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import streamlit as st
from openai import OpenAI
st.title("Chat Demo")
'''
This application presents a traditional chat interface to a range of open source or open weights models running on the National Research Platform (<https://nrp.ai>). Unlike the other two demos, this pattern does not use specified data resources.
'''
with st.sidebar:
model = st.radio("Select an LLM:", ['olmo', 'gemma2', 'phi3', 'llama3', 'embed-mistral', 'mixtral', 'gorilla', 'groq-tools', 'llava'])
st.session_state["model"] = model
## dockerized streamlit app wants to read from os.getenv(), otherwise use st.secrets
import os
api_key = os.getenv("LITELLM_KEY")
if api_key is None:
api_key = st.secrets["LITELLM_KEY"]
if "messages" not in st.session_state:
st.session_state.messages = []
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
client = OpenAI(
api_key = api_key,
base_url = "https://llm.nrp-nautilus.io"
)
# Button to clear session state
if st.button('Clear History'):
st.session_state.clear()
if prompt := st.chat_input("What is up?"):
st.session_state.messages.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.markdown(prompt)
with st.chat_message("assistant"):
stream = client.chat.completions.create(
model=st.session_state["model"],
messages=[
{"role": m["role"], "content": m["content"]}
for m in st.session_state.messages
],
stream=True,
)
response = st.write_stream(stream)
st.session_state.messages.append({"role": "assistant", "content": response})
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