hugchat / app.py
LovnishVerma's picture
Create app.py
0d1f5ef
import streamlit as st
from hugchat import hugchat
from hugchat.login import Login
# App title
st.set_page_config(page_title="πŸ€—πŸ’¬ HugChat")
# Hugging Face Credentials
with st.sidebar:
st.title('πŸ€—πŸ’¬ HugChat')
if ('EMAIL' in st.secrets) and ('PASS' in st.secrets):
st.success('HuggingFace Login credentials already provided!', icon='βœ…')
hf_email = st.secrets['EMAIL']
hf_pass = st.secrets['PASS']
else:
hf_email = st.text_input('Enter E-mail:', type='password')
hf_pass = st.text_input('Enter password:', type='password')
if not (hf_email and hf_pass):
st.warning('Please enter your credentials!', icon='⚠️')
else:
st.success('Proceed to entering your prompt message!', icon='πŸ‘‰')
st.markdown('πŸ“– Learn how to build this app in this [blog](https://blog.streamlit.io/how-to-build-an-llm-powered-chatbot-with-streamlit/)!')
# Store LLM generated responses
if "messages" not in st.session_state.keys():
st.session_state.messages = [{"role": "assistant", "content": "How may I help you?"}]
# Display chat messages
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.write(message["content"])
# Function for generating LLM response
def generate_response(prompt_input, email, passwd):
# Hugging Face Login
sign = Login(email, passwd)
cookies = sign.login()
# Create ChatBot
chatbot = hugchat.ChatBot(cookies=cookies.get_dict())
return chatbot.chat(prompt_input)
# User-provided prompt
if prompt := st.chat_input(disabled=not (hf_email and hf_pass)):
st.session_state.messages.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.write(prompt)
# Generate a new response if last message is not from assistant
if st.session_state.messages[-1]["role"] != "assistant":
with st.chat_message("assistant"):
with st.spinner("Thinking..."):
response = generate_response(prompt, hf_email, hf_pass)
st.write(response)
message = {"role": "assistant", "content": response}
st.session_state.messages.append(message)