Update app.py

app.py

@@ -785,40 +785,29 @@ with gr.Blocks(css=css_tech_theme) as demo:
                 eval_button = gr.Button("📈 Evaluate",scale=1,min_width=1200)
                 submit_button = gr.Button("📤 Prove and Submit to Leaderboard", elem_id="evaluation-status", visible=False,scale=1,min_width=1200)
                 eval_status = gr.Textbox(label="🛠️ Evaluation Status", interactive=False,scale=1,min_width=1200)
-        
-        # Define the functions outside the `with` block
-        # def handle_evaluation(file, model_name):
-        #     # Check if required inputs are provided
-        #     if not file:
-        #         return "Error: Please upload a prediction file.", 0, gr.update(visible=False)
-        #     if not model_name or model_name.strip() == "":
-        #         return "Error: Please enter a model name.", 0, gr.update(visible=False)
-        
-        #     try:
-        #         # Load predictions file
-        #         predictions_df = pd.read_csv(file.name)
-        
-        #         # Validate required columns in the prediction file
-        #         required_columns = ['question_id', 'predicted_answer']
-        #         missing_columns = [col for col in required_columns if col not in predictions_df.columns]
-        #         if missing_columns:
-        #             return (f"Error: Missing required columns in prediction file: {', '.join(missing_columns)}.",
-        #                     0, gr.update(visible=False))
-        
-        #         # Perform evaluation
-        #         status, leaderboard = evaluate_predictions(file, model_name, add_to_leaderboard=False)
-        #         if leaderboard.empty:
-        #             overall_accuracy = 0
-        #         else:
-        #             overall_accuracy = leaderboard.iloc[-1]["Overall Accuracy"]
 
+
+        with gr.TabItem("📤 Submission-Pro"):
+            gr.Markdown("""
+            <div class="submission-section" style="border: 3px solid #6a1b9a; padding: 20px; border-radius: 12px; box-shadow: 0 4px 10px rgba(106, 27, 154, 0.2);">
+            <h2 style="color: #6a1b9a; text-align: center;">Submit Your Predictions</h2>
+            <p style="font-size: 1.2em; color: #333; text-align: center;">Upload your prediction file and provide your model name to evaluate and optionally submit your results to the leaderboard.</p>
+            </div>
+            """)
+            with gr.Row(elem_id="submission-fields"):
+                file_input = gr.File(label="📂 Upload Prediction CSV for Mobile-MMLU-Pro", file_types=[".csv"], interactive=True,scale=1, min_width=12000)
+                model_name_input = gr.Textbox(label="🏷️ Model Name", placeholder="Enter your model name",scale=1,  min_width=800)
+                Team_name_input = gr.Textbox(label="🏷️ Team Name", placeholder="Enter your Team name",scale=1,  min_width=800)
+        
+            with gr.Row(elem_id="submission-results"):
+                overall_accuracy_display = gr.Number(label="📊 Overall Accuracy (%)", interactive=False,scale=1,min_width=1200)
         
-        #         # Show the submit button after successful evaluation
-        #         return status, overall_accuracy, gr.update(visible=True)
+            with gr.Row(elem_id="submission-buttons"):
+                eval_button = gr.Button("📈 Evaluate",scale=1,min_width=1200)
+                submit_button = gr.Button("📤 Prove and Submit to Leaderboard", elem_id="evaluation-status", visible=False,scale=1,min_width=1200)
+                eval_status = gr.Textbox(label="🛠️ Evaluation Status", interactive=False,scale=1,min_width=1200)
         
-        #     except Exception as e:
-        #         # Handle unexpected errors
-        #         return f"Error during evaluation: {str(e)}", 0, gr.update(visible=False)
+       
 
         def handle_evaluation(file, model_name, Team_name):
             if not file: