mirror of
https://github.com/JimLiu/baoyu-skills.git
synced 2026-07-13 22:29:48 +08:00
2c800c670a
* 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(drop stub warning) so it stays functional alongside baoyu-imagine, and update CLAUDE.md to reflect that both superseded skills are kept in sync rather than stubbed.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.
181 lines
5.1 KiB
TypeScript
181 lines
5.1 KiB
TypeScript
import assert from "node:assert/strict";
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import test, { type TestContext } from "node:test";
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import type { CliArgs } from "../types.ts";
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import {
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buildRequestBody,
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buildZaiUrl,
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extractImageFromResponse,
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getDefaultModel,
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getModelFamily,
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parseAspectRatio,
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parseSize,
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resolveSizeForModel,
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validateArgs,
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} from "./zai.ts";
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function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
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return {
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prompt: null,
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promptFiles: [],
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imagePath: null,
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provider: null,
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model: null,
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aspectRatio: null,
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size: null,
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quality: null,
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imageSize: null,
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referenceImages: [],
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n: 1,
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batchFile: null,
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jobs: null,
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json: false,
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help: false,
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...overrides,
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};
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}
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function useEnv(
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t: TestContext,
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values: Record<string, string | null>,
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): void {
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const previous = new Map<string, string | undefined>();
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for (const [key, value] of Object.entries(values)) {
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previous.set(key, process.env[key]);
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if (value == null) {
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delete process.env[key];
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} else {
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process.env[key] = value;
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}
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}
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t.after(() => {
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for (const [key, value] of previous.entries()) {
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if (value == null) {
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delete process.env[key];
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} else {
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process.env[key] = value;
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}
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}
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});
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}
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test("Z.AI default model prefers env override and otherwise uses glm-image", (t) => {
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useEnv(t, {
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ZAI_IMAGE_MODEL: null,
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BIGMODEL_IMAGE_MODEL: null,
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});
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assert.equal(getDefaultModel(), "glm-image");
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process.env.BIGMODEL_IMAGE_MODEL = "cogview-4-250304";
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assert.equal(getDefaultModel(), "cogview-4-250304");
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});
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test("Z.AI URL builder normalizes host, v4 base, and full endpoint inputs", (t) => {
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useEnv(t, { ZAI_BASE_URL: "https://api.z.ai" });
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assert.equal(buildZaiUrl(), "https://api.z.ai/api/paas/v4/images/generations");
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process.env.ZAI_BASE_URL = "https://proxy.example.com/api/paas/v4/";
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assert.equal(buildZaiUrl(), "https://proxy.example.com/api/paas/v4/images/generations");
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process.env.ZAI_BASE_URL = "https://proxy.example.com/custom/images/generations";
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assert.equal(buildZaiUrl(), "https://proxy.example.com/custom/images/generations");
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});
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test("Z.AI model family and parsing helpers recognize documented formats", () => {
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assert.equal(getModelFamily("glm-image"), "glm");
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assert.equal(getModelFamily("cogview-4-250304"), "legacy");
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assert.deepEqual(parseAspectRatio("16:9"), { width: 16, height: 9 });
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assert.equal(parseAspectRatio("wide"), null);
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assert.deepEqual(parseSize("1280x1280"), { width: 1280, height: 1280 });
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assert.deepEqual(parseSize("1472*1088"), { width: 1472, height: 1088 });
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assert.equal(parseSize("big"), null);
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});
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test("Z.AI size resolution follows documented recommended ratios and validates custom sizes", () => {
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assert.equal(
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resolveSizeForModel("glm-image", makeArgs({ aspectRatio: "16:9", quality: "2k" })),
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"1728x960",
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);
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assert.equal(
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resolveSizeForModel("cogview-4-250304", makeArgs({ aspectRatio: "4:3", quality: "normal" })),
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"1152x864",
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);
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assert.equal(
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resolveSizeForModel("glm-image", makeArgs({ size: "1568x1056", quality: "2k" })),
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"1568x1056",
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);
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const uncommon = resolveSizeForModel(
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"glm-image",
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makeArgs({ aspectRatio: "5:2", quality: "normal" }),
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);
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const parsed = parseSize(uncommon);
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assert.ok(parsed);
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assert.ok(parsed.width % 32 === 0);
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assert.ok(parsed.height % 32 === 0);
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assert.ok(parsed.width * parsed.height <= 2 ** 22);
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assert.throws(
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() => resolveSizeForModel("glm-image", makeArgs({ size: "1000x1000", quality: "2k" })),
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/between 1024 and 2048/,
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);
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assert.throws(
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() => resolveSizeForModel("glm-image", makeArgs({ size: "1280x1260", quality: "2k" })),
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/divisible by 32/,
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);
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assert.throws(
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() => resolveSizeForModel("cogview-4-250304", makeArgs({ size: "2048x2048", quality: "2k" })),
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/must not exceed 2\^21 total pixels/,
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);
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});
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test("Z.AI validation rejects unsupported refs and multi-image requests", () => {
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assert.throws(
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() => validateArgs("glm-image", makeArgs({ referenceImages: ["ref.png"] })),
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/text-to-image only/,
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);
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assert.throws(
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() => validateArgs("glm-image", makeArgs({ n: 2 })),
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/single image per request/,
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);
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});
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test("Z.AI request body maps skill quality and resolved size into provider fields", () => {
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const body = buildRequestBody(
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"A cinematic science poster",
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"glm-image",
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makeArgs({ aspectRatio: "4:3", quality: "normal" }),
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);
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assert.deepEqual(body, {
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model: "glm-image",
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prompt: "A cinematic science poster",
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quality: "standard",
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size: "1472x1088",
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});
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});
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test("Z.AI response extraction downloads the returned image URL", async (t) => {
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const originalFetch = globalThis.fetch;
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t.after(() => {
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globalThis.fetch = originalFetch;
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});
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globalThis.fetch = async () =>
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new Response(Uint8Array.from([1, 2, 3]), {
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status: 200,
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headers: { "Content-Type": "image/png" },
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});
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const image = await extractImageFromResponse({
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data: [{ url: "https://cdn.example.com/glm-image.png" }],
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});
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assert.deepEqual([...image], [1, 2, 3]);
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await assert.rejects(
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() => extractImageFromResponse({ data: [{}] }),
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/No image URL/,
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);
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});
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