Update app.py

app.py

@@ -11,7 +11,7 @@ import contractions
 import tensorflow as tf
 from nltk.stem import WordNetLemmatizer
 from nltk.tokenize import word_tokenize
-from nltk.corpus import stopwords, wordnet
+from nltk.corpus import wordnet
 from tensorflow.keras.layers import Layer
 from tensorflow.keras import backend as K
 from tensorflow.keras.preprocessing.sequence import pad_sequences
@@ -101,13 +101,6 @@ def cleaning(text):
 
         return mapped_tags
     
-    def remove_stopwords(text):
-        stop_words = set(stopwords.words('english'))
-        tokens = word_tokenize(text)
-        filtered_text = [word for word in tokens if word.lower() not in stop_words]
-        return ' '.join(filtered_text)
-    text = remove_stopwords(text)
-    
     def pos_tag_and_lemmatize(text):
         tokens = word_tokenize(text)
         pos_tags = nltk.pos_tag(tokens)