Email for AG2 Multi-Agent Conversations

import requests
from autogen import AssistantAgent, UserProxyAgent

MULTIMAIL_API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_your_api_key"}

def send_email(to: str, subject: str, body: str,
               mailbox_id: str) -> str:
    """Send an email via MultiMail.
    In gated_send mode, queues for human approval."""
    resp = requests.post(f"{MULTIMAIL_API}/send",
                         headers=HEADERS,
                         json={"mailbox_id": mailbox_id,
                               "to": to, "subject": subject,
                               "body": body})
    return str(resp.json())

def check_inbox(mailbox_id: str, limit: int = 10) -> str:
    """Check inbox for recent messages."""
    resp = requests.get(
        f"{MULTIMAIL_API}/mailboxes/{mailbox_id}/inbox",
        headers=HEADERS, params={"limit": limit})
    return str(resp.json())

def reply_email(message_id: str, body: str) -> str:
    """Reply to an email within its thread."""
    resp = requests.post(f"{MULTIMAIL_API}/reply",
                         headers=HEADERS,
                         json={"message_id": message_id,
                               "body": body})
    return str(resp.json())

from autogen import AssistantAgent, UserProxyAgent, config_list_from_json

llm_config = {
    "config_list": [{"model": "gpt-4o", "api_key": "your_openai_key"}],
    "temperature": 0.1
}

"cm"># Create the email assistant
email_assistant = AssistantAgent(
    name="EmailAssistant",
    system_message=(
        "You are an email assistant using MultiMail. "
        "Use the provided functions to send, read, and reply to "
        "emails. All outbound emails use gated_send mode — they "
        "are queued for human approval before delivery. "
        "Always confirm email content with the user before sending."
    ),
    llm_config=llm_config
)

"cm"># Create the user proxy (handles function execution)
user_proxy = UserProxyAgent(
    name="User",
    human_input_mode="NEVER",
    code_execution_config={"work_dir": "email_workspace"}
)

"cm"># Register email functions
for func in [send_email, check_inbox, reply_email]:
    email_assistant.register_for_llm(
        name=func.__name__,
        description=func.__doc__
    )(func)
    user_proxy.register_for_execution(
        name=func.__name__
    )(func)

"cm"># Start the conversation
user_proxy.initiate_chat(
    email_assistant,
    message="Check my inbox and summarize any new messages."
)

from autogen import GroupChat, GroupChatManager

"cm"># Create specialized agents
researcher = AssistantAgent(
    name="Researcher",
    system_message="You research topics and provide summaries. "
                   "You do not send emails directly.",
    llm_config=llm_config
)

email_agent = AssistantAgent(
    name="EmailAgent",
    system_message=(
        "You handle email communications via MultiMail. "
        "Only send emails when explicitly asked or when the "
        "group agrees on the content. All sends use gated_send "
        "mode (queued for human approval)."
    ),
    llm_config=llm_config
)

"cm"># Register email functions only with the email agent
for func in [send_email, check_inbox, reply_email]:
    email_agent.register_for_llm(
        name=func.__name__, description=func.__doc__
    )(func)
    user_proxy.register_for_execution(
        name=func.__name__
    )(func)

"cm"># Create group chat
group_chat = GroupChat(
    agents=[user_proxy, researcher, email_agent],
    messages=[],
    max_round=10
)

manager = GroupChatManager(
    groupchat=group_chat, llm_config=llm_config
)

user_proxy.initiate_chat(
    manager,
    message="Research AI safety best practices and email "
            "a summary to [email protected]"
)