update app.py

app.py

@@ -14,16 +14,16 @@ from src.about import (
 )
 from src.display.css_html_js import custom_css
 from src.display.utils import (
-    BENCHMARK_COLS,
+    COLUMNS,
     COLS,
+    BENCHMARK_COLS,
     EVAL_COLS,
     EVAL_TYPES,
-    COLUMNS,  # Added this line
-    AutoEvalColumn,
     ModelType,
     WeightType,
     Precision
 )
+
 from src.envs import API, EVAL_REQUESTS_PATH, EVAL_RESULTS_PATH, QUEUE_REPO, REPO_ID, RESULTS_REPO, TOKEN
 from src.populate import get_evaluation_queue_df, get_leaderboard_df
 from src.submission.submit import add_new_eval
@@ -58,21 +58,18 @@ LEADERBOARD_DF = get_leaderboard_df(EVAL_RESULTS_PATH, EVAL_REQUESTS_PATH, COLS,
 
 def init_leaderboard(dataframe):
     if dataframe is None or dataframe.empty:
-        # Instead of raising an error, display an empty leaderboard with a message
         print("Leaderboard DataFrame is empty. No models have been evaluated yet.")
-        # Create an empty DataFrame with the necessary columns
-        dataframe = pd.DataFrame(columns=[c.name for c in COLUMNS])
-        # Optionally, you can add a message to the interface to inform users
+        dataframe = pd.DataFrame(columns=[col.name for col in COLUMNS])
     return Leaderboard(
         value=dataframe,
-        datatype=[c.type for c in COLUMNS],
+        datatype=[col.type for col in COLUMNS],
         select_columns=SelectColumns(
-            default_selection=[c.name for c in COLUMNS if c.displayed_by_default],
-            cant_deselect=[c.name for c in COLUMNS if c.never_hidden],
+            default_selection=[col.name for col in COLUMNS if col.displayed_by_default],
+            cant_deselect=[col.name for col in COLUMNS if col.never_hidden],
             label="Select Columns to Display:",
         ),
-        search_columns=[c.name for c in COLUMNS if c.name in ["model", "license"]],
-        hide_columns=[c.name for c in COLUMNS if c.hidden],
+        search_columns=[col.name for col in COLUMNS if col.name in ["model", "license"]],
+        hide_columns=[col.name for col in COLUMNS if col.hidden],
         filter_columns=[
             ColumnFilter("model_type", type="checkboxgroup", label="Model types"),
             ColumnFilter("precision", type="checkboxgroup", label="Precision"),