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* feat: add dropped column preservation toggle Closes #690 Signed-off-by: Nabin Mulepati <nmulepati@nvidia.com> * fix: reject dropped column policy resume mismatch Signed-off-by: Nabin Mulepati <nmulepati@nvidia.com> --------- Signed-off-by: Nabin Mulepati <nmulepati@nvidia.com> |
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| src/data_designer | ||
| tests | ||
| pyproject.toml | ||
| README.md | ||
data-designer-config
Configuration layer for NeMo Data Designer synthetic data generation framework.
This package provides the configuration API for defining synthetic data generation pipelines. It's a lightweight dependency that can be used standalone for configuration management.
Installation
pip install data-designer-config
Usage
import data_designer.config as dd
# Initialize config builder with model config(s)
config_builder = dd.DataDesignerConfigBuilder(
model_configs=[
dd.ModelConfig(
alias="my-model",
model="nvidia/nemotron-3-nano-30b-a3b",
provider="nvidia",
inference_parameters=dd.ChatCompletionInferenceParams(temperature=0.7),
),
]
)
# Add columns
config_builder.add_column(
dd.SamplerColumnConfig(
name="user_id",
sampler_type=dd.SamplerType.UUID,
params=dd.UUIDSamplerParams(prefix="user-"),
)
)
config_builder.add_column(
dd.LLMTextColumnConfig(
name="description",
prompt="Write a product description",
model_alias="my-model",
)
)
# Build configuration
config = config_builder.build()
See main README.md for more information.