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Voice-first local agent orchestration runtime for auditable DAG workflows.
| Date | Stars |
|---|---|
| 2026-07-31 | 772 |
| 2026-08-04 | 833 |
| 2026-08-06 | 833 |
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# HomeRail English | [中文](README.zh-CN.md) HomeRail is a TypeScript runtime that turns one-off agent chats into auditable, reusable workflows. The name comes from what it is: **Home** — it runs on your own homelab, NAS, or home server, serving the people who live there; **Rail** — the track shape of a DAG, where agent work flows node to node along explicit edges instead of pooling in a single chat. The design bet is that a person's attention is the scarcest resource in any automation, so the system should ask for very little of it. The long-term shape is a resident home-datacenter agent you talk to — voice in, a generated interface out, a DAG of agents doing the work behind it. What is in this tree today is the foundation it runs on: a DAG engine, a CLI, a voice surface, and the first steps toward a generated UI. ## Why Human bandwidth is narrow; the work we want done is not. HomeRail is shaped like an inverted funnel that widens toward the machine: - **Voice** — the preferred input, because it asks the least of you. You speak; the agent listens, confirms, and narrows ambiguity before doing anything. Text is always available too — for quiet settings, for precision, or for anyone not ready to talk to their computer yet. - **Generative UI** — the agent does not dump logs or JSON at you. The interface is generated for the moment and shaped to be easy to read. - **DAG** — the execution engine behind both. Multiple agents, multiple roles, multiple environments, with every handoff traced and every run replayable. A chat session is a black box. A DAG is a graph you can inspect, replay, and improve. HomeRail is what sits between the two — narrow where the person is, wide where the machine is. ## What works today - **DAG runtime** *(most mature)* — multi-agent orchestration with explicit handoffs, workspace isolation per run, replay, scorecards, and run evaluation. - **CLI `hr`** — `start`, `config`, `doctor`, `run`, `smoke`, `dag supervise`, `scorecard`, `eval-run`, `replay`. The primary way to operate HomeRail. - **Voice surface** — a Voice Surface Contract with ASR / TTS / VAD, Chinese by default, served through a desktop voice shell. The agent collects intent across turns before acting. - **Generative UI** *(in exploration)* — instead of dumping logs or JSON, the agent produces structured, generated views meant to be read at a glance. The shape of these views is still being designed through real use cases; the contract and the widget set will keep changing. - **Docker Worker** — Manager and Node run as local services; Node uses Docker to provision Worker containers, one per DAG node, sharing a workspace per run. ## Hand this README to an agent HomeRail is designed to be operated by agents as much as by people. This README is written so that it doubles as an agent-readable runbook: the commands below are plain `hr` invocations with self-describing names, and each step says what to expect. You can hand the whole file to your agent (Claude Code, Codex, or any tool that can run shell commands and read output) and ask it to install, configure, and verify HomeRail on your machine following the Quickstart. ## Quickstart Requirements: - Node.js 20+ and npm 10+ - Docker, used by Node to provision Worker containers - A Claude Agent SDK-compatible model endpoint for live agent runs Platform notes: - **macOS** — install [Docker Desktop](https://www.docker.com/products/docker-desktop/). The default `host.docker.internal` mapping works out of the box. - **Windows** — Docker Desktop (WSL 2 or Hyper-V backend both work), and run the CLI from Git Bash (or another POSIX-compatible shell). Some scripts assume a Unix-like shell and will not run correctly under `cmd.exe` or PowerShell. - **Linux** — Docker Engine. Worker-to-Manager networking may need extra setup; see the [Configuration](#configuration) notes on Worker callback URLs. Install and build from this source checkout: ```bash npm run insta
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matched fp:c880228044ffaad9, desc:agent orchestration