Update app.py

app.py

@@ -13,12 +13,16 @@ def decide(text):
   tokenized_text = tokenizer.texts_to_sequences([text])
   padded_tokens = pad_sequences(tokenized_text, maxlen= 200)
   result = model.predict(padded_tokens, verbose=0)
-  if result[:] < 0.5 :
-    output = "negative"
+  if result[:] > 0.6 :
+    output = f"Positive review with {result : .0%} confidence score"
+  elif result[:] < 0.4:
+    output = f"Negative review with {result : .0%} confidence score"
   else:
-    output = "positive"
+    output = "Neutral"
   return output
   
+
+  
 example_sentence_1 = "I hate the movie, they made no effort in making the movie. Waste of time!"
 example_sentence_2 = "Awesome movie! Loved the way in which the hero acted."
 examples = [[example_sentence_1], [example_sentence_2]]