import streamlit as st
from transformers import pipeline


# Load the conversational model from Hugging Face
chatbot = pipeline('conversational', 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)