update populate

src/populate.py

@@ -8,17 +8,20 @@ from src.display.utils import AutoEvalColumn, EvalQueueColumn
 from src.leaderboard.read_evals import get_raw_eval_results
 
 
-def get_leaderboard_df(results_path: str, requests_path: str, cols: list, benchmark_cols: list) -> pd.DataFrame:
-    """Creates a dataframe from all the individual experiment results"""
-    raw_data = get_raw_eval_results(results_path, requests_path)
-    all_data_json = [v.to_dict() for v in raw_data]
-
-    df = pd.DataFrame.from_records(all_data_json)
+def get_leaderboard_df(eval_results_path, eval_requests_path, cols, benchmark_cols):
+    # Load evaluation results into a DataFrame
+    df = load_evaluation_results(eval_results_path)
+
+    # Check if the DataFrame is empty
+    if df.empty:
+        print("No evaluation results found. The leaderboard is currently empty.")
+        # Create an empty DataFrame with the required columns
+        df = pd.DataFrame(columns=cols)
+        return df
+
+    # Proceed to sort the DataFrame by 'average' if it's not empty
     df = df.sort_values(by=['average'], ascending=False)
-    df = df[cols].round(decimals=2)
 
-    # Filter out if any of the benchmarks have not been produced
-    df = df[has_no_nan_values(df, benchmark_cols)]
     return df