fix: include multi_modal_context columns in required_columns (#520) (#522)

`LLMTextColumnConfig.required_columns` and `ImageColumnConfig.required_columns`
only extracted dependencies from Jinja2 prompt templates, missing columns
referenced via `multi_modal_context`. This caused the async engine's execution
graph to dispatch LLM tasks before their multi-modal seed columns were loaded,
resulting in KeyError failures under DATA_DESIGNER_ASYNC_ENGINE=1.

Author: nabinchha

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

@@ -185,14 +185,17 @@ def get_column_emoji() -> str:
 
     @property
     def required_columns(self) -> list[str]:
-        """Get columns referenced in the prompt and system_prompt templates.
+        """Get columns referenced in prompt templates and multi-modal context.
 
         Returns:
-            List of unique column names referenced in Jinja2 templates.
+            List of unique column names referenced in Jinja2 templates
+            and multi-modal context configurations.
         """
         required_cols = list(extract_keywords_from_jinja2_template(self.prompt))
         if self.system_prompt:
             required_cols.extend(list(extract_keywords_from_jinja2_template(self.system_prompt)))
+        if self.multi_modal_context:
+            required_cols.extend(ctx.column_name for ctx in self.multi_modal_context)
         return list(set(required_cols))
 
     @property
@@ -593,12 +596,16 @@ def get_column_emoji() -> str:
 
     @property
     def required_columns(self) -> list[str]:
-        """Get columns referenced in the prompt template.
+        """Get columns referenced in the prompt template and multi-modal context.
 
         Returns:
-            List of unique column names referenced in Jinja2 templates.
+            List of unique column names referenced in Jinja2 templates
+            and multi-modal context configurations.
         """
-        return list(extract_keywords_from_jinja2_template(self.prompt))
+        required_cols = list(extract_keywords_from_jinja2_template(self.prompt))
+        if self.multi_modal_context:
+            required_cols.extend(ctx.column_name for ctx in self.multi_modal_context)
+        return list(set(required_cols))
 
     @model_validator(mode="after")
     def assert_prompt_valid_jinja(self) -> Self:

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

@@ -9,6 +9,7 @@
 from data_designer.config.column_configs import (
     EmbeddingColumnConfig,
     ExpressionColumnConfig,
+    ImageColumnConfig,
     LLMCodeColumnConfig,
     LLMJudgeColumnConfig,
     LLMStructuredColumnConfig,
@@ -26,6 +27,7 @@
     is_plugin_column_type,
 )
 from data_designer.config.errors import InvalidConfigError
+from data_designer.config.models import ImageContext
 from data_designer.config.sampler_params import (
     CategorySamplerParams,
     GaussianSamplerParams,
@@ -122,6 +124,36 @@ def test_llm_text_column_config():
         )
 
 
+def test_llm_text_column_config_required_columns_includes_multi_modal_context():
+    config = LLMTextColumnConfig(
+        name="test_llm_text",
+        prompt="Classify this image: {{ description }}",
+        model_alias=stub_model_alias,
+        multi_modal_context=[ImageContext(column_name="image_base64")],
+    )
+    assert set(config.required_columns) == {"description", "image_base64"}
+
+
+def test_llm_text_column_config_required_columns_deduplicates_multi_modal_and_prompt():
+    config = LLMTextColumnConfig(
+        name="test_llm_text",
+        prompt="Classify this: {{ image_col }}",
+        model_alias=stub_model_alias,
+        multi_modal_context=[ImageContext(column_name="image_col")],
+    )
+    assert config.required_columns == ["image_col"]
+
+
+def test_image_column_config_required_columns_includes_multi_modal_context():
+    config = ImageColumnConfig(
+        name="test_image",
+        prompt="Generate based on {{ style }}",
+        model_alias=stub_model_alias,
+        multi_modal_context=[ImageContext(column_name="reference_image")],
+    )
+    assert set(config.required_columns) == {"style", "reference_image"}
+
+
 def test_llm_text_column_config_with_trace_serialization() -> None:
     """Test that with_trace field serializes and deserializes correctly."""
     config = LLMTextColumnConfig(