pip install ag2[commsagent-discord]

pip install ag2[commsagent-slack]

pip install ag2[commsagent-telegram]

# Agents are available in the autogen.agents namespace
from autogen import ConversableAgent
from autogen.agents.experimental import DiscordAgent

# LLM configuration for our agent to select the tools and craft the message
# Put your key in the OPENAI_API_KEY environment variable
llm_config = {"api_type": "openai", "model": "gpt-4o-mini"}

# Tokens and Ids (CHANGE THESE)
my_discord_bot_token = "ABC..."
my_discord_guild_name = "My Discord Server Name"
my_discord_channel_name = "general"

# Create DiscordAgent with defaults
discord_agent = DiscordAgent(
    name="discord_agent",
    llm_config=llm_config,
    bot_token=my_discord_bot_token,
    guild_name=my_discord_guild_name,
    channel_name=my_discord_channel_name,
)

# Tool execution is carried out by another agent
# Will output TERMINATE to end the conversation when complete
tool_executor = ConversableAgent(
    name="tool_executor",
    system_message=(
        "You execute send and retrieve functions for Discord platforms.\n"
        "Respond with 'TERMINATE' when finished."
        ),
    llm_config=llm_config,
    human_input_mode="NEVER",
    )

# Register the tools from the DiscordAgent with the tool_executor for execution
for tool in discord_agent.tools:
    tool.register_for_execution(tool_executor)

# Let's get the latest message from Discord and send one back as a poem.
tool_executor.initiate_chat(
    recipient=discord_agent,
    message="Get the latest message from Discord and send back a message with a poem about it."
)

# Tools are available in the autogen.tools namespace
from autogen import ConversableAgent, register_function
from autogen.tools.experimental import SlackRetrieveTool, SlackSendTool

# LLM configuration for our agent to select the tools and craft the message
# Put your key in the OPENAI_API_KEY environment variable
llm_config = {"api_type": "openai", "model": "gpt-4o-mini"}

# 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",
)

# The main star of the show, our ConversableAgent-based agent
# We will attach the tools to this agent
slack_agent = ConversableAgent(
    name="slack_agent",
    llm_config=llm_config,
)

# Create tools and register them with the agents

_bot_token = "xoxo..."  # CHANGE THIS, OAuth token
_channel_id = "C1234567"  # CHANGE THIS, ID of the Slack channel

# Create our Send tool
slack_send_tool = SlackSendTool(bot_token=_bot_token, channel_id=_channel_id)

# Register it for recommendation by our Slack agent
slack_send_tool.register_for_llm(slack_agent)

# Register it for execution by our executor agent
slack_send_tool.register_for_execution(executor_agent)

# And the same for our our Retrieve tool
slack_retrieve_tool = SlackRetrieveTool(bot_token=_bot_token, channel_id=_channel_id)
slack_retrieve_tool.register_for_llm(slack_agent)
slack_retrieve_tool.register_for_execution(executor_agent)

# Here we create a dummy weather function that will be used by our agent
def get_weather():
    return "The weather today is 25 degrees Celsius and sunny, with a late storm."

# Register it with the slack_agent for LLM tool recommendations
# and the executor_agent to execute it
register_function(
    get_weather,
    caller=slack_agent,
    executor=executor_agent,
    description="Get the current weather forecast",
)

# Start the conversation
# The slack_agent suggests the weather and send tools, crafting the Slack message
# while the executor_agent executes the weather tool and the Slack send 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,
)