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Upload 4 files
Browse files- .devcontainer/devcontainer.json +33 -0
- .streamlit/config.toml +6 -0
- requirements.txt +2 -0
- streamlit_app.py +84 -0
.devcontainer/devcontainer.json
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{
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"name": "Python 3",
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// Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile
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"image": "mcr.microsoft.com/devcontainers/python:1-3.11-bullseye",
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"customizations": {
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"codespaces": {
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"openFiles": [
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"README.md",
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"streamlit_app.py"
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]
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},
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"vscode": {
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"settings": {},
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"extensions": [
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"ms-python.python",
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"ms-python.vscode-pylance"
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]
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}
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},
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"updateContentCommand": "[ -f packages.txt ] && sudo apt update && sudo apt upgrade -y && sudo xargs apt install -y <packages.txt; [ -f requirements.txt ] && pip3 install --user -r requirements.txt; pip3 install --user streamlit; echo 'β
Packages installed and Requirements met'",
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"postAttachCommand": {
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"server": "streamlit run streamlit_app.py --server.enableCORS false --server.enableXsrfProtection false"
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},
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"portsAttributes": {
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"8501": {
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"label": "Application",
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"onAutoForward": "openPreview"
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}
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},
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"forwardPorts": [
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8501
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]
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}
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.streamlit/config.toml
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[theme]
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primaryColor="#F63366"
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backgroundColor="#FFFFFF"
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secondaryBackgroundColor="#F0F2F6"
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textColor="#262730"
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font="sans serif"
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requirements.txt
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streamlit
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replicate
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streamlit_app.py
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import streamlit as st
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import replicate
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import os
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# App title
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st.set_page_config(page_title="π¦π¬ Llama 2 Chatbot")
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# Replicate Credentials
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with st.sidebar:
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st.title('π¦π¬ Llama 2 Chatbot')
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if 'REPLICATE_API_TOKEN' in st.secrets:
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st.success('API key already provided!', icon='β
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replicate_api = st.secrets['REPLICATE_API_TOKEN']
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else:
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replicate_api = st.text_input('Enter Replicate API token:', type='password')
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if not (replicate_api.startswith('r8_') and len(replicate_api)==40):
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st.warning('Please enter your credentials!', icon='β οΈ')
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else:
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st.success('Proceed to entering your prompt message!', icon='π')
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# Refactored from https://github.com/a16z-infra/llama2-chatbot
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st.subheader('Models and parameters')
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selected_model = st.sidebar.selectbox('Choose a Llama2 model', ['Llama2-7B', 'Llama2-13B', 'Llama2-70B'], key='selected_model')
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if selected_model == 'Llama2-7B':
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llm = 'a16z-infra/llama7b-v2-chat:4f0a4744c7295c024a1de15e1a63c880d3da035fa1f49bfd344fe076074c8eea'
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elif selected_model == 'Llama2-13B':
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llm = 'a16z-infra/llama13b-v2-chat:df7690f1994d94e96ad9d568eac121aecf50684a0b0963b25a41cc40061269e5'
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else:
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llm = 'replicate/llama70b-v2-chat:e951f18578850b652510200860fc4ea62b3b16fac280f83ff32282f87bbd2e48'
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temperature = st.sidebar.slider('temperature', min_value=0.01, max_value=5.0, value=0.1, step=0.01)
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top_p = st.sidebar.slider('top_p', min_value=0.01, max_value=1.0, value=0.9, step=0.01)
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max_length = st.sidebar.slider('max_length', min_value=64, max_value=4096, value=512, step=8)
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language = st.sidebar.selectbox('Language', ['English', 'Spanish'], index=0)
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st.markdown('π Learn how to build this app in this [blog](https://blog.streamlit.io/how-to-build-a-llama-2-chatbot/)!')
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os.environ['REPLICATE_API_TOKEN'] = replicate_api
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# Store LLM generated responses
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if "messages" not in st.session_state.keys():
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st.session_state.messages = [{"role": "assistant", "content": "How may I assist you today?"}]
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# Display or clear chat messages
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for message in st.session_state.messages:
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with st.chat_message(message["role"]):
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st.write(message["content"])
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def clear_chat_history():
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st.session_state.messages = [{"role": "assistant", "content": "How may I assist you today?"}]
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st.sidebar.button('Clear Chat History', on_click=clear_chat_history)
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# Function for generating LLaMA2 response
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def generate_llama2_response(prompt_input, language='English'):
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string_dialogue = "You are a helpful assistant. You do not respond as 'User' or pretend to be 'User'. You only respond once as 'Assistant'."
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for dict_message in st.session_state.messages:
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if dict_message["role"] == "user":
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string_dialogue += "User: " + dict_message["content"] + "\n\n"
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else:
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string_dialogue += "Assistant: " + dict_message["content"] + "\n\n"
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output = replicate.run(llm,
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input={"prompt": f"{string_dialogue} {prompt_input} Assistant: ",
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"temperature":temperature, "top_p":top_p, "max_length":max_length, "repetition_penalty":1, "language": language})
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return output
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# User-provided prompt
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if prompt := st.chat_input(disabled=not replicate_api):
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st.session_state.messages.append({"role": "user", "content": prompt})
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with st.chat_message("user"):
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st.write(prompt)
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# Generate a new response if last message is not from assistant
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if st.session_state.messages[-1]["role"] != "assistant":
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with st.chat_message("assistant"):
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with st.spinner("Thinking..."):
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response = generate_llama2_response(prompt, language='Spanish')
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placeholder = st.empty()
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full_response = ''
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for item in response:
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full_response += item
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placeholder.markdown(full_response)
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placeholder.markdown(full_response)
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message = {"role": "assistant", "content": full_response}
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st.session_state.messages.append(message)
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