Ag2 Network Quickstart

AG2 Network — Quickstart

The network turns a collection of Agent instances into a coordinated multi-agent system. A central Hub holds authoritative state (registry, audit log, write-ahead logs per channel); each agent lives behind a thin AgentClient that connects through a HubClient. Every send goes through the hub, so every interaction is replayable and observable.

The network is opt-in. Bare Agent continues to work standalone — the network only activates when you import from ag2.network.

When to use

Load this skill whenever the user wants two or more agents to interact. Concrete trigger phrases:

• "Have two agents talk to each other"
• "Set up a multi-agent system / multi-agent chat / agent network"
• "Agents that can call each other"
• "Replace the classic GroupChat / ConversableAgent.handoffs"
• "Add a registry / audit trail / shared inbox for my agents"

Not a network task: if the user is asking one agent to spawn its own sub-tasks (recursive task fan-out, parallel sub-task execution), use ag2-subagent-delegation instead. The network is for distinct, registered agents collaborating.

Mental model

                        ┌────────────────┐
                        │      Hub       │  ←── audit log, registry, channels,
                        │ ── adapters ── │       WAL, sweepers, expectation
                        │ ── channels ── │       evaluators
                        │ ── audit log ──│
                        └────────┬───────┘
                                 │  in-process duplex (LocalLink)
              ┌──────────────────┼──────────────────┐
              ▼                  ▼                  ▼
        ┌──────────┐       ┌──────────┐       ┌──────────┐
        │AgentClient│      │AgentClient│      │AgentClient│
        │  alice    │      │   bob     │      │   carol   │
        │  Agent    │      │  Agent    │      │  Agent    │
        └──────────┘       └──────────┘       └──────────┘

| Concept | Lives in | Purpose | |---|---|---| | Hub | One per network | Authoritative state — registry, audit log, channel table, WAL, sweepers | | Passport | Hub registry | Stable identity (name, hub-stamped agent_id, optional owner, model) | | Resume | Hub registry | Capability claims plus hub-mutated observed track record | | HubClient | One per process | Per-process broker; manages registration | | AgentClient | One per registered Agent | Wraps the Agent; sends envelopes, runs the notify handler | | Envelope | The wire format | Hub-stamped record of one event in one channel | | Channel | Created by agent_client.open(...) | A bounded multi-party exchange governed by an adapter |

The hub assigns the agent_id at registration. Use it (alice.agent_id) for routing rather than the human-readable name.

The smallest possible network

A single-process hub, two agents, a consulting channel (strict 1Q1R, auto-closes after the reply):

import asyncio

from ag2 import Agent
from ag2.config import AnthropicConfig
from ag2.knowledge import MemoryKnowledgeStore
from ag2.network import (
    EV_CHANNEL_CLOSED,
    EV_TEXT,
    Hub,
    HubClient,
    LocalLink,
    Passport,
    Resume,
)

async def main() -> None:
    config = AnthropicConfig(model="claude-sonnet-4-6")

    # 1. Boot the hub. MemoryKnowledgeStore for in-process; DiskKnowledgeStore(path)
    #    for durability across restarts.
    hub = await Hub.open(MemoryKnowledgeStore(), ttl_sweep_interval=0)
    link = LocalLink(hub)  # in-process duplex transport

    # 2. One HubClient per process boundary; here we use two for clarity.
    alice_hc = HubClient(link, hub=hub)
    bob_hc = HubClient(link, hub=hub)

    # 3. Register each Agent. The hub stamps the agent_id and returns an AgentClient.
    #    attach_plugin=False gives a bare agent (no peers/channels/tasks/context/
    #    delegate tools) — fine here since alice & bob just send/reply. The `say`
    #    tool is offered per-turn by the adapter, not the plugin (see below).
    alice = await alice_hc.register(
        Agent("alice", prompt="Ask one focused question and stop.", config=config),
        Passport(name="alice"),
        Resume(),
        attach_plugin=False,
    )
    bob = await bob_hc.register(
        Agent("bob", prompt="Answer in one short sentence.", config=config),
        Passport(name="bob"),
        Resume(),
        attach_plugin=False,
    )

    # 4. Open a consulting channel. The adapter posts EV_CHANNEL_INVITE to bob,
    #    bob's default handler auto-acks, channel goes ACTIVE.
    channel = await alice.open(type="consulting", target="bob")
    await channel.send(
        "What's the single most important property of a distributed system?",
        audience=[bob.agent_id],
    )

    # 5. Bob's default handler probes can_send, runs Agent.ask on the inbound
    #    text, sends the reply. ConsultingAdapter sees both flags set and
    #    auto-closes with reason "consulting_complete".
    close_env = await alice.wait_for_channel_event(
        channel_id=channel.channel_id,
        predicate=lambda e: e.event_type == EV_CHANNEL_CLOSED,
        timeout=60.0,
    )
    print(f"closed: {close_env.event_data.get('reason')!r}")

    # 6. Replay the conversation from the hub's WAL.
    wal = await hub.read_wal(channel.channel_id)
    for env in wal:
        if env.event_type == EV_TEXT:
            speaker = "alice" if env.sender_id == alice.agent_id else "bob"
            print(f"{speaker}: {env.event_data['text']}")

    await alice_hc.close()
    await bob_hc.close()
    await hub.close()

asyncio.run(main())

That's the entire mandatory surface. Everything else below is variation.

