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GET
/
models
/
{model_id}
Get Model
curl --request GET \
  --url https://api.woodwide.ai/models/{model_id} \
  --header 'Authorization: Bearer <token>'
{
  "model_id": "b2c3d4e5-0000-0000-0000-000000000001",
  "name": "churn_predictor",
  "description": "Predicts customer churn from usage data.",
  "model_type": "prediction",
  "status": "ready",
  "current_metrics": {
    "accuracy": 0.92
  },
  "current_version": {
    "version_id": "b2c3d4e5-0000-0000-0000-000000000002",
    "version": 1,
    "status": "ready",
    "metrics": {
      "accuracy": 0.92
    }
  },
  "created_at": "2025-01-15T11:00:00Z",
  "updated_at": "2025-01-15T11:05:00Z"
}

Documentation Index

Fetch the complete documentation index at: https://docs.woodwide.ai/llms.txt

Use this file to discover all available pages before exploring further.

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

Response

Successful Response

Model response model.

​
model_id
string<uuid>
required
​
name
string
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
​
description
string | null
​
status
enum<string>
default:queued
Available options:
queued,
training,
ready,
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.

​
current_version
CurrentVersion · object

Current version summary embedded in the Model response.