[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(drop stub warning) so it stays functional alongside baoyu-imagine, and update CLAUDE.md to reflect that both superseded skills are kept in sync rather than stubbed.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.
2026-07-12 05:51:44 +08:00 · 2026-04-19 00:48:44 -05:00
parent 5b20f9a746
commit 2c800c670a
58 changed files with 3895 additions and 3269 deletions
@@ -62,6 +62,7 @@ const DEFAULT_PROVIDER_RATE_LIMITS: Record<Provider, ProviderRateLimit> = {
  jimeng: { concurrency: 3, startIntervalMs: 1100 },
  seedream: { concurrency: 3, startIntervalMs: 1100 },
  azure: { concurrency: 3, startIntervalMs: 1100 },
+  zai: { concurrency: 3, startIntervalMs: 1100 },
 };

 function printUsage(): void {
@@ -76,7 +77,7 @@ Options:
  --image <path>            Output image path (required in single-image mode)
  --batchfile <path>        JSON batch file for multi-image generation
  --jobs <count>            Worker count for batch mode (default: auto, max from config, built-in default 10)
-  --provider google|openai|openrouter|dashscope|minimax|replicate|jimeng|seedream|azure  Force provider (auto-detect by default)
+  --provider google|openai|openrouter|dashscope|minimax|replicate|jimeng|seedream|azure|zai  Force provider (auto-detect by default)
  -m, --model <id>          Model ID
  --ar <ratio>              Aspect ratio (e.g., 16:9, 1:1, 4:3)
  --size <WxH>              Size (e.g., 1024x1024)
@@ -118,6 +119,8 @@ Environment variables:
  JIMENG_ACCESS_KEY_ID      Jimeng Access Key ID
  JIMENG_SECRET_ACCESS_KEY  Jimeng Secret Access Key
  ARK_API_KEY               Seedream/Ark API key
+  ZAI_API_KEY               Z.AI API key (alias: BIGMODEL_API_KEY)
+  BIGMODEL_API_KEY          Z.AI API key alias (legacy BigModel credentials)
  OPENAI_IMAGE_MODEL        Default OpenAI model (gpt-image-1.5)
  OPENROUTER_IMAGE_MODEL    Default OpenRouter model (google/gemini-3.1-flash-image-preview)
  GOOGLE_IMAGE_MODEL        Default Google model (gemini-3-pro-image-preview)
@@ -126,6 +129,8 @@ Environment variables:
  REPLICATE_IMAGE_MODEL     Default Replicate model (google/nano-banana-pro)
  JIMENG_IMAGE_MODEL        Default Jimeng model (jimeng_t2i_v40)
  SEEDREAM_IMAGE_MODEL      Default Seedream model (doubao-seedream-5-0-260128)
+  ZAI_IMAGE_MODEL           Default Z.AI model (glm-image)
+  BIGMODEL_IMAGE_MODEL      Z.AI model alias (legacy BigModel variable)
  OPENAI_BASE_URL           Custom OpenAI endpoint
  OPENAI_IMAGE_USE_CHAT     Use /chat/completions instead of /images/generations (true|false)
  OPENROUTER_BASE_URL       Custom OpenRouter endpoint
@@ -142,6 +147,8 @@ Environment variables:
  AZURE_API_VERSION         Azure API version (default: 2025-04-01-preview)
  AZURE_OPENAI_IMAGE_MODEL  Backward-compatible Azure deployment/model alias (defaults to gpt-image-1.5)
  SEEDREAM_BASE_URL         Custom Seedream endpoint
+  ZAI_BASE_URL              Custom Z.AI endpoint (defaults to https://api.z.ai/api/paas/v4)
+  BIGMODEL_BASE_URL         Z.AI endpoint alias (legacy BigModel variable)
  BAOYU_IMAGE_GEN_MAX_WORKERS  Override batch worker cap
  BAOYU_IMAGE_GEN_<PROVIDER>_CONCURRENCY  Override provider concurrency
  BAOYU_IMAGE_GEN_<PROVIDER>_START_INTERVAL_MS  Override provider start gap in ms
