## The open source dark software factory for expert engineers
AI coding agents are powerful but unpredictable. You either babysit every step or review a 50-file diff you don't trust. Fabro gives you a middle path: define the process as a graph, let agents execute it, and intervene only where it matters. [Why Fabro?](https://docs.fabro.sh/getting-started/why-fabro)
[](https://github.com/fabro-sh/fabro/actions/workflows/rust.yml)
[](LICENSE.md)
[](https://docs.fabro.sh)
```bash
# With Claude Code
curl -fsSL https://fabro.sh/install.md | claude
# With Codex
codex "$(curl -fsSL https://fabro.sh/install.md)"
# With Homebrew
brew install fabro-sh/tap/fabro-nightly
# With Bash
curl -fsSL https://fabro.sh/install.sh | bash
```
Then run `fabro server start` to finish setup in your browser. The server opens a web wizard, exits when the wizard completes, and starts in configured mode the next time you run it.
---
## Use Cases
- **Extend disengagement time** — Stop babysitting an agent REPL. Define a workflow with verification gates and walk away — Fabro keeps the process on track without you.
- **Leverage ensemble intelligence** — Seamlessly combine models from different vendors. Use one model to implement, another to cross-critique, and a third to summarize — all in a single workflow.
- **Share best practices across your team** — Collaborate on version-controlled workflows that encode your software processes as code. Review, iterate, and reuse them like any other source file.
- **Reduce token bills** — Route cheap tasks to fast, inexpensive models and reserve frontier models for the steps that need them. CSS-like stylesheets make this a one-line change.
- **Improve agent security** — Run agents in cloud sandboxes with full network and filesystem isolation. Keep untrusted code off your laptop and out of your production environment.
- **Run agents 24/7** — Fabro's API server queues and executes runs continuously. Close your laptop — workflows keep running and results are waiting when you return.
- **Scale infinitely** — Move execution off your laptop and into cloud sandboxes. Run as many concurrent workflows as your infrastructure allows.
- **Guarantee code quality** — Layer deterministic verifications — test suites, linters, type checkers, LLM-as-judge — into your workflow graph. Failures trigger fix loops automatically.
- **Inspect every run** — Query durable event streams, checkpoints, conclusions, and stage outputs to understand what happened and improve the workflow.
- **Specify in natural language** — Define requirements as natural-language specs and let Fabro generate — and regenerate — implementations that conform to them.
---
## Key Features
| | Feature | Description |
| --- | ------------------------------ | ----------------------------------------------------------------------------------------------------- |
| 🔀 | Deterministic workflow graphs | Define pipelines in Graphviz DOT with branching, loops, parallelism, and human gates. Diffable, reviewable, version-controlled |
| 🙋 | Human-in-the-loop | Approval gates pause for human decisions. Steer running agents mid-turn. Interview steps collect structured input |
| 🎨 | Multi-model routing | CSS-like stylesheets route each node to the right model and provider, with automatic fallback chains |
| ☁️ | Cloud sandboxes | Run agents in isolated Daytona cloud VMs with snapshot-based setup, network controls, and automatic cleanup |
| 🔌 | SSH access and preview links | Shell into running sandboxes with `fabro sandbox ssh` and expose ports with `fabro sandbox preview` for live debugging |
| 🌲 | Git checkpointing | Every stage commits code changes and execution metadata to Git branches. Resume, revert, or trace any change |
| 📊 | Run observability | Durable events, checkpoints, conclusions, and stage outputs make every run inspectable and exportable |
| ⚡ | Comprehensive API | REST API with SSE event streaming and a React web UI. Run workflows programmatically or as a service |
| 🦀 | Single binary, no runtime | One compiled Rust executable with zero dependencies. No Python, no Node, no Docker required |
| ⚖️ | Open source (MIT) | Full source code, no vendor lock-in. Self-host, fork, or extend to fit your workflow |
---
## Example Workflow
A plan-approve-implement workflow where a human reviews the plan before the agent writes code:
```dot
digraph PlanImplement {
graph [
goal="Plan, approve, implement, and simplify a change"
model_stylesheet="
* { model: claude-haiku-4-5; reasoning_effort: low; }
.coding { model: claude-sonnet-4-5; reasoning_effort: high; }
"
]
start [shape=Mdiamond, label="Start"]
exit [shape=Msquare, label="Exit"]
plan [label="Plan", prompt="Analyze the goal and codebase. Write a step-by-step plan.", reasoning_effort="high"]
approve [shape=hexagon, label="Approve Plan"]
implement [label="Implement", class="coding", prompt="Read plan.md and implement every step."]
