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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
import os
# Streamlit page config
st.set_page_config(page_title="HugChat - An LLM-powered Streamlit app")
# Sidebar contents
with st.sidebar:
st.title('🤗💬 HugChat App')
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
💡 Note: No API key required!
''')
add_vertical_space(5)
st.write('Made with ❤️ by [Data Professor](https://youtube.com/dataprofessor)')
# Initialize chatbot and session state
if 'chatbot' not in st.session_state:
# Create ChatBot instance
st.session_state.chatbot = hugchat.ChatBot()
if 'generated' not in st.session_state:
st.session_state['generated'] = ["I'm HugChat, How may I help you?"]
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
def get_text():
return st.text_input("You: ", "", key="input")
with input_container:
user_input = get_text()
# AI Response Generation
def generate_response(prompt):
try:
response = st.session_state.chatbot.chat(prompt)
return response
except Exception as e:
return f"An error occurred: {e}"
# Display conversation
with response_container:
if user_input:
response = generate_response(user_input)
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=f"{i}_user")
message(st.session_state["generated"][i], key=f"{i}") |