Update app.py

app.py

@@ -1,12 +1,13 @@
 import gradio as gr
 import tensorflow as tf
 from tensorflow.keras.models import load_model
+from tensorflow.keras.preprocessing.sequence import pad_sequences
 
 model = load_model("romangpt.h5")
 
 def generate_response(question):
     input_data = [question]
-    input_sequence = tf.convert_to_tensor(input_data, dtype=tf.string)
+    input_sequence = pad_sequences(tokenizer.texts_to_sequences(input_data), maxlen=max_sequence_length-1)
 
     response = model.predict(input_sequence)[0]