Update app.py

app.py

@@ -44,8 +44,8 @@ st.subheader("Next Word Prediction AI Model by Webraft-AI")
 #Picking what NLP task you want to do
 option = st.selectbox('Model',('1')) #option is stored in this variable
 #Textbox for text user is entering
-st.subheader("Enter the text you'd like to analyze.")
-text = st.text_input('Enter word: ') #text is stored in this variable
+st.subheader("Enter a word from which a sentence would be predicted")
+text2 = st.text_input('Enter word: ') #text is stored in this variable
 
 if option == '1':
     with open("data2.txt","r") as f:
@@ -81,30 +81,31 @@ if option == '1':
     chatbot.compile(optimizer="adam", loss="sparse_categorical_crossentropy")
     
     for i in range(1):
-        other_text1 = text
+        other_text1 = text2
         other_text1 = other_text1.lower()
         other_words1 = other_text1.split()
         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(15):
+        for _ in range(1):
             predicted_token = np.argmax(chatbot.predict(input_sequence1), axis=-1)
             predicted_token = predicted_token.item()
             out = num_to_word[predicted_token]
-            if out == ".":
-                break
+            
     
             output_sentence += " " + out
+            if out == ".":
+                break
             given_X1 = given_X1[1:]
             given_X1.append(predicted_token)
             input_sequence1 = pad_sequences([given_X1], maxlen=max_len, padding='post')
 
-        out = output_sentence
+        out2 = output_sentence
         
     
 else:
-    out = "Wrong Model"
+    out2 = "Wrong Model"
     
 st.write("Predicted Text: ")
-st.write(out)
+st.write(out2)