simplify [label="Simplify", class="coding", prompt="Review the changes for clarity and correctness."]
start -> plan -> approve
approve -> implement [label="[A] Approve"]
approve -> plan [label="[R] Revise"]
implement -> simplify -> exit
}
```
Agents run as multi-turn LLM sessions with tool access. Human gates (`hexagon`) pause for approval. The stylesheet routes planning to a cheap model and coding to a frontier model. See the [Graphviz DOT language reference](https://docs.fabro.sh/reference/dot-language) for the full syntax.
---
## 📖 Documentation
Fabro ships with [comprehensive documentation](https://docs.fabro.sh) covering every feature in depth:
- [**Getting Started**](https://docs.fabro.sh/getting-started/introduction) -- Installation, first workflow, and why Fabro exists
- [**Defining Workflows**](https://docs.fabro.sh/workflows/stages-and-nodes) -- Node types, transitions, variables, stylesheets, and human gates
- [**Executing Workflows**](https://docs.fabro.sh/execution/run-configuration) -- Run configuration, sandboxes, checkpoints, observability, and failure handling
- [**Tutorials**](https://docs.fabro.sh/tutorials/hello-world) -- Step-by-step guides from hello world to parallel multi-model ensembles
- [**API Reference**](https://docs.fabro.sh/api-reference/overview) -- Full OpenAPI spec with authentication, SSE events, and client SDKs
---
## Quick Start
### Install
```bash
# With Claude Code
curl -fsSL https://fabro.sh/install.md | claude
# With Codex
codex "$(curl -fsSL https://fabro.sh/install.md)"
# With Homebrew
brew install fabro-sh/tap/fabro-nightly
# With Bash
curl -fsSL https://fabro.sh/install.sh | bash
```
Release binaries and the multi-arch Docker image ship with SLSA Build Provenance attestations. See [Verifying Releases](https://docs.fabro.sh/reference/verifying-releases) to check an artifact was built by our GitHub Actions workflow.
Then finish setup in your browser and initialize Fabro in your project:
```bash
fabro server start # opens a web install wizard in your browser
# (server exits when the wizard finishes — start it again to run Fabro)
cd my-project
fabro repo init # per project
```
For headless or scripted environments, `fabro install` runs the same setup as a CLI-only wizard.
---
## Running Fabro
Fabro runs as a server. You choose where it runs:
- **On your laptop** — install the CLI (above) and run `fabro server start`. Workflows pause when your laptop sleeps.
- **On a host (self-hosted)** — deploy the Docker image with `docker compose` or any cloud container service (ECS, Cloud Run, Kubernetes). See [Self-host with Docker](https://docs.fabro.sh/administration/self-host-docker).
One-click managed alternative for the same Docker image:
[](https://railway.com/deploy/UcEy5m?referralCode=E5TucU&utm_medium=integration&utm_source=template&utm_campaign=generic)
See the [deployment overview](https://docs.fabro.sh/administration/deployment) for the full picture.
---
## Contributing to Fabro
Outside contributions are welcome! Whether it's a bug fix, a new feature, documentation, or a typo -- we'd love your help making Fabro better.
- **Bug fixes and small improvements** -- Send a pull request directly.
- **Larger features or changes** -- Open a [GitHub Issue](https://github.com/fabro-sh/fabro/issues) or start a [Discussion](https://github.com/fabro-sh/fabro/discussions) first so we can align on the approach.
- **Questions** -- Open a Discussion or email [bryan@qlty.sh](mailto:bryan@qlty.sh).
See [CONTRIBUTING.md](CONTRIBUTING.md) for build instructions and development workflow.
---
## Help or Feedback
- [Bug reports](https://github.com/fabro-sh/fabro/issues) via GitHub Issues
- [Feature requests](https://github.com/fabro-sh/fabro/discussions) via GitHub Discussions
- Email [bryan@qlty.sh](mailto:bryan@qlty.sh) for questions
- See [CONTRIBUTING.md](CONTRIBUTING.md) for build instructions and development workflow
---
## License
Fabro is licensed under the [MIT License](LICENSE.md).
