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}")