Update app.py

app.py

@@ -2,13 +2,21 @@ import gradio as gr
 import tensorflow as tf
 import numpy as np
 from tensorflow.keras.preprocessing.sequence import pad_sequences
+from tensorflow.keras.preprocessing.text import Token
 import pickle 
 
 # Load the trained model
 model = pickle.load(open('model.pkl','rb'))
 
 def spam_detection(message):
+    vocab_size = 1000
+    embedding_dim = 16
+    max_length = 100
+    trunc_type='post'
+    padding_type='post'
+    oov_tok = "<OOV>"
     # Preprocess the input message
+    tokenizer = Tokenizer(num_words = vocab_size, oov_token=oov_tok)
     sequence = tokenizer.texts_to_sequences([message])
     padded_sequence = pad_sequences(sequence, maxlen=max_length, padding=padding_type, truncating=trunc_type)