feat(baoyu-imagine): add Z.AI GLM-Image provider

Adds the Z.AI (智谱) provider supporting glm-image and cogview-4-250304 models via the Z.AI sync image API. Configure with ZAI_API_KEY (or BIGMODEL_API_KEY for backward compat). Reference images are not supported yet.
2026-07-12 05:51:44 +08:00 · 2026-04-12 00:30:49 -05:00
parent ec5f4ffcc9
commit eaa0f1aa11
10 changed files with 683 additions and 19 deletions
@@ -1,7 +1,7 @@
 ---
 name: baoyu-imagine
-description: AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, Jimeng, Seedream and Replicate APIs. Supports text-to-image, reference images, aspect ratios, and batch generation from saved prompt files. Sequential by default; use batch parallel generation when the user already has multiple prompts or wants stable multi-image throughput. Use when user asks to generate, create, or draw images.
-version: 1.56.4
+description: AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream and Replicate APIs. Supports text-to-image, reference images, aspect ratios, and batch generation from saved prompt files. Sequential by default; use batch parallel generation when the user already has multiple prompts or wants stable multi-image throughput. Use when user asks to generate, create, or draw images.
+version: 1.57.0
 metadata:
  openclaw:
    homepage: https://github.com/JimLiu/baoyu-skills#baoyu-imagine
@@ -13,7 +13,7 @@ metadata:

 # Image Generation (AI SDK)

-Official API-based image generation. Supports OpenAI, Azure OpenAI, Google, OpenRouter, DashScope (阿里通义万象), MiniMax, Jimeng (即梦), Seedream (豆包) and Replicate providers.
+Official API-based image generation. Supports OpenAI, Azure OpenAI, Google, OpenRouter, DashScope (阿里通义万象), Z.AI GLM-Image, MiniMax, Jimeng (即梦), Seedream (豆包) and Replicate providers.

 ## Script Directory

@@ -103,6 +103,12 @@ ${BUN_X} {baseDir}/scripts/main.ts --prompt "为咖啡品牌设计一张 21:9
 # DashScope legacy Qwen fixed-size model
 ${BUN_X} {baseDir}/scripts/main.ts --prompt "一张电影感海报" --image out.png --provider dashscope --model qwen-image-max --size 1664x928

+# Z.AI GLM-image
+${BUN_X} {baseDir}/scripts/main.ts --prompt "一张带清晰中文标题的科技海报" --image out.png --provider zai
+
+# Z.AI GLM-image with explicit custom size
+${BUN_X} {baseDir}/scripts/main.ts --prompt "A science illustration with labels" --image out.png --provider zai --model glm-image --size 1472x1088
+
 # MiniMax
 ${BUN_X} {baseDir}/scripts/main.ts --prompt "A fashion editorial portrait by a bright studio window" --image out.jpg --provider minimax

@@ -161,8 +167,8 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
 | `--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\|azure\|openrouter\|dashscope\|minimax\|jimeng\|seedream\|replicate` | Force provider (default: auto-detect) |
-| `--model <id>`, `-m` | Model ID (Google: `gemini-3-pro-image-preview`; OpenAI: `gpt-image-1.5`; Azure: deployment name such as `gpt-image-1.5` or `image-prod`; OpenRouter: `google/gemini-3.1-flash-image-preview`; DashScope: `qwen-image-2.0-pro`; MiniMax: `image-01`) |
+| `--provider google\|openai\|azure\|openrouter\|dashscope\|zai\|minimax\|jimeng\|seedream\|replicate` | Force provider (default: auto-detect) |
+| `--model <id>`, `-m` | Model ID (Google: `gemini-3-pro-image-preview`; OpenAI: `gpt-image-1.5`; Azure: deployment name such as `gpt-image-1.5` or `image-prod`; OpenRouter: `google/gemini-3.1-flash-image-preview`; DashScope: `qwen-image-2.0-pro`; Z.AI: `glm-image`; MiniMax: `image-01`) |
 | `--ar <ratio>` | Aspect ratio (e.g., `16:9`, `1:1`, `4:3`) |
 | `--size <WxH>` | Size (e.g., `1024x1024`) |
 | `--quality normal\|2k` | Quality preset (default: `2k`) |
@@ -180,6 +186,8 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
 | `OPENROUTER_API_KEY` | OpenRouter API key |
 | `GOOGLE_API_KEY` | Google API key |
 | `DASHSCOPE_API_KEY` | DashScope API key (阿里云) |
+| `ZAI_API_KEY` | Z.AI API key |
+| `BIGMODEL_API_KEY` | Backward-compatible alias for Z.AI API key |
 | `MINIMAX_API_KEY` | MiniMax API key |
 | `REPLICATE_API_TOKEN` | Replicate API token |
 | `JIMENG_ACCESS_KEY_ID` | Jimeng (即梦) Volcengine access key |
@@ -191,6 +199,8 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
 | `OPENROUTER_IMAGE_MODEL` | OpenRouter model override (default: `google/gemini-3.1-flash-image-preview`) |
 | `GOOGLE_IMAGE_MODEL` | Google model override |
 | `DASHSCOPE_IMAGE_MODEL` | DashScope model override (default: `qwen-image-2.0-pro`) |
+| `ZAI_IMAGE_MODEL` | Z.AI model override (default: `glm-image`) |
+| `BIGMODEL_IMAGE_MODEL` | Backward-compatible alias for Z.AI model override |
 | `MINIMAX_IMAGE_MODEL` | MiniMax model override (default: `image-01`) |
 | `REPLICATE_IMAGE_MODEL` | Replicate model override (default: google/nano-banana-pro) |
 | `JIMENG_IMAGE_MODEL` | Jimeng model override (default: jimeng_t2i_v40) |
@@ -203,6 +213,8 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
 | `OPENROUTER_TITLE` | Optional app name for OpenRouter attribution |
 | `GOOGLE_BASE_URL` | Custom Google endpoint |
 | `DASHSCOPE_BASE_URL` | Custom DashScope endpoint |
+| `ZAI_BASE_URL` | Custom Z.AI endpoint (default: `https://api.z.ai/api/paas/v4`) |
+| `BIGMODEL_BASE_URL` | Backward-compatible alias for Z.AI endpoint |
 | `MINIMAX_BASE_URL` | Custom MiniMax endpoint (default: `https://api.minimax.io`) |
 | `REPLICATE_BASE_URL` | Custom Replicate endpoint |
 | `JIMENG_BASE_URL` | Custom Jimeng endpoint (default: `https://visual.volcengineapi.com`) |
@@ -277,6 +289,32 @@ Official references:
 - [Text-to-image guide](https://help.aliyun.com/zh/model-studio/text-to-image)
 - [Qwen-Image Edit API](https://help.aliyun.com/zh/model-studio/qwen-image-edit-api)

+### Z.AI Models
+
+Use `--model glm-image` or set `default_model.zai` / `ZAI_IMAGE_MODEL` when the