chore: Avoid rendering empty columns as part of detailed results rendering of eval results

It is common for expected response and expected tool calls column to be empty for user simulated conversations. So, we don't render those.

Co-authored-by: Ankur Sharma <ankusharma@google.com>
PiperOrigin-RevId: 826202867

src/google/adk/cli/cli_eval.py

@@ -214,14 +214,16 @@ def pretty_print_eval_result(eval_result: EvalCaseResult):
     expected_invocation = per_invocation_result.expected_invocation
     row_data = {
         "prompt": _convert_content_to_text(actual_invocation.user_content),
-        "expected_response": _convert_content_to_text(
+        "expected_response": (
-            expected_invocation.final_response if expected_invocation else None
+            _convert_content_to_text(expected_invocation.final_response)
+            if expected_invocation
+            else None
         ),
         "actual_response": _convert_content_to_text(
             actual_invocation.final_response
         ),
-        "expected_tool_calls": _convert_tool_calls_to_text(
+        "expected_tool_calls": (
-            expected_invocation.intermediate_data
+            _convert_tool_calls_to_text(expected_invocation.intermediate_data)
             if expected_invocation
             else None
         ),
@@ -252,11 +254,23 @@ def pretty_print_eval_result(eval_result: EvalCaseResult):
     )
     click.echo("Invocation Details:")
     df = pd.DataFrame(data)
+
+    # Identify columns where ALL values are exactly None
+    columns_to_keep = []
     for col in df.columns:
-      if df[col].dtype == "object":
+      # Check if all elements in the column are NOT None
-        df[col] = df[col].str.wrap(40)
+      if not df[col].apply(lambda x: x is None).all():
-    click.echo(tabulate(df, headers="keys", tablefmt="grid"))
+        columns_to_keep.append(col)
-  click.echo("\n\n")  # Few empty lines for visual clarity
+
+    # Select only the columns to keep
+    df_result = df[columns_to_keep]
+
+    for col in df_result.columns:
+      if df_result[col].dtype == "object":
+        df_result[col] = df_result[col].str.wrap(40)
+
+    click.echo(tabulate(df_result, headers="keys", tablefmt="grid"))
+    click.echo("\n\n")  # Few empty lines for visual clarity
 
 
 def get_eval_sets_manager(