app.py

import streamlit as st
from transformers import T5ForConditionalGeneration, T5Tokenizer


model = T5ForConditionalGeneration.from_pretrained("t5-small")
tokenizer = T5Tokenizer.from_pretrained("t5-small")


def generate_response(input_text):
    input_ids = tokenizer.encode("chatbot: " + input_text, return_tensors="pt", max_length=512)
    output_ids = model.generate(input_ids, max_length=100, num_beams=1, early_stopping=True)
    response = tokenizer.decode(output_ids[0], skip_special_tokens=True)
    return response

# Set up Streamlit app
st.title("Simple Chatbot with T5")
user_input = st.text_input("You:", "")

if st.button("Send"):
    if user_input.strip() != "":
        response = generate_response(user_input)
        st.text_area("Bot:", response)
    else:
        st.warning("Please enter a valid input.")