@@ -243,7 +250,8 @@ export function parseArgs(argv: string[]): CliArgs {
        v !== "replicate" &&
        v !== "jimeng" &&
        v !== "seedream" &&
-        v !== "azure"
+        v !== "azure" &&
+        v !== "zai"
      ) {
        throw new Error(`Invalid provider: ${v}`);
      }
@@ -400,6 +408,7 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
          jimeng: null,
          seedream: null,
          azure: null,
+          zai: null,
        };
        currentKey = "default_model";
        currentProvider = null;
@@ -427,7 +436,8 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
          key === "replicate" ||
          key === "jimeng" ||
          key === "seedream" ||
-          key === "azure"
+          key === "azure" ||
+          key === "zai"
        )
      ) {
        config.batch ??= {};
@@ -445,7 +455,8 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
          key === "replicate" ||
          key === "jimeng" ||
          key === "seedream" ||
-          key === "azure"
+          key === "azure" ||
+          key === "zai"
        )
      ) {
        const cleaned = value.replace(/['"]/g, "");
@@ -540,9 +551,10 @@ export function getConfiguredProviderRateLimits(
    jimeng: { ...DEFAULT_PROVIDER_RATE_LIMITS.jimeng },
    seedream: { ...DEFAULT_PROVIDER_RATE_LIMITS.seedream },
    azure: { ...DEFAULT_PROVIDER_RATE_LIMITS.azure },
+    zai: { ...DEFAULT_PROVIDER_RATE_LIMITS.zai },
  };

-  for (const provider of ["replicate", "google", "openai", "openrouter", "dashscope", "minimax", "jimeng", "seedream", "azure"] as Provider[]) {
+  for (const provider of ["replicate", "google", "openai", "openrouter", "dashscope", "minimax", "jimeng", "seedream", "azure", "zai"] as Provider[]) {
    const envPrefix = `BAOYU_IMAGE_GEN_${provider.toUpperCase()}`;
    const extendLimit = extendConfig.batch?.provider_limits?.[provider];
    configured[provider] = {
@@ -625,6 +637,7 @@ export function detectProvider(args: CliArgs): Provider {
  const hasReplicate = !!process.env.REPLICATE_API_TOKEN;
  const hasJimeng = !!(process.env.JIMENG_ACCESS_KEY_ID && process.env.JIMENG_SECRET_ACCESS_KEY);
  const hasSeedream = !!process.env.ARK_API_KEY;
+  const hasZai = !!(process.env.ZAI_API_KEY || process.env.BIGMODEL_API_KEY);
  const modelProvider = inferProviderFromModel(args.model);

  if (modelProvider === "seedream") {
@@ -664,13 +677,14 @@ export function detectProvider(args: CliArgs): Provider {
    hasReplicate && "replicate",
    hasJimeng && "jimeng",
    hasSeedream && "seedream",
+    hasZai && "zai",
  ].filter(Boolean) as Provider[];

  if (available.length === 1) return available[0]!;
  if (available.length > 1) return available[0]!;

  throw new Error(
-    "No API key found. Set GOOGLE_API_KEY, GEMINI_API_KEY, OPENAI_API_KEY, AZURE_OPENAI_API_KEY+AZURE_OPENAI_BASE_URL, OPENROUTER_API_KEY, DASHSCOPE_API_KEY, MINIMAX_API_KEY, REPLICATE_API_TOKEN, JIMENG keys, or ARK_API_KEY.\n" +
+    "No API key found. Set GOOGLE_API_KEY, GEMINI_API_KEY, OPENAI_API_KEY, AZURE_OPENAI_API_KEY+AZURE_OPENAI_BASE_URL, OPENROUTER_API_KEY, DASHSCOPE_API_KEY, MINIMAX_API_KEY, REPLICATE_API_TOKEN, JIMENG keys, ARK_API_KEY, or ZAI_API_KEY/BIGMODEL_API_KEY.\n" +
      "Create ~/.baoyu-skills/.env or <cwd>/.baoyu-skills/.env with your keys."
