SlackAgent

If you need an agent to send messages to your Slack channel and/or retrieve Slack messages to action, SlackAgent can help you.

If you haven’t had a chance to read about how AG2’s Communication Platform agents and tools work, read the overview first.

Installation

Install AG2 with the LLM model provider and Slack platform extra.

pip install ag2[openai,commsagent-slack]

Capabilities

SlackAgent can:

• Construct and send a message to the configured channel. If a message is longer than the platforms permitted message length, they will split the message into multiple messages.
• Retrieve the latest X messages from a channel.
• Retrieve messages since a given date.
• Retrieve messages since a given message ID.
• Retrieve a message given its ID.

It will also automatically append Slack’s messaging requirements to the system message:

• 40,000 character limit
• Markdown
• bold/italic/code
• emojis
• notification formats

This is on by default, but you can turn these off by setting has_writing_instructions to False when creating the agent.

In-built Tools

The SlackAgent has two in-built tools that it will call upon as it needs:

• SlackSendTool
• SlackRetrieveTool

Find out more about these tools and how you can add them to your own AG2 agents in the Slack Tools documentation.

Platform configuration

Each agent is configured for a specific channel. This configuration is applied when you create the agent.

The SlackAgent require authentication (OAuth token) and channel details in order to send/retrieve messages.

Here are the steps to get a token:

• Create an app, from scratch, at https://api.slack.com/apps
• In your app settings, go to Features > OAuth & Permissions:
  • Under “Bot Token Scopes”, add these permissions:
    • chat:write (to send messages)
    • channels:history
    • channels:read (to access channel info)
    • groups:read (for private channels)
    • im:read (for direct messages)
    • users:read (to get user info)
    • files:read (to access file attachments)
    • groups:history
    • im:history
    • mpim:history
• With your app setup, now install it in your workspace, using the “Install App” menu, to create an OAuth Token.

To get the ID for your channel:

• Open Slack in a browser
• Navigate to your channel
• Get the channel ID from the URL (e.g., …/C12345678)

Finally you need to add the bot to your channel:

• In Slack, go to your channel
• Type /invite @YourBotName, e.g. /invite @ag2commsagent

Now you should be good to go with your OAuth token, channel ID, and a bot on your channel ready to send and retrieve messages!

Code example

Here’s a simple example using the SlackAgent that gets the current weather and sends a message to a Slack channel to give them a weather forecast.

# Agents are available in the autogen.agents namespace
from autogen import ConversableAgent, register_function, LLMConfig
from autogen.agents.experimental import SlackAgent

# For running the code in Jupyter, use nest_asyncio to allow nested event loops
#import nest_asyncio
#nest_asyncio.apply()

llm_config = LLMConfig(model="gpt-4o-mini", api_type="openai")

# Our Slack credentials
_bot_token = "xoxo..."  # OAuth token
_channel_id = "C1234567"  # ID of the Slack channel

# Our tool executor agent, which will run the tools once recommended by the slack_agent, no LLM required
executor_agent = ConversableAgent(
    name="executor_agent",
    human_input_mode="NEVER",
)

with llm_config:
    slack_agent = SlackAgent(
        name="slack_agent",
        bot_token=_bot_token,
        channel_id=_channel_id,
    )

# We get the registered tools and register them for execution with the tool executor
for tool in slack_agent.tools:
    tool.register_for_execution(executor_agent)

# Weather function
def get_weather():
    return "The weather today is 25 degrees Celsius and sunny, with a late storm."

# Register for LLM recommendation with our slack_agent and for execution with our executor_agent
register_function(
    get_weather,
    caller=slack_agent,
    executor=executor_agent,
    description="Get the current weather forecast",
)

# Ask the SlackAgent to get the weather (using the get_weather tool) and then send a message out (using its SlackSendTool tool)
executor_agent.initiate_chat(
    recipient=slack_agent,
    message="Get the latest weather forecast and send it to our Slack channel. Use some emojis to make it fun!",
    max_turns=3,
)

Here’s the message it sent:

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