Update app.py

app.py

@@ -478,17 +478,6 @@ def create_leaderboard(selected_categories):
     
     return df
 
-first_model = next(iter(models.values()))
-category_choices = list(first_model['scores'].keys())
-
-with gr.Column(visible=True) as leaderboard_tab:
-    leaderboard_output = gr.DataFrame(
-        value=create_leaderboard(category_choices),
-        interactive=False,
-        wrap=True,
-        datatype=["markdown", "markdown", "markdown"] + ["markdown"] * (len(category_choices)+1)  # Support markdown in all columns
-    )
-
 def hex_to_rgba(hex_color, alpha):
     """Convert hex color to rgba string with given alpha value."""
     hex_color = hex_color.lstrip('#')
@@ -832,14 +821,16 @@ with gr.Blocks(css=css) as demo:
     initial_df = create_leaderboard(category_choices)
     
     with gr.Row():
-        tab_selection = gr.Radio(["Leaderboard", "Category Analysis", "Detailed Scorecard"], 
-                               label="Select Tab", value="Leaderboard")
+        # Change tab order to put Detailed Scorecard first, Category Analysis second, and Leaderboard third
+        tab_selection = gr.Radio(["Detailed Scorecard", "Category Analysis", "Leaderboard"], 
+                               label="Select Tab", value="Detailed Scorecard")
     
     with gr.Row():
+        # Make model_chooser visible by default since Detailed Scorecard is first tab
         model_chooser = gr.Dropdown(choices=[""] + list(models.keys()),
                                   label="Select AI System for Details", 
                                   value="",
-                                  interactive=True, visible=False)
+                                  interactive=True, visible=True)
         model_multi_chooser = gr.Dropdown(choices=list(models.keys()),
                                         label="Select AI Systems for Comparison",
                                         value=[],
@@ -853,7 +844,8 @@ with gr.Blocks(css=css) as demo:
                                      label="Filter Categories", 
                                      value=category_choices)
     
-    with gr.Column(visible=True) as leaderboard_tab:
+    # Make leaderboard tab not visible by default
+    with gr.Column(visible=False) as leaderboard_tab:
         leaderboard_output = gr.DataFrame(
             value=initial_df,
             interactive=False,
@@ -861,15 +853,17 @@ with gr.Blocks(css=css) as demo:
             datatype=["markdown", "markdown", "markdown"] + ["markdown"] * (len(category_choices)+1)  # Support markdown in all columns
         )
     
+    # Make category analysis tab not visible by default
     with gr.Column(visible=False) as category_analysis_tab:
         # 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()
+    # Make detailed scorecard tab visible by default
+    with gr.Column(visible=True) as detailed_scorecard_tab:
+        model_metadata = gr.HTML(value="Please select a model to view details.", visible=True)
+        all_category_cards = gr.HTML(visible=False)
+        total_score = gr.Markdown(visible=False)
 
     def update_dashboard(tab, selected_models, selected_model, selected_categories):
         # Default visibility states