Picking a channel adapter

Every channel is governed by an adapter that defines participants, turn order, and termination. Four adapters ship; pick one when you call agent_client.open(type=..., target=...).

| Adapter | Participants | Turn order | Termination | Default view | |---|---|---|---|---| | consulting | Exactly 2 | Strict 1Q1R (initiator → respondent) | Auto-closes after respondent's reply | FullTranscript() | | conversation | Exactly 2 | Free-form (either side, any time) | Explicit channel.close() or TTL | WindowedSummary(recent_n=10) | | discussion | 2+ | Round-robin via ordering="round_robin" | Explicit close or TTL | WindowedSummary(recent_n=N*2) | | workflow | 2+ | Declarative TransitionGraph | Graph terminates (TerminateTarget / max_turns) | WindowedSummary(recent_n=N*2) |

This skill covers consulting and conversation (the 2-party adapters). For the others:

• N-party round-robin → load ag2-network-discussion.
• Declarative orchestration with TransitionGraph, conditional handoffs, or migrating from classic GroupChat → load ag2-network-workflow.

Plugin tools vs. adapter tools — attach_plugin and say

HubClient.register(...) attaches NetworkPlugin by default. The plugin contributes the identity-level cross-cutting tools — peers / channels / tasks / context / delegate — and nothing channel-specific. Channel-specific tools (notably say, which posts a text envelope into the channel) are offered per turn by the channel's adapter via adapter.tools_for(...), regardless of attach_plugin:

| Adapter | Offers say? | |---|---| | consulting | only to the participant whose turn it is in the 1Q1R | | conversation | always (no turn order) | | discussion | only to expected_next_speaker | | workflow | never — routing is your @tool handoff functions |

So attach_plugin=False no longer means "no say" — it means "no delegate / peers / channels / tasks / context". Pass it for a bare agent (tests, pure pipeline workers); keep the default if the agent needs those cross-cutting verbs.

You normally don't need to think about say at all: the default handler always posts the round-end envelope from the agent's plain reply, so an agent that just answers is fine. say is for the rare cases of posting an extra message in a turn, or posting into a different channel the agent is also in. (Edge case to avoid: an agent on a consulting channel that calls say(...) and also returns a non-empty reply double-sends — the second envelope trips channel is closed on the strict 1Q1R adapter. If you don't want the agent calling say, just don't prompt it to.) Full detail: ag2-network-tools-and-views → "Adapter-owned tools (tools_for)".

consulting — strict 1Q1R

The example above. Initiator sends exactly one substantive envelope; respondent sends exactly one reply; the adapter auto-closes with event_data["reason"] == "consulting_complete".

State on the hub side:

@dataclass(slots=True)
class ConsultingState:
    initiator_sent: bool = False
    respondent_replied: bool = False

ConsultingAdapter.validate_send rejects:

• Out-of-order sends (respondent speaking before initiator's first envelope).
• Any send after both flags are set — raises ProtocolError, propagated back to the caller's channel.send(...).

Default expectations are strict: acks_within(30s, auto_close) and reply_within(600s, auto_close). If the respondent doesn't ack the invite within 30s, or doesn't reply within 10 minutes, the hub auto-closes with "expectation_violated:acks_within" or "expectation_violated:reply_within". Tune these via ag2-network-governance.

conversation — free-form 2-party

Either side sends at any time, any order. The adapter never auto-closes; you halt via channel.close() or rely on TTL.

channel = await alice.open(type="conversation", target="bob")
await channel.send("Hi bob, what's a good first ML concept to learn?")

Both default handlers run Agent.ask on every inbound EV_TEXT, so once started the conversation auto-drives. Two halt patterns:

1. Application-side cap — poll the WAL until you've seen N text envelopes, then await channel.close().
2. Empty reply as halt signal — the default handler treats an empty body as "don't send", so an LLM that replies with "" ends the chain. Pair with a prompt like "reply with empty string when you have nothing useful to add".

ConversationAdapter.validate_send only checks "is the sender a participant?" — same-side sends in a row are allowed because the adapter doesn't model turn order.

Default expectation is lenient: max_silence(3600s, audit) (logs to the audit kind AUDIT_KIND_EXPECTATION_VIOLATED but does not close).

Use conversation when: two specialists genuinely converse without a fixed order (analyst ↔ critic); chat UIs where your application controls the stop signal.

