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cli-agent-orchestrator

awslabs · awslabs/cli-agent-orchestrator

Trình điều phối này cho phép các tác nhân mã hóa AI như Claude Code và Cursor CLI hoạt động cùng nhau song song hoặc tuần tự trong các phiên tmux riêng biệt.

Multi-agent orchestration for AI coding CLIs — Claude Code, Kiro, Codex, and more, coordinated in isolated tmux sessions

1.4k sao291Giấy phép: Apache-2.0Cập nhật 12 ngày trước0 lượt mở

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Bạn có thể làm gì với nó

  • Giao các tác vụ mã hóa phức tạp cho một nhóm tác nhân AI chuyên biệt.
  • Tự động hóa các quy trình phát triển nhiều bước bằng cách sắp xếp các CLI AI khác nhau.
  • So sánh kết quả đầu ra từ nhiều tác nhân mã hóa trên cùng một tác vụ để tăng độ tin cậy.

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Trích từ README

CLI Agent Orchestrator (CAO)

English | 简体中文

CLI Agent Orchestrator (CAO) coordinates multiple AI coding CLIs so a supervisor can delegate work to specialist agents in parallel or sequence.

📚 Documentation — guides, reference, and two interactive courses.

What CAO does

CAO runs a local cao-server, starts provider CLIs in isolated terminal sessions, and gives a supervisor tools for coordinating workers. The agents remain full CLI processes with their native authentication and capabilities. See CODEBASE.md for the runtime architecture and package layout.

Prerequisites

Install:

The focused provider guides contain installation, authentication, and provider-specific behavior.

Install CAO

Install the current main branch as a uv tool:

uv tool install git+https://github.com/awslabs/cli-agent-orchestrator.git@main --upgrade
cao --help

For a tagged release, install cli-agent-orchestrator from PyPI. See DEVELOPMENT.md for a source checkout. For container-based installation, see the devcontainer feature.

To update an existing CAO installation:

cao update

See Updating CAO for source-aware behavior and edge cases.

First supervisor launch

The unqualified commands below use CAO's default Kiro CLI provider. If you installed a different provider, follow its focused guide above for the provider override while keeping the same sequence.

  1. Install the built-in supervisor profile:

    cao install code_supervisor
    
  2. In terminal A, start the local server and leave it running:

    cao-server
    
  3. In terminal B, change to the project directory the agents should work in, then launch the supervisor:

    cd /path/to/your/project
    cao launch --agents code_supervisor
    
  4. Observe the supervisor in the attached launch terminal, open the Web UI at http://localhost:9889, or follow the tmux guide to attach to its session.

  5. Stop the named session when finished:

    cao shutdown --session {session-name}
    

    To stop every CAO session instead, run cao shutdown --all.

Where to go next

Operate CAO

  • Control-plane selection: choose the Web UI, shell CLI, operations MCP server, or plugins.
  • Web UI and MCP Apps: browser and host-rendered fleet interfaces.
  • Flows and workflows: scheduled runs and multi-step pipelines.
  • Skills: install, scope, and author reusable agent guidance.
  • Memory and self-learning: persistent cross-session memory, and the opt-in loop that turns workflow outcomes into lessons and promoted instructions.
  • AI-DLC portfolio example: coordinate parallel AI-DLC intents across repositories and isolated worktrees.
  • Tool restrictions: roles, allowlists, and provider enforcement.
  • Kubernetes deployment: run a supervisor and worker fleet on Amazon EKS, with shared workspace, per-pod state, and credential delivery.
  • Updating CAO: update an installed uv tool.

Configure and integrate

Contribute

Contributing

See CONTRIBUTING.md and DEVELOPMENT.md before submitting changes. Documentation changes must also follow the documentation maintenance rule.

License

Thi

Xem mã nguồn trên GitHub