code update

src/leaderboard/read_evals.py

@@ -203,14 +203,14 @@ def get_raw_eval_results(results_path: str, requests_path: str) -> list[EvalResu
     """From the path of the results folder root, extract all needed info for results"""
     model_result_filepaths = []
 
-    print(f"DEBUG: Results path: {results_path}")
-    try:
-        files = os.listdir(results_path)
-        for f in files:
-            print(f)
-    except FileNotFoundError:
-        print(f"Error: Directory not found at {results_path}")
-        return [] # Exit early if path doesn't exist
+    # print(f"DEBUG: Results path: {results_path}")
+    # try:
+    #     files = os.listdir(results_path)
+    #     for f in files:
+    #         print(f)
+    # except FileNotFoundError:
+    #     print(f"Error: Directory not found at {results_path}")
+    #     return [] # Exit early if path doesn't exist
 
 
     

src/populate.py

@@ -10,13 +10,13 @@ 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:
     raw_data = get_raw_eval_results(results_path, requests_path)
-    print(f"DEBUG: Raw data: {raw_data}")
+    # print(f"DEBUG: Raw data: {raw_data}")
     all_data_json = [v.to_dict() for v in raw_data]
-    print(f"DEBUG: All data JSON: {all_data_json}")
+    # print(f"DEBUG: All data JSON: {all_data_json}")
 
     df = pd.DataFrame.from_records(all_data_json)
-    print(f"DEBUG: DataFrame columns: {list(df.columns)}")
-    print(f"DEBUG: Looking for column: {AutoEvalColumn.average.name}")
+    # print(f"DEBUG: DataFrame columns: {list(df.columns)}")
+    # print(f"DEBUG: Looking for column: {AutoEvalColumn.average.name}")
     df = df.sort_values(by=[AutoEvalColumn.average.name], ascending=False)
     df = df[cols].round(decimals=2)