temp.py

import streamlit as st
from transformers import pipeline


# Load the conversational model from Hugging Face
# chatbot = pipeline('text-generation', model='shaneperry0101/Health-Llama-3.2-1B')
chatbot = pipeline('text-generation', model='microsoft/DialoGPT-medium')

# Initialize session state for storing the conversation
if 'conversation' not in st.session_state:
    st.session_state.conversation = []

# Streamlit app layout
st.title("Chatbot Application")
user_input = st.text_input("You:", key="input")

if st.button("Send"):
    if user_input:
        # Append user input to the conversation
        st.session_state.conversation.append({"role": "user", "content": user_input})

        # Generate response
        response = chatbot(user_input)
        bot_response = response[0]['generated_text']

        # Append bot response to the conversation
        st.session_state.conversation.append({"role": "bot", "content": bot_response})

# Display the conversation
for message in st.session_state.conversation:
    if message["role"] == "user":
        st.text_area("You:", value=message["content"], key=f"user_{message['content']}", height=50)
    else:
        st.text_area("Bot:", value=message["content"], key=f"bot_{message['content']}", height=50)