Update app.py

app.py

@@ -34,6 +34,30 @@ def cached_list_items(username, kind):
     return []
 
 
+# Function to fetch trending model repositories
+@lru_cache(maxsize=1)
+def get_trending_accounts(limit=100):
+    try:
+        # Fetch trending models, datasets, and spaces
+        trending_models = list(api.list_models(sort="trending", limit=limit))
+        trending_datasets = list(api.list_datasets(sort="trending", limit=limit))
+        trending_spaces = list(api.list_spaces(sort="trending", limit=limit))
+        
+        # Extract unique authors
+        authors = set()
+        for item in trending_models + trending_datasets + trending_spaces:
+            if hasattr(item, "author"):
+                authors.add(item.author)
+            elif hasattr(item, "id") and "/" in item.id:
+                authors.add(item.id.split("/")[0])
+        
+        # Return sorted list of unique authors
+        return sorted(list(authors))[:limit]
+    except Exception as e:
+        st.error(f"Error fetching trending accounts: {str(e)}")
+        return ["ritvik77", "facebook", "google", "stabilityai", "Salesforce", "tiiuae", "bigscience"]
+
+
 # Rate limiting
 class RateLimiter:
     def __init__(self, calls_per_second=10):
@@ -180,37 +204,99 @@ def make_calendar_heatmap(df, title, year):
 # Sidebar
 with st.sidebar:
     st.title("👤 Contributor")
-    username = st.selectbox(
-        "Select or type a username",
-        options=["ritvik77", "facebook", "google", "stabilityai", "Salesforce", "tiiuae", "bigscience"],
-        index=0
-    )
-    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")
-    if custom.strip():
-        username = custom.strip()
+    
+    # Fetch trending accounts with a loading spinner
+    with st.spinner("Loading top trending accounts..."):
+        trending_accounts = get_trending_accounts(limit=100)
+    
+    # Create a tab interface for selection method
+    tab1, tab2 = st.tabs(["Top 100 Trending", "Custom User"])
+    
+    with tab1:
+        # Show trending accounts list with search filter
+        st.subheader("🔥 Top Trending Accounts")
+        search_filter = st.text_input("Filter accounts", key="trending_filter")
+        
+        # Filter accounts based on search
+        filtered_accounts = [acc for acc in trending_accounts if search_filter.lower() in acc.lower()] if search_filter else trending_accounts
+        
+        # Show account count
+        st.caption(f"Showing {len(filtered_accounts)} accounts")
+        
+        # Create a scrollable container for the accounts list
+        account_container = st.container()
+        with account_container:
+            selected_trending = st.selectbox(
+                "Select trending account",
+                options=filtered_accounts,
+                index=0 if filtered_accounts else None,
+                key="trending_selectbox"
+            )
+            
+            if selected_trending:
+                username = selected_trending
+    
+    with tab2:
+        st.subheader("🔎 Custom Account")
+        default_accounts = ["ritvik77", "facebook", "google", "stabilityai", "Salesforce", "tiiuae", "bigscience"]
+        custom_account = st.selectbox(
+            "Select or type a username",
+            options=default_accounts,
+            index=0
+        )
+        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")
+        if custom.strip():
+            username = custom.strip()
+        elif tab2._active and not tab1._active:  # Only set if tab2 is active
+            username = custom_account
+    
+    # Year selection (outside tabs to always be visible)
+    st.subheader("🗓️ Time Period")
     year_options = list(range(datetime.now().year, 2017, -1))
-    selected_year = st.selectbox("🗓️ Year", options=year_options)
+    selected_year = st.selectbox("Select Year", options=year_options)
+    
+    # Additional options for customization
+    st.subheader("⚙️ Display Options")
+    show_models = st.checkbox("Show Models", value=True)
+    show_datasets = st.checkbox("Show Datasets", value=True)
+    show_spaces = st.checkbox("Show Spaces", value=True)
 
 # Main Content
 st.title("🤗 Hugging Face Contributions")
 if username:
-    with st.spinner("Fetching commit data..."):
+    with st.spinner(f"Fetching commit data for {username}..."):
         # Create a dictionary to store commits by type
         commits_by_type = {}
         commit_counts_by_type = {}
-
-        # Fetch commits for each type separately
-        for kind in ["model", "dataset", "space"]:
+        
+        # Determine which types to fetch based on checkboxes
+        types_to_fetch = []
+        if show_models:
+            types_to_fetch.append("model")
+        if show_datasets:
+            types_to_fetch.append("dataset")
+        if show_spaces:
+            types_to_fetch.append("space")
+        
+        if not types_to_fetch:
+            st.warning("Please select at least one content type to display (Models, Datasets, or Spaces)")
+            st.stop()
+
+        # Fetch commits for each selected type
+        for kind in types_to_fetch:
             try:
                 items = cached_list_items(username, kind)
                 repo_ids = [item.id for item in items]
+                
+                st.info(f"Found {len(repo_ids)} {kind}s for {username}")
 
