Update app.py

app.py

@@ -162,7 +162,6 @@
 
 # demo.launch()
 
-
 import gradio as gr
 import pandas as pd
 import re
@@ -173,38 +172,42 @@ import os
 
 # Constants for Hugging Face repositories
 HF_TOKEN = os.getenv("HF_TOKEN")  # Hugging Face token stored as an environment variable
+if not HF_TOKEN:
+    raise ValueError("HF_TOKEN is not set. Please add it as a secret in your Hugging Face Space.")
+
 LEADERBOARD_REPO = "SondosMB/leaderboard-dataset"  # Replace with your leaderboard dataset name
 GROUND_TRUTH_REPO = "SondosMB/ground-truth-dataset"  # Replace with your ground truth dataset name
 LAST_UPDATED = datetime.now().strftime("%B %d, %Y")
 
 def load_ground_truth():
     """
-    Load the ground truth file from a private Hugging Face dataset.
+    Load the ground truth file from a gated Hugging Face dataset.
     """
     try:
-        print("Attempting to fetch ground truth...")
+        print("Fetching ground truth file...")
         ground_truth_path = hf_hub_download(
             repo_id=GROUND_TRUTH_REPO,
             filename="ground_truth.csv",
             use_auth_token=HF_TOKEN
         )
-        print(f"Ground truth file downloaded to: {ground_truth_path}")
+        print(f"Ground truth file downloaded: {ground_truth_path}")
         return pd.read_csv(ground_truth_path)
     except Exception as e:
-        print(f"Error loading ground truth: {e}")
+        print(f"Error loading ground truth file: {e}")
         return None
 
-
 def load_leaderboard():
     """
-    Load the leaderboard from a private Hugging Face dataset.
+    Load the leaderboard from a gated Hugging Face dataset.
     """
     try:
+        print("Fetching leaderboard file...")
         leaderboard_path = hf_hub_download(
             repo_id=LEADERBOARD_REPO,
             filename="leaderboard.csv",
             use_auth_token=HF_TOKEN
         )
+        print(f"Leaderboard file downloaded: {leaderboard_path}")
         return pd.read_csv(leaderboard_path)
     except Exception as e:
         print(f"Error loading leaderboard: {e}")
@@ -219,7 +222,7 @@ def load_leaderboard():
 
 def update_leaderboard(results):
     """
-    Append new submission results to the private leaderboard dataset.
+    Append new submission results to the gated leaderboard dataset.
     """
     try:
         # Load existing leaderboard or create a new one
@@ -229,7 +232,8 @@ def update_leaderboard(results):
             use_auth_token=HF_TOKEN
         )
         df = pd.read_csv(leaderboard_path)
-    except:
+    except Exception as e:
+        print(f"Error loading leaderboard: {e}")
         df = pd.DataFrame(columns=[
             "Model Name", "Overall Accuracy", "Valid Accuracy",
             "Correct Predictions", "Total Questions", "Timestamp"
@@ -308,7 +312,7 @@ def evaluate_predictions(prediction_file, model_name, add_to_leaderboard):
 
 # Gradio Interface
 with gr.Blocks() as demo:
-    gr.Markdown("# Secure Prediction Evaluation Tool with Private Leaderboard")
+    gr.Markdown("# Secure Prediction Evaluation Tool with Gated Leaderboard")
     
     with gr.Tabs():
         # Submission Tab
@@ -350,3 +354,4 @@ with gr.Blocks() as demo:
 demo.launch()
 
 
+