Don't use conversation for: strict 1Q1R (use consulting); multi-participant chats (use discussion or workflow).

A non-LLM participant — HumanClient

Not every participant is an Agent. HumanClient is a network member with no LLM, no NetworkPlugin, no assembly policies — a person at a UI, a bridge to another system, or a scripted "user" that seeds a channel. Register it with register_human (not register — that path now rejects kind="human" and points you here):

from ag2.network import HumanClient, Passport

user_hc = HubClient(link, hub=hub)
user = await user_hc.register_human(Passport(name="user", kind="human"))   # resume=, rule=, auto_ack_invites= optional

It implements the same NetworkClient surface as AgentClient for outbound — user.open(type=..., target=...), user.send(channel_id, text, audience=...), user.post_envelope(env) (the escape hatch for adapter-shaped envelopes like a workflow EV_PACKET) — and gives you two ways to consume inbound envelopes:

• Push — user.on_envelope(callback); the coroutine fires once per inbound envelope. Multiple callbacks compose; a raising callback is logged, never propagated.
• Pull — await user.next_envelope(predicate=..., timeout=...) blocks for the next match; async for env in user.envelopes(): ... streams everything until user.disconnect().

It auto-acks channel invites (auto_ack_invites=True default) so the hub's join handshake completes without UI round-trips; pass auto_ack_invites=False to gate joins yourself. Discover humans via hub.list_agents(kind="human").

Common uses: the kickoff seeder for a workflow channel (FromSpeaker(user) → AgentTarget(first_agent) — see ag2-network-workflow), the human leg of a consulting Q&A, or a participant in a discussion round-robin. The agent-side surface (custom handlers, headless workers, gateways) is in ag2-network-tools-and-views.

Identity — Passport and Resume

Three dataclasses describe an agent on the network. Tenant supplies most fields; the hub stamps the rest.

from ag2.network import Passport, Resume, ResumeExample

passport = Passport(
    name="alice",          # required, unique within the hub
    owner="acme",          # optional, tenant id for multi-tenant deployments
    model="claude-sonnet-4-6",  # optional, surfaces on peer-lookup results
    kind="agent",          # optional: "agent" (default / None) | "human" | "remote_agent"
)

resume = Resume(
    claimed_capabilities=["analysis", "policy"],
    domains=["finance"],
    summary="Senior policy analyst — scenario synthesis and rebuttal review.",
    examples=[ResumeExample(title="Q3 risk brief", note="…")],
)

The hub stamps Passport.agent_id and Passport.created_at at registration. Passport.kind (type alias PassportKind) discriminates participant types — None/"agent" for the usual LLM-backed AgentClient, "human" for a HumanClient (use register_human, not register), "remote_agent" reserved for A2A/federation. hub.list_agents(kind=...) filters by it. The Resume.observed field (per-capability ObservedStat counts) is hub-mutated as the agent runs capability-tagged tasks — see ag2-network-governance for how to wire that up.

For the smallest case you can pass Passport(name="alice") and Resume() and call it done.

Channel lifecycle

agent_client.open(type=..., target=...)
    │
    ▼
PENDING ──┬─ all targets ack ──→ ACTIVE ──┬─ adapter terminates ──→ CLOSED
          │                                │
          └─ ack timeout ──→ CLOSED       └─ explicit channel.close() ──→ CLOSING ──→ CLOSED
                  (invite_timeout)               or TTL expired

The default invite_ack_timeout on Hub.open(...) is 30s; if any invited target doesn't ack within that window, create_channel raises ProtocolError and the channel goes straight to CLOSED with reason "invite_timeout". (The separate expectation-sweeper path — the acks_within expectation — auto-closes with "expectation_violated:acks_within" instead; see the consulting section below.)

Sending an envelope

await channel.send(text, audience=[bob.agent_id])

audience controls who sees the envelope (default: all participants). The hub stamps Envelope.envelope_id, sender_id, created_at, and writes it to the WAL.

For custom event types, send raw envelopes via agent_client.send_envelope(envelope). The full Envelope shape and the EV_* event constants are documented in ag2-network-tools-and-views.

The five channel-close routes

Every channel terminates with an EV_CHANNEL_CLOSED envelope. Five routes lead there; pick by who decides:

| Pattern | Who decides | Best for | |---|---|---| | channel.close(reason=...) | Your orchestration code | Custom caps (turn count, time, predicate) | | Agent-side tool (ChannelInject) | The LLM | "Agent decides we're done" | | Adapter sentinel (subclass) | The framework | Content-based stop ("TERMINATE" keyword) | | Workflow TerminateTarget | A declarative graph | Multi-step orchestrations | | TTL / expectations | The hub's sweepers | Time- or expectation-based safety nets |

Adapter compatibility:

| | Auto-close | App close | Agent tool | S

…

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: ag2ai
• Source: ag2ai/ag2-skills
• License: Apache-2.0

Install and usage instructions live in the source repository linked above.