fix(config): round-trip processors and profilers

packages/data-designer-config/src/data_designer/config/config_builder.py

@@ -140,6 +140,12 @@ def from_config(cls, config: dict | str | Path | BuilderConfig) -> Self:
                 selection_strategy=seed_config.selection_strategy,
             )
 
+        for processor in data_designer_config.processors or []:
+            builder.add_processor(processor)
+
+        for profiler in data_designer_config.profilers or []:
+            builder.add_profiler(profiler)
+
         return builder
 
     def __init__(

packages/data-designer-config/tests/config/test_config_builder.py

@@ -33,11 +33,12 @@
     InvalidColumnTypeError,
     InvalidConfigError,
 )
+from data_designer.config.mcp import ToolConfig
 from data_designer.config.models import ChatCompletionInferenceParams, ModelConfig
 from data_designer.config.processors import DropColumnsProcessorConfig, SchemaTransformProcessorConfig
 from data_designer.config.sampler_constraints import ColumnInequalityConstraint, ScalarInequalityConstraint
 from data_designer.config.sampler_params import SamplerType, UUIDSamplerParams
-from data_designer.config.seed import SamplingStrategy
+from data_designer.config.seed import IndexRange, SamplingStrategy
 from data_designer.config.seed_source import HuggingFaceSeedSource
 from data_designer.config.seed_source_dataframe import DataFrameSeedSource
 from data_designer.config.utils.code_lang import CodeLang
@@ -97,6 +98,87 @@ def test_from_config(stub_data_designer_builder_config_str):
     assert isinstance(builder_from_object.get_column_config(name="code_id"), SamplerColumnConfig)
 
 
+def test_from_config_restores_processors_and_profilers(stub_model_configs: list[ModelConfig]) -> None:
+    builder = DataDesignerConfigBuilder(model_configs=stub_model_configs)
+    builder.add_column(SamplerColumnConfig(name="test_id", sampler_type="uuid", params=UUIDSamplerParams()))
+    processor_config = SchemaTransformProcessorConfig(name="records", template={"id": "{{ test_id }}"})
+    profiler_config = JudgeScoreProfilerConfig(model_alias="stub-model", summary_score_sample_size=5)
+
+    builder.add_processor(processor_config)
+    builder.add_profiler(profiler_config)
+
+    loaded_builder = DataDesignerConfigBuilder.from_config(builder.get_builder_config())
+
+    assert loaded_builder.get_processor_configs() == [processor_config]
+    assert loaded_builder.get_profilers() == [profiler_config]
+
+
+def test_from_config_restores_drop_column_processor_side_effects(stub_model_configs: list[ModelConfig]) -> None:
+    builder = DataDesignerConfigBuilder(model_configs=stub_model_configs)
+    for column_name in ("col_a", "col_b", "other"):
+        builder.add_column(SamplerColumnConfig(name=column_name, sampler_type="uuid", params=UUIDSamplerParams()))
+    processor_config = DropColumnsProcessorConfig(name="cleanup", column_names=["col_*"])
+
+    builder.add_processor(processor_config)
+
+    loaded_builder = DataDesignerConfigBuilder.from_config(builder.get_builder_config())
+
+    assert loaded_builder.get_processor_configs() == [processor_config]
+    assert loaded_builder.get_column_config("col_a").drop is True
+    assert loaded_builder.get_column_config("col_b").drop is True
+    assert loaded_builder.get_column_config("other").drop is False
+
+
+def test_from_config_round_trips_all_data_designer_config_fields(stub_model_configs: list[ModelConfig]) -> None:
+    data_designer_config_fields = set(DataDesignerConfig.model_fields)
+
+    builder = DataDesignerConfigBuilder(
+        model_configs=stub_model_configs,
+        tool_configs=[
+            ToolConfig(
+                tool_alias="lookup-tools",
+                providers=["local-tools"],
+                allow_tools=["lookup"],
+                max_tool_call_turns=2,
+                timeout_sec=1.0,
+            )
+        ],
+    )
+    builder.with_seed_dataset(
+        HuggingFaceSeedSource(path="datasets/test-repo/data/*.parquet", token="test-token"),
+        sampling_strategy=SamplingStrategy.SHUFFLE,
+        selection_strategy=IndexRange(start=1, end=3),
+    )
+    builder.add_column(
+        name="age",
+        column_type=DataDesignerColumnType.SAMPLER,
+        sampler_type=SamplerType.UNIFORM,
+        params={"low": 1, "high": 100},
+    )
+    builder.add_column(
+        name="height",
+        column_type=DataDesignerColumnType.SAMPLER,
+        sampler_type=SamplerType.UNIFORM,
+        params={"low": 15, "high": 200},
+    )
+    builder.add_column(
+        SamplerColumnConfig(name="internal_id", sampler_type=SamplerType.UUID, params=UUIDSamplerParams())
+    )
+    builder.add_constraint(ScalarInequalityConstraint(target_column="age", operator="gt", rhs=18))
+    builder.add_constraint(ColumnInequalityConstraint(target_column="height", operator="gt", rhs="age"))
+    builder.add_processor(SchemaTransformProcessorConfig(name="records", template={"age": "{{ age }}"}))
+    builder.add_processor(DropColumnsProcessorConfig(name="cleanup", column_names=["internal_*"]))
+    builder.add_profiler(JudgeScoreProfilerConfig(model_alias="stub-model", summary_score_sample_size=5))
+
+    original_config = builder.build()
+    loaded_config = DataDesignerConfigBuilder.from_config(BuilderConfig(data_designer=original_config)).build()
+
+    assert set(original_config.model_fields_set) == data_designer_config_fields
+    assert set(loaded_config.model_fields_set) == data_designer_config_fields
+    for field_name in sorted(data_designer_config_fields):
+        assert getattr(loaded_config, field_name) == getattr(original_config, field_name)
+
+
 def test_from_config_auto_wraps_bare_data_designer_config(stub_data_designer_config_str: str) -> None:
     """Test that from_config auto-wraps a bare DataDesignerConfig (no 'data_designer' wrapper)."""
     builder = DataDesignerConfigBuilder.from_config(config=stub_data_designer_config_str)