Update app.py

still punkt issue

app.py

@@ -14,17 +14,21 @@ from nltk.tokenize import word_tokenize, sent_tokenize
 from sklearn.feature_extraction.text import CountVectorizer
 
 nltk_data_path = '/home/user/nltk_data'
+
 if not os.path.exists(nltk_data_path):
     os.makedirs(nltk_data_path)
+
+nltk.data.path.append(nltk_data_path)
+if not os.path.exists(os.path.join(nltk_data_path, "tokenizers/punkt")):
     nltk.download('punkt', download_dir=nltk_data_path)
+if not os.path.exists(os.path.join(nltk_data_path, "corpora/stopwords")):
     nltk.download('stopwords', download_dir=nltk_data_path)
-else:
-    if not os.path.exists(os.path.join(nltk_data_path, "tokenizers/punkt")):
-        nltk.download('punkt', download_dir=nltk_data_path)
-    if not os.path.exists(os.path.join(nltk_data_path, "corpora/stopwords")):
-        nltk.download('stopwords', download_dir=nltk_data_path)
 
-nltk.data.path.append(nltk_data_path)
+from nltk.corpus import stopwords
+from nltk.tokenize import sent_tokenize
+
+stop_words = set(stopwords.words('english'))
+
     
 model = load_model('model_improved.keras')
 vectorizer = joblib.load('vectorizer.joblib')
@@ -34,7 +38,6 @@ with open('product_mapping.json', 'r') as file1:
 reverse_mapping = {v: k for k, v in product_mapping.items()}
 
 lemmatizer = WordNetLemmatizer()
-stop_words = set(stopwords.words('english'))
 
 def clean_text(text):
     if text is None: