All 67 Dependencies
Every package fabro depends on, ranked by repo health score.
Fabro is an open source AI workflow orchestration platform built for engineers who want control over their AI coding agents without babysitting every step. Rather than watching an agent REPL or reviewing an opaque 50-file diff, Fabro lets you define the process as a Graphviz DOT graph — with branching, loops, parallelism, and human approval gates — and then executes that graph using LLM agents as the compute layer.
At its core, Fabro separates workflow definition from execution: you write a `.fabro` graph file describing stages (plan, implement, verify, simplify) and transitions, while Fabro's Rust-based server handles the state machine, checkpointing every stage to Git branches, streaming events over SSE, and exposing the full run history via a REST API and React web UI.
Fabro's multi-model routing is a key differentiator. A CSS-like stylesheet attached to the graph controls which model handles each node — route cheap tasks to fast, inexpensive models and reserve frontier models for implementation. This makes it practical to run ensemble workflows where one model generates, another critiques, and a third summarizes, all within a single graph definition.
The entire stack ships as a single Rust binary with zero runtime dependencies — no Python, no Node required to run the server. Workflows can execute locally, in Daytona cloud sandboxes with full network and filesystem isolation, or be self-hosted via Docker on any cloud container platform. All artifacts are SLSA Build Provenance attested.
