tuned the model

app.py

@@ -74,8 +74,7 @@ def LemNormalize(text):
   return LemTokens(nltk.word_tokenize(text.lower().translate(remove_punct_dict)))
 
 def NLTK(input):
-    return None
-    f = open('corpus.txt', errors='strict')
+    f = open('/content/corpus.txt', errors='strict')
     data = f.read()
     data = data.lower()
     sent_tokens = nltk.sent_tokenize(data)
@@ -103,7 +102,7 @@ def generator(input=None):
 
         out1 = NLTK(input)
         if(out1):
-            response.append(out)
+            response.append(out1)
 
         out2 = pattern(input)
         if(out2):