ForecastingWorkflowConfig#

class openstef_foundation_models.presets.forecasting_workflow.ForecastingWorkflowConfig(**data: Any) → None[source]

Bases: BaseConfig

Declarative configuration for a foundation-model forecasting workflow.

Selects a model family and the checkpoint that backs it, the requested quantiles and horizons, the target column, and the columns to keep before forecasting. Every kept non-target column is treated as a known covariate, so weather forecasts condition the prediction. Compute settings (execution providers, session options) live on the nested backend config.

Parameters:: data (Any)

model: Literal['chronos2']

checkpoint: Annotated[LocalCheckpoint | HubCheckpoint, FieldInfo(annotation=NoneType, required=True, discriminator='kind')]

quantiles: list[Quantile]

horizons: list[LeadTime]

target_column: str

selected_features: FeatureSelection

backend: OnnxBackendConfig

chronos2_hyperparams: Chronos2HyperParams

model_id: ModelIdentifier

run_name: str | None

experiment_tags: dict[str, str]

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': False, 'extra': 'ignore', 'protected_namespaces': ()}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].