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serverless-devs/agentrun-cli

Deployment & DevOps

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21 stars 품질 52 트렌드 14NOASSERTION

AgentRun CLI (agentrun / ar) — A command-line tool for managing AI agent infrastructure on the AgentRun platform.

개요

Command-line tool for managing AI-agent infrastructure on the AgentRun platform. ar (or agentrun) is a single-binary CLI that wraps the AgentRun Python SDK. It lets developers, CI pipelines, and LLM-powered agents create and operate sandboxes, tools, skills, model services and — most importantly — : platform-hosted AI agents that you configure declaratively without writing or deploying any runtime code. - — ar super-agent run creates a hosted agent and drops you into a chat REPL in seconds. - — Kubernetes-style YAML (ar sa apply -f superagent.yaml) for reproducible, version-controlled agents. - — ar runtime apply -f runtime.yaml deploys an Agent Runtime from an image, or invokes a cloud build first when the YAML defines cloudBuild. - — config, model, sandbox, tool, skill, super-agent, runtime, all following the same ar pattern. - — store multiple sets of credentials in ~/.agentrun/config.json and switch with --profile. - — json (default), table, yaml, and quiet for shell piping.

README

원문 README의 일부입니다. 원문 보기.

English | 简体中文

AgentRun CLI

Command-line tool for managing AI-agent infrastructure on the AgentRun platform.

ar (or agentrun) is a single-binary CLI that wraps the AgentRun Python SDK. It lets developers, CI pipelines, and LLM-powered agents create and operate sandboxes, tools, skills, model services and — most importantly — super agents: platform-hosted AI agents that you configure declaratively without writing or deploying any runtime code.

Features

  • One-command super agent — ar super-agent run creates a hosted agent and drops you into a chat REPL in seconds.
  • Declarative deployment — Kubernetes-style YAML (ar sa apply -f superagent.yaml) for reproducible, version-controlled agents.
  • Runtime declarative deploy — ar runtime apply -f runtime.yaml deploys an Agent Runtime from an image, or invokes a cloud build first when the YAML defines cloudBuild.
  • Seven resource groups — config, model, sandbox, tool, skill, super-agent, runtime, all following the same ar pattern.
  • Multi-profile config — store multiple sets of credentials in ~/.agentrun/config.json and switch with --profile.
  • Multiple output formats — json (default), table, yaml, and quiet for shell piping.
  • Agent-friendly — JSON-by-default output, deterministic exit codes, no interactive prompts when stdin isn’t a TTY.
  • Rich sandbox primitives — code execution, file system, process management, and CDP/VNC-backed browser automation.
  • Single-file distribution — PyInstaller produces standalone ar / agentrun binaries for Linux, macOS and Windows (x86_64 + arm64).

Installation

pip install agentrun-cli

Prebuilt binary

Download a single self-contained binary from Releases. No Python required.

Linux / macOS (x86_64 or arm64):

curl -fsSL https://raw.githubusercontent.com/Serverless-Devs/agentrun-cli/main/scripts/install.sh | sh

Windows (x86_64, PowerShell):

irm https://raw.githubusercontent.com/Serverless-Devs/agentrun-cli/main/scripts/install.ps1 | iex

Pin a specific version with AGENTRUN_VERSION=v0.1.0 …. Change the install directory with AGENTRUN_INSTALL=…. Both installers verify the SHA256 checksum before placing the binary.

Or download the archive manually from the Releases page — naming scheme:

agentrun---.
# e.g. agentrun-0.1.0-linux-amd64.tar.gz
#      agentrun-0.1.0-darwin-arm64.tar.gz
#      agentrun-0.1.0-windows-amd64.zip

From source

git clone https://github.com/Serverless-Devs/agentrun-cli.git
cd agentrun-cli
make install            # editable install into .venv
make build              # standalone binary → dist/agentrun

Verify

ar --version            # or: agentrun --version

Prerequisites

GitHub에서 전체 README 보기

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