Files
baoyu-skills/skills/baoyu-image-gen/scripts/providers/zai.test.ts
T
Jim Liu 宝玉 2c800c670a [codex] Refactor skills into focused references (#135)
* docs: add runtime-neutral User Input Tools convention across skills

Introduce docs/user-input-tools.md as the author-side canonical source
and inline the tool-selection rule into every SKILL.md that prompts
the user. Also add Skill Self-Containment and User Input Tools sections
to CLAUDE.md and the copy-verbatim template to docs/creating-skills.md,
so skills stay portable across Claude Code, Codex, Hermes, and other
runtimes.

* feat: runtime-neutral image generation convention across skills

- Introduce inline `## Image Generation Tools` rule in every rendering SKILL.md so skills delegate backend choice instead of hard-coding one; author-side canonical copy lives in docs/image-generation-tools.md.
- Add `## Reference Images` support (`--ref`, frontmatter `references:` with direct/style/palette usage) to all seven image-rendering skills.
- Move build-batch.ts (with ref propagation into batch JSON) from baoyu-article-illustrator to baoyu-imagine so non-backend skills don't own backend-specific scripts; update baoyu-image-gen stub in sync and relax the CLAUDE.md deprecation note accordingly.

* refactor: slim heavy SKILL.md files and move detail to references/

Trim the four largest active skills and move presets, option tables, and
confirmation scripts into per-skill references/ so SKILL.md stays focused
on the decision flow.

- baoyu-slide-deck: 761→258, + styles-gallery.md, confirmation.md
- baoyu-image-cards: 657→280, + gallery.md, confirmation.md
- baoyu-post-to-wechat: 518→267, + multi-account.md, api-setup.md
- baoyu-imagine: 500→230, + providers/, usage-examples.md

Also un-deprecate baoyu-image-gen (drop stub warning) so it stays functional
alongside baoyu-imagine, and update CLAUDE.md to reflect that both
superseded skills are kept in sync rather than stubbed.

* refactor: slim four medium SKILL.md files into references/

Continue the P2 pattern on the next tier of skills — move option catalogs,
per-provider/adapter detail, and repeated EXTEND.md path boilerplate into
their own references so SKILL.md stays focused on the decision flow.

- baoyu-comic: 380→297 (art/tone/preset tables → auto-selection.md;
  Step 7 expanded detail → workflow.md)
- baoyu-infographic: 312→207 (layouts/styles/combinations/keywords →
  gallery.md; ASCII box tables → markdown tables)
- baoyu-format-markdown: 376→296 (title + summary generation →
  title-summary.md; ASCII box tables → markdown tables)
- baoyu-url-to-markdown: 334→169 (quality gate + recovery →
  quality-gate.md; adapters + media download → adapters.md)

* chore: sync deprecated skills with their replacements

Per project policy, baoyu-xhs-images and baoyu-image-gen are kept
functional alongside the active skills they were superseded by. Sync
their SKILL.md bodies and references/ to the slimmed baoyu-image-cards
and baoyu-imagine versions respectively, so cross-cutting fixes stay
consistent. Only the frontmatter (name, description, version, homepage)
differs — content is identical.

- baoyu-xhs-images: 657→281 (synced with baoyu-image-cards + new
  confirmation.md, gallery.md)
- baoyu-image-gen: 408→231 (synced with baoyu-imagine + new
  providers/, usage-examples.md)

* refactor: collapse EXTEND.md boilerplate into priority tables

Replace the dual bash/powershell existence-check blocks and ASCII box
art with a single markdown priority table across nine SKILL.md files.
The runtime-neutral phrasing removes shell-specific snippets without
losing the priority semantics.

* fix: address refactor-skills branch review findings

- image-gen: restore EXTEND.md paths to baoyu-image-gen (were pointing at
  baoyu-imagine) and mark descriptions of both deprecated skills as
  [Deprecated].
- xhs-images: sync neon/warm palettes with image-cards to add the
  "do not render color names/hex as visible text" safety sentence.
- infographic: restore Layout Gallery (21), Style Gallery (21),
  Recommended Combinations, and Keyword Shortcuts inline (previous
  refactor split them out but SKILL.md still depended on them), and add
  the missing references/config/first-time-setup.md + preferences-schema.md.
- image-cards / xhs-images / slide-deck / format-markdown: restore the
  sections that got over-slimmed into references/ (galleries, presets,
  dimensions, auto-selection, style x layout matrix, title/summary flow)
  and drop the now-empty shell files.
- docs/image-generation-tools.md: note that backend skills themselves
  (baoyu-imagine, baoyu-image-gen, baoyu-danger-gemini-web) are exempt
  from the ## Image Generation Tools section requirement.

* feat(image-gen): sync Z.AI GLM-Image provider from baoyu-imagine

Add Z.AI as a full provider in the deprecated baoyu-image-gen skill so
it stays in sync with baoyu-imagine's provider list.

- new scripts/providers/zai.ts + zai.test.ts (verbatim port; test
  factory trimmed to match image-gen's CliArgs shape).
- types.ts: "zai" added to Provider union and default_model.
- main.ts: rate-limit defaults, provider help text, env var help,
  --provider validation, loadProviderModule, detectProvider
  auto-detect chain, getModelForProvider, YAML parser allow-lists.
- references/config: Q2e Z.AI model question + zai slot in the
  preferences schema and batch.provider_limits.

Scope is intentionally limited to the Z.AI chain; unrelated drift
between image-gen and imagine (OpenAI image-API dialect,
aspectRatioSource, imageSizeSource) is left alone.

