Files
gstack/design/scripts/live-model-check.ts
T
garrytan ec35833218 E5: GSTACK_DESIGN_IMAGE_MODEL override; the live model check always tests the defaults
The image_generation tool model gains an env override validated against a
conservative gpt-image-<version> pattern; a bad value fails before any
request and the error names the variable. Pairing and rejection hints name
the tool model actually requested. design/scripts/live-model-check.ts now
ignores GSTACK_DESIGN_MODEL and GSTACK_DESIGN_IMAGE_MODEL (and says so), so
an override cannot mask a retirement of a default, and its exit 2 (no key)
says nothing was checked.
2026-10-04 17:53:29 +00:00

121 lines
5.0 KiB
TypeScript

/**
* Live check of the design binary's OpenAI defaults (#2807, E5). It spends
* real tokens (one low-quality 1024x1024 image, one short vision answer).
*
* OPENAI_API_KEY=... bun run design/scripts/live-model-check.ts
*
* Sends exactly the request bodies the design commands send (built by
* design/src/models.ts) with the DEFAULT models: GSTACK_DESIGN_MODEL and
* GSTACK_DESIGN_IMAGE_MODEL are ignored (and named when set), so an override
* cannot mask a retirement of a default. Prints the models requested and
* returned, HTTP status, token usage and PASS/FAIL per call — never the key,
* and any key-shaped text in an error body is redacted.
* Exit 0 both pass, 1 any fail, 2 OPENAI_API_KEY unset: a skip that checked
* nothing, which a caller must record as skipped with no coverage credit.
*/
import {
DESIGN_IMAGE_MODEL_ENV,
DESIGN_MODEL_ENV,
designModel,
imageRequestBody,
imageToolModel,
visionRequestBody,
} from "../src/models";
import { receiptedFetch } from "../src/receipted-fetch";
const TINY_PNG = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkAAIAAAoAAv/lxKUAAAAASUVORK5CYII=";
const ignored = [DESIGN_MODEL_ENV, DESIGN_IMAGE_MODEL_ENV].filter((name) => process.env[name]?.trim());
for (const name of ignored) delete process.env[name];
console.log(`testing defaults: image=${designModel("image")} tool=${imageToolModel()} vision=${designModel("vision")}` +
(ignored.length ? ` (ignored: ${ignored.join(", ")})` : ""));
const key = process.env.OPENAI_API_KEY?.trim();
if (!key) {
console.log("SKIP: OPENAI_API_KEY is not set; the design model defaults were not checked (no coverage)");
process.exit(2);
}
const redact = (s: string) => s.replace(/\b(?:sk|org|proj)-[A-Za-z0-9_*.-]{4,}/g, "[redacted]").slice(0, 400);
async function post(payloadClass: string, url: string, body: string, timeoutMs: number) {
const controller = new AbortController();
const timer = setTimeout(() => controller.abort(), timeoutMs);
const started = Date.now();
try {
const res = await receiptedFetch(payloadClass, url, {
method: "POST",
headers: { Authorization: `Bearer ${key}`, "Content-Type": "application/json" },
body,
signal: controller.signal,
});
const text = await res.text();
let json: any = null;
try { json = JSON.parse(text); } catch { /* non-JSON error body */ }
return { status: res.status, ok: res.ok, json, text, ms: Date.now() - started };
} catch (err) {
return { status: 0, ok: false, json: null, text: (err as Error).message, ms: Date.now() - started };
} finally {
clearTimeout(timer);
}
}
const report = (fields: Record<string, unknown>) =>
console.log(Object.entries(fields).map(([k, v]) => `${k}=${typeof v === "string" ? v : JSON.stringify(v)}`).join(" "));
let failed = false;
let image = TINY_PNG;
// 1. Image generation: Responses API + image_generation tool.
{
let body: string;
try {
body = imageRequestBody("Draw a plain blue square on a white background.", { size: "1024x1024", quality: "low" });
} catch (err) {
body = "";
report({ call: "image", result: "FAIL", error: (err as Error).message });
failed = true;
}
if (body) {
const r = await post("live-check-image-request", "https://api.openai.com/v1/responses", body, 240_000);
const item = r.json?.output?.find((o: any) => o.type === "image_generation_call");
const pass = r.ok && typeof item?.result === "string" && item.result.length > 0;
if (pass) image = item.result;
report({
call: "image", result: pass ? "PASS" : "FAIL", status: r.status, ms: r.ms,
requested_model: designModel("image"), returned_model: r.json?.model ?? null,
tool_model: imageToolModel(), image_bytes: pass ? Buffer.from(item.result, "base64").length : 0,
...(pass ? {} : { error: redact(r.json?.error?.message ?? r.text) }),
});
failed ||= !pass;
}
}
// 2. Vision analysis: Chat Completions with an image input.
{
const body = visionRequestBody([{
role: "user",
content: [
{ type: "image_url", image_url: { url: `data:image/png;base64,${image}` } },
{ type: "text", text: "Reply with exactly one word: PASS." },
],
}], 20);
const r = await post("live-check-vision-request", "https://api.openai.com/v1/chat/completions", body, 120_000);
const choice = r.json?.choices?.[0];
const content = String(choice?.message?.content ?? "").trim();
const pass = r.ok && content.length > 0;
report({
call: "vision", result: pass ? "PASS" : "FAIL", status: r.status, ms: r.ms,
requested_model: designModel("vision"), returned_model: r.json?.model ?? null,
max_completion_tokens: JSON.parse(body).max_completion_tokens, finish_reason: choice?.finish_reason ?? null,
completion_tokens: r.json?.usage?.completion_tokens ?? null,
reasoning_tokens: r.json?.usage?.completion_tokens_details?.reasoning_tokens ?? null,
answer: content.slice(0, 40),
...(pass ? {} : { error: redact(r.json?.error?.message ?? r.text) }),
});
failed ||= !pass;
}
process.exit(failed ? 1 : 0);