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* fix(make-pdf,design): real TOC page numbers and anchors; design models move to gpt-5.5 + gpt-image-2 (#2903, #2807) * ci: pin every action to a SHA, Scorecard, checksummed Bun, scoped Codex CLI in the CI image, macOS named-regressions job (#1948, #1706, #1997) * fix(cso,browse): Windows/macOS lease identity, retention skips bad runs, truthful 'not assessed' reports, env.kv false positive, Windows browse spawn fixes (#2894, #2912, #2048, #2637, #2805) * fix(outside-voice): one Codex model precedence for probe and dispatch, bounded timeouts with KILL escalation, probe cache identity, guarded mktemp, skills hidden in nested Codex (#2776, #2914, #2787, #2881, #2847) * feat(setup): install registry, ./setup --status, staged activation, per-scope migrations, host tiers and conformance kit, OpenCode/Hermes fixes, Copilot CLI (experimental), disabled_skills, slimmer CLAUDE.md (#1925, #2879, #2347, #2338, #2626, #2629, #2825, #2015, #393, #1206, #2096) Co-authored-by: Andrey Esipov <61357035+andrey-esipov@users.noreply.github.com> Co-authored-by: Matthew Williams <5863886+ridermw@users.noreply.github.com> Co-authored-by: Rocky Wu <92764750+lolisaigao1234@users.noreply.github.com> * fix(preamble): skills start in worktree-isolated Claude Code sessions — one literal skill-start line, context-recovery helper, no eval in skill blocks, $N token tripwire, honest plan-mode precedence (#2763, #2896, #2851) * fix(setup): per-install renders for renamed, vendored and custom-config installs, space-safe alias roots, per-host /cso launcher path (#1882, #2906) * test: free tests never write the real HOME (home-write tripwire), no orphaned browse daemons, symlinked-TMPDIR (macOS) fixes, gbrain-on-PATH isolation (#2895, #2816, #2829, #2841, #2982, #2911, #2909, #2908, #2910) * chore: integrate wave follow-ups — regenerate all hosts, README model docs, TODOS, touchfiles, duration seeds, Bun 1.3 telemetry test fix, replay fixtures pinned to their recorded bytes * v1.91.14.0: release metadata * test(browse): group-kill cleanup falls back to the leader when macOS returns EPERM for a live group * ci: Codex login steps run under bash (the CI container's default sh rejects pipefail) * fix: full-suite repairs — private state roots for 7 real-HOME writers, truthful home-guard attribution with --attribute-home, gstack-paths shim in ship-hook fixtures, Copilot in team-init probes, test-of-test detector, cookie review fixture pinned to the approved excerpt * fix(windows): LF for Dockerfiles, normalized home-guard exclusions, path.relative fixture containment, ship push test spawn timeouts * test(design-detect): widen the whole-scan budget test's timing margins so a loaded macOS runner can't time out the single-batch call * fix(evals): qa protocol names defined for the judge, async PTY judge so overlapping sessions keep their cleanup deadline, bws setup cases use the standard JUDGE_MS tier * test(pty): the non-blocking judge case is POSIX-only (its fake judge is a shebang script, like the PTY harness it covers) * test(evals): ship-coverage-audit names absolute skill paths, uses Read, and skips the Step 7 artifact nothing consumes (removes the mechanism behind 3 of 4 historical timeouts) * test: deflake terminal-agent concurrent startup (write the placeholder record before spawning, like the product) and qa-evidence resumed pipe (barrier on a full high-water mark instead of a sleep) * fix(design): daemon log stream handles open errors instead of crashing the daemon; shutdown test awaits the stubbed exit * test(evals): skillify checks the product's resolved state root (no GSTACK_HOME bypass), negative cases check every root; tpa shims live outside the agent's cwd and answer consistently * test(evals): coverage-audit detector splits parallel columns at │ rails and [+] groups; coverage prompts name absolute skill paths; TODOs from the gate eval census * fix(plan-eng-review): scope gate always sends the menu (no headless 'Scope pending' exit); PTY harness ends idle turn-ends and API-error panels promptly with a precise diagnostic * test(evals): one position-bound coverage-read rule credits read-only && chains (labels, context ranges, git displays in either order) and still rejects forged output * fix(ship): documentation section has one saved source inserted by cat (never retyped); spawned-marker evidence is the child output; refreshed codex/factory ship goldens * test(docsync): the byte-exact insert positive is POSIX-only (the bash-command observer refuses backslash paths by design) * test(evals): plan-design-with-ui focus-title rule accepts the comma-less 'dimensions or focus' wording (replayed on the captured CI run, negative controls kept) * fix(qa-callers): exploratory preflight says the scope/method Reads come after exploratory.md; design-review scan check credits an executed scan proven by one engine run over the changed files --------- Co-authored-by: Andrey Esipov <61357035+andrey-esipov@users.noreply.github.com> Co-authored-by: Matthew Williams <5863886+ridermw@users.noreply.github.com> Co-authored-by: Rocky Wu <92764750+lolisaigao1234@users.noreply.github.com>
108 lines
4.7 KiB
TypeScript
108 lines
4.7 KiB
TypeScript
/**
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* The OpenAI models the design binary calls: one place, one override (#2807).
