Conditional flow with tool calls

Hi there,

I'm interested in this package for a more complex chatbot that I've been developing. I need to preferably stream openAI responses with tools. Getting this to work with the shiny chat component has been a little tricky, but then I came across a reference to chatlas in the docstring for the shiny Chat class. Working through your docs and examples, I can get so far with it.

This approach allows for streaming responses with tool calls and shiny ui
widgets. Though the tool calls need to be self-contained. Whatever the tool
returns is fed into the model for a subsequent response, rather than being
available for additional conditional flow.

I would like to instead receive the function name and parameter values and
call get_current_temperature(), passing the json response back to model.
This would allow me to display a notification without relying on a side
effect.

from chatlas import ChatOpenAI, Turn
from shiny.express import ui
import dotenv
import requests

openai_key = dotenv.dotenv_values()["OPENAI_KEY"]
messages = [Turn(role="system", contents="You are a helpful but terse assistant.")]
messages.append(Turn(role="assistant", contents = "Hi! How can I help you today?"))


# func contains side effect which I would prefer to handle outside
def get_current_temperature(latitude: float, longitude: float):
    """
    Get the current weather given a latitude and longitude.

    Parameters
    ----------
    latitude
        The latitude of the location.
    longitude
        The longitude of the location.
    """
    lat_lng = f"latitude={latitude}&longitude={longitude}"
    url = f"https://api.open-meteo.com/v1/forecast?{lat_lng}&current=temperature_2m,wind_speed_10m&hourly=temperature_2m,relative_humidity_2m,wind_speed_10m"
    response = requests.get(url)
    json = response.json()
    weather_now = json['current']
    ui.notification_show(f"Queried weather API... {weather_now}")
    return weather_now


chat_model = ChatOpenAI(
    api_key=openai_key,
    turns=messages,
    )
chat_model.register_tool(get_current_temperature)
chat = ui.Chat(
    id="ui_chat",
    messages=["Hi! How can I help you today?"],
)
chat.ui()


@chat.on_user_submit
async def handle_user_input():
    response = chat_model.stream(chat.user_input())
    await chat.append_message_stream(response)

Start with the ChatOpenAI, register_tool, and stream usage shown in the issue, then reproduce the example with the Shiny Chat component. Trace how tool-call results are currently returned to the model and determine how callers could receive the function name and parameters instead. Done means conditional callers can handle the tool invocation, display a notification, and pass the returned JSON back for a subsequent response.