Update src/populate.py

src/populate.py

@@ -1,70 +1 @@
-import os
-import pandas as pd
-import json
-
-from src.display.utils import COLUMNS, EVAL_COLS, Tasks
-from src.envs import EVAL_RESULTS_PATH
-
-def get_leaderboard_df(eval_results_path, eval_requests_path, cols, benchmark_cols):
-    # Initialize an empty DataFrame
-    df = pd.DataFrame(columns=cols)
-
-    # Load evaluation results from JSON files
-    if os.path.exists(eval_results_path):
-        result_files = [
-            os.path.join(eval_results_path, f) 
-            for f in os.listdir(eval_results_path) 
-            if f.endswith('.json')
-        ]
-        data_list = []
-        for file in result_files:
-            with open(file, 'r') as f:
-                data = json.load(f)
-                flattened_data = {}
-                flattened_data.update(data.get('config', {}))
-                flattened_data.update(data.get('results', {}))
-                data_list.append(flattened_data)
-        if data_list:
-            df = pd.DataFrame(data_list)
-
-    # Ensure DataFrame has all columns
-    for col in cols:
-        if col not in df.columns:
-            df[col] = None
-
-    # Convert 'average' column to float and handle errors
-    if 'average' in df.columns:
-        df['average'] = pd.to_numeric(df['average'], errors='coerce')
-
-    # Sort by 'average' column if it exists
-    if 'average' in df.columns:
-        df = df.sort_values(by=['average'], ascending=False)
-
-    return df
-
-def get_evaluation_queue_df(eval_requests_path, eval_cols):
-    # Initialize empty DataFrames
-    finished_df = pd.DataFrame(columns=eval_cols)
-    running_df = pd.DataFrame(columns=eval_cols)
-    pending_df = pd.DataFrame(columns=eval_cols)
-
-    # Load evaluation requests from JSON files
-    if os.path.exists(eval_requests_path):
-        request_files = [
-            os.path.join(eval_requests_path, f) 
-            for f in os.listdir(eval_requests_path) 
-            if f.endswith('.json')
-        ]
-        data_list = []
-        for file in request_files:
-            with open(file, 'r') as f:
-                data = json.load(f)
-                data_list.append(data)
-        if data_list:
-            df = pd.DataFrame(data_list)
-            # Split DataFrame based on status
-            finished_df = df[df['status'] == 'finished']
-            running_df = df[df['status'] == 'running']
-            pending_df = df[df['status'] == 'pending']
-
-    return finished_df, running_df, pending_df
+d