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*
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* Two call types, each with its own default:
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* - "image": Responses API (`/v1/responses`) orchestrator driving the
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* hosted `image_generation` tool — generate, variants, iterate, evolve.
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* - "vision": Chat Completions (`/v1/chat/completions`) screenshot/mockup
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* analysis — check, diff, memory, design-to-code, evolve's analysis step.
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*
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* `GSTACK_DESIGN_MODEL` (named like `GSTACK_CODEX_MODEL`) replaces both.
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*
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* Defaults (checked against OpenAI's model and deprecation pages, 2026-10):
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* gpt-5.5 lists Chat Completions, image input and the Responses
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* image_generation tool, and has no announced shutdown. The tool's model is
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* pinned to gpt-image-2: an unpinned tool falls back to gpt-image-1, which
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* shuts down 2026-10-23. gpt-image-2 needs a gpt-5-class orchestrator (#1771:
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* gpt-4o + gpt-image-2 is a 400), so an override to an older model fails
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* before any request is sent, naming GSTACK_DESIGN_MODEL.
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*
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* Vision requests carry `max_completion_tokens`, never `max_tokens` (the
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* gpt-5 family rejects it), and that limit covers reasoning tokens too: each
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* call's visible-answer budget gets REASONING_HEADROOM_TOKENS on top, so a
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* reasoning model cannot spend the whole limit thinking and return nothing.
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* The limit is a cap, not a charge — only generated tokens are billed.
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*
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* `bun run design/scripts/live-model-check.ts` probes these defaults with a
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* real key (opt-in, not in any test lane).
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*/
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export const DESIGN_MODEL_ENV = "GSTACK_DESIGN_MODEL";
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export type DesignCall = "image" | "vision";
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export const DEFAULT_DESIGN_MODELS: Readonly<Record<DesignCall, string>> = {
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image: "gpt-5.5",
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vision: "gpt-5.5",
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};
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/** The image model the hosted image_generation tool runs; never omitted (the API default is gpt-image-1). */
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export const IMAGE_TOOL_MODEL = "gpt-image-2";
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/** Reasoning allowance added to every vision call's visible-answer budget. */
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export const REASONING_HEADROOM_TOKENS = 8192;
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/** The model for one call type: `GSTACK_DESIGN_MODEL` when set, else that call type's default. */
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export function designModel(call: DesignCall, env: Record<string, string | undefined> = process.env): string {
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return env[DESIGN_MODEL_ENV]?.trim() || DEFAULT_DESIGN_MODELS[call];
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}
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/** Why `orchestrator` cannot drive the IMAGE_TOOL_MODEL tool, or null when it can. */
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export function imagePairingProblem(orchestrator: string): string | null {
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if (!/^(?:gpt-4|gpt-3|chatgpt-4o)/i.test(orchestrator)) return null;
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return `${orchestrator} cannot drive the ${IMAGE_TOOL_MODEL} image_generation tool (OpenAI returns 400 for that pairing); ` +
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`set ${DESIGN_MODEL_ENV} to a gpt-5-class model such as ${DEFAULT_DESIGN_MODELS.image}, or unset it`;
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}
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/**
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* Responses API body for an image call: the image orchestrator plus the
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* image_generation tool with its model pinned. Throws (before any request)
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* when the orchestrator cannot drive that tool model.
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*/
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export function imageRequestBody(
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input: string,
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tool: { size: string; quality: string },
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extra: Record<string, unknown> = {},
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): string {
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const model = designModel("image");
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const problem = imagePairingProblem(model);
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if (problem) throw new Error(problem);
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return JSON.stringify({
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model,
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input,
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...extra,
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tools: [{ type: "image_generation", model: IMAGE_TOOL_MODEL, size: tool.size, quality: tool.quality }],
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});
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}
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/** Chat Completions body for a vision call; `visibleTokens` is the answer's budget, reasoning headroom is added. */
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export function visionRequestBody(
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messages: unknown[],
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visibleTokens: number,
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extra: Record<string, unknown> = {},
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): string {
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return JSON.stringify({
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model: designModel("vision"),
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messages,
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max_completion_tokens: visibleTokens + REASONING_HEADROOM_TOKENS,
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...extra,
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});
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}
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/**
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* Suffix for an OpenAI error message when the failure is about the model or a
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* parameter the model rejects: names the model sent and `GSTACK_DESIGN_MODEL`,
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* so a rejected override (or a retired default) says how to fix it. Empty for
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* every other failure.
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*/
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export function modelRejectionHint(status: number, body: string, call: DesignCall): string {
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if (![400, 403, 404].includes(status)) return "";
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if (!/\bmodel\b|unsupported (?:parameter|value)|not supported/i.test(body)) return "";
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const model = designModel(call);
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const source = process.env[DESIGN_MODEL_ENV]?.trim() ? `${DESIGN_MODEL_ENV}=${model}` : `the default model ${model}`;
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const what = call === "image"
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? `image-generation (Responses API, tool model ${IMAGE_TOOL_MODEL})`
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: "vision (Chat Completions)";
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return ` — OpenAI rejected ${source} for this ${what} call; set ${DESIGN_MODEL_ENV} to a model your account can use for it`;
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}
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