* docs: align inline-convention wording and note backend-skill exemption

- docs/user-input-tools.md: fix stale "links here" wording so it
  matches the inline convention already enforced everywhere else.
- CLAUDE.md §Image Generation Tools: inline the backend-skill
  exemption so readers don't need to cross-reference
  docs/image-generation-tools.md.
2026-04-19 00:48:44 -05:00

181 lines
5.1 KiB
TypeScript

import assert from "node:assert/strict";
import test, { type TestContext } from "node:test";
import type { CliArgs } from "../types.ts";
import {
buildRequestBody,
buildZaiUrl,
extractImageFromResponse,
getDefaultModel,
getModelFamily,
parseAspectRatio,
parseSize,
resolveSizeForModel,
validateArgs,
} from "./zai.ts";
function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
return {
prompt: null,
promptFiles: [],
imagePath: null,
provider: null,
model: null,
aspectRatio: null,
size: null,
quality: null,
imageSize: null,
referenceImages: [],
n: 1,
batchFile: null,
jobs: null,
json: false,
help: false,
...overrides,
};
}
function useEnv(
t: TestContext,
values: Record<string, string | null>,
): void {
const previous = new Map<string, string | undefined>();
for (const [key, value] of Object.entries(values)) {
previous.set(key, process.env[key]);
if (value == null) {
delete process.env[key];
} else {
process.env[key] = value;
}
}
t.after(() => {
for (const [key, value] of previous.entries()) {
if (value == null) {
delete process.env[key];
} else {
process.env[key] = value;
}
}
});
}
test("Z.AI default model prefers env override and otherwise uses glm-image", (t) => {
useEnv(t, {
ZAI_IMAGE_MODEL: null,
BIGMODEL_IMAGE_MODEL: null,
});
assert.equal(getDefaultModel(), "glm-image");
process.env.BIGMODEL_IMAGE_MODEL = "cogview-4-250304";
assert.equal(getDefaultModel(), "cogview-4-250304");
});
test("Z.AI URL builder normalizes host, v4 base, and full endpoint inputs", (t) => {
useEnv(t, { ZAI_BASE_URL: "https://api.z.ai" });
assert.equal(buildZaiUrl(), "https://api.z.ai/api/paas/v4/images/generations");
process.env.ZAI_BASE_URL = "https://proxy.example.com/api/paas/v4/";
assert.equal(buildZaiUrl(), "https://proxy.example.com/api/paas/v4/images/generations");
process.env.ZAI_BASE_URL = "https://proxy.example.com/custom/images/generations";
assert.equal(buildZaiUrl(), "https://proxy.example.com/custom/images/generations");
});
test("Z.AI model family and parsing helpers recognize documented formats", () => {
assert.equal(getModelFamily("glm-image"), "glm");
assert.equal(getModelFamily("cogview-4-250304"), "legacy");
assert.deepEqual(parseAspectRatio("16:9"), { width: 16, height: 9 });
assert.equal(parseAspectRatio("wide"), null);
assert.deepEqual(parseSize("1280x1280"), { width: 1280, height: 1280 });
assert.deepEqual(parseSize("1472*1088"), { width: 1472, height: 1088 });
assert.equal(parseSize("big"), null);
});
test("Z.AI size resolution follows documented recommended ratios and validates custom sizes", () => {
assert.equal(
resolveSizeForModel("glm-image", makeArgs({ aspectRatio: "16:9", quality: "2k" })),
"1728x960",
);
assert.equal(
resolveSizeForModel("cogview-4-250304", makeArgs({ aspectRatio: "4:3", quality: "normal" })),
"1152x864",
);
assert.equal(
resolveSizeForModel("glm-image", makeArgs({ size: "1568x1056", quality: "2k" })),
"1568x1056",
);
const uncommon = resolveSizeForModel(
"glm-image",
makeArgs({ aspectRatio: "5:2", quality: "normal" }),
);
const parsed = parseSize(uncommon);
assert.ok(parsed);
assert.ok(parsed.width % 32 === 0);
assert.ok(parsed.height % 32 === 0);
assert.ok(parsed.width * parsed.height <= 2 ** 22);
assert.throws(
() => resolveSizeForModel("glm-image", makeArgs({ size: "1000x1000", quality: "2k" })),
/between 1024 and 2048/,
);
assert.throws(
() => resolveSizeForModel("glm-image", makeArgs({ size: "1280x1260", quality: "2k" })),
/divisible by 32/,
);
assert.throws(
() => resolveSizeForModel("cogview-4-250304", makeArgs({ size: "2048x2048", quality: "2k" })),
/must not exceed 2\^21 total pixels/,
);
});
test("Z.AI validation rejects unsupported refs and multi-image requests", () => {
assert.throws(
() => validateArgs("glm-image", makeArgs({ referenceImages: ["ref.png"] })),
/text-to-image only/,
);
assert.throws(
() => validateArgs("glm-image", makeArgs({ n: 2 })),
/single image per request/,
);
});
test("Z.AI request body maps skill quality and resolved size into provider fields", () => {
const body = buildRequestBody(
"A cinematic science poster",
"glm-image",
makeArgs({ aspectRatio: "4:3", quality: "normal" }),
);
assert.deepEqual(body, {
model: "glm-image",
prompt: "A cinematic science poster",
quality: "standard",
size: "1472x1088",
});
});
test("Z.AI response extraction downloads the returned image URL", async (t) => {
const originalFetch = globalThis.fetch;
t.after(() => {
globalThis.fetch = originalFetch;
});
globalThis.fetch = async () =>
new Response(Uint8Array.from([1, 2, 3]), {
status: 200,
headers: { "Content-Type": "image/png" },
});
const image = await extractImageFromResponse({
data: [{ url: "https://cdn.example.com/glm-image.png" }],
});
assert.deepEqual([...image], [1, 2, 3]);
await assert.rejects(
() => extractImageFromResponse({ data: [{}] }),
/No image URL/,
);
});