Update app.py

app.py

@@ -431,7 +431,9 @@ with gr.Column(visible=True) as leaderboard_tab:
 
 def create_category_chart(selected_models, selected_categories):
     if not selected_models:
-        return px.bar(title='Please select at least one model for comparison')
+        fig = px.bar(title='Please select at least one model for comparison')
+        fig.update_layout(showlegend=True)  # Ensure legend remains visible
+        return fig
     
     # Sort categories before processing
     selected_categories = sort_categories(selected_categories)
@@ -453,17 +455,19 @@ def create_category_chart(selected_models, selected_categories):
                 data.append({
                     'Model': model,
                     'Category': category,
-                    'Score Percentage': score_percentage
+                    'Completion Rate': score_percentage
                 })
     
     df = pd.DataFrame(data)
     if df.empty:
-        return px.bar(title='No data available for the selected models and categories')
+        fig = px.bar(title='No data available for the selected models and categories')
+    else:
+        fig = px.bar(df, x='Model', y='Completion Rate', color='Category',
+                     title='AI Model Evaluation Completion Rates by Category',
+                     labels={'Completion Rate': 'Completion Rate (%)'},
+                     category_orders={"Category": selected_categories})
     
-    fig = px.bar(df, x='Model', y='Score Percentage', color='Category',
-                 title='AI Model Scores by Category',
-                 labels={'Score Percentage': 'Score Percentage'},
-                 category_orders={"Category": selected_categories})
+    fig.update_layout(showlegend=True)  # Ensure legend remains visible
     return fig
 
 def update_detailed_scorecard(model, selected_categories):
@@ -1238,111 +1242,94 @@ with gr.Blocks(css=css) as demo:
                                         interactive=True, 
                                         visible=False,
                                         info="Select one or more models")
-                                        
+    
     # Category filter now visible for all tabs
     category_filter = gr.CheckboxGroup(choices=category_choices,
                                      label="Filter Categories", 
                                      value=category_choices)
     
     with gr.Column(visible=True) as leaderboard_tab:
+        # Initialize with data
+        initial_df = create_leaderboard(category_choices)
         leaderboard_output = gr.DataFrame(
-            value=create_leaderboard(category_filter.value),  # Initialize with all categories selected
+            value=initial_df,
             interactive=False,
             wrap=True
-    )
+        )
     
     with gr.Column(visible=False) as category_analysis_tab:
-        category_chart = gr.Plot()
+        # Initialize with empty plot
+        initial_plot = create_category_chart([], category_choices)
+        category_chart = gr.Plot(value=initial_plot)
     
     with gr.Column(visible=False) as detailed_scorecard_tab:
         model_metadata = gr.HTML()
         all_category_cards = gr.HTML()
         total_score = gr.Markdown()
 
-    # Initialize the dashboard
-    def init_leaderboard():
-        df = create_leaderboard(category_filter.value)
-        return df
-
-    leaderboard_output.value = init_leaderboard()
-    
-    # Update handlers
     def update_dashboard(tab, selected_models, selected_model, selected_categories):
-        leaderboard_visibility = gr.update(visible=False)
-        category_chart_visibility = gr.update(visible=False)
-        detailed_scorecard_visibility = gr.update(visible=False)
-        model_chooser_visibility = gr.update(visible=False)
-        model_multi_chooser_visibility = gr.update(visible=False)
-
-        if tab == "Leaderboard":
-            leaderboard_visibility = gr.update(visible=True)
-            df = create_leaderboard(selected_categories)
-            return [leaderboard_visibility, category_chart_visibility, detailed_scorecard_visibility,
-                    model_chooser_visibility, model_multi_chooser_visibility,
-                    gr.update(value=df), gr.update(), gr.update(), gr.update(), gr.update()]
+        # Default visibility states
+        component_states = {
+            "leaderboard": False,
+            "category_chart": False,
+            "detailed_scorecard": False,
+            "model_chooser": False,
+            "model_multi_chooser": False
+        }
         
