Update app.py

app.py

@@ -354,7 +354,6 @@
 #     gr.Markdown(f"Last updated on **{LAST_UPDATED}**")
 
 # demo.launch()
-
 import gradio as gr
 import pandas as pd
 import os
@@ -364,12 +363,15 @@ from datetime import datetime
 LEADERBOARD_FILE = "leaderboard.csv"  # File to store all submissions persistently
 LAST_UPDATED = datetime.now().strftime("%B %d, %Y")
 
-# Initialize the leaderboard file if it doesn't exist
-if not os.path.exists(LEADERBOARD_FILE):
-    pd.DataFrame(columns=[
-        "Model Name", "Overall Accuracy", "Valid Accuracy",
-        "Correct Predictions", "Total Questions", "Timestamp"
-    ]).to_csv(LEADERBOARD_FILE, index=False)
+def initialize_leaderboard_file():
+    """
+    Check if the leaderboard file exists. If not, create it with appropriate headers.
+    """
+    if not os.path.exists(LEADERBOARD_FILE):
+        pd.DataFrame(columns=[
+            "Model Name", "Overall Accuracy", "Valid Accuracy",
+            "Correct Predictions", "Total Questions", "Timestamp"
+        ]).to_csv(LEADERBOARD_FILE, index=False)
 
 def clean_answer(answer):
     """
@@ -403,11 +405,20 @@ def load_leaderboard():
     """
     Load all submissions from the leaderboard file.
     """
+    if not os.path.exists(LEADERBOARD_FILE):
+        return pd.DataFrame({
+            "Model Name": [],
+            "Overall Accuracy": [],
+            "Valid Accuracy": [],
+            "Correct Predictions": [],
+            "Total Questions": [],
+            "Timestamp": [],
+        })
     return pd.read_csv(LEADERBOARD_FILE)
 
 def evaluate_predictions_and_update_leaderboard(prediction_file):
     """
-    Evaluate predictions and append results to the leaderboard.
+    Evaluate predictions, update the leaderboard, and return the updated leaderboard.
     """
     ground_truth_file = "ground_truth.csv"
     if not os.path.exists(ground_truth_file):
@@ -449,6 +460,9 @@ def evaluate_predictions_and_update_leaderboard(prediction_file):
     except Exception as e:
         return f"Error during evaluation: {str(e)}", load_leaderboard()
 
+# Initialize leaderboard file
+initialize_leaderboard_file()
+
 # Gradio Interface
 with gr.Blocks() as demo:
     gr.Markdown("# Prediction Evaluation Tool with Leaderboard")