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Create app.py
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app.py
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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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# Sidebar contents
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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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# Generate empty lists for generated and past.
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## generated stores AI generated responses
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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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## past stores User's questions
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if 'past' not in st.session_state:
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st.session_state['past'] = ['Hi!']
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# Layout of input/response containers
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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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# User input
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## Function for taking user provided prompt as input
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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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## Applying the user input box
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with input_container:
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user_input = get_text()
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# Response output
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## Function for taking user prompt as input followed by producing AI generated responses
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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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## Conditional display of AI generated responses as a function of user provided prompts
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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))
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