Update app.py

app.py

@@ -1800,8 +1800,10 @@ with gr.Blocks(theme='shivi/calm_seafoam', css_paths='style.css', js=js_func) as
                 df = calculate_average_metrics(df, selected_metrics)
                 
                 if flag_TQA:
-                    df["target_answer"] = df["target_answer"] = df["target_answer"].apply(lambda x: "[" + ", ".join(map(str, x)) + "]")
-                    
+                    df["target_answer"] = df["target_answer"].apply(
+                        lambda x: "[" + ", ".join(map(str, x)) + "]" if isinstance(x, (list, tuple))
+                        else ("[]" if pd.isna(x) else str(x))
+                    )
                     worst_cases_df = df.groupby(['model', 'tbl_name', 'test_category', 'question', 'target_answer', 'predicted_answer', 'answer', 'sql_tag'])['avg_metric'].mean().reset_index()
                 else:
                     worst_cases_df = df.groupby(['model', 'tbl_name', 'test_category', 'question', 'query', 'predicted_sql', 'answer', 'sql_tag'])['avg_metric'].mean().reset_index()