Release Process

Open Notebook uses a flow-driven release process. Work moves from ready issues into pull requests, pull requests merge to main, and maintainers cut a version when the branch has enough validated change to ship.

This document covers both the mechanics (how to cut, build and publish) and the confidence process (how we know a release is good before users get it). It was redesigned during the v1.11.0 release (ADR-005).

Release Model

Patch releases ship backwards-compatible fixes.
Minor releases ship backwards-compatible features and improvements.
Major releases are planned with a milestone when they include breaking changes or migrations that need user coordination.
Use the in-dev-build label for changes available in development images and released for shipped work. (The released label was recreated during v1.12.0 — it had been dropped from the curated label taxonomy while this document still required it. If a label this document references is missing, recreate it rather than skipping the step.)

Normal Flow

Triage issues into ready once the scope and design are clear.
Implement each change in a focused pull request linked to the approved issue.
Merge the pull request after review and required checks pass.
Let the development build publish the v1-dev image from main.
Cut a stable release when main has a coherent set of changes ready for users — following the confidence process below.

The Confidence Process

Releases keep getting bigger; ad-hoc verification does not scale. Before cutting, run this sequence:

0. Changelog audit

Diff git log <last-tag>..main against the [Unreleased] section of the CHANGELOG. Every merged PR must be represented (entries reference the issue number when one exists, the PR number otherwise). The changelog is the input for both the test plan and the release notes — close the gaps first, via PR.

1. Risk-based test matrix

Build a matrix from the actual release diff: each change → what it can break and for whom → which bucket tests it. Pay special attention to "does the protection break legitimate use?" for security changes (e.g. an SSRF guard vs. self-hosted Ollama on localhost) and to anything a reverse proxy, an upgrade, or a big upload would exercise.

Buckets:

A — automated, high confidence, run now: full backend suite, frontend lint/tests/production build, the smoke-e2e agent (full API happy path + UI verification), targeted regression probes for the release's specific risks, dependency audit.
B — automatable with investment: decide per item whether to build the muscle now (it compounds: the image gate below started as a bucket-B item) or verify manually this once.
C — needs the release owner: real provider credentials, real TTS podcast generation, visual/UX judgment, and the final check of the pushed image.

2. The image gate — test the artifact, not the repo

A green suite on main is not a working image. Run:

make docker-build-local          # builds <version> + local tags
make release-test TAG=<new> OLD_TAG=<previous>

This runs two scenarios against real containers (scripts/release-test/):

Fresh install: empty DB → migrations on boot → in-image worker processes a source → API/frontend/nginx-proxied checks.
Upgrade: boot the published previous image, seed data, swap to the new image on the same volume → migrations apply, data survives.

Caveat: docker-build-local tags with the current pyproject.toml version — docker pull the genuine previous tag before the upgrade test so you are not comparing the new build against itself.

3. Fix loop with a re-test policy

Findings become focused PRs through the normal review flow. After each merge: the cheap suite always re-runs; smoke/image gates re-run only if the fix touches what they cover; manual verification is not repeated unless the fix touches what was manually verified. Pre-existing bugs found along the way that are not release regressions become backlog issues instead of scope creep.

Cutting A Stable Release

Confirm main is green and the confidence process above has run.
Open the cut PR: bump pyproject.toml, date the [Unreleased] section as [<version>] - <date>.
After merge: make tag.
Build and push version images via CI (it holds the registry credentials): trigger the Build and Release workflow with push_latest=false. Local make docker-push also works but requires docker login on both registries.
Verify the pushed image (bucket C, final gate): run it locally with make release-stack TAG=<version> [DUMP=<dev-data-dump>] — a browsable, isolated stack, optionally with a copy of real data — and walk the core flows in the browser.
Publish the GitHub release. A non-prerelease publication triggers the workflow again and pushes the v1-latest tags automatically.
Verify the v1-latest manifests on Docker Hub and GHCR (both arches, both variants), and mark shipped issues with released.

Communication

Release notes follow this structure (see v1.11.0 as the reference):

One-line verdict + upgrade recommendation.
Sections: Security, Features, Performance, Notable fixes.
Behavior changes for self-hosters — anything that can require a config tweak on upgrade gets an explicit callout.
Thanks — credit every contributor by handle with what they shipped (collect via git log <last-tag>..<tag> + gh pr view for handles), plus the issue reporters collectively. Never skip this section.

Announce on Discord after v1-latest is live.

Retro

Close every release by asking: what should improve in this process? Apply the accepted improvements immediately — update this document, the scripts under scripts/release-test/, and the decision log while the context is fresh.

Docker Image Publishing (reference)

Command	What it does	Updates latest?
`make docker-build-local`	Build for current platform only (tags `<version>` + `local`)	No registry push
CI Build and Release (`push_latest=false`)	Push version tags via CI credentials	❌ No
GitHub release published (non-prerelease)	CI pushes version + `v1-latest`	✅ Yes
`make docker-push` / `docker-push-latest`	Local equivalents (need `docker login`)	❌ / ✅
`make tag`	Create and push a git tag matching `pyproject.toml`	—

Platforms: linux/amd64, linux/arm64
Registries: Docker Hub + GitHub Container Registry
Image variants: regular + single-container (-single). Both are built from the same Dockerfile: regular is the default/runtime target, single is --target single
Version source: pyproject.toml
Build issues: docker builder prune, then make docker-buildx-reset

Known Gotchas

RC stack on non-default ports needs API_URL or the browser talks to host:5055 — on a dev machine that is the development API (data crossover). rc-stack.sh sets it; remember this for any custom setup.
Containerized app + host services: credentials pointing at local services (Ollama, LM Studio) need http://host.docker.internal:<port>.
SurrealDB import: OVERWRITE goes after the type keyword (DEFINE FIELD OVERWRITE …), and the exporter can leak a log line into the dump — rc-stack.sh handles both.
Multiple local SurrealDB instances: check which one the dev .env actually points at (SURREAL_URL) before exporting data.
Dev-machine ports may belong to other projects: check who owns 3000/5055/8000 (lsof -nP -iTCP:<port> -sTCP:LISTEN + the process cwd) before starting or killing anything. The frontend runs fine on an alternate port for smoke testing (PORT=3001 npm run dev) — pass the URL to the smoke agent.
Manual error-path checklist items must be validated against the code first: some "missing configuration" scenarios are deliberate fallbacks, not errors (e.g. transformation and tools defaults fall back to the chat default). Confirm the expected behavior in the provisioning code before putting "should show an error" on the bucket-C checklist.
The test suite runs against the live dev database when a developer .env is loaded. During bucket A, snapshot record counts per table before and after the suite (e.g. credentials count) — a diff means a test is leaking writes (this caught 48 leaked Test credentials in v1.12.0).

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