app.py

import streamlit as st
import os
from openai import OpenAI

api_key = os.getenv("NVIDIANIM_API_KEY")

client = OpenAI(
    base_url="https://integrate.api.nvidia.com/v1",
    api_key=api_key,
)

model_name = "meta/llama-3.1-405b-instruct"

if "messages" not in st.session_state:
    st.session_state.messages = []

def get_llama_response(question):
    st.session_state.messages.append({"role": "user", "content": question})
    response = client.chat.completions.create(
        model=model_name,
        messages=st.session_state.messages,
        temperature=0.2,
        top_p=0.7,
        max_tokens=1024,
        stream=True
    )

    response_text = ""
    for chunk in response:
        if chunk.choices[0].delta.content is not None:
            response_text += chunk.choices[0].delta.content

    st.session_state.messages.append({"role": "assistant", "content": response_text})
    return response_text

st.title("Ask Llama 3.1 405B on Nvidia NIM")

for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.markdown(message["content"])

if "user_input" not in st.session_state:
    st.session_state.user_input = ""

user_input_displayed = st.session_state.user_input  # Capture current displayed input

if st.button("Submit"):
    if user_input_displayed:  # Check if user previously entered input
        st.session_state.messages.append({"role": "user", "content": user_input_displayed})
        with st.chat_message("user"):
            st.markdown(user_input_displayed)  # Display previously entered input
        response = get_llama_response(user_input_displayed)
        with st.chat_message("assistant"):
            st.markdown(response)