Mount Multiple Slack Bots
Serve a research bot and an analysis bot from one AgentOS.
Serve a research bot and an analysis bot from one AgentOS. Each Slack app has its own credentials, URL prefix, identity, and entity-scoped thread sessions.
"""
Mount Multiple Slack Bots
=========================
Serve a research bot and an analysis bot from one AgentOS. Each Slack app has
its own credentials, URL prefix, identity, and entity-scoped thread sessions.
Prerequisites: RESEARCH_SLACK_TOKEN, RESEARCH_SLACK_SIGNING_SECRET, ANALYST_SLACK_TOKEN, ANALYST_SLACK_SIGNING_SECRET, OPENAI_API_KEY
Run: .venvs/demo/bin/python cookbook/05_agent_os/17_slack/multiple_bots.py
Try in Slack: Ask the research bot for sources, then ask the analyst bot for a brief
Slack scopes: app_mentions:read, assistant:write, chat:write, im:history (per app)
"""
from os import getenv
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
def required_env(name: str) -> str:
value = getenv(name)
if not value:
raise ValueError(f"{name} is required for this example")
return value
# ---------------------------------------------------------------------------
# Create Multi-bot Slack AgentOS
# ---------------------------------------------------------------------------
research_token = required_env("RESEARCH_SLACK_TOKEN")
research_secret = required_env("RESEARCH_SLACK_SIGNING_SECRET")
analyst_token = required_env("ANALYST_SLACK_TOKEN")
analyst_secret = required_env("ANALYST_SLACK_SIGNING_SECRET")
db = SqliteDb(
id="slack-multiple-bots-db",
db_file="tmp/slack_multiple_bots.db",
)
researcher = Agent(
id="slack-research-bot",
name="Slack Research Bot",
model=OpenAIResponses(id="gpt-5.5"),
db=db,
tools=[WebSearchTools()],
instructions=[
"Research current questions and cite source links.",
"Introduce yourself as the Research Bot.",
],
add_history_to_context=True,
num_history_runs=3,
markdown=True,
)
analyst = Agent(
id="slack-analysis-bot",
name="Slack Analysis Bot",
model=OpenAIResponses(id="gpt-5.5"),
db=db,
instructions=[
"Turn information from the user into concise findings and next steps.",
"Introduce yourself as the Analysis Bot.",
],
add_history_to_context=True,
num_history_runs=3,
markdown=True,
)
agent_os = AgentOS(
id="slack-multiple-bots-os",
description="AgentOS serving two separately credentialed Slack apps.",
agents=[researcher, analyst],
interfaces=[
Slack(
agent=researcher,
prefix="/research",
token=research_token,
signing_secret=research_secret,
streaming=True,
),
Slack(
agent=analyst,
prefix="/analyst",
token=analyst_token,
signing_secret=analyst_secret,
streaming=True,
),
],
)
app = agent_os.get_app()
# ---------------------------------------------------------------------------
# Run Multi-bot 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/activatePrepare 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 openaiExport your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
export RESEARCH_SLACK_TOKEN="your_research_slack_token_here"
export RESEARCH_SLACK_SIGNING_SECRET="your_research_slack_signing_secret_here"
export ANALYST_SLACK_TOKEN="your_analyst_slack_token_here"
export ANALYST_SLACK_SIGNING_SECRET="your_analyst_slack_signing_secret_here"Run the example
Save the code above as multiple_bots.py, then run:
python multiple_bots.pyConnect Slack to the running server
Keep Python and ngrok running. In each app's Slack settings, prepend your public HTTPS origin to these paths:
| App | Event subscriptions | Interactivity |
|---|---|---|
| Research app | /research/events | /research/interactions |
| Analyst app | /analyst/events | /analyst/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/multiple_bots.py