  );
 }
@@ -715,6 +729,7 @@ async function loadProviderModule(provider: Provider): Promise<ProviderModule> {
  if (provider === "jimeng") return (await import("./providers/jimeng")) as ProviderModule;
  if (provider === "seedream") return (await import("./providers/seedream")) as ProviderModule;
  if (provider === "azure") return (await import("./providers/azure")) as ProviderModule;
+  if (provider === "zai") return (await import("./providers/zai")) as ProviderModule;
  return (await import("./providers/openai")) as ProviderModule;
 }

@@ -745,6 +760,7 @@ function getModelForProvider(
    if (provider === "jimeng" && extendConfig.default_model.jimeng) return extendConfig.default_model.jimeng;
    if (provider === "seedream" && extendConfig.default_model.seedream) return extendConfig.default_model.seedream;
    if (provider === "azure" && extendConfig.default_model.azure) return extendConfig.default_model.azure;
+    if (provider === "zai" && extendConfig.default_model.zai) return extendConfig.default_model.zai;
  }
  return providerModule.getDefaultModel();
 }
@@ -964,7 +980,7 @@ async function runBatchTasks(
  const acquireProvider = createProviderGate(providerRateLimits);
  const workerCount = getWorkerCount(tasks.length, jobs, maxWorkers);
  console.error(`Batch mode: ${tasks.length} tasks, ${workerCount} workers, parallel mode enabled.`);
-  for (const provider of ["replicate", "google", "openai", "openrouter", "dashscope", "jimeng", "seedream", "azure"] as Provider[]) {
+  for (const provider of ["replicate", "google", "openai", "openrouter", "dashscope", "jimeng", "seedream", "azure", "zai"] as Provider[]) {
    const limit = providerRateLimits[provider];
    console.error(`- ${provider}: concurrency=${limit.concurrency}, startIntervalMs=${limit.startIntervalMs}`);
  }
@@ -0,0 +1,180 @@
+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/,
+  );
+});
@@ -0,0 +1,306 @@
+import type { CliArgs, Quality } from "../types";
+
+type ZaiModelFamily = "glm" | "legacy";
+
+type ZaiRequestBody = {
+  model: string;
+  prompt: string;
+  quality: "hd" | "standard";
+  size: string;
+};
+
+type ZaiResponse = {
+  data?: Array<{ url?: string }>;
+};
+
+const DEFAULT_MODEL = "glm-image";
+const GLM_MAX_PIXELS = 2 ** 22;
+const LEGACY_MAX_PIXELS = 2 ** 21;
+const GLM_SIZE_STEP = 32;
+const LEGACY_SIZE_STEP = 16;
+
+const GLM_RECOMMENDED_SIZES: Record<string, string> = {
+  "1:1": "1280x1280",
+  "3:2": "1568x1056",
+  "2:3": "1056x1568",
+  "4:3": "1472x1088",
+  "3:4": "1088x1472",
+  "16:9": "1728x960",
+  "9:16": "960x1728",
+};
+
+const LEGACY_RECOMMENDED_SIZES: Record<string, string> = {
+  "1:1": "1024x1024",
+  "9:16": "768x1344",
+  "3:4": "864x1152",
+  "16:9": "1344x768",
+  "4:3": "1152x864",
+  "2:1": "1440x720",
+  "1:2": "720x1440",
+};
+
+export function getDefaultModel(): string {
+  return process.env.ZAI_IMAGE_MODEL || process.env.BIGMODEL_IMAGE_MODEL || DEFAULT_MODEL;
+}
+
+function getApiKey(): string | null {
+  return process.env.ZAI_API_KEY || process.env.BIGMODEL_API_KEY || null;
+}
+
+export function buildZaiUrl(): string {
+  const base = (process.env.ZAI_BASE_URL || process.env.BIGMODEL_BASE_URL || "https://api.z.ai/api/paas/v4")
+    .replace(/\/+$/g, "");
+  if (base.endsWith("/images/generations")) return base;
+  if (base.endsWith("/api/paas/v4")) return `${base}/images/generations`;
+  if (base.endsWith("/v4")) return `${base}/images/generations`;
+  return `${base}/api/paas/v4/images/generations`;
+}
+
+export function getModelFamily(model: string): ZaiModelFamily {
+  return model.trim().toLowerCase() === "glm-image" ? "glm" : "legacy";
+}
+
+export function parseAspectRatio(ar: string): { width: number; height: number } | null {
+  const match = ar.match(/^(\d+(?:\.\d+)?):(\d+(?:\.\d+)?)$/);
+  if (!match) return null;
+  const width = Number(match[1]);
+  const height = Number(match[2]);
+  if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
+    return null;
+  }
+  return { width, height };
+}
+
+export function parseSize(size: string): { width: number; height: number } | null {
+  const match = size.trim().match(/^(\d+)\s*[xX*]\s*(\d+)$/);
+  if (!match) return null;
+  const width = parseInt(match[1]!, 10);
+  const height = parseInt(match[2]!, 10);
+  if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
+    return null;
+  }
+  return { width, height };
+}
+
+function formatSize(width: number, height: number): string {
+  return `${width}x${height}`;
+}
+
+function roundToStep(value: number, step: number): number {
+  return Math.max(step, Math.round(value / step) * step);
+}
+
+function getRatioValue(ar: string): number | null {
+  const parsed = parseAspectRatio(ar);
+  if (!parsed) return null;
+  return parsed.width / parsed.height;
+}
+
+function findClosestRatioKey(ar: string, candidates: string[]): string | null {
+  const targetRatio = getRatioValue(ar);
+  if (targetRatio == null) return null;
+
+  let bestKey: string | null = null;
+  let bestDiff = Infinity;
+  for (const candidate of candidates) {
+    const candidateRatio = getRatioValue(candidate);
+    if (candidateRatio == null) continue;
+    const diff = Math.abs(candidateRatio - targetRatio);
+    if (diff < bestDiff) {
+      bestDiff = diff;
+      bestKey = candidate;
+    }
+  }
+
+  return bestDiff <= 0.05 ? bestKey : null;
+}
+
+function getTargetPixels(quality: Quality): number {
+  return quality === "normal" ? 1024 * 1024 : 1536 * 1536;
+}
+
+function fitToPixelBudget(
+  width: number,
+  height: number,
+  targetPixels: number,
+  maxPixels: number,
+  step: number,
+): { width: number; height: number } {
+  let nextWidth = width;
+  let nextHeight = height;
+  const pixels = nextWidth * nextHeight;
+
+  if (pixels > maxPixels) {
+    const scale = Math.sqrt(maxPixels / pixels);
+    nextWidth *= scale;
+    nextHeight *= scale;
+  } else {
+    const scale = Math.sqrt(targetPixels / pixels);
+    nextWidth *= scale;
+    nextHeight *= scale;
+  }
+
+  let roundedWidth = roundToStep(nextWidth, step);
+  let roundedHeight = roundToStep(nextHeight, step);
+  let roundedPixels = roundedWidth * roundedHeight;
+
+  while (roundedPixels > maxPixels && (roundedWidth > step || roundedHeight > step)) {
+    if (roundedWidth >= roundedHeight && roundedWidth > step) {
+      roundedWidth -= step;
+    } else if (roundedHeight > step) {
+      roundedHeight -= step;
+    } else {
+      break;
+    }
+    roundedPixels = roundedWidth * roundedHeight;
+  }
+
+  return { width: roundedWidth, height: roundedHeight };
+}
+
+function validateCustomSize(
+  size: string,
+  family: ZaiModelFamily,
+): string {
+  const parsed = parseSize(size);
+  if (!parsed) {
+    throw new Error("Z.AI --size must be in WxH format, for example 1280x1280.");
+  }
+
+  const widthStep = family === "glm" ? GLM_SIZE_STEP : LEGACY_SIZE_STEP;
+  const minEdge = family === "glm" ? 1024 : 512;
+  const maxPixels = family === "glm" ? GLM_MAX_PIXELS : LEGACY_MAX_PIXELS;
+
+  if (parsed.width < minEdge || parsed.width > 2048 || parsed.height < minEdge || parsed.height > 2048) {
+    throw new Error(
+      family === "glm"
+        ? "GLM-image custom size requires width and height between 1024 and 2048."
+        : "Z.AI legacy image models require width and height between 512 and 2048."
+    );
+  }
+
+  if (parsed.width % widthStep !== 0 || parsed.height % widthStep !== 0) {
+    throw new Error(
+      family === "glm"
+        ? "GLM-image custom size requires width and height divisible by 32."
+        : "Z.AI legacy image models require width and height divisible by 16."
+    );
+  }
+
+  if (parsed.width * parsed.height > maxPixels) {
+    throw new Error(
+      family === "glm"
+        ? "GLM-image custom size must not exceed 2^22 total pixels."
+        : "Z.AI legacy image size must not exceed 2^21 total pixels."
