Update app.py

app.py

@@ -265,71 +265,124 @@ def make_calendar_heatmap(df, title, year):
     st.pyplot(fig)
 
 
+# Fetch trending accounts with a loading spinner (do this once at the beginning)
+with st.spinner("Loading trending accounts..."):
+    trending_accounts, top_owners_spaces, top_owners_models = get_trending_accounts(limit=100)
+
 # Sidebar
 with st.sidebar:
     st.title("👤 Contributor")
     
-    # Fetch trending accounts with a loading spinner
-    with st.spinner("Loading top trending accounts..."):
-        trending_accounts, top_owners = get_trending_accounts(limit=100)
-    
-    # Show trending accounts list
-    st.subheader("🔥 Top 30 Trending Accounts")
-    
-    # Display the top 30 accounts list with their scores
-    st.markdown("### Trending Contributors Ranking")
+    # Create tabs for Spaces and Models rankings
+    tab1, tab2 = st.tabs(["Spaces Ranking", "Models Ranking"])
     
-    # Create a data frame for the table
-    if top_owners:
-        ranking_data = pd.DataFrame(top_owners[:30], columns=["Contributor", "Spaces Count"])
-        ranking_data.index = ranking_data.index + 1  # Start index from 1 for ranking
+    with tab1:
+        # Show trending accounts list by Spaces
+        st.subheader("🚀 Top 30 by Spaces")
         
-        # Style the table
-        # Add a score column based on spaces count
-        ranking_data["Score"] = ranking_data["Spaces Count"].apply(lambda x: x * 10)  # Multiply by 10 for a score metric
+        # Display the top 30 accounts list with their scores
+        st.markdown("### Spaces Contributors Ranking")
         
-        st.dataframe(
-            ranking_data,
-            column_config={
-                "Contributor": st.column_config.TextColumn("Contributor"),
-                "Spaces Count": st.column_config.NumberColumn("Spaces Count (based on top 500 spaces)", format="%d"),
-                "Score": st.column_config.ProgressColumn(
-                    "Score (within TOP 500 SPACES)",
-                    min_value=0,
-                    max_value=ranking_data["Score"].max() * 1.1,  # Add 10% to max for visual scale
-                    format="%d pts"
-                )
-            },
-            use_container_width=True,
-            hide_index=False
-        )
-    
-    # Add stats expander with visualization
-    with st.expander("View Top 30 Contributor Chart"):
-        # Create a bar chart for top 30 contributors
-        if top_owners:
-            chart_data = pd.DataFrame(top_owners[:30], columns=["Owner", "Spaces Count"])
+        # Create a data frame for the table
+        if top_owners_spaces:
+            ranking_data_spaces = pd.DataFrame(top_owners_spaces[:30], columns=["Contributor", "Spaces Count"])
+            ranking_data_spaces.index = ranking_data_spaces.index + 1  # Start index from 1 for ranking
+            
+            # Add a score column based on spaces count
+            ranking_data_spaces["Score"] = ranking_data_spaces["Spaces Count"].apply(lambda x: x * 10)  # Multiply by 10 for a score metric
             
-            fig, ax = plt.subplots(figsize=(10, 8))
-            bars = ax.barh(chart_data["Owner"], chart_data["Spaces Count"])
+            st.dataframe(
+                ranking_data_spaces,
+                column_config={
+                    "Contributor": st.column_config.TextColumn("Contributor"),
+                    "Spaces Count": st.column_config.NumberColumn("Spaces Count (based on top 500 spaces)", format="%d"),
+                    "Score": st.column_config.ProgressColumn(
+                        "Score (within TOP 500 SPACES)",
+                        min_value=0,
+                        max_value=ranking_data_spaces["Score"].max() * 1.1,  # Add 10% to max for visual scale
+                        format="%d pts"
+                    )
+                },
+                use_container_width=True,
+                hide_index=False
+            )
+        
+        # Add stats expander with visualization
+        with st.expander("View Top 30 Spaces Contributors Chart"):
+            # Create a bar chart for top 30 contributors
+            if top_owners_spaces:
+                chart_data = pd.DataFrame(top_owners_spaces[:30], columns=["Owner", "Spaces Count"])
+                
+                fig, ax = plt.subplots(figsize=(10, 8))
+                bars = ax.barh(chart_data["Owner"], chart_data["Spaces Count"])
+                
+                # Add color gradient to bars
+                for i, bar in enumerate(bars):
+                    bar.set_color(plt.cm.viridis(i/len(bars)))
+                
+                ax.set_title("Top 30 Contributors by Number of Spaces")
+                ax.set_xlabel("Number of Spaces")
+                plt.tight_layout()
+                st.pyplot(fig)
+    
+    with tab2:
+        # Show trending accounts list by Models
+        st.subheader("🧠 Top 30 by Models")
+        
+        # Display the top 30 accounts list with their scores
+        st.markdown("### Models Contributors Ranking")
+        
+        # Create a data frame for the table
+        if top_owners_models:
+            ranking_data_models = pd.DataFrame(top_owners_models[:30], columns=["Contributor", "Models Count"])
+            ranking_data_models.index = ranking_data_models.index + 1  # Start index from 1 for ranking
             
