fix add nltk download

app.py

@@ -7,6 +7,10 @@ import tensorflow as tf
 from tensorflow.keras.models import Sequential, Model
 from tensorflow.keras.layers import Embedding, TextVectorization, GlobalAveragePooling1D, Input, LSTM, GRU, Dropout, Dense
 
+import nltk
+import func
+nltk.download('wordnet')
+nltk.download('punkt')
 from func import TextProcess, Label, TextProcess2
 
 lda_model_inf =  gensim.models.LdaModel.load('lda.model')

func.py

@@ -1,5 +1,6 @@
 import re
 import string
+import nltk
 from nltk.tokenize import word_tokenize
 import pandas as pd
 import numpy as np
@@ -9,6 +10,9 @@ import string
 from nltk.tokenize import word_tokenize
 from nltk.stem.porter import *
 
+nltk.download('wordnet')
+nltk.download('punkt')
+
 # A Function to use in the dataframe
 kamus = pd.read_csv('kamus.txt', sep="	", header=None,names=['slang', 'fix'])
 slang_list = kamus['slang'].tolist()