Update app.py

app.py

@@ -19,12 +19,12 @@ nltk.download('punkt')
 from nltk.stem.porter import PorterStemmer
 stemmer = PorterStemmer()
 
-def tokenize(input_text):
+def tokenize(sentence):
     """
     split sentence into array of words/tokens
     a token can be a word or punctuation character, or number
     """
-    return nltk.word_tokenize(input_text)
+    return nltk.word_tokenize(sentence)
 
 # print(tokenize('Hello how are you'))
 
@@ -295,8 +295,8 @@ bot_name = "Sam"
 
 
 def get_response(msg):
-    input_text= tokenize(msg)
-    X = bag_of_words(input_text, all_words)
+    sentence= tokenize(msg)
+    X = bag_of_words(sentence, all_words)
     X = X.reshape(1, X.shape[0])
     X = torch.from_numpy(X).to(device)
 
@@ -317,12 +317,15 @@ def get_response(msg):
 print("Let's chat! (type 'quit' to exit)")
 while True:
     # sentence = "do you use credit cards?"
-    input_text= str(input("You: "))
-    if input_text== "quit":
+    try:
+        sentence= input("You: ")
+    except EOFError as e:
+        print(end="")
+    if sentence== "quit":
         break
 
-    input_text= tokenize(input_text)
-    X = bag_of_words(input_text, all_words)
+    sentence= tokenize(sentence)
+    X = bag_of_words(sentence, all_words)
     X = X.reshape(1, X.shape[0])
     X = torch.from_numpy(X).to(device)
 
@@ -342,9 +345,9 @@ while True:
 
 
 
-#def get_chatbot(input_text):
+#def get_chatbot(sentence):
   
-  #return classifier(input_text)
+  #return classifier(sentence)
 
 title = "ChatBOT"