Update app.py

app.py

@@ -21,12 +21,17 @@ def predict(name, description):
     definition1 = corpus.iloc[output[0][0].get('corpus_id'),1]
     IRDI1 = corpus.iloc[output[0][0].get('corpus_id'),4]
     score1 = output[0][0].get('score')
-
-    return preferedName1, definition1, IRDI1, score1
+    if score1 < 0.5:
+        reliable = 'false'
+    else:
+        reliable = 'true'
+    scoreOutput = reliable + ' score: ' + score1
+    
+    return preferedName1, definition1, IRDI1, scoreOutput
 
 interface = gr.Interface(fn = predict, 
             inputs = [gr.Textbox(label="Name:", placeholder="Name of the Pump Property", lines=1), gr.Textbox(label="Description:", placeholder="Description of the Pump Property", lines=1)], 
-            outputs = [gr.Textbox(label = 'preferedName'),gr.Textbox(label = 'definition'), gr.Textbox(label = 'IDRI'),gr.Textbox(label = 'score')],
+            outputs = [gr.Textbox(label = 'preferedName'),gr.Textbox(label = 'definition'), gr.Textbox(label = 'IDRI'),gr.Textbox(label = 'prediction reliable')],
             #outputs = [gr.Dataframe(row_count = (5, "fixed"), col_count=(3, "fixed"), label="Predictions", headers=['ECLASS preferedName', 'ECLASS IRDI', 'simularity score'])],
             examples = [['Device type', 'describing a set of common specific characteristics in products or goods'], ['Item type','the type of product, an item can be assigned to'], 
                         ['Nominal power','power being consumed by or dissipated within an electric component as a variable'], ['Power consumption', 'power that is typically taken from the auxiliary power supply when the device is operating normally']],