I have just added a new SSE component to the dash-extensions library. It was designed to provide an easy way to stream text to Dash applications, similar to how the UI of ChatGPT works. Here is a minimal example,
import os
from dash_extensions.enrich import DashProxy, html, dcc, Input, Output, State
from dash_extensions import SSE
from dash.exceptions import PreventUpdate
from dash_extensions.streaming import sse_options
from models import Query
app = DashProxy()
app.layout = html.Div(
[
dcc.Input(id="query", value="What is Plotly Dash?", type="text"),
html.Button("Submit", id="submit"),
dcc.Markdown(id="response", dangerously_allow_html=True, dedent=False),
# Configure the SSE component to concatenate the stream values, and animate the result.
SSE(id="sse", concat=True, animate_chunk=5, animate_delay=10),
]
)
# Expose server variable for gunicon to run the server.
server = app.server
# Configure the stream URL dependent on the environment.
stream_url = os.getenv("STREAM_URL", "http://127.0.0.1:8000/stream")
@app.callback([Output("sse", "url"), Output("sse", "options")], Input("submit", "n_clicks"), State("query", "value"))
def submit_query(n_clicks, query) -> tuple[str, dict[str, list[dict[str, str]]]]:
if n_clicks is None:
raise PreventUpdate
# Create message structure to be consumed by the Azure OpenAI API.
messages = [{"role": "user", "content": query}]
# Pass the messages to the stream endpoint to trigger streaming.
return stream_url, sse_options(payload=Query(messages=messages))
# Render (concatenated, animated) text from the SSE component.
app.clientside_callback("function(x){return x};", Output("response", "children"), Input("sse", "animation"))
if __name__ == "__main__":
app.run_server()
which yields,
You can see the complete code, including the streaming server (also written in Python), along with dockerization of the complete solution here. You’ll need an Azure OpenAI model deployment to run the example.
The component has not yet been added to the official documentation, but I expect to add it soon 
