Bohan Jiang 3e21e58df0 feat(channel): channel-agnostic engine (Supervisor + Router); Feishu as channel.Channel (MUL-3620) (#4512)
* feat(channel): add channel-agnostic engine Supervisor (MUL-3620)

Stage-1 (MUL-3515) shipped the channel abstraction but nothing drove it.
Add the generic engine that does:

- channel.InboundHandler + Config.Handler: the single shared inbound entry
  the engine injects into every adapter (Hermes set_message_handler model).
- channel.Channel.Connect now blocks for the connection lifetime (doc), so
  the supervisor can tie lease renewal to connection liveness.
- new package channel/engine: Supervisor, generalized out of lark.Hub. It
  enumerates active installations across ALL channel types (no hard-coded
  feishu), fences each behind the WS lease CAS, builds the platform Channel
  via channel.Registry, drives Connect/Disconnect with backoff+jitter, and
  restarts on credential rotation. Knows nothing about any platform.

channel.Channel is now driven by an engine; integrations/channel has an
external consumer. Feishu adapter + boot cutover follow next.

Tests: supervisor_test.go covers lease CAS, reclaim, reap-on-revoke,
rotation restart + token fencing, backoff on build error, lease-loss
teardown, bounded release, shutdown timeout. Race-clean.

Co-authored-by: multica-agent <github@multica.ai>

* feat(lark): drive Feishu through the channel engine; remove lark.Hub (MUL-3620)

Refactor Feishu into the first channel.Channel and cut boot over to the
channel-agnostic engine.Supervisor, removing the Feishu-only Hub.

- feishuChannel implements channel.Channel: Connect runs the existing
  WS long-conn connector for one installation; Send posts a text reply
  via the Lark IM API; Capabilities declares Feishu's feature set.
  RegisterFeishu wires it to channel.TypeFeishu — adding a platform is
  now 'register a Factory', no engine edit.
- FeishuRuntime extracts the former Hub.handleEvent / scheduleReply:
  runs the Dispatcher and drives the detached typing indicator +
  OutcomeReplier off the connector ACK path. main.go drains it on
  shutdown after the supervisor stops delivering events.
- channelInstallationStore (engine.InstallationStore) enumerates active
  installations across ALL channel types via the new de-hardcoded query
  ListAllActiveChannelInstallations; the Supervisor routes each row to
  its registered Factory by channel_type. Generic per-row fingerprint
  replaces the feishu-specific one.
- boot: engine.Supervisor replaces lark.Hub.Run; MULTICA_LARK_HUB_DISABLED
  keeps its name for runbook compatibility.
- delete hub.go / hub_pgx.go / hub_test.go; relocate the connector
  contract (EventConnector/EventEmitter), uuidString, and the reply-path
  tests (-> feishu_runtime_test.go) so coverage is preserved.

No channel_* schema change. Feishu behaviour unchanged; lark + channel +
engine tests green under -race; go build/vet ./... clean.

Remaining (follow-up): lift the Dispatcher pipeline into a channel-
agnostic engine.Router over channel.InboundMessage + resolver interfaces,
so the inbound core stops being Lark-shaped and adding a channel needs
zero core edits (validated by Slack, MUL-3516).

Co-authored-by: multica-agent <github@multica.ai>

* feat(channel): add channel-agnostic engine.Router (inbound pipeline) (MUL-3620)

Generalize lark.Dispatcher's inbound pipeline into engine.Router: the single
shared channel.InboundHandler the Supervisor injects into every Channel. It
routes by ChannelType to a registered ResolverSet and runs the same ordered
pipeline for every platform (install route -> two-phase dedup -> group @bot
filter -> identity+membership -> ensure session -> append+mark -> /issue ->
debounced run), then drives the detached OutboundReplier + typing indicator.

Platform specifics live behind resolver interfaces (InstallationResolver,
IdentityResolver, Deduper, SessionBinder, Auditor, OutboundReplier,
TypingNotifier) + shared services (IssueCreator/TaskEnqueuer/SessionReader).
Adding a platform is 'register a ResolverSet', not 'edit the Router'. Outcome
/ DropReason values match the legacy lark ones 1:1.

Additive: lark.Dispatcher untouched and still wired; the feishu ResolverSet,
the cutover, and the old-path removal land next. channel.InboundMessage gains
ForceFresh (the normalized /fresh affordance). Batcher moved into engine.

router_test.go covers the pipeline invariants (routing, dedup finalize
states, group filter, identity, membership, ensure/append, /issue, debounce,
flush offline, force-fresh, drain) with generic fakes; race-clean.

Co-authored-by: multica-agent <github@multica.ai>

* feat(lark): cut Feishu over to engine.Router; remove lark.Dispatcher; core no longer Lark-shaped (MUL-3620)

Wire the channel-agnostic engine.Router (added in the prior commit) as the
shared inbound handler and refactor Feishu into a ResolverSet, completing the
generic-engine cutover. The inbound core (engine.Router) now contains zero
platform specifics.

- Feishu ResolverSet (feishu_resolvers.go): InstallationResolver,
  IdentityResolver, Deduper, SessionBinder, Auditor, OutboundReplier,
  TypingNotifier — each backed by the existing ChannelStore / ChatSessionService
  / OutcomeReplier / typing indicator, translating at the channel.InboundMessage
  boundary (platform fields read from Raw). origin_type stays 'lark_chat'.
- feishuChannel now produces a normalized channel.InboundMessage and hands it to
  the engine handler via channel.Config.Handler; the old Raw round-trip through
  lark.Dispatcher is gone.
- Remove lark.Dispatcher, FeishuRuntime, and lark's pending_batcher (the engine
  owns the pipeline + batcher now); their behavioural coverage moved to
  engine.Router tests. Surviving native types (InboundMessage / Outcome /
  DispatchResult) relocated to feishu_types.go.

elon review nits addressed:
- The channel engine (Registry + Router + Supervisor) is now built
  UNCONDITIONALLY, outside the MULTICA_LARK_SECRET_KEY gate, so a non-Lark
  deployment runs it; Feishu registers its Factory + ResolverSet only when its
  key is present.
- channel.Config.Raw is now genuinely the platform config JSONB
  (channel_installation.config): the feishu factory builds a credentials-only
  Installation from it, and the workspace/agent identity is resolved per message
  by the Router — no full-db-row marshaling.
- feishuChannel gains direct unit tests: factory config decode, Send text +
  reply-target mapping, Capabilities, inbound normalization + Raw round-trip,
  msg-type + result mapping.

No channel_* schema change. go build/vet ./... clean; channel + engine + lark
green under -race. Feishu behaviour preserved (pipeline logic lifted verbatim,
only generalized).

Co-authored-by: multica-agent <github@multica.ai>

* docs(channel): fix stale comments on the channel engine boot (MUL-3620)

Address Elon's review nit: three comments still described the pre-cutover
behavior.

- handler.go: ChannelSupervisor is built UNCONDITIONALLY now, not nil when
  MULTICA_LARK_SECRET_KEY is unset.
- main.go: same — the supervisor always exists; only MULTICA_LARK_HUB_DISABLED
  parks it.
- router.go: with no platform registered the store still lists active rows;
  Registry.Build returns ErrUnknownType and the supervisor backs off (it does
  not 'find no installations').

Comment-only; no behavior change.

Co-authored-by: multica-agent <github@multica.ai>

---------

Co-authored-by: J <j@multica.ai>
Co-authored-by: multica-agent <github@multica.ai>
2026-06-24 17:01:33 +08:00
2026-06-16 08:38:53 +08:00
2026-06-19 06:26:14 +02:00

Multica — humans and agents, side by side

Multica

Multica

Your next 10 hires won't be human.

The open-source managed agents platform.
Turn coding agents into real teammates — assign tasks, track progress, compound skills.

CI GitHub stars Discord

Website · Cloud · Discord · X · Self-Hosting · Contributing

English | 简体中文

What is Multica?

Multica turns coding agents into real teammates. Assign issues to an agent like you'd assign to a colleague — they'll pick up the work, write code, report blockers, and update statuses autonomously.

No more copy-pasting prompts. No more babysitting runs. Your agents show up on the board, participate in conversations, and compound reusable skills over time. Think of it as open-source infrastructure for managed agents — vendor-neutral, self-hosted, and designed for human + AI teams. Works with Claude Code, Codex, GitHub Copilot CLI, OpenClaw, OpenCode, Hermes, Gemini, Pi, Cursor Agent, Kimi, Kiro CLI, and Qoder CLI.

For larger teams, Squads add a stable routing layer: assign work to a group led by an agent, and the leader delegates to the right member.

Multica board view

Why "Multica"?

Multica — Multiplexed Information and Computing Agent.

The name is a nod to Multics, the pioneering operating system of the 1960s that introduced time-sharing — letting multiple users share a single machine as if each had it to themselves. Unix was born as a deliberate simplification of Multics: one user, one task, one elegant philosophy.

We think the same inflection is happening again. For decades, software teams have been single-threaded — one engineer, one task, one context switch at a time. AI agents change that equation. Multica brings time-sharing back, but for an era where the "users" multiplexing the system are both humans and autonomous agents.

In Multica, agents are first-class teammates. They get assigned issues, report progress, raise blockers, and ship code — just like their human colleagues. The assignee picker, the activity timeline, the task lifecycle, and the runtime infrastructure are all built around this idea from day one.

Like Multics before it, the bet is on multiplexing: a small team shouldn't feel small. With the right system, two engineers and a fleet of agents can move like twenty.

Features

Multica manages the full agent lifecycle: from task assignment to execution monitoring to skill reuse.

  • Agents as Teammates — assign to an agent like you'd assign to a colleague. They have profiles, show up on the board, post comments, create issues, and report blockers proactively.
  • Squads — group agents (and humans) under a leader agent and assign work to the squad. The leader decides who should pick it up, so routing stays stable as the team grows. @FrontendTeam instead of @alice-or-bob-or-carol.
  • Autonomous Execution — set it and forget it. Full task lifecycle management (enqueue, claim, start, complete/fail) with real-time progress streaming via WebSocket.
  • Autopilots — schedule recurring work for agents. Cron triggers, webhooks, or manual runs — each autopilot creates the issue and routes it to an agent automatically, so daily standups, weekly reports, and periodic audits run themselves.
  • Reusable Skills — every solution becomes a reusable skill for the whole team. Deployments, migrations, code reviews — skills compound your team's capabilities over time.
  • Unified Runtimes — one dashboard for all your compute. Local daemons and cloud runtimes, auto-detection of available CLIs, real-time monitoring.
  • Multi-Workspace — organize work across teams with workspace-level isolation. Each workspace has its own agents, issues, and settings.

Quick Install

brew install multica-ai/tap/multica

Use brew upgrade multica-ai/tap/multica to keep the CLI current.

macOS / Linux (install script)

curl -fsSL https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.sh | bash

Use this if Homebrew is not available. The script installs the Multica CLI on macOS and Linux by using Homebrew when it is on PATH, otherwise it downloads the binary directly.

Windows (PowerShell)

irm https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.ps1 | iex

Then configure, authenticate, and start the daemon in one command:

multica setup          # Connect to Multica Cloud, log in, start daemon

Self-hosting? Add --with-server to deploy a full Multica server on your machine:

curl -fsSL https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.sh | bash -s -- --with-server
multica setup self-host

This pulls the official Multica images from GHCR (latest stable by default). Requires Docker. See the Self-Hosting Guide for details. If the selected GHCR tag has not been published yet, fall back to make selfhost-build from a checkout.


Getting Started

1. Set up and start the daemon

multica setup           # Configure, authenticate, and start the daemon

The daemon runs in the background and auto-detects agent CLIs (claude, codex, copilot, openclaw, opencode, hermes, gemini, pi, cursor-agent, kimi, kiro-cli, agy, qodercli) on your PATH.

2. Verify your runtime

Open your workspace in the Multica web app. Navigate to Settings → Runtimes — you should see your machine listed as an active Runtime.

What is a Runtime? A Runtime is a compute environment that can execute agent tasks. It can be your local machine (via the daemon) or a cloud instance. Each runtime reports which agent CLIs are available, so Multica knows where to route work.

3. Create an agent

Go to Settings → Agents and click New Agent. Pick the runtime you just connected and choose a provider (Claude Code, Codex, GitHub Copilot CLI, OpenClaw, OpenCode, Hermes, Gemini, Pi, Cursor Agent, Kimi, Kiro CLI, Antigravity, or Qoder CLI). Give your agent a name — this is how it will appear on the board, in comments, and in assignments.

4. Assign your first task

Create an issue from the board (or via multica issue create), then assign it to your new agent. The agent will automatically pick up the task, execute it on your runtime, and report progress — just like a human teammate.


CLI

The multica CLI connects your local machine to Multica — authenticate, manage workspaces, and run the agent daemon.

Command Description
multica login Authenticate (opens browser)
multica daemon start Start the local agent runtime
multica daemon status Check daemon status
multica setup One-command setup for Multica Cloud (configure + login + start daemon)
multica setup self-host Same, but for self-hosted deployments
multica workspace list List your workspaces (current is marked with *)
multica workspace switch <id|slug> Switch the default workspace for this profile
multica issue list List issues in your workspace
multica issue create Create a new issue
multica update Update to the latest version

See the CLI and Daemon Guide for the full command reference.


Architecture

┌──────────────┐     ┌──────────────┐     ┌──────────────────┐
│   Next.js    │────>│  Go Backend  │────>│   PostgreSQL     │
│   Frontend   │<────│  (Chi + WS)  │<────│   (pgvector)     │
└──────────────┘     └──────┬───────┘     └──────────────────┘
                            │
                     ┌──────┴───────┐
                     │ Agent Daemon │  runs on your machine
                     └──────────────┘  (Claude Code, Codex, GitHub Copilot CLI,
                                        OpenCode, OpenClaw, Hermes, Gemini,
                                        Pi, Cursor Agent, Kimi, Kiro CLI, Qoder CLI)
Layer Stack
Frontend Next.js 16 (App Router)
Backend Go (Chi router, sqlc, gorilla/websocket)
Database PostgreSQL 17 with pgvector
Agent Runtime Local daemon executing Claude Code, Codex, GitHub Copilot CLI, OpenClaw, OpenCode, Hermes, Gemini, Pi, Cursor Agent, Kimi, Kiro CLI, or Qoder CLI

Development

For contributors working on the Multica codebase, see the Contributing Guide.

Prerequisites: Node.js v20+, pnpm v10.28+, Go v1.26+, Docker

make dev

make dev auto-detects your environment (main checkout or worktree), creates the env file, installs dependencies, sets up the database, runs migrations, and starts all services.

See CONTRIBUTING.md for the full development workflow, worktree support, testing, and troubleshooting.

An iOS mobile client lives in apps/mobile/ — see its README for how to build it onto your own iPhone.

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