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import streamlit as st |
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from streamlit_chat import message |
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from streamlit_extras.colored_header import colored_header |
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from streamlit_extras.add_vertical_space import add_vertical_space |
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from hugchat import hugchat |
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st.set_page_config(page_title="HugChat - An LLM-powered Streamlit app") |
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with st.sidebar: |
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st.title('🤗💬 HugChat App') |
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st.markdown(''' |
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## About |
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This app is an LLM-powered chatbot built using: |
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- [Streamlit](https://streamlit.io/) |
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- [HugChat](https://github.com/Soulter/hugging-chat-api) |
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- [OpenAssistant/oasst-sft-6-llama-30b-xor](https://huggingface.co/OpenAssistant/oasst-sft-6-llama-30b-xor) LLM model |
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💡 Note: No API key required! |
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''') |
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add_vertical_space(5) |
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st.write('Made with ❤️ by [Data Professor](https://youtube.com/dataprofessor)') |
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if 'generated' not in st.session_state: |
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st.session_state['generated'] = ["I'm HugChat, How may I help you?"] |
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if 'past' not in st.session_state: |
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st.session_state['past'] = ['Hi!'] |
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input_container = st.container() |
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colored_header(label='', description='', color_name='blue-30') |
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response_container = st.container() |
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def get_text(): |
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input_text = st.text_input("You: ", "", key="input") |
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return input_text |
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with input_container: |
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user_input = get_text() |
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def generate_response(prompt): |
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chatbot = hugchat.ChatBot() |
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response = chatbot.chat(prompt) |
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return response |
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with response_container: |
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if user_input: |
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response = generate_response(user_input) |
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st.session_state.past.append(user_input) |
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st.session_state.generated.append(response) |
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if st.session_state['generated']: |
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for i in range(len(st.session_state['generated'])): |
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message(st.session_state['past'][i], is_user=True, key=str(i) + '_user') |
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message(st.session_state["generated"][i], key=str(i)) |