Update app.py

app.py

@@ -19,14 +19,14 @@ vectorizer.adapt(X.values)
 def evaluate_comment(Comment):
     processed_Comment = vectorizer([Comment])
     res = model.predict(processed_Comment)
-
+    display = {}
     text = ''
     for i, col in enumerate(df.columns[2:]):
-        text += '{}: {}\n'.format(col, 'Violate' if res[0][i] > 0.5 else 'None')
+        display[col] = '🆘' if res[0][i] > 0.5 else '😄'
     
-    return text
+    return display
     
-interface = gr.Interface(fn = evaluate_comment, inputs = gr.inputs.Textbox(lines = 4, placeholder='Comment to evaluate'), 
-                        outputs = 'text', description="An NLP model that classifies level of toxicity of the sentence.")
+interface = gr.Interface(fn = evaluate_comment, live = True, title='ToxClass', inputs = gr.inputs.Textbox(lines = 4, placeholder='Comment to evaluate'), 
+                        outputs = 'label', description="An NLP model that classifies level of toxicity of the sentence.")
                          
 interface.launch()