app_v2.py

import streamlit as st
from streamlit_chat import message
from streamlit_extras.colored_header import colored_header
from streamlit_extras.add_vertical_space import add_vertical_space
from hugchat import hugchat
from hugchat.login import Login

st.set_page_config(page_title="HugChat - An LLM-powered Streamlit app")

# Sidebar contents
with st.sidebar:
    st.title('🤗💬 HugChat App')
    
    st.header('Hugging Face Login')
    hf_email = st.text_input('Enter E-mail:', type='password')
    hf_pass = st.text_input('Enter password:', type='password')
    
    st.markdown('''
    ## About
    This app is an LLM-powered chatbot built using:
    - [Streamlit](https://streamlit.io/)
    - [HugChat](https://github.com/Soulter/hugging-chat-api)
    - [OpenAssistant/oasst-sft-6-llama-30b-xor](https://huggingface.co/OpenAssistant/oasst-sft-6-llama-30b-xor) LLM model

    ''')
    add_vertical_space(5)
    st.write('Made with ❤️ by [Data Professor](https://youtube.com/dataprofessor)')

# Generate empty lists for generated and past.
## generated stores AI generated responses
if 'generated' not in st.session_state:
    st.session_state['generated'] = ["I'm HugChat, How may I help you?"]
## past stores User's questions
if 'past' not in st.session_state:
    st.session_state['past'] = ['Hi!']

# Layout of input/response containers
input_container = st.container()
colored_header(label='', description='', color_name='blue-30')
response_container = st.container()

# User input
## Function for taking user provided prompt as input
def get_text():
    input_text = st.text_input("You: ", "", key="input")
    return input_text
## Applying the user input box
with input_container:
    user_input = get_text()

# Response output
## Function for taking user prompt as input followed by producing AI generated responses
def generate_response(prompt, email, passwd):
    # Hugging Face Login
    sign = Login(email, passwd)
    cookies = sign.login()
    sign.saveCookies()
    # Create ChatBot                        
    chatbot = hugchat.ChatBot(cookies=cookies.get_dict())
    response = chatbot.chat(prompt)
    return response

## Conditional display of AI generated responses as a function of user provided prompts
with response_container:
    if user_input and hf_email and hf_pass:
        response = generate_response(user_input, hf_email, hf_pass)
        st.session_state.past.append(user_input)
        st.session_state.generated.append(response)
        
    if st.session_state['generated']:
        for i in range(len(st.session_state['generated'])):
            message(st.session_state['past'][i], is_user=True, key=str(i) + '_user')
            message(st.session_state["generated"][i], key=str(i))