-            # Add color gradient to bars
-            for i, bar in enumerate(bars):
-                bar.set_color(plt.cm.viridis(i/len(bars)))
+            # Add a score column based on models count
+            ranking_data_models["Score"] = ranking_data_models["Models Count"].apply(lambda x: x * 10)  # Multiply by 10 for a score metric
             
-            ax.set_title("Top 30 Contributors by Number of Spaces")
-            ax.set_xlabel("Number of Spaces")
-            plt.tight_layout()
-            st.pyplot(fig)
+            st.dataframe(
+                ranking_data_models,
+                column_config={
+                    "Contributor": st.column_config.TextColumn("Contributor"),
+                    "Models Count": st.column_config.NumberColumn("Models Count (based on top 500 models)", format="%d"),
+                    "Score": st.column_config.ProgressColumn(
+                        "Score (within TOP 500 MODELS)",
+                        min_value=0,
+                        max_value=ranking_data_models["Score"].max() * 1.1,  # Add 10% to max for visual scale
+                        format="%d pts"
+                    )
+                },
+                use_container_width=True,
+                hide_index=False
+            )
+        
+        # Add stats expander with visualization
+        with st.expander("View Top 30 Models Contributors Chart"):
+            # Create a bar chart for top 30 contributors
+            if top_owners_models:
+                chart_data = pd.DataFrame(top_owners_models[:30], columns=["Owner", "Models Count"])
+                
+                fig, ax = plt.subplots(figsize=(10, 8))
+                bars = ax.barh(chart_data["Owner"], chart_data["Models Count"])
+                
+                # Add color gradient to bars
+                for i, bar in enumerate(bars):
+                    bar.set_color(plt.cm.plasma(i/len(bars)))  # Use a different colormap for models
+                
+                ax.set_title("Top 30 Contributors by Number of Models")
+                ax.set_xlabel("Number of Models")
+                plt.tight_layout()
+                st.pyplot(fig)
     
-    # Display trending accounts without additional filtering
+    # Display trending accounts selection dropdown
+    st.subheader("Select Contributor")
     selected_trending = st.selectbox(
         "Select trending account",
         options=trending_accounts[:30],  # Limit to top 30
         index=0 if trending_accounts else None,
         key="trending_selectbox"
     )
-        
+    
     # Custom account input option
     st.markdown("<div style='text-align: center; margin: 10px 0;'>OR</div>", unsafe_allow_html=True)
     custom = st.text_input("", placeholder="Enter custom username/org")
@@ -357,7 +410,7 @@ with st.sidebar:
 st.title("🤗 Hugging Face Contributions")
 if username:
     with st.spinner(f"Fetching commit data for {username}..."):
-        # Display contributor rank if in top 100
+        # Display contributor rank if in top 30
         if username in trending_accounts[:30]:
             rank = trending_accounts.index(username) + 1
             st.success(f"🏆 {username} is ranked #{rank} in the top trending contributors!")
@@ -452,7 +505,7 @@ if username:
             st.metric("Total Commits", total_commits)
             
             # Show contributor rank if in top owners
-            for owner, count in top_owners:
+            for owner, count in top_owners_spaces:
                 if owner.lower() == username.lower():
                     st.metric("Spaces Count", count)
                     break