app.py

import streamlit as st
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

# Load model and tokenizer
model_name = "facebook/blenderbot-90M"
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

def chatbot_response(input_text):
    inputs = tokenizer(input_text, return_tensors="pt")
    outputs = model.generate(**inputs, max_length=100)
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return response

# Streamlit UI
st.title("Emotional Support Chatbot")
st.write("Chat with the emotional support bot below:")

user_input = st.text_input("Your Message")
if user_input:
    response = chatbot_response(user_input)
    st.text_area("Chatbot Response", response, height=150)