feat: GenAI Client(evals) - Support show() for EvaluationDataset built from eval_cases

agentplatform/_genai/_evals_common.py

@@ -357,6 +357,16 @@ def _eval_cases_to_dataframe(
                     case.user_scenario.conversation_plan
                 )
 
+        if case.interactions_data_source:
+            row["interaction"] = getattr(
+                case.interactions_data_source, "interaction", None
+            )
+            gemini_cfg = getattr(
+                case.interactions_data_source, "gemini_agent_config", None
+            )
+            if gemini_cfg:
+                row["gemini_agent"] = getattr(gemini_cfg, "gemini_agent", None)
+
         rows.append(row)
     return pd.DataFrame(rows)
 

agentplatform/_genai/_evals_visualization.py

@@ -25,6 +25,7 @@
 import pandas as pd
 from pydantic import errors
 
+from . import _evals_common
 from . import types
 
 
@@ -1552,15 +1553,18 @@ def display_evaluation_dataset(eval_dataset_obj: types.EvaluationDataset) -> Non
     else:
         from IPython import display
 
-    if (
-        eval_dataset_obj.eval_dataset_df is None
-        or eval_dataset_obj.eval_dataset_df.empty
-    ):
-        logger.warning("No inference data to display.")
-        return
+    df = eval_dataset_obj.eval_dataset_df
+
+    # Fall back to eval_cases when eval_dataset_df is not populated (e.g.
+    # when the dataset was constructed manually with eval_cases).
+    if df is None or df.empty:
+        if eval_dataset_obj.eval_cases:
+            df = _evals_common._eval_cases_to_dataframe(eval_dataset_obj.eval_cases)
+        if df is None or df.empty:
+            logger.warning("No inference data to display.")
+            return
 
     processed_rows = []
-    df = eval_dataset_obj.eval_dataset_df
 
     for _, row in df.iterrows():
         processed_row = {}