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import streamlit as st
import replicate
import os
from transformers import AutoTokenizer
# Set assistant icon to Snowflake logo
icons = {"assistant": "./Snowflake_Logomark_blue.svg", "user": "⛷️"}
# App title
st.set_page_config(page_title="Snowflake Arctic")
# Replicate Credentials
with st.sidebar:
st.title('Snowflake Arctic')
if 'REPLICATE_API_TOKEN' in st.secrets:
replicate_api = st.secrets['REPLICATE_API_TOKEN']
else:
replicate_api = st.text_input('Enter Replicate API token:', type='password')
if not (replicate_api.startswith('r8_') and len(replicate_api)==40):
st.warning('Please enter your Replicate API token.', icon='⚠️')
st.markdown("**Don't have an API token?** Head over to [Replicate](https://replicate.com) to sign up for one.")
os.environ['REPLICATE_API_TOKEN'] = replicate_api
st.subheader("Adjust model parameters")
temperature = st.sidebar.slider('temperature', min_value=0.01, max_value=5.0, value=0.3, step=0.01)
top_p = st.sidebar.slider('top_p', min_value=0.01, max_value=1.0, value=0.9, step=0.01)
# Store LLM-generated responses
if "messages" not in st.session_state.keys():
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."}]
# Display or clear chat messages
for message in st.session_state.messages:
with st.chat_message(message["role"], avatar=icons[message["role"]]):
st.write(message["content"])
def clear_chat_history():
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."}]
st.sidebar.button('Clear chat history', on_click=clear_chat_history)
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).')
st.sidebar.caption('Build your own app powered by Arctic and [enter to win](https://arctic-streamlit-hackathon.devpost.com/) $10k in prizes.')
@st.cache_resource(show_spinner=False)
def get_tokenizer():
"""Get a tokenizer to make sure we're not sending too much text
text to the Model. Eventually we will replace this with ArcticTokenizer
"""
return AutoTokenizer.from_pretrained("huggyllama/llama-7b")
def get_num_tokens(prompt):
"""Get the number of tokens in a given prompt"""
tokenizer = get_tokenizer()
tokens = tokenizer.tokenize(prompt)
return len(tokens)
# Function for generating Snowflake Arctic response
def generate_arctic_response():
prompt = []
for dict_message in st.session_state.messages:
if dict_message["role"] == "user":
prompt.append("<|im_start|>user\n" + dict_message["content"] + "<|im_end|>")
else:
prompt.append("<|im_start|>assistant\n" + dict_message["content"] + "<|im_end|>")
prompt.append("<|im_start|>assistant")
prompt.append("")
prompt_str = "\n".join(prompt)
if get_num_tokens(prompt_str) >= 3072:
st.error("Conversation length too long. Please keep it under 3072 tokens.")
st.button('Clear chat history', on_click=clear_chat_history, key="clear_chat_history")
st.stop()
for event in replicate.stream("snowflake/snowflake-arctic-instruct",
input={"prompt": prompt_str,
"prompt_template": r"{prompt}",
"temperature": temperature,
"top_p": top_p,
}):
yield str(event)
# User-provided prompt
if prompt := st.chat_input(disabled=not replicate_api):
st.session_state.messages.append({"role": "user", "content": prompt})
with st.chat_message("user", avatar="⛷️"):
st.write(prompt)
# Generate a new response if last message is not from assistant
if st.session_state.messages[-1]["role"] != "assistant":
with st.chat_message("assistant", avatar="./Snowflake_Logomark_blue.svg"):
response = generate_arctic_response()
full_response = st.write_stream(response)
message = {"role": "assistant", "content": full_response}
st.session_state.messages.append(message) |