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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 | |
st.set_page_config(page_title="HugChat - An LLM-powered Streamlit app") | |
# image = "0_AI4xFlr8mYASsylX.png" # Replace with the actual path to your image | |
# st.image(image, caption="Robotic Llama", use_column_width=1) | |
with st.sidebar: | |
st.title('π€π¬ 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 | |
π‘ Note: No API key required! | |
''') | |
add_vertical_space(5) | |
st.write('Thanks Meta for LLAMA and hugging face- hugchat') | |
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!'] | |
input_container = st.container() | |
colored_header(label='', description='', color_name='blue-70') | |
response_container = st.container() | |
# User input | |
## Function for taking user provided prompt as input | |
def get_text(): | |
input_text = st.text_input("You: ", "", key="input") | |
return input_text | |
## Applying the user input box | |
with input_container: | |
user_input = get_text() | |
# Response output | |
## Function for taking user prompt as input followed by producing AI generated responses | |
def generate_response(prompt): | |
chatbot = hugchat.ChatBot() | |
response = chatbot.chat(prompt) | |
return response | |
## Conditional display of AI generated responses as a function of user provided prompts | |
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=str(i) + '_user') | |
message(st.session_state['generated'][i], key=str(i)) | |