Update app.py

app.py

@@ -19,11 +19,11 @@ def predict_NB(text):
   ps = PorterStemmer()
   text = ' '.join([ps.stem(word) for word in text.split()])
   X = tfidf.transform([text]).toarray()
-  return 'spam' if model.predict(X)[0] == 1 else 0
+  return 'spam' if model.predict(X)[0] == 1 else 'not_spam'
 
 def predict_PIPE(text):
   result = pipe(text)[0]
-  return f'''{'spam' if result['label']=='LABEL_1' else 0}
+  return f'''{'spam' if result['label']=='LABEL_1' else 'not_spam'}
 confidence : {result['score']}'''
 
 def fn(model_choice, input):