  "label_column": "churnReason",
  "created_at": "2025-01-15T11:00:00Z",
  "updated_at": "2025-01-15T11:05:00Z"
}

Authorizations

Authorization · string · header · required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Path Parameters

model_id · string<uuid> · required

Body

application/json

Request to update model metadata.

name · string

description · string | null

Response

200

application/json

Successful Response

Model response model.

model_id · string<uuid> · required

model_type · enum<string> · required

Canonical model types supported by the platform.

• prediction -- Supervised prediction (classification or regression) on a target column.
• anomaly -- Unsupervised anomaly detection. Returns anomaly scores and anomalous row IDs.
• embedding -- Generate dense vector embeddings for each row.
• clustering -- Unsupervised clustering. Returns cluster labels and descriptions.
• factors -- Factor analysis / dimensionality reduction.
• search -- Semantic nearest-neighbor search over the training dataset.

Available options: prediction, anomaly, embedding, clustering, factors, search

created_at · string<date-time> · required

updated_at · string<date-time> · required

status · string · default: processing

Aggregated from the current version: ready, processing, or failed.

current_metrics · Current Metrics · object

Validation metrics from the current (latest) version, promoted for convenience. Keys depend on model type: prediction (classification): accuracy (0–1). prediction (regression): r2 (R-squared). clustering: n_clusters, silhouette_score (−1 to 1). Other model types do not produce metrics.

Show child attributes

current_version · CurrentVersion · object

Current version summary embedded in the Model response.

Show child attributes

training_dataset_id · string<uuid> | null

Dataset used to train the current version (if known).

training_dataset_name · string | null

Display name of the training dataset for the current version.

label_column · string | null

Target column used to train the current version (prediction models only). Omitted for other model types.