add modality

graphs/leaderboard.py

@@ -40,7 +40,7 @@ def create_leaderboard(filtered_df, country_df, developer_df, model_df, start_ti
     ).drop(columns=["metric"])
 
     model_df = model_df.merge(
-        filtered_df[["country", "author", "downloads", "org_or_user", "model"]].drop_duplicates(subset=["model"]),
+        filtered_df[["country", "author", "downloads", "org_or_user", "model", "merged_modality"]].drop_duplicates(subset=["model"]),
         left_on="metric", right_on="model", how="left"
     ).drop(columns=["metric"])
 
@@ -71,7 +71,7 @@ def create_leaderboard(filtered_df, country_df, developer_df, model_df, start_ti
         top["% of total"] = top["Total Value"] / total_value * 100 if total_value else 0
 
         # All relevant metadata columns
-        meta_cols = ["country", "author", "downloads", "org_or_user"]
+        meta_cols = ["country", "author", "downloads", "org_or_user", "merged_modality"]
         # Collect all metadata per top n for each category (country, author, model)
         meta_map = {}
         for name in top["Name"]:
@@ -104,6 +104,9 @@ def create_leaderboard(filtered_df, country_df, developer_df, model_df, start_ti
             for d in meta.get("downloads", []):
                 if pd.notna(d):  # Check if d is not NaN
                     chips.append(("⬇️", f"{int(d):,}"))
+            # Modality
+            for m in meta.get("merged_modality", []):
+                chips.append(("", m))
             return chips
         
         # Apply metadata builder to top dataframe