Update app.py

app.py

@@ -106,36 +106,39 @@ def create_stats_html():
         type_dist['model_type'] = type_dist['model_type'].str.capitalize()
         
         # Create bar chart with better formatting
-        fig_types = px.bar(
-            type_dist, 
-            x='model_type', 
-            y='downloads_30d',
-            title='Downloads by Model Type',
-            labels={
-                'downloads_30d': 'Downloads (last 30 days)', 
-                'model_type': 'Model Type'
-            },
-            text=type_dist['downloads_30d'].apply(format_number)  # Add value labels
-        )
+        fig_types = go.Figure()
+        
+        # Add bars
+        fig_types.add_trace(go.Bar(
+            x=type_dist['model_type'],
+            y=type_dist['downloads_30d'],
+            text=type_dist['downloads_30d'].apply(format_number),
+            textposition='outside',
+        ))
         
-        # Update layout for better readability and fix y-axis
-        fig_types.update_traces(textposition='outside')
+        # Update layout
         fig_types.update_layout(
-            uniformtext_minsize=8,
-            uniformtext_mode='hide',
-            xaxis_tickangle=0,
-            yaxis_title="Downloads",
+            title='Downloads by Model Type',
+            yaxis_type="log",  # Set y-axis to log scale
+            yaxis=dict(
+                title="Downloads",
+                type='log',
+                dtick=1,  # This controls the tick spacing
+                tickformat=".1s"  # Format ticks with K, M suffix
+            ),
+            xaxis=dict(
+                title="Model Type"
+            ),
             plot_bgcolor='white',
             bargap=0.3,
-            yaxis=dict(
-                type='log',  # Use log scale for better visualization
-                range=[0, np.log10(type_dist['downloads_30d'].max() * 1.2)],  # Add some padding at the top
-            )
+            height=600,
+            showlegend=False,
+            margin=dict(t=100, b=50)  # Add margin for labels
         )
         
     else:
         # Create empty figure if no data
-        fig_types = px.bar(title='No data available')
+        fig_types = go.Figure()
     
     # Create top models table
     if len(derivative_df) > 0: