refactor(record): merge the three image record loops into one script (#1541)

The app layer recorded its pushes with record_app_image_tag.py and the base and runtime layers with record_runtime_image.py, and the two had drifted: three copies of _git / _gh_api, two composite actions whose interpreter dance was byte-identical, and two of the three wheel-info copies.

One entry point now covers all three: scripts/record_image.py –layer {base,runtime,app}. What each layer commits is genuinely different (a changelog date for base/runtime; the status matrix image_tag plus a docs pipeline re-run for app), so the layer body stays separate and only the shared mechanics — the Harbor push_time query, the rebase-and-retry push onto a per-record branch, the review-gated PR — move into scripts/ record_common.py. gen_wheel_info.py imports the same module instead of carrying a third copy.

The two composite actions collapse into .github/actions/record-image/, which all five image workflows now use.

Co-authored-by: flagos-ci noreply@flagos.net

build-infra

FlagOS container image build infrastructure. This repo defines and builds the base images — a vendor’s SDK and toolchain on an OS base — that FlagOS runtime images are built on.

📖 Documentation: https://flagos-ai.github.io/release-info/

The docs (supported backends, per-image environment, dependencies) are generated from configs.yaml + base/, so they can’t drift from the source.

Layout

Path	What
`configs.yaml`	Source of truth: per-backend deps, versions, image env
`base/<vendor>-<backend>`	Base image containerfiles
`scripts/build_base.py`	Build a base image (reads OCI labels + registry)
`scripts/generate_matrix.py`	Emit the CI build matrix from `configs.yaml`
`scripts/build_runtime.py`	Build a runtime image
`.github/build-config.yml`	Global build config: registry + per-backend runners
`runtime/`	Runtime Containerfile + per-image readmes
`packaging/flagtree/`	Low-glibc FlagTree wheel builders
`docs/`	Hugo docs site + data-generation scripts

Quick start

Build a base image locally:

python scripts/build_base.py nvidia-cuda12.8 --dry-run   # preview
python scripts/build_base.py nvidia-cuda12.8 --push      # build + push

In CI, base images are built on demand via the Base Image Build (manual) workflow (workflow_dispatch) — pick a backend (or all) and whether to push.

To add a vendor/backend, see the onboarding guide.