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carolinefrascasnowflake
commited on
Commit
•
5823809
1
Parent(s):
85894bf
Add simplified version of app
Browse files- simple_app.py +95 -0
simple_app.py
ADDED
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import streamlit as st
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import replicate
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import os
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from transformers import AutoTokenizer
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# Set assistant icon to Snowflake logo
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icons = {"assistant": "./Snowflake_Logomark_blue.svg", "user": "⛷️"}
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# App title
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st.set_page_config(page_title="Snowflake Arctic")
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# Replicate Credentials
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with st.sidebar:
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st.title('Snowflake Arctic')
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if 'REPLICATE_API_TOKEN' in st.secrets:
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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 Replicate API token.', icon='⚠️')
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st.markdown("**Don't have an API token?** Head over to [Replicate](https://replicate.com) to sign up for one.")
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os.environ['REPLICATE_API_TOKEN'] = replicate_api
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st.subheader("Adjust model parameters")
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temperature = st.sidebar.slider('temperature', min_value=0.01, max_value=5.0, value=0.3, 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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# 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": "Hi. I'm Arctic, a new, efficient, intelligent, and truly open language model created by Snowflake AI Research. Ask me anything."}]
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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"], avatar=icons[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": "Hi. I'm Arctic, a new, efficient, intelligent, and truly open language model created by Snowflake AI Research. Ask me anything."}]
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st.sidebar.button('Clear chat history', on_click=clear_chat_history)
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st.sidebar.caption('Built by [Snowflake](https://snowflake.com/) to demonstrate [Snowflake Arctic](https://www.snowflake.com/blog/arctic-open-and-efficient-foundation-language-models-snowflake). App hosted on [Streamlit Community Cloud](https://streamlit.io/cloud). Model hosted by [Replicate](https://replicate.com/snowflake/snowflake-arctic-instruct).')
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st.sidebar.caption('Build your own app powered by Arctic and [enter to win](https://arctic-streamlit-hackathon.devpost.com/) $10k in prizes.')
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@st.cache_resource(show_spinner=False)
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def get_tokenizer():
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"""Get a tokenizer to make sure we're not sending too much text
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text to the Model. Eventually we will replace this with ArcticTokenizer
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"""
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return AutoTokenizer.from_pretrained("huggyllama/llama-7b")
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def get_num_tokens(prompt):
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"""Get the number of tokens in a given prompt"""
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tokenizer = get_tokenizer()
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tokens = tokenizer.tokenize(prompt)
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return len(tokens)
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# Function for generating Snowflake Arctic response
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def generate_arctic_response():
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prompt = []
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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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prompt.append("<|im_start|>user\n" + dict_message["content"] + "<|im_end|>")
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else:
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prompt.append("<|im_start|>assistant\n" + dict_message["content"] + "<|im_end|>")
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prompt.append("<|im_start|>assistant")
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prompt.append("")
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prompt_str = "\n".join(prompt)
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if get_num_tokens(prompt_str) >= 3072:
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st.error("Conversation length too long. Please keep it under 3072 tokens.")
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st.button('Clear chat history', on_click=clear_chat_history, key="clear_chat_history")
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st.stop()
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for event in replicate.stream("snowflake/snowflake-arctic-instruct",
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input={"prompt": prompt_str,
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"prompt_template": r"{prompt}",
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"temperature": temperature,
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"top_p": top_p,
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}):
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yield str(event)
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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", avatar="⛷️"):
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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", avatar="./Snowflake_Logomark_blue.svg"):
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response = generate_arctic_response()
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full_response = st.write_stream(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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