The site.yml workflow deploys on push to main, so the site only goes live once
site/ is on main. Bring site/index.html + icons + the workflow so a GitHub
Pages deploy (Settings -> Pages -> Source: GitHub Actions) publishes it at
justvugg.github.io/colibri.
Refs #424
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
GitHub Actions shells are format strings; the bare 'msys2' string made the
v1.0.0 tag build fail before its first step ('Invalid shell option'). Same
invocation ci.yml already uses. path-type: inherit so the Package step can
reach the runner's 7z.exe.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
- c/version.py: single source of truth (__version__ = "1.0.0")
- coli: reads version.py, banner shows dynamic version, --version flag
- .github/workflows/release.yml: tag push triggers cross-platform build
(Linux x86_64, macOS ARM64, Windows x86_64) and creates a GitHub
Release with packaged binaries + changelog notes
- CHANGELOG.md: v1.0.0 baseline documenting all shipped features
To cut a release:
1. bump c/version.py
2. add a CHANGELOG section
3. git tag v1.0.0 && git push --tags
engine-cuda-syntax compiles backend_cuda.cu with nvcc's GCC host on Linux, and
check.yml's windows job is MinGW/UCRT64 CPU-only by design (#140). Neither
exercises nvcc's MSVC host — the only host compiler nvcc accepts on Windows — so
`make cuda-dll` and `make glm CUDA_DLL=1` are currently built by nothing.
The gap has already cost real bugs, all compile-time, all catchable without a GPU:
- #158: MSVC rejects the GCC-style -Xcompiler=-Wall,-Wextra ("D8021 invalid
numeric argument '/Wextra'"), CUDA_HOME/NVCC defaults were unresolvable, and
the kernel test used POSIX setenv. `make cuda-dll` was unbuildable as shipped.
- #314: CUDA_HOME containing spaces — the CUDA installer's default layout. This
job installs to exactly that path, so it reproduces the condition by default.
Two Windows-specific facts the job encodes, both verified by making it fail first:
- sub-packages needs "cudart", not just "nvcc": cuda-dll *links* the runtime, and
on Windows the headers/import lib are a separate installer component. With
'["nvcc"]' alone it dies at `#include <cuda_runtime.h>` — the Linux syntax job
never notices because it only compiles.
- runs-on is pinned to windows-2022: windows-latest now ships Visual Studio 18
(MSVC 14.5x) and CUDA's crt/host_config.h hard-errors on any host newer than
VS 2022. That is a real constraint on every Windows CUDA user today, so the pin
tracks what the toolkit supports rather than papering over it with
-allow-unsupported-compiler.
Build-only on purpose: hosted runners have no NVIDIA device, so this proves the
Windows+MSVC CUDA build stays buildable, not that the kernels or the DLL loader
behave on real silicon — that still needs hardware (#157). A check that overclaims
buys the false confidence the engine-cuda-syntax comment already warns about.
Verified green on a fork before proposing:
https://github.com/lEWFkRAD/colibri/actions/runs/29524302993
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
@ZacharyZcR's workflow, already green on dev (78c77bf): engine + C suite,
web build + vitest, python suite, and a real CUDA syntax check.
Only the workflow file is cherry-picked here — main's engine code stays at
54cfe56 and nothing else from dev comes along. main is where the checks are
worth the most and where they were missing entirely.
Includes the two fixes the first run exposed: the pinned action's version
table stops at 12.6.2 (12.6.3 failed the install), and `nvcc ... | head -40`
took its exit status from head, so the job could never fail.
Co-Authored-By: ZacharyZcR <#144>
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Two independent defects in the CUDA syntax job, both caught on its first run.
1. `cuda: '12.6.3'` — Jimver/cuda-toolkit@v0.2.19's version table stops at
12.6.2, so the install step died with "Version not available: 12.6.3"
before nvcc was ever invoked. One digit.
2. `nvcc ... 2>&1 | head -40` — a pipeline exits with the status of its LAST
command, so head's 0 masked every nvcc error. The job printed "CUDA syntax
check passed" unconditionally: it could not fail. Defect 1 is why we found
out, since it broke the step *before* the pipe.
The second one is the one that matters. backend_cuda.cu is compiled by nothing
else in this repo — no local build, no test — so this job is the only thing
standing between a CUDA change and a user's GPU. A check that cannot fail is
worse than no check: it buys false confidence in exactly the file that most
needs the real thing. #298 spent a night debugging CUDA against no oracle at
all; this job is supposed to be that oracle.
It is also, precisely, the disease of the week in YAML form: a signal that
measures its own intention rather than the thing it claims to measure. See the
`~335 GB I/O saved` counter that counted dropped experts instead of bytes not
read (#303), and `route_agree: 95.3%` cited as "quality preserved" when it
only measures which experts coincide.
The other three jobs (engine, web, python) passed on the first run.
Co-Authored-By: ZacharyZcR <#144>
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The repo's own dependency-free gate, on the three claimed platforms, for
every PR and push to main/dev. The windows job is the one that would have
caught #68/#137 pre-merge. No CUDA, no Metal, no model downloads in v1.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Four jobs, all fast, all free on public repos:
- engine: make glm + make test-c (Linux, CPU, native arch)
- engine-cuda-syntax: nvcc compile-only check (no GPU needed, catches
backend_cuda.cu syntax/type errors before they reach a real machine)
- web: npm ci + build + vitest (Node 22, cached deps)
- python: unittest discover on c/tests/test_*.py (Python 3.12)
Triggers on push/PR to dev and main. No 20-minute pipelines — the whole
matrix finishes in under 3 minutes on GitHub-hosted runners.
JustVugg