Update app.py

app.py

@@ -79,34 +79,27 @@ if option == '1':
     chatbot.load_weights("predict3")
     chatbot.build(input_shape=(None, max_len)) # Build the model
     chatbot.compile(optimizer="adam", loss="sparse_categorical_crossentropy")
-    other_text1 = text
+    
     for i in range(1):
-
+        other_text1 = text
         other_text1 = other_text1.lower()
         other_words1 = other_text1.split()
-        if len(other_words1) > 1:
-            st.write("Error: Found more than 1 word . There should not be more than one word in the prompt ")
-        for word in other_words1:
-            if word not in word_to_num:
-                st.write("Error: The word ` ",word," ` doesn't exist in the vocabulary and hence the model wasn't train on that. ")
-            else:
-                other_num1 = word_to_num[word]
-
+        other_num1 = [word_to_num[word] for word in other_words1]
         given_X1 = other_num1
         input_sequence1 = pad_sequences([given_X1], maxlen=max_len, padding='post')
-        output_sentence = other_text1 + ""
-        for _ in range(16):
+        output_sentence = other_text1+""
+        for _ in range(15):
             predicted_token = np.argmax(chatbot.predict(input_sequence1), axis=-1)
             predicted_token = predicted_token.item()
             out = num_to_word[predicted_token]
-            
-
-            output_sentence += " " + out
             if out == ".":
                 break
+    
+            output_sentence += " " + out
             given_X1 = given_X1[1:]
             given_X1.append(predicted_token)
             input_sequence1 = pad_sequences([given_X1], maxlen=max_len, padding='post')
+
         out = output_sentence