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Duplicate from Sanyam0605/Chatbot
Browse filesCo-authored-by: Sanyam Jain <Sanyam0605@users.noreply.huggingface.co>
- .gitattributes +34 -0
- README.md +13 -0
- app.py +67 -0
- main.py +67 -0
- requirements.txt +4 -0
.gitattributes
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README.md
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---
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title: Chatbot
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emoji: π
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colorFrom: pink
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colorTo: red
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sdk: streamlit
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sdk_version: 1.19.0
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app_file: app.py
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pinned: false
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duplicated_from: Sanyam0605/Chatbot
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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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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# image = "0_AI4xFlr8mYASsylX.png" # Replace with the actual path to your image
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# st.image(image, caption="Robotic Llama", use_column_width=1)
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with st.sidebar:
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st.title('π€π¬ 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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π‘ Note: No API key required!
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''')
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add_vertical_space(5)
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st.write('Thanks Meta for LLAMA and hugging face- hugchat')
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if 'generated' not in st.session_state:
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st.session_state['generated'] = ["I'm HugChat [created by Sanyam] , 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-70')
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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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main.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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# image = "0_AI4xFlr8mYASsylX.png" # Replace with the actual path to your image
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# st.image(image, caption="Robotic Llama", use_column_width=1)
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with st.sidebar:
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st.title('π€π¬ 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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π‘ Note: No API key required!
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''')
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add_vertical_space(5)
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st.write('Thanks Meta for LLAMA and hugging face- hugchat')
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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-70')
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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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requirements.txt
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streamlit
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hugchat
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streamlit-chat
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streamlit-extras
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