Handle empty DataFrame in leaderboard initialization

app.py

@@ -59,7 +59,36 @@ LEADERBOARD_DF = get_leaderboard_df(EVAL_RESULTS_PATH, EVAL_REQUESTS_PATH, COLS,
 
 def init_leaderboard(dataframe):
     if dataframe is None or dataframe.empty:
-        raise ValueError("Leaderboard DataFrame is empty or None.")
+        # Create empty DataFrame with proper columns for display
+        empty_df = pd.DataFrame(columns=[c.name for c in fields(AutoEvalColumn)])
+        return Leaderboard(
+            value=empty_df,
+            datatype=[c.type for c in fields(AutoEvalColumn)],
+            select_columns=SelectColumns(
+                default_selection=[c.name for c in fields(AutoEvalColumn) if c.displayed_by_default],
+                cant_deselect=[c.name for c in fields(AutoEvalColumn) if c.never_hidden],
+                label="Select Columns to Display:",
+            ),
+            search_columns=[AutoEvalColumn.model.name, AutoEvalColumn.license.name],
+            hide_columns=[c.name for c in fields(AutoEvalColumn) if c.hidden],
+            filter_columns=[
+                ColumnFilter(AutoEvalColumn.model_type.name, type="checkboxgroup", label="Model types"),
+                ColumnFilter(AutoEvalColumn.precision.name, type="checkboxgroup", label="Precision"),
+                ColumnFilter(
+                    AutoEvalColumn.params.name,
+                    type="slider",
+                    min=0.01,
+                    max=150,
+                    label="Select the number of parameters (B)",
+                ),
+                ColumnFilter(
+                    AutoEvalColumn.still_on_hub.name, type="boolean", label="Deleted/incomplete", default=True
+                ),
+            ],
+            bool_checkboxgroup_label="Hide models",
+            interactive=False,
+        )
+    
     return Leaderboard(
         value=dataframe,
         datatype=[c.type for c in fields(AutoEvalColumn)],