Update app.py

app.py

@@ -175,7 +175,7 @@ def create_overall_summary(model_data, selected_categories):
     
     # Create summary HTML
     html = "<div class='card overall-summary-card'>"
-    html += "<div class='card-title'>📊 Overall Model Evaluation Summary</div>"
+    html += "<div class='card-title'>📊 Overall AI System Evaluation Summary</div>"
     
     # Key metrics section
     html += "<div class='summary-grid'>"
@@ -276,7 +276,7 @@ def get_modality_icon(modality):
 def create_metadata_card(metadata):
     """Create a formatted HTML card for metadata."""
     html = "<div class='card metadata-card'>"
-    html += "<div class='card-title'>Model Information</div>"
+    html += "<div class='card-title'>AI System Information</div>"
     html += "<div class='metadata-content'>"
     
     # Handle special formatting for modalities
@@ -374,12 +374,16 @@ def create_leaderboard(selected_categories):
         # Calculate overall score
         score_percentage = (total_score / total_questions * 100) if total_questions > 0 else 0
         
-        # Get model type
+        # Get model type and URL
         model_type = data['metadata'].get('Type', 'Unknown')
+        model_url = data['metadata'].get('URL', '')
+        
+        # Create model name with HTML link if URL exists
+        model_display = f'<a href="{model_url}" target="_blank">{model}</a>' if model_url else model
         
         # Create entry with numerical scores
         model_entry = {
-            'AI System': model,
+            'AI System': model_display,
             'Type': model_type,
             'Overall Completion Rate': score_percentage
         }
@@ -453,7 +457,7 @@ def create_category_chart(selected_models, selected_categories):
                 
                 score_percentage = (total_score / total_questions * 100) if total_questions > 0 else 0
                 data.append({
-                    'Model': model,
+                    'AI System': model,
                     'Category': category,
                     'Completion Rate': score_percentage
                 })
@@ -462,8 +466,8 @@ def create_category_chart(selected_models, selected_categories):
     if df.empty:
         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',
+        fig = px.bar(df, x='AI System', y='Completion Rate', color='Category',
+                     title='AI System Evaluation Completion Rates by Category',
                      labels={'Completion Rate': 'Completion Rate (%)'},
                      category_orders={"Category": selected_categories})
     
@@ -1224,7 +1228,7 @@ first_model = next(iter(models.values()))
 category_choices = list(first_model['scores'].keys())
 
 with gr.Blocks(css=css) as demo:
-    gr.Markdown("# AI Model Social Impact Scorecard Dashboard")
+    gr.Markdown("# AI System Social Impact Dashboard")
     
     with gr.Row():
         tab_selection = gr.Radio(["Leaderboard", "Category Analysis", "Detailed Scorecard"], 
@@ -1232,16 +1236,16 @@ with gr.Blocks(css=css) as demo:
     
     with gr.Row():
         model_chooser = gr.Dropdown(choices=[""] + list(models.keys()),
-                                  label="Select Model for Details", 
+                                  label="Select AI System for Details", 
                                   value="",
                                   interactive=True, visible=False)
         model_multi_chooser = gr.Dropdown(choices=list(models.keys()),
-                                        label="Select Models for Comparison",
+                                        label="Select AI Systems for Comparison",
                                         value=[],
                                         multiselect=True, 
                                         interactive=True, 
                                         visible=False,
-                                        info="Select one or more models")
+                                        info="Select one or more AI Systems")
     
     # Category filter now visible for all tabs
     category_filter = gr.CheckboxGroup(choices=category_choices,
@@ -1249,12 +1253,11 @@ with gr.Blocks(css=css) as demo:
                                      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=initial_df,
+            value=create_leaderboard(category_choices),
             interactive=False,
-            wrap=True
+            wrap=True,
+            datatype=["markdown", "markdown", "markdown"] + ["markdown"] * len(category_choices)  # Set markdown type for all columns
         )
     
     with gr.Column(visible=False) as category_analysis_tab: