MLModelConfigOutput

"""ML model configuration for training pipelines"""
type MLModelConfigOutput @iac_resource(name: "ml_model_config") @iac_precondition(field: "authoringRevision", input: "expectedRevision") @iac_guide(ref: "ml-guide") @iac_ops(create: "upsertMLModelSource", read: "getMLModelConfig", update: "upsertMLModelSource", delete: "deleteMLModelConfig") {
  """
  Author-owned XML source envelope used to reproduce and edit this model configuration; runtime results are stored separately.
  """
  source: String! @iac_validate(with: ["ml-model-source"]) @iac_artifact(language: XML) @iac_input(path: "sourceXML")
  """
  Monotonic source/configuration revision used to reject stale authoring updates; independent of trained model versions.
  """
  authoringRevision: Int! @iac_computed
  """Unique identifier"""
  id: MLModelConfigID! @iac_identity(assignedBy: SERVER) @iac_computed
  """Tenant this config belongs to"""
  tenantId: TenantID! @iac_computed
  """Config name"""
  name: String! @iac_computed
  """Config description"""
  description: String @iac_computed
  """Type of ML model"""
  modelType: MLModelType! @iac_computed
  """Engine that trains/serves this model"""
  backend: MLBackend! @iac_computed
  """
  MicroSQL query for data retrieval. Each SQL page has a 30-second statement timeout; preview sampling does not limit the full training query.
  """
  dataQuerySQL: String @iac_computed @iac_artifact(language: SQL)
  """Concept-specific configuration (tabular or time-series)"""
  spec: MLModelSpec! @iac_computed @iac_validate(with: ["ml-model-spec"])
  """
  Status of the latest training run. A published version remains available for serving while retraining or after a failed run.
  """
  status: MLModelTrainingStatus! @iac_computed
  """Blob storage key for the trained model"""
  trainedModelID: String @iac_computed
  """When the model was last trained (ISO8601)"""
  lastTrainedAt: String @iac_computed
  """Duration of last training run in milliseconds"""
  trainingDurationMs: Int @iac_computed
  """Metrics from last training run"""
  trainingMetrics: TrainingMetrics @iac_computed
  """
  Error message if last training failed; SQL source pages have a 30-second statement timeout
  """
  trainingError: String @iac_computed
  """Feature importance from trained model"""
  featureImportance: [MLFeatureImportance!] @iac_computed
  """Per-round evaluation history"""
  evaluationHistory: [MLEvaluationEntry!] @iac_computed
  """Original CSV filename (if CSV data source)"""
  csvFilename: String @iac_computed
  """Size of uploaded CSV in bytes"""
  csvSizeBytes: Int @iac_computed
  """Whether a CSV file has been uploaded as training data"""
  hasTrainingCSV: Boolean! @iac_computed
  """First few rows of CSV data for preview (header + up to 10 rows)"""
  csvPreviewRows: [[String!]!] @iac_computed
  """
  JSON Schema describing the model's input features (types, enum values). Generated after training.
  """
  inferenceSchema: String @iac_computed
  """
  The pipeline's emitted columns + types (cached from the last preview of the saved config)
  """
  emittedSchema: [MLEmittedColumn!] @iac_computed
  """ID of the version currently used for predictions"""
  publishedVersionId: MLModelConfigVersionID @iac_writtenBy(operation: "publishMLModelVersion", argument: "versionId")
  """Version number of the published version (e.g. 1, 2, 3)"""
  publishedVersionNumber: Int @iac_computed
  """Whether new versions are automatically published after training"""
  autoPublish: Boolean! @iac_computed
  """
  Whether this model is system-managed (auto-created and auto-retrained by the platform)
  """
  isSystem: Boolean! @iac_computed
  """Creation timestamp (ISO8601)"""
  createdAt: String! @iac_computed
  """Last update timestamp (ISO8601)"""
  updatedAt: String! @iac_computed
}