Fix context manager and launch order

app.py

@@ -14,7 +14,7 @@ import tempfile
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 # Constants
-MODEL_ID = "Tumo505/SSL-ECG-CLASSIFICATION"
+MODEL_ID = "Tumo505/ssrl-ecg-simclr-finetuned"
 CLASS_LABELS = ["NORM", "MI", "STTC", "HYP", "CD"]
 CLASS_COLORS = {
     "NORM": "#90EE90",
@@ -42,7 +42,6 @@ def predict_ecg(file_obj):
         return (
             "**Model Loading Error**\n"
             "The model failed to load. Please try again or contact support.",
-            None,
             None
         )
     
@@ -65,9 +64,8 @@ def predict_ecg(file_obj):
         if ecg.ndim != 2:
             return (
                 "**Invalid Format**\n"
-                f"Expected 2D array, got shape {{ecg.shape}}\n"
+                f"Expected 2D array, got shape {ecg.shape}\n"
                 "Expected: (12 leads, N samples)",
-                None,
                 None
             )
         
@@ -78,9 +76,8 @@ def predict_ecg(file_obj):
             else:
                 return (
                     "**Invalid Dimensions**\n"
-                    f"Got shape {{ecg.shape}}, expected (12, N)\n"
+                    f"Got shape {ecg.shape}, expected (12, N)\n"
                     "Ensure file has 12 leads (rows) × N samples (columns)",
-                    None,
                     None
                 )
         
@@ -173,17 +170,16 @@ def predict_ecg(file_obj):
         return output_md, fig, None
         
     except FileNotFoundError:
-        return "**File Error:** Could not read uploaded file", None, None
+        return "**File Error:** Could not read uploaded file", None
     except Exception as e:
         import traceback
-        error_msg = f"**Error:** {{str(e)}}\n\nDebug: {{traceback.format_exc()}}"
-        return error_msg, None, None
+        error_msg = f"**Error:** {str(e)}\n\nDebug: {traceback.format_exc()}"
+        return error_msg, None
 
 
 # Create interface
 with gr.Blocks(
-    title="ECG Classification with Self-Supervised Learning",
-    theme=gr.themes.Soft(primary_hue="emerald")
+    title="ECG Classification with Self-Supervised Learning"
 ) as demo:
     
     gr.Markdown("""
@@ -245,9 +241,9 @@ with gr.Blocks(
     submit_btn.click(
         fn=predict_ecg,
         inputs=[file_input],
-        outputs=[output_text, chart_output, None]
+        outputs=[output_text, chart_output]
     )
-    
+
     # Info section
     gr.Markdown("""
     ---
@@ -269,7 +265,7 @@ with gr.Blocks(
     
     **Research Only** - Not validated for clinical use
     
-    [View Model Card](https://huggingface.co/{MODEL_ID})  
+    [View Model Card](https://huggingface.co/Tumo505/ssrl-ecg-simclr-finetuned)  
     [GitHub Repository](https://github.com/Tumo505/SSL-for-ECG-classification)
     """)