open-refinery 0.13.13

A factory for producing artifacts under governance — provenance, ownership, authorization, and an append-only audit trail on every output.

open-refinery

An open factory to shine light into the dark.

open-refinery is a self-hosted control plane for AI-driven software work. Teams define the processes their work moves through — a kanban board, a vulnerability-remediation doctrine, whatever fits — connect their repositories, and ship work through those processes. Every step is owned, authorized, recorded, and queryable. It runs "dark" (lights-out automation) but stays "open": nothing happens without an attributable, auditable trail.

What it is

The platform layer between your harnesses (agents, scripts, CI — the in-process, app-owned side) and your targets (repos, models, tools). It governs how work reaches those targets: identity and roles, authorization, provenance, an append-only audit trail, oversight gates, and metrics. Install it on any VPS with pip install and one command; manage everything from the web dashboard.

What it does

• Ships work through customizable processes — ordered steps with feedback loops (board or doctrine archetypes).
• Puts a human-oversight dial on every process (L0 manual → L4 fully dark), with approvals and quality-gate attestations where you want them.
• Records a complete, attributed audit trail — who did what, to which work item, with what inputs — and derives metrics (WIP, lead time, throughput) from it.
• Enforces ownership: developers see their own work; platform sets org-wide standards; admins audit everything.

What it doesn't do

• It is not a CI runner, a build system, or an agent framework — it governs work, it doesn't execute your builds or own your prompts.
• It is not multi-tenant SaaS. One install serves one organization, self-hosted and single-tenant by design.
• It doesn't hide anything: no opaque automation, no un-owned actions.

Philosophy & goals

Automation you can't audit isn't trustworthy. open-refinery's goal is to make lights-out software work safe to trust by making it legible — every production authorized, owned, provenanced, and logged, with human oversight configurable to each team's philosophy. Minimal to run (one process, SQLite, env-light), everything managed through the UI, and completely open source.

The orchestrator is a queue, not an agent. Work advances through processes via deterministic code (the transition loop over a durable store), not an LLM deciding what happens next. That determinism is the point: it's cheap (no model call to move a step), reproducible, and auditable — the agent's judgment is confined to the work inside a step, while sequencing stays plain software. It also keeps work items partitionable: independent items advance through the queue without intercommunication, which — per Brooks in The Mythical Man-Month — is the condition under which adding effort actually adds throughput, whereas work requiring communication incurs overhead that a central agent bottleneck would impose.

Status: 0.13.0. Roles are admin-configurable — a seeded developer/platform/admin ladder that admins extend and re-rank via the UI (/roles); rank comparisons, invitations, and approval chains resolve against it. Packs — opt-in, role-gated starter bundles of guidance (enable via the CLI or the Packs tab); the base install seeds almost nothing. Policies are authored harness artifacts (rule / skill / command / agent) with a strict override lock (default an admin setting). Configuration lives in the database, not the env — OAuth provider creds are UI-managed (platform/admin) and encrypted at rest, so only SECRET_KEY is required in the environment. Atop role-gated invitations, structured output, the async approval queue + chained approvals, the configurable risk profile, the executor, policy governance, targets / routing / quotas, integrations, oversight, metrics, and a full audit trail. Self-hosted API docs at /api-docs. See CHANGELOG.md.

Quickstart

Requires Python 3.11+. SQLite ships with Python — there is no separate database to install.

pip install open-refinery        # or: uv pip install open-refinery
open-refinery serve              # server + dashboard on port 8000

Open http://your-host:8000 — on a fresh instance the dashboard walks you through creating the first admin (no CLI needed), then signs you in. From there, manage repos, processes, work, oversight, and the audit trail. The UI (React + shadcn/ui, light/dark/auto themes) is bundled in the package — no Node to run.

Prefer the CLI to seed the admin? open-refinery create-admin --email [e-mail] still works.