                 # Process repos in chunks
                 chunk_size = 5
                 total_commits = 0
                 all_commit_dates = []
 
+                progress_bar = st.progress(0)
                 for i in range(0, len(repo_ids), chunk_size):
                     chunk = repo_ids[i:i + chunk_size]
                     with ThreadPoolExecutor(max_workers=min(5, len(chunk))) as executor:
@@ -223,6 +309,13 @@ if username:
                             if repo_commits:
                                 all_commit_dates.extend(repo_commits)
                                 total_commits += repo_count
+                    
+                    # Update progress
+                    progress = min(1.0, (i + len(chunk)) / max(1, len(repo_ids)))
+                    progress_bar.progress(progress)
+                
+                # Complete progress
+                progress_bar.progress(1.0)
 
                 commits_by_type[kind] = all_commit_dates
                 commit_counts_by_type[kind] = total_commits
@@ -236,7 +329,20 @@ if username:
         total_commits = sum(commit_counts_by_type.values())
 
         st.subheader(f"{username}'s Activity in {selected_year}")
-        st.metric("Total Commits", total_commits)
+        
+        # Profile information
+        profile_col1, profile_col2 = st.columns([1, 3])
+        with profile_col1:
+            # Try to get avatar
+            try:
+                avatar_url = f"https://huggingface.co/avatars/{username}"
+                st.image(avatar_url, width=150)
+            except:
+                st.info("No profile image available")
+        
+        with profile_col2:
+            st.metric("Total Commits", total_commits)
+            st.markdown(f"[View Profile on Hugging Face](https://huggingface.co/{username})")
 
         # Create DataFrame for all commits
         all_commits = []
@@ -248,26 +354,30 @@ if username:
 
         make_calendar_heatmap(all_df, "All Commits", selected_year)
 
-        # Metrics and heatmaps for each type
-        col1, col2, col3 = st.columns(3)
-        for col, kind, emoji, label in [
-            (col1, "model", "🧠", "Models"),
-            (col2, "dataset", "📦", "Datasets"),
-            (col3, "space", "🚀", "Spaces")
-        ]:
-            with col:
-                try:
-                    total = len(cached_list_items(username, kind))
-                    commits = commits_by_type.get(kind, [])
-                    commit_count = commit_counts_by_type.get(kind, 0)
-                    df_kind = pd.DataFrame(commits, columns=["date"])
-                    if not df_kind.empty:
-                        df_kind = df_kind.drop_duplicates()  # Remove any duplicate dates
-                    st.metric(f"{emoji} {label}", total)
-                    st.metric(f"Commits in {selected_year}", commit_count)
-                    make_calendar_heatmap(df_kind, f"{label} Commits", selected_year)
-                except Exception as e:
-                    st.warning(f"Error processing {label}: {str(e)}")
-                    st.metric(f"{emoji} {label}", 0)
-                    st.metric(f"Commits in {selected_year}", 0)
-                    make_calendar_heatmap(pd.DataFrame(), f"{label} Commits", selected_year)
+        # Metrics and heatmaps for each selected type
+        cols = st.columns(len(types_to_fetch)) if types_to_fetch else st.columns(1)
+        
+        for i, (kind, emoji, label) in enumerate([
+            ("model", "🧠", "Models"),
+            ("dataset", "📦", "Datasets"),
+            ("space", "🚀", "Spaces")
+        ]):
+            if kind in types_to_fetch:
+                with cols[types_to_fetch.index(kind)]:
+                    try:
+                        total = len(cached_list_items(username, kind))
+                        commits = commits_by_type.get(kind, [])
+                        commit_count = commit_counts_by_type.get(kind, 0)
+                        df_kind = pd.DataFrame(commits, columns=["date"])
+                        if not df_kind.empty:
+                            df_kind = df_kind.drop_duplicates()  # Remove any duplicate dates
+                        st.metric(f"{emoji} {label}", total)
+                        st.metric(f"Commits in {selected_year}", commit_count)
+                        make_calendar_heatmap(df_kind, f"{label} Commits", selected_year)
+                    except Exception as e:
+                        st.warning(f"Error processing {label}: {str(e)}")
+                        st.metric(f"{emoji} {label}", 0)
+                        st.metric(f"Commits in {selected_year}", 0)
+                        make_calendar_heatmap(pd.DataFrame(), f"{label} Commits", selected_year)
+else:
+    st.info("Please select an account from the sidebar to view contributions.")