ralph-workflow 0.9.7

An autonomous coding-agent orchestrator: hand off a well-specified task and return to reviewable, tested work.

ralph-workflow

Ralph Workflow is a free, open-source orchestrator for AI coding agents. Hand it a well-specified task, let agents plan, build, verify, and fix, and come back to reviewable, tested work.

Install

pipx install ralph-workflow
ralph --version

pipx keeps the install isolated from your other Python projects; the post-condition is that ralph --version prints the installed package version.

First run

The complete first-run path is six short steps and does not require opening any other config file before your first run.

1. Install Ralph Workflow. Use pipx install ralph-workflow (or pip install ralph-workflow).
2. Start in your project. cd /path/to/your/project and run ralph --init. It creates your user-global config and a PROMPT.md; project-local config is optional later via ralph --init-local-config.
3. Confirm a coding agent. Ralph Workflow looks for supported agents already on your PATH and enables the ones it finds. Install and authenticate an agent first if none are found.
4. Check the setup. Run ralph --diagnose and fix any reported problem before starting work.
5. Describe the task. Edit PROMPT.md with the outcome and checks you expect. For a task-shaped starter, use ralph --init feature-spec, guardrail, refactor, test-coverage, or docs before a prompt file exists.
6. Run Ralph Workflow. Run ralph, then read the finish-receipt artifact: it names the change, checks run, and review focus before you decide what to do next.

The canonical first-run walkthrough is Getting started. For agent-specific model-string formats, see Agent compatibility.

Supported agents

Eight built-in agents ship with Ralph Workflow:

Agent	Notes
Claude Code	Anthropic's CLI for Claude (interactive, PTY transport).
Claude Code (Headless)	Same claude binary in headless subprocess mode (claude-headless).
Codex	OpenAI's Codex CLI.
OpenCode	Open-source terminal coding agent.
Nanocoder	Local-only TUI coding agent.
Google Anti Gravity (AGY)	Google's Antigravity CLI (agy), measured on v1.1.8: gemini-3.6-flash-low, gemini-3.6-flash-high --effort high, stream-json init/step_update/result, and the manual smoke's exit-0 validated fallback-artifact path have live evidence. Re-run the manual smoke after AGY updates.
Pi	Minimal coding agent. Headless mode is pi --mode json <prompt>.
Cursor	Cursor Agent CLI (agent), headless --print mode.

Pick one, authenticate it on your machine once, and Ralph Workflow uses it. The selection and trust-boundary story is in the maintained Sphinx manual under agents and agent-compatibility.

Requirements

• Python ≥ 3.12
• Local execution; no daemon, no cloud dependency
• One supported agent CLI installed and authenticated

License

AGPL-3.0-or-later.

Documentation

The maintained operator manual is at docs/sphinx/index.rst — tutorial, configuration reference, MCP / artifact / pipeline configuration, concepts, troubleshooting, diagnostics, and developer internals.

Project home

• Repository: https://github.com/Ralph-Workflow/Ralph-Workflow
• PyPI: https://pypi.org/project/ralph-workflow/
• Issue tracker: https://github.com/Ralph-Workflow/Ralph-Workflow/issues/new
• Contribution route: CONTRIBUTING.md