Background it on a VPS however you like — &, nohup, screen, tmux, or your process manager:

open-refinery serve --port 9000 &                # or: PORT=9000 open-refinery serve
curl localhost:9000/health                       # {"status": "ok"}

Using the API

Authenticate every request with the admin token from create-admin:

TOKEN=<paste the token>
H="Authorization: Bearer $TOKEN"

# register a repository (a repo = a project, whatever the code architecture)
curl -s -H "$H" localhost:9000/repositories \
  -d '{"name":"my-app","git_url":"[e-mail]:me/my-app.git"}'

# define a process: steps + oversight (dark = lights-out; assisted needs approval)
curl -s -H "$H" localhost:9000/processes \
  -d '{"name":"remediate","archetype":"doctrine",
       "stages":["detect","triage","patch","verify","close"],
       "transitions":[["detect","triage"],["triage","patch"],["patch","verify"],
                      ["verify","close"],["verify","patch"]],
       "oversight":"supervised","gates":["close"]}'

# ship work through it, then move it a step (approve=true when a gate needs sign-off)
curl -s -H "$H" localhost:9000/work-items \
  -d '{"repo_id":"<repo>","process_id":"<proc>","title":"CVE-1234"}'
curl -s -H "$H" localhost:9000/work-items/<item>/transition -d '{"to":"triage"}'

# read the audit trail — every move, owned and attributed
curl -s -H "$H" "localhost:9000/events?subject=<item>"

Config is env-only, all optional: PORT (or --port), DATABASE_URL (sqlite:///open-refinery.db default), LOG_LEVEL.

Sign in with GitHub (optional)

Set these and the dashboard shows a "Sign in with GitHub" button:

export GITHUB_CLIENT_ID=...       # from your GitHub OAuth App
export GITHUB_CLIENT_SECRET=...
export APP_BASE_URL=https://or.example.com   # optional; used to build the callback

Register the OAuth App's callback as <APP_BASE_URL>/auth/github/callback. A GitHub login is accepted only when its verified primary email matches an existing user — provision accounts first (an admin creates them in the UI); unknown emails are denied. (Roadmap: OAuth client id/secret move to DB settings, editable in the UI by platform/admin — so only SECRET_KEY is required in the environment; everything else lives in the database.) API/CI accounts keep using tokens.

Library

open-refinery is also an embeddable core — the same governed-production loop without the server:

from open_refinery import Factory

factory = Factory()

@factory.recipe("upper")
def upper(text: str) -> str:
    return text.upper()

artifact, record = factory.produce("upper", actor="ian", text="hello")

open-refinery demo prints one such record.

Pillars

Pillar	Where it lives
Authorization	Authorizer (AllowAll, AllowList) — checked before produce
Provenance	Record — recipe, actor, timestamp, input/output digests
Ownership	owner on every record (defaults to the actor)
Auditability	AuditSink (MemorySink, JsonlSink) — append-only trail
Logging	stdlib logging, logger name open_refinery
Oversight	Per-process autonomy levels L0–L4; gated steps need recorded approvals
Observability	GET /metrics — WIP, event counts, per-actor activity, lead times over the audit trail
Governance	(roadmap) policy layer that constrains what may be produced

Durable audit trail

from open_refinery import Factory, JsonlSink

factory = Factory(audit=JsonlSink("audit.jsonl"))

Each production appends one JSON line — a replayable record of who produced what, from which inputs, and when.

Development

make install            # backend: uv sync --extra dev
make test               # uv run pytest
make serve              # run the server locally
make help               # list all tasks

open-refinery seed      # optional: load EXAMPLE data + login tokens (never auto-run)

Frontend (dashboard) lives in frontend/ — React + TypeScript + Vite + Tailwind

• shadcn/ui, built with bun:

make ui-dev             # Vite dev server (proxies API to :8000)
make ui                 # build the SPA into the package
make dist               # build UI + wheel (the wheel bundles the SPA)

The build step is release-time only; end users never need bun/node.

For a full fresh-VPS walkthrough — install, background the server, create the admin, ports, and HTTPS/TLS on a public host — see USER_GUIDE.md.

See also PLAN.md, CONTRIBUTING.md, and docs/ARCHITECTURE.md.

Credits

The harness-vs-platform framing that shapes open-refinery's design — the platform as the out-of-process governance layer that harnesses call through — draws on Traefik Labs' mental model: Harness engineering vs platform engineering.

The deterministic-queue orchestrator — the orchestrator is the queue (plain code), not an agent, for cost, determinism, and parallelism — is inspired by Mike Piccolo's Loop Engineering.

The stance that decomposition belongs in deterministic orchestration rather than agent-spawned sub-agents (sub-agent delegation is a harness concern, not the platform's) draws on Anton Vinogradov's "You don't need sub-agents".

License

MIT © Ian Johnson