app.py

import streamlit as st

from transformers import GPT2Tokenizer, GPT2LMHeadModel

model_path='KhantKyaw/GPT2_chatbot2'
  
tokenizer = GPT2Tokenizer.from_pretrained(model_path)
tokenizer.pad_token = tokenizer.eos_token  
model = GPT2LMHeadModel.from_pretrained(model_path)
prompt = st.chat_input(placeholder="Say Something!",key=None, max_chars=None, disabled=False, on_submit=None, args=None, kwargs=None)

input_ids = tokenizer.encode(prompt, return_tensors='pt')
print(input_ids)
   
output_sequences = model.generate(
    input_ids=input_ids,
    max_length=100,
    temperature=1.0,
    top_k=50,
    top_p=0.95,
    repetition_penalty=1.2,
    do_sample=True,
    pad_token_id=tokenizer.eos_token_id,
    )

print(output_sequences)   
generated_text = tokenizer.decode(output_sequences[0], skip_special_tokens=True)

if prompt:
   with st.chat_message(name="AI",avatar=None):
    st.write(generated_text)