Spaces:
Running
Running
File size: 1,286 Bytes
d2a3567 73afc0c d2a3567 73afc0c d2a3567 73afc0c d2a3567 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 |
import streamlit as st
from openai import OpenAI
st.title("Chat Demo")
with st.sidebar:
model = st.radio("Select an LLM:", ['llava', 'gemma2', 'phi3', 'llama3', 'embed-mistral', 'mixtral', 'gorilla', 'groq-tools'])
st.session_state["model"] = model
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 = st.secrets["LITELLM_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})
|