Update app.py

app.py

@@ -401,98 +401,34 @@ with gr.Blocks(css=css_tech_theme) as demo:
                     <li>5️⃣ <strong>Leaderboard:</strong> View real-time rankings on the leaderboard.</li>
                 </ul>
             </div>
-            """)    
-
-
-        # with gr.TabItem("📤 Submission"):
-        #     gr.Markdown("<div class='tabs'><h2>Submit Your Predictions</h2></div>")
-        #     with gr.Row():
-        #         file_input = gr.File(label="Upload Prediction CSV", file_types=[".csv"], interactive=True)
-        #         model_name_input = gr.Textbox(label="Model Name", placeholder="Enter your model name")
-
-        #     with gr.Row():
-        #         overall_accuracy_display = gr.Number(label="Overall Accuracy", interactive=False)
-        #         add_to_leaderboard_checkbox = gr.Checkbox(label="Add to Leaderboard?", value=True)
-
-        #     eval_button = gr.Button("Evaluate")
-        #     eval_status = gr.Textbox(label="Evaluation Status", interactive=False)
-
-        #     def handle_evaluation(file, model_name, add_to_leaderboard):
-        #         status, leaderboard = evaluate_predictions(file, model_name, add_to_leaderboard)
-        #         if leaderboard.empty:
-        #             overall_accuracy = 0
-        #         else:
-        #             overall_accuracy = leaderboard.iloc[-1]["Overall Accuracy"]
-        #         return status, overall_accuracy
-
-        #     eval_button.click(
-        #         handle_evaluation,
-        #         inputs=[file_input, model_name_input, add_to_leaderboard_checkbox],
-        #         outputs=[eval_status, overall_accuracy_display],
-        #     )
-
-        # with gr.TabItem("📤 Submission"):
-        #     with gr.Row():
-        #         file_input = gr.File(label="Upload Prediction CSV", file_types=[".csv"], interactive=True)
-        #         model_name_input = gr.Textbox(label="Model Name", placeholder="Enter your model name")
-        #     with gr.Row():
-        #         overall_accuracy_display = gr.Number(label="Overall Accuracy", interactive=False)
-        #         eval_button = gr.Button("Evaluate")
-        #         eval_status = gr.Textbox(label="Evaluation Status", interactive=False)
-        #         submit_button = gr.Button("Prove and Submit to Leaderboard", visible=False)  # Initially hidden
-        #     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)
-        #         # 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"]
-        #             # Show the submit button after evaluation
-        #             return status, overall_accuracy, gr.update(visible=True)
-        #     def handle_submission(file, model_name):
-        #         # Handle leaderboard submission
-        #         status, _ = evaluate_predictions(file, model_name, add_to_leaderboard=True)
-        #         return f"Submission to leaderboard completed: {status}"
-        #     eval_button.click(
-        #         handle_evaluation,
-        #         inputs=[file_input, model_name_input],
-        #         outputs=[eval_status, overall_accuracy_display, submit_button],)
-        #     submit_button.click(
-        #         handle_submission,
-        #         inputs=[file_input, model_name_input],
-        #         outputs=[eval_status],)
+            """)  
+            
         with gr.TabItem("📤 Submission"):
             with gr.Markdown("""
             <div class="submission-section">
             <h2>Submit Your Predictions</h2>
             <p>Upload your prediction file and provide your model name to evaluate and submit to the leaderboard.</p> </div>"""):
-                
-        with gr.Row(elem_id="submission-fields"):
-            file_input = gr.File(label="Upload Prediction CSV", file_types=[".csv"], interactive=True)
-            model_name_input = gr.Textbox(label="Model Name", placeholder="Enter your model name")
-        with gr.Row(elem_id="submission-results"):
-            overall_accuracy_display = gr.Number(label="Overall Accuracy", interactive=False)
-        with gr.Row(elem_id="submission-buttons"):
-            eval_button = gr.Button("Evaluate")
-            submit_button = gr.Button("Prove and Submit to Leaderboard", visible=False)
-            eval_status = gr.Textbox(label="Evaluation Status", interactive=False)
-    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)
-        # 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.Row(elem_id="submission-fields"):
+                file_input = gr.File(label="Upload Prediction CSV", file_types=[".csv"], interactive=True)
+                model_name_input = gr.Textbox(label="Model Name", placeholder="Enter your model name")
+            with gr.Row(elem_id="submission-results"):
+                overall_accuracy_display = gr.Number(label="Overall Accuracy", interactive=False)
+            with gr.Row(elem_id="submission-buttons"):
+                eval_button = gr.Button("Evaluate")
+                submit_button = gr.Button("Prove and Submit to Leaderboard", visible=False)
+                eval_status = gr.Textbox(label="Evaluation Status", interactive=False)
+            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)
+                    # 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"]
         # Show the submit button after evaluation
         return status, overall_accuracy, gr.update(visible=True)
     def handle_submission(file, model_name):