rolling back to good version

app.py

@@ -327,14 +327,14 @@ def transform_image(image_bytes):
 def get_prediction(image_tensor, model):
     """Get prediction from model - optimized"""
     try:
-    with torch.no_grad():
+        with torch.no_grad():
             # Ensure tensor is on CPU for consistency
             if image_tensor.device.type != 'cpu':
                 image_tensor = image_tensor.cpu()
             
-        outputs = model(image_tensor)
-        probabilities = torch.nn.functional.softmax(outputs[0], dim=0)
-        top5_prob, top5_indices = torch.topk(probabilities, 5)
+            outputs = model(image_tensor)
+            probabilities = torch.nn.functional.softmax(outputs[0], dim=0)
+            top5_prob, top5_indices = torch.topk(probabilities, 5)
             
             # Convert to Python types immediately for faster processing
             top5_prob = top5_prob.cpu().numpy()
@@ -344,7 +344,7 @@ def get_prediction(image_tensor, model):
         for i in range(5):
             predictions.append({
                 'food': CLASS_NAMES[top5_indices[i]],
-                    'confidence': float(top5_prob[i] * 100)
+                'confidence': float(top5_prob[i] * 100)
             })
         
         return predictions