app.py

import gradio as gr
import os
from langchain_openai import ChatOpenAI

# Set up the SambaNova Chat API client
api_key = os.environ.get("FEATHERLESS_API_KEY")
llm = ChatOpenAI(
    base_url="https://api.featherless.ai/v1/",
    api_key=api_key,
    streaming=True,
    model="mistralai/Magistral-Small-2506",
)

def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    messages = [{"role": "system", "content": system_message}]

    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})

    messages.append({"role": "user", "content": message})

    # Update the ChatOpenAI instance with the current parameters
    llm.max_tokens = max_tokens
    llm.temperature = temperature
    llm.top_p = top_p

    response = ""
    for chunk in llm.stream(messages):
        token = chunk.content
        response += token
        yield response

demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=2.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.95,
            step=0.05,
            label="Top-p (nucleus sampling)",
        ),
    ],
)

if __name__ == "__main__":
    demo.launch()