+    );
+  }
+
+  return formatSize(parsed.width, parsed.height);
+}
+
+export function resolveSizeForModel(
+  model: string,
+  args: Pick<CliArgs, "size" | "aspectRatio" | "quality">,
+): string {
+  const family = getModelFamily(model);
+  const quality = args.quality === "normal" ? "normal" : "2k";
+
+  if (args.size) {
+    return validateCustomSize(args.size, family);
+  }
+
+  const recommended = family === "glm" ? GLM_RECOMMENDED_SIZES : LEGACY_RECOMMENDED_SIZES;
+  const defaultSize = family === "glm" ? "1280x1280" : "1024x1024";
+
+  if (!args.aspectRatio) return defaultSize;
+
+  const recommendedRatio = findClosestRatioKey(args.aspectRatio, Object.keys(recommended));
+  if (recommendedRatio) {
+    return recommended[recommendedRatio]!;
+  }
+
+  const parsedRatio = parseAspectRatio(args.aspectRatio);
+  if (!parsedRatio) return defaultSize;
+
+  const targetPixels = getTargetPixels(quality);
+  const maxPixels = family === "glm" ? GLM_MAX_PIXELS : LEGACY_MAX_PIXELS;
+  const step = family === "glm" ? GLM_SIZE_STEP : LEGACY_SIZE_STEP;
+  const fit = fitToPixelBudget(
+    parsedRatio.width,
+    parsedRatio.height,
+    targetPixels,
+    maxPixels,
+    step,
+  );
+  return formatSize(fit.width, fit.height);
+}
+
+function getZaiQuality(quality: CliArgs["quality"]): "hd" | "standard" {
+  return quality === "normal" ? "standard" : "hd";
+}
+
+export function validateArgs(_model: string, args: CliArgs): void {
+  if (args.referenceImages.length > 0) {
+    throw new Error("Z.AI GLM-image currently supports text-to-image only in baoyu-image-gen. Remove --ref or choose another provider.");
+  }
+
+  if (args.n > 1) {
+    throw new Error("Z.AI image generation currently returns a single image per request in baoyu-image-gen.");
+  }
+}
+
+export function buildRequestBody(
+  prompt: string,
+  model: string,
+  args: CliArgs,
+): ZaiRequestBody {
+  validateArgs(model, args);
+  return {
+    model,
+    prompt,
+    quality: getZaiQuality(args.quality),
+    size: resolveSizeForModel(model, args),
+  };
+}
+
+export async function extractImageFromResponse(result: ZaiResponse): Promise<Uint8Array> {
+  const url = result.data?.[0]?.url;
+  if (!url) {
+    throw new Error("No image URL in Z.AI response");
+  }
+
+  const imageResponse = await fetch(url);
+  if (!imageResponse.ok) {
+    throw new Error(`Failed to download image from Z.AI: ${imageResponse.status}`);
+  }
+
+  return new Uint8Array(await imageResponse.arrayBuffer());
+}
+
+export async function generateImage(
+  prompt: string,
+  model: string,
+  args: CliArgs,
+): Promise<Uint8Array> {
+  const apiKey = getApiKey();
+  if (!apiKey) {
+    throw new Error("ZAI_API_KEY is required. Get one from https://docs.z.ai/.");
+  }
+
+  const response = await fetch(buildZaiUrl(), {
+    method: "POST",
+    headers: {
+      "Content-Type": "application/json",
+      Authorization: `Bearer ${apiKey}`,
+    },
+    body: JSON.stringify(buildRequestBody(prompt, model, args)),
+  });
+
+  if (!response.ok) {
+    const err = await response.text();
+    throw new Error(`Z.AI API error (${response.status}): ${err}`);
+  }
+
+  const result = (await response.json()) as ZaiResponse;
+  return extractImageFromResponse(result);
+}
@@ -7,7 +7,8 @@ export type Provider =
  | "replicate"
  | "jimeng"
  | "seedream"
-  | "azure";
+  | "azure"
+  | "zai";
 export type Quality = "normal" | "2k";

 export type CliArgs = {
@@ -66,6 +67,7 @@ export type ExtendConfig = {
    jimeng: string | null;
    seedream: string | null;
    azure: string | null;
+    zai: string | null;
  };
  batch?: {
    max_workers?: number | null;