Configure Slack Streaming UX

Show a streaming response with rotating loading messages, dynamic suggested prompts, and plan-mode task cards for tool calls.

streaming_ux.py
"""
Configure Slack Streaming UX
=============================

Show a streaming response with rotating loading messages, dynamic suggested
prompts, and plan-mode task cards for tool calls.

Prerequisites: SLACK_TOKEN, SLACK_SIGNING_SECRET, OPENAI_API_KEY
Run: .venvs/demo/bin/python cookbook/05_agent_os/17_slack/streaming_ux.py
Try in Slack: Ask "What changed in Python packaging this year? Cite sources."
Slack scopes: app_mentions:read, assistant:write, chat:write, im:history
"""

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
from agno.os import AgentOS
from agno.os.interfaces.slack import Slack
from agno.tools.websearch import WebSearchTools

# ---------------------------------------------------------------------------
# Create Streaming Slack AgentOS
# ---------------------------------------------------------------------------

db = SqliteDb(
    id="slack-streaming-db",
    db_file="tmp/slack_streaming.db",
)

researcher = Agent(
    id="slack-streaming-researcher",
    name="Slack Streaming Researcher",
    model=OpenAIResponses(id="gpt-5.5"),
    db=db,
    tools=[WebSearchTools()],
    instructions=[
        "Research current questions with web search.",
        "Use more than one source when the answer benefits from comparison.",
        "Return a concise synthesis with source links.",
    ],
    add_history_to_context=True,
    num_history_runs=3,
    markdown=True,
)

agent_os = AgentOS(
    id="slack-streaming-os",
    description="AgentOS demonstrating Slack streaming presentation controls.",
    agents=[researcher],
    interfaces=[
        Slack(
            agent=researcher,
            streaming=True,
            task_display_mode="plan",
            loading_text="Researching...",
            loading_messages=[
                "Searching current sources...",
                "Comparing the evidence...",
                "Preparing a concise answer...",
            ],
            suggested_prompts=[
                {
                    "title": "Technology brief",
                    "message": "Summarize today's most important AI infrastructure news.",
                },
                {
                    "title": "Compare approaches",
                    "message": "Compare two current approaches to Python dependency management.",
                },
            ],
        )
    ],
)
app = agent_os.get_app()

# ---------------------------------------------------------------------------
# Run Streaming Slack AgentOS
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    agent_os.serve(app=app)

Run the Example

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate

Prepare the Slack app

Follow Slack setup to create and install the app, obtain its bot token and signing secret, and configure its current agent experience. Add the bot scopes listed in this example's source docstring and reinstall after changing scopes. Subscribe to app_mention and message.im; configure interactivity for buttons and forms.

Install ngrok and run ngrok http 7777 in another terminal. Keep the tunnel running. After starting this example's server, use the callback paths listed on this page under your public HTTPS URL and complete Slack's verification challenge. Configure each app separately for a multi-app example.

Streaming requires the corresponding Slack app capability. The current Agno adapter initializes suggested prompts on the legacy assistant_thread_started event; the setup guide explains the new-app limitation. Keep only one standalone example on port 7777 at a time.

Install dependencies

uv pip install -U "agno[os,slack]" ddgs openai

Export environment variables

export OPENAI_API_KEY="your_openai_api_key_here"
export SLACK_SIGNING_SECRET="your_slack_signing_secret_here"
export SLACK_TOKEN="your_slack_token_here"

Run the example

Save the code above as streaming_ux.py, then run:

python streaming_ux.py

Connect Slack to the running server

Keep Python and ngrok running. In each app's Slack settings, prepend your public HTTPS origin to these paths:

AppEvent subscriptionsInteractivity
Slack app/slack/events/slack/interactions

Complete URL verification, then send a DM or invite the app to a channel and @mention it. Ordinary channel replies require an @mention with the default configuration.

Full source: cookbook/05_agent_os/17_slack/streaming_ux.py