+        # Initialize outputs with None
+        outputs = {
+            "leaderboard": None,
+            "category_chart": None,
+            "model_metadata": None,
+            "category_cards": None,
+            "total_score": None
+        }
+        
+        # Update visibility based on selected tab
+        if tab == "Leaderboard":
+            component_states["leaderboard"] = True
+            outputs["leaderboard"] = create_leaderboard(selected_categories)
             
         elif tab == "Category Analysis":
-            category_chart_visibility = gr.update(visible=True)
-            model_multi_chooser_visibility = gr.update(visible=True)
-            category_filter_visibility = gr.update(visible=True)
-            category_plot = create_category_chart(selected_models or [], selected_categories)
-            return [leaderboard_visibility, category_chart_visibility, detailed_scorecard_visibility,
-                    model_chooser_visibility, model_multi_chooser_visibility, category_filter_visibility,
-                    None, gr.update(value=category_plot), gr.update(), gr.update(), gr.update()]
-        
+            component_states["category_chart"] = True
+            component_states["model_multi_chooser"] = True
+            if selected_models:  # Only update chart if models are selected
+                outputs["category_chart"] = create_category_chart(selected_models, selected_categories)
+            
         elif tab == "Detailed Scorecard":
-            detailed_scorecard_visibility = gr.update(visible=True)
-            model_chooser_visibility = gr.update(visible=True)
-            category_filter_visibility = gr.update(visible=True)
+            component_states["detailed_scorecard"] = True
+            component_states["model_chooser"] = True
             if selected_model:
                 scorecard_updates = update_detailed_scorecard(selected_model, selected_categories)
-            else:
-                scorecard_updates = [
-                    gr.update(value="Please select a model to view details.", visible=True),
-                    gr.update(visible=False),
-                    gr.update(visible=False)
-                ]
-            return [leaderboard_visibility, category_chart_visibility, detailed_scorecard_visibility,
-                    model_chooser_visibility, model_multi_chooser_visibility, category_filter_visibility,
-                    None, None] + scorecard_updates
+                outputs["model_metadata"] = scorecard_updates[0]
+                outputs["category_cards"] = scorecard_updates[1]
+                outputs["total_score"] = scorecard_updates[2]
+        
+        # Return updates in the correct order
+        return [
+            gr.update(visible=component_states["leaderboard"]),
+            gr.update(visible=component_states["category_chart"]),
+            gr.update(visible=component_states["detailed_scorecard"]),
+            gr.update(visible=component_states["model_chooser"]),
+            gr.update(visible=component_states["model_multi_chooser"]),
+            outputs["leaderboard"] if outputs["leaderboard"] is not None else gr.update(),
+            outputs["category_chart"] if outputs["category_chart"] is not None else gr.update(),
+            outputs["model_metadata"] if outputs["model_metadata"] is not None else gr.update(),
+            outputs["category_cards"] if outputs["category_cards"] is not None else gr.update(),
+            outputs["total_score"] if outputs["total_score"] is not None else gr.update()
+        ]
 
     # Set up event handlers
-    tab_selection.change(
-        fn=update_dashboard,
-        inputs=[tab_selection, model_multi_chooser, model_chooser, category_filter],
-        outputs=[leaderboard_tab, category_analysis_tab, detailed_scorecard_tab,
-                model_chooser, model_multi_chooser,
-                leaderboard_output, category_chart, model_metadata,
-                all_category_cards, total_score]
-    )
-
-    model_chooser.change(
-        fn=update_dashboard,
-        inputs=[tab_selection, model_multi_chooser, model_chooser, category_filter],
-        outputs=[leaderboard_tab, category_analysis_tab, detailed_scorecard_tab,
-                model_chooser, model_multi_chooser, category_filter,
-                leaderboard_output, category_chart, model_metadata,
-                all_category_cards, total_score]
-    )
-
-    model_multi_chooser.change(
-        fn=update_dashboard,
-        inputs=[tab_selection, model_multi_chooser, model_chooser, category_filter],
-        outputs=[leaderboard_tab, category_analysis_tab, detailed_scorecard_tab,
-                model_chooser, model_multi_chooser, category_filter,
-                leaderboard_output, category_chart, model_metadata,
-                all_category_cards, total_score]
-    )
-
-    category_filter.change(
-        fn=update_dashboard,
-        inputs=[tab_selection, model_multi_chooser, model_chooser, category_filter],
-        outputs=[leaderboard_tab, category_analysis_tab, detailed_scorecard_tab,
-                model_chooser, model_multi_chooser,
-                leaderboard_output, category_chart, model_metadata,
-                all_category_cards, total_score]
-    )
+    for component in [tab_selection, model_chooser, model_multi_chooser, category_filter]:
+        component.change(
+            fn=update_dashboard,
+            inputs=[tab_selection, model_multi_chooser, model_chooser, category_filter],
+            outputs=[leaderboard_tab, category_analysis_tab, detailed_scorecard_tab,
+                    model_chooser, model_multi_chooser,
+                    leaderboard_output, category_chart, model_metadata,
+                    all_category_cards, total_score]
+        )
 
 # Launch the app
 if __name__ == "__main__":