update-model-versions
GitHub自动检测并升级已用AI模型版本,优先更新TanStack AI依赖族,验证适配器支持后提交PR。严禁添加未适配的新模型或绕过限制,确保类型检查和测试通过。
Trigger Scenarios
Install
npx skills add openstory-so/openstory --skill update-model-versions -g -y
SKILL.md
Frontmatter
{
"name": "update-model-versions",
"description": "Check whether newer versions of the AI models we already use (fal.ai image, video\/motion, audio; BytePlus Ark ids; OpenRouter text) have shipped, and open a PR bumping any genuine successor. Use when asked to \"check for model updates\", \"are our models current\", \"bump models\", or when run by the daily model-freshness routine. Bumps @tanstack\/ai* first, then bumps EXISTING models to a newer version of the same model — only ids the TanStack AI adapters already support. It does not add net-new models. Other npm dependency bumps are Dependabot's."
}
Update model versions
Our model registries are the single source of truth:
| Class | File | Export |
|---|---|---|
| Text (OpenRouter) | src/models/models.config.ts |
SCRIPT_ANALYSIS_MODELS |
| Image (fal.ai) | src/models/models.ts |
IMAGE_MODELS |
| Video / motion (fal.ai) | src/models/models.ts |
IMAGE_TO_VIDEO_MODELS |
| Audio (fal.ai) | src/models/models.ts |
AUDIO_MODELS |
| BytePlus Ark ids | src/models/models.ts |
byteplusId fields |
A model with a native BytePlus route (#1157) carries two ids under one
key: the fal endpoint id AND a byteplusId (Ark model id). A version bump
must move BOTH — bumping only the fal id silently routes Ark traffic to the
older model (and vice versa), and the pricing alias
(applyBytePlusRouteAliases) would quote the wrong rate for whichever id was
left behind.
The goal each run: bump @tanstack/ai* → detect newer model versions →
verify each is a real successor the adapters support → open a focused PR that
bumps it → leave everything green.
Never hack around TanStack AI. A model the installed adapter doesn't know
is not ready to adopt. Do not add CATALOG_LAG_MODELS (or Grok/Gemini lag)
entries, casts, or patches to force an id through — skip the model and say so
in the run summary. It gets picked up on a later run, once TanStack AI ships it.
Other npm packages stay out of scope (Dependabot).
0. Bump TanStack AI first
bun outdated '@tanstack/ai*'
If anything is behind Latest (not just Update — 0.x minors break), bump
the whole family in lockstep before looking at models: @tanstack/ai and
every @tanstack/ai-* adapter in package.json (they peer on @tanstack/ai),
plus the @tanstack/ai-devtools-core override. Then follow through:
@openrouter/sdkis hard-pinned to the exact version@tanstack/ai-openrouterdepends on — move it to the new adapter's version, orcreateAdapterstops typechecking (two SDK copies).patches/@tanstack%2Fai-grok@<version>.patchis version-pinned. On a Grok bump, check whether upstream fixed what the patch does; drop it if so, else re-create it for the new version (bun patch).bun typecheckfails incatalog-lag.test.tsfor every bridged id the new catalogs now ship — delete thoseCATALOG_LAG_MODELS/GROK_CATALOG_LAG_MODELS/GEMINI_CATALOG_LAG_MODELSentries (src/models/server/create-adapter.ts).- Read each adapter's changelog for breaking changes and fix call sites.
Gates: bun install, bun typecheck, bun lint, bun run test. Open it as
its own PR — branch auto/tanstack-ai-<@tanstack/ai version>, title
chore(deps): bump @tanstack/ai* to <version> — so a model bump never hides a
dependency break. If Dependabot (or an earlier run) already has an open PR
bumping these packages, don't open a second one: use that branch.
If the bump cascades into non-trivial breakage, open an issue instead and run
the model check against the installed versions.
Every model step below then runs on top of that branch (branch model PRs from it, base them on it), so "does the adapter support it" is answered against the newest TanStack AI.
1. Detect candidates
bun models:check # human-readable report
bun models:check --json # { ok, errorCount, hasUpdates, models[] }
scripts/check-model-updates.ts reads the registries and queries public,
unauthenticated catalogs (fal.ai /api/models, OpenRouter /api/v1/models).
BytePlus Ark ids are checked offline against the installed
@tanstack/ai-byteplus model catalog — Ark publishes no unauthenticated
catalog, so the adapter's lists are the freshness source. Everything else is
HTTP-only so it runs anywhere — no FAL_KEY or MCP needed.
Behind a proxy it routes through curl (Bun's fetch can't traverse a
TLS-intercepting proxy), so curl must be on PATH in that case.
Candidates are heuristic (same brand, higher version number, same modality, not already adopted). Treat them as leads to verify, not facts.
Check ok before trusting the result. ok: false (equivalently, a non-zero
exit code or errorCount > 0) means one or more lookups FAILED — the report is
INCOMPLETE, not "all current". Do not treat a failed run as "nothing to do":
fix connectivity and re-run. Only when ok is true does hasUpdates: false
genuinely mean every model is current — in that case, stop.
2. Verify each candidate is a genuine successor
Do not bump on the heuristic alone. For each flagged candidate decide: is this the same model, one version newer — or a different product line / tier?
fal models — prefer the fal tooling (richest signal):
- genmedia CLI (what the fal community skills use; works headless):
curl https://genmedia.sh/install -fsS | bash # once, if missing genmedia setup --non-interactive --api-key "$FAL_KEY" genmedia models --endpoint_id <candidate-id> --json # confirm it exists genmedia schema <candidate-id> --json # compare input params genmedia pricing <candidate-id> --json # cost delta - fal-ai MCP if available in this session:
search_models,get_model_schema,get_pricinggive the same data. - Fallback (zero-auth): the OpenAPI spec — a 200 means the endpoint is real:
curl -s -o /dev/null -w "%{http_code}" "https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=<id>", andhttps://fal.ai/models/<path>/llms.txtfor param specs (see AGENTS.md).
text models: confirm the candidate id resolves on
https://openrouter.ai/api/v1/models and keeps the same tier (don't turn a
-mini into a non-mini, or a pro into flash).
BytePlus Ark ids: verify against the live ModelArk docs
(docs.byteplus.com/en/docs/ModelArk/…) plus the installed adapter's
model-meta (its JSDoc records doc-vs-reality findings, e.g. per-model
resolution tiers). Ark ids end in a yymmdd snapshot date; tier suffixes
(-fast, -mini, -lite, -pro) are different products, not successors.
Two Ark-specific gotchas: a new model answers 404 ModelNotOpen until
activated in the Ark console (verify at request time, not startup), and
resolution tiers are per-model AND per-tier priced — the adapter's model-meta
and BytePlus's own pricing page have disagreed about which tiers exist (e.g.
Seedance 2.5's 1080p), so check the official rate table
(docs.byteplus.com/en/docs/ModelArk/1544106) for the tier the request
builders ask for, and confirm the rate-card entry matches THAT tier's price.
Reject a candidate when it is a different tier/variant (fast/lite/standard vs pro, lora/trainer/edit gear), a different modality, a preview/experimental build replacing a stable one, or its schema/pricing changed so much it needs product judgement. When unsure, skip it and note it in the PR body rather than guessing.
3. Apply the bump (one PR per upgrade)
Work one upgrade at a time so each PR is reviewable and revertible.
Idempotency — check first: gh pr list --state open --search "in:title model".
If an open PR or branch already covers this exact bump, skip it. Branch name:
auto/model-update-<registry-key>-<new-version> (e.g.
auto/model-update-minimax_hailuo_02-2.3).
Golden rule: change the id (and metadata), never the registry KEY. Keys
are persisted in the DB (a team's selected model) and referenced across selectors
and schemas — renaming one is a breaking migration, out of scope here.
Per class, edit and follow through:
- Text (
models.config.ts): updateid,name,description,contextWindow. If you bumpDEFAULT_ANALYSIS_MODEL's model, the constant references a key, so it's unaffected. Adapter support gate: the@tanstack/ai-openrouter(and native Grok / Gemini) adapters ship a codegen snapshot of the provider's model list. If the new id isn't in it —bun typecheckfails at thecreateAdaptercall sites — the model is not supported yet: revert the bump and skip it. Never bridge it with aCATALOG_LAG_MODELSentry. - Image (
models.tsIMAGE_MODELS): updateid,name,description,maxPromptLength. If the model has anEDIT_ENDPOINTSentry, update that endpoint id too. Confirm the new endpoint still supports the edit/reference flow if it had one. - Video / motion (
models.tsIMAGE_TO_VIDEO_MODELS): updateid+ meta, then regenerate the schemas —bun motion:codegen(writessrc/motion/server/generated/**andsrc/motion/server/endpoint-map.ts). Never hand-write motion schemas. Re-checkmaxPromptLengthagainst the new schema. - Audio (
models.tsAUDIO_MODELS): updateid+capabilities(durations, formats) from the new schema. - BytePlus-routed models (a
byteplusIdon the entry): bump thebyteplusIdin the same PR as the fal id — never one without the other. Then follow through:src/billing/byteplus-pricing.ts— the rate card is keyed by Ark model id, so the old id's entry must be replaced with the new id at the new model's advertised rate (BytePlus publishes no pricing API; read the pricing page, re-date the header comment, and note the rate is advertised-not-verified). A missed rename means Ark generations bill $0 — exactly the #1069 failure mode the card exists to prevent.src/billing/fal-cost.tsENDPOINT_STRATEGY— if the old fal endpoint ids appear there (token-billed Seedance endpoints do), rename them too.- The request builders (
build-byteplus-video-request.ts/build-byteplus-image-request.ts) read the id from the registry, but re-check their baked-in assumptions (resolution tier, watermark default, frame-vs-reference roles) against the new model's docs. - e2e fixtures live under a fal-endpoint-keyed dir and each fixture's
match.modelis the fal endpoint id, which aimock matches on — migrate them (rename dir + editmatch.model) rather than re-recording when the prompt is unchanged.
- fal pricing: model ids are pricing keys in
model_pricing(D1, seesrc/billing/server/fal-pricing-live.ts) (auto-generated). After any fal id change runbun scripts/update-fal-pricing.ts(needsFAL_KEY). If it can't run, add the new id's pricing manually via the override path documented in that script and flag it in the PR.
4. Quality gates (must pass before opening the PR)
bun typecheck
bun lint
bun run test src/models src/motion # registry + motion suites
bun run test src/billing # pricing/cost if fal pricing changed
Fix anything that breaks. If a bump cascades into non-trivial changes (schema shape changed, pricing model differs, tests need rework), stop and open an issue describing it instead of forcing a half-working PR.
5. Open the PR
git checkout -b auto/model-update-<key>-<version>
git commit -am "chore(models): bump <name> <old> → <new>"
gh pr create --title "chore(models): bump <name> <old> → <new>" --body "<body>"
PR body must include, per change: registry key, old id → new id, why it's a genuine successor, links (fal model page / OpenRouter), pricing delta, and which generated files / pricing were regenerated. End with: "🤖 Opened by the daily model-freshness routine (#792). Verify pricing & quality before merge."
Leave PRs as draft only if a quality gate is amber (e.g. pricing couldn't be auto-fetched); otherwise ready-for-review. Do not merge — a human reviews.
Version History
-
85b16bc
Current 2026-10-18 17:15
新增优先升级@tanstack/ai*依赖族的流程,包含SDK版本同步、补丁处理及类型检查修复;移除对npm包版本的扫描职责,禁止强行接入未适配模型。
- d07a9cf 2026-09-27 11:33
-
9c69ec3
2026-09-11 13:36
配置文件路径从 src/lib/ai/ 迁移至 src/models/
-
5f42c66
2026-09-02 21:22
新增对BytePlus Ark ID的支持,要求同时更新fal ID和Ark ID;增加离线检查逻辑及代理支持说明。
- 65820a4 2026-08-27 09:05


