Files
multi-agent-mux/deploy
GodopuandClaude Opus 5 508ca99d71 docs(issue-5): phase 1 benchmark results, contract mapping, task checklist
Records the measured numbers and syncs every document that names the
delegation script paths, then bumps the framework to 4.3.0 in the three-way
lockstep (lib.sh, VERSIONS.md current + matrix, eight SKILL.md frontmatters).

phase1-benchmark.md carries both arms. The deterministic fake transport is what
CI asserts on: 50 publishes cost 50 connections one-shot and 1 persistent, p50
54.813ms -> 0.002ms. The real broker run is informational, since the PoC
default is a public broker: p50 1892.728ms -> 275.992ms, about 85% off.

It also corrects the plan's own estimate rather than repeating it. D8 predicted
the new shell path would drop from 3 forks to 2; the implementation is still 3,
because keeping the `_delegate_script publish_event.py` lookup is the only
thing that produces the "missing script tree does nothing" non-fatal contract
that C-02 pins. Saving that fork would change the contract, so it is deferred
to phase 4 rather than taken quietly.

SKILL.md gains the context table saying which tree wins where, so an operator
reading it knows a frozen loop runs frozen delegation code. The script paths in
every document remain correct and every quoted command still works verbatim.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01UrDNJkHmm18uu7n7JwV5Qd
2026-09-06 15:48:38 +09:00
..

🚀 Multi-Agent Mux (MAM) Deployment & Gitea Integration

This directory contains packaging templates and installation scripts to deploy the Multi-Agent Mux framework into workspaces hosted on Gitea (or GitHub).


📁 Deployment Directory Structure

  • install.sh: A self-contained, idempotent remote shell installer (via curl) that checks system requirements (herdr, python3), sets up a local python virtual environment (.venv), and performs 3-way refresh with key-level registry merge (Rev.2).
  • install_mam.sh: A local-clone installer that copies rules/skills (.agents/), AGENTS.md, manifests, and asset hashes into target projects.
  • lib_ownership.sh: Single source of truth for framework-owned files and key-level registry files.
  • update.sh: In-place updater script installed into target .mam_deploy/update.sh.
  • remove.sh: Clean uninstaller script installed into target .mam_deploy/remove.sh.
  • generate-env.sh: Environment configuration bootstrap helper.
  • INSTALL.md: Detailed installation and quick-start user manual.
  • plugin.json: Metadata declaration file to register MAM as an installable plugin for AI Agent coding platforms.
  • gitea-ci.yml: CI/CD pipeline definition template for Gitea Actions (running ShellCheck linting, Python syntax checks, and pytest suite).

📦 How to Install and Deploy

1. Simple One-Liner Installation (from Gitea repository)

Once you push this repository to your Gitea instance, users can install it in their local workspace directory by running:

curl -fsSL https://git.godopu.com/tmpl/multi-agent-mux/raw/branch/main/deploy/install.sh | bash

Alternatively, if they have cloned the repository, they can execute:

bash deploy/install.sh

2. Local-Clone Installation

If you already have cloned this repository locally, you can port MAM to other local target projects:

bash deploy/install_mam.sh --target /path/to/your/project

Refer to INSTALL.md inside this directory for the full instructions and workflows.

Note

install_mam.sh automatically deploys .mam_deploy/update.sh and .mam_deploy/remove.sh into target workspaces, recording install manifests and asset hashes to enable clean updates and uninstalls.

3. Custom Fork / Private Mirror Installations

If you run a private mirror or fork, you can override the source URLs during installation using environment variables:

# Installing from a custom mirror (pipe prepends must be applied to the bash command)
curl -fsSL https://my-mirror.example.com/.../install.sh \
  | MAM_REPO_URL=https://my-mirror.example.com/me/multi-agent-mux.git \
    MAM_ARCHIVE_URL=https://my-mirror.example.com/me/multi-agent-mux/archive/main.tar.gz \
    bash

# Updating an existing workspace against a mirror
MAM_INSTALLER_URL=https://my-mirror.example.com/.../install.sh bash deploy/update.sh

4. Registering as a Workspace Plugin

To register these skills globally or for a specific workspace:

  • Workspace Level: Copy the .agents/ folder into your project root.
  • Global Level (Gemini/Antigravity): Register the plugin path in your global config file at ~/.gemini/config/skills.json:
    {
      "entries": [
        { "path": "/absolute/path/to/multi-agent-mux/.agents/skills" }
      ]
    }
    

5. Private NATS Broker & Submodule Integration (nats-docker)

For production deployments and private networks, MAM utilizes a dedicated NATS broker (nats:2.12-alpine with MQTT 3.1.1 and JetStream enabled). The container assets and deployment guides are managed in the nats-docker submodule:

# When cloning the repository with internal credentials:
git clone --recurse-submodules https://git.godopu.com/tmpl/multi-agent-mux.git

# Or initialize submodules in an existing clone:
git submodule update --init --recursive

Note

nats-docker is an optional submodule hosted in the private repository laa/nats-docker. If cloning without internal credentials, omit --recurse-submodules. The MAM framework functions out-of-the-box using standard MQTT brokers configured in .mam.env.

Refer to nats-docker/PRIVATE_SERVER.md and MESSAGING.md for detailed configuration, .mam.env generation, and security guidelines.


🤖 Gitea Actions CI/CD Setup

To automate testing and script linting on your Gitea repository:

  1. Ensure Gitea Actions is enabled on your Gitea instance.
  2. Copy the Gitea CI workflow to your workspace's workflow folder:
    mkdir -p .gitea/workflows
    cp deploy/gitea-ci.yml .gitea/workflows/ci.yml
    
  3. Commit and push to your Gitea repository. The pipeline will validate shell syntax and python file compilation on every push to main and pull requests.