nemo_microservices.data_designer.config.data_designer_config

Module Contents

Classes

DataDesignerConfig

Configuration for NeMo Data Designer.

API

class nemo_microservices.data_designer.config.data_designer_config.DataDesignerConfig(/, **data: typing.Any)

Bases: nemo_microservices.data_designer.config.base.ExportableConfigBase

Configuration for NeMo Data Designer.

This class defines the main configuration structure for NeMo Data Designer, which orchestrates the generation of synthetic data.

Attributes: columns: Required list of column configurations defining how each column should be generated. Must contain at least one column. model_configs: Optional list of model configurations for LLM-based generation. Each model config defines the model, provider, and inference parameters. seed_config: Optional seed dataset settings to use for generation. constraints: Optional list of column constraints. profilers: Optional list of column profilers for analyzing generated data characteristics.

Initialization

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

columns: list[Annotated[nemo_microservices.data_designer.config.column_types.ColumnConfigT, Field(discriminator='column_type')]]

‘Field(…)’

constraints: Optional[list[nemo_microservices.data_designer.config.sampler_constraints.ColumnConstraintT]]

None

model_configs: Optional[list[nemo_microservices.data_designer.config.models.ModelConfig]]

None

processors: Optional[list[nemo_microservices.data_designer.config.processors.ProcessorConfig]]

None

profilers: Optional[list[nemo_microservices.data_designer.config.analysis.column_profilers.ColumnProfilerConfigT]]

None

seed_config: Optional[nemo_microservices.data_designer.config.seed.SeedConfig]

None