app update

app.py

@@ -21,17 +21,18 @@ class_label_mapping = {label: idx for idx, label in enumerate(learner_inf.dls.vo
 # Define a function to make predictions
 def predict_text(text):
     prediction = learner_inf.blurr_predict(text)[0]
-    predicted_class_index = prediction['class_index']
-    predicted_class_label = list(class_label_mapping.keys())[list(class_label_mapping.values()).index(predicted_class_index)]
-    return predicted_class_label
+    predicted_probs = prediction['probs']
+    top_5_indices = predicted_probs.argsort(descending=True)[:5]
+    top_5_labels = [list(class_label_mapping.keys())[list(class_label_mapping.values()).index(idx)] for idx in top_5_indices]
+    return top_5_labels
 
 # Create a Gradio interface
 iface = gr.Interface(
     fn=predict_text,
     inputs="text",
-    outputs="text",
-    title="Text Classification App",
-    description="Enter a text, and it will predict the class label.",
+    outputs=gr.outputs.Label(num_top_classes=5),
+    title="Food Origin Classification App",
+    description="Enter a Recipe, and it will predict the class label.",
 )
 
 # Start the Gradio app