Update app.py

app.py

@@ -290,12 +290,12 @@ def evaluate_scientific_submission(
     description: str,
     detected_category: str,
     validation_info: Dict,
-) -> Tuple[str, pd.DataFrame, object, object, object]:
+) -> Tuple[str, pd.DataFrame, object, object]:
     """Evaluate validated predictions using scientific methodology."""
     
     try:
         if predictions_df is None:
-            return "❌ No valid predictions to evaluate", None, None, None, None
+            return "❌ No valid predictions to evaluate", None, None, None
         
         # Get complete test set with targets
         global complete_test_set, current_leaderboard
@@ -310,7 +310,7 @@ def evaluate_scientific_submission(
         
         if any(track_data.get('error') for track_data in evaluation_results.get('tracks', {}).values()):
             errors = [track_data['error'] for track_data in evaluation_results['tracks'].values() if track_data.get('error')]
-            return f"❌ Evaluation errors: {'; '.join(errors)}", None, None, None, None
+            return f"❌ Evaluation errors: {'; '.join(errors)}", None, None, None
         
         # Add to scientific leaderboard
         print("🏆 Adding to scientific leaderboard...")
@@ -387,11 +387,11 @@ def evaluate_scientific_submission(
 {report}
         """
         
-        return success_msg, display_leaderboard, summary_plot, cross_track_plot, updated_leaderboard
+        return success_msg, display_leaderboard, summary_plot, cross_track_plot
 
     except Exception as e:
         error_msg = f"❌ Scientific evaluation failed: {str(e)}\n\nTraceback:\n{traceback.format_exc()}"
-        return error_msg, None, None, None, None
+        return error_msg, None, None, None
 
 def refresh_track_leaderboard(
     track: str,
@@ -1217,7 +1217,7 @@ with gr.Blocks(
     # Submit for evaluation
     def handle_scientific_submission(predictions, model_name, author, description, category, validation_info):
         if predictions is None:
-            return "❌ Please validate your submission first", None, None, None, None
+            return "❌ Please validate your submission first", None, None, None
         
         return evaluate_scientific_submission(
             predictions, model_name, author, description, category, validation_info
@@ -1226,7 +1226,7 @@ with gr.Blocks(
     submit_btn.click(
         fn=handle_scientific_submission,
         inputs=[predictions_validated, model_name_input, author_input, description_input, detected_category_state, validation_info_state],
-        outputs=[evaluation_output, results_table, submission_plot, cross_track_plot, current_leaderboard]
+        outputs=[evaluation_output, results_table, submission_plot, cross_track_plot]
     )
     
     # Track leaderboard refresh functions
@@ -1274,27 +1274,31 @@ with gr.Blocks(
         outputs=[comparison_output, comparison_plot]
     )
     
-    # Update dropdown choices when leaderboard changes
-    def update_dropdown_choices():
+    # Load initial data and update dropdowns
+    def load_initial_data():
+        # Load initial Google track data
+        google_data = refresh_google_track("", "all", 0.0)
+        
+        # Update dropdown choices
         if current_leaderboard is not None and not current_leaderboard.empty:
             model_choices = current_leaderboard['model_name'].tolist()
         else:
             model_choices = []
         
         return (
-            gr.Dropdown(choices=model_choices),
-            gr.CheckboxGroup(choices=model_choices)
+            google_data[0],  # google_leaderboard
+            google_data[1],  # google_ranking_plot  
+            google_data[2],  # google_comparison_plot
+            google_data[3],  # google_stats
+            gr.Dropdown(choices=model_choices),  # model_select
+            gr.CheckboxGroup(choices=model_choices)  # comparison_models
         )
     
-    # Load initial data and update dropdowns
     demo.load(
-        fn=lambda: (
-            refresh_google_track("", "all", 0.0),
-            update_dropdown_choices()
-        ),
+        fn=load_initial_data,
         outputs=[
-            [google_leaderboard, google_ranking_plot, google_comparison_plot, google_stats],
-            [model_select, comparison_models]
+            google_leaderboard, google_ranking_plot, google_comparison_plot, google_stats,
+            model_select, comparison_models
         ]
     )