| name | deploy |
| description | Clarifies what “ship” means for kokoro-coreml: there is no Cloudflare-style multi-worker deploy script. Use for tagging releases, pushing the branch, coordinating with the macOS app repo, or verifying exports before handoff. Before treating a revision as releasable, run the repo’s primary checks (see git-commit / audit). Do not use when the user only wants local experiments with no remote or release intent. |
Deploy (kokoro-coreml)
Purpose
This repository is a PyTorch → Core ML conversion and model-artifact tree for
Kokoro TTS. It is not the Roast Cloudflare monorepo: there are no
pnpm deploy:* scripts or Workers/Pages pipelines here.
“Deploy” in this context means release engineering appropriate to this repo:
- Git: push branches, tags, or PRs (often via
git-push).
- Artifacts:
.mlpackage bundles under coreml/, checkpoints, and export
scripts consumed by a separate macOS app (e.g. TalkToMe).
- Verification: run
pytest (or targeted export smoke scripts) before
declaring a revision ready for downstream integration.
Default interpretation
- “Ship it” / “deploy” → confirm what the user means: push to GitHub,
cut a tag, or hand models to the app—not a cloud deploy unless they
name another system.
Pre-ship gate (recommended)
From the repository root, when a change touches Python export, Core ML, or
tests:
pytest (full test pass when tests are present).
- If the change is export-only, at minimum run the relevant
examples/ or
test_*.py scripts the guides mention.
There is no single CI workflow in .github/workflows/ for this repo yet; treat
local green tests as the main gate before pushing risky changes.
Procedure (agent)
- Read
README.md, CLAUDE.md (PyTorch → Core ML playbook), and the
relevant README/*.md guide for the subsystem (conversion, runtime,
export).
- Do not run Cloudflare/Roast deploy commands—they do not apply.
- Run Pre-ship gate before advising “ready to
ship.”
- For git remote operations, follow
git-push when the user wants push
Anti-patterns
- Copying Roast
pnpm deploy:staging / Workers steps into this repo.
- Pushing large binary or regenerated
.mlpackage changes without noting
what was regenerated and how to verify.
Related skills
git-push: commit, merge, push, chase CI when CI exists.
git-commit: post-commit pytest awareness (non-blocking heads-up).
audit: full review when the user says audit.