app update

app.py

@@ -21,19 +21,19 @@ 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_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
+    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
 
 # Create a Gradio interface
 iface = gr.Interface(
     fn=predict_text,
     inputs="text",
-    outputs=gr.outputs.Label(num_top_classes=5),
+    outputs="text",
     title="Food Origin Classification App",
     description="Enter a Recipe, and it will predict the class label.",
 )
 
 # Start the Gradio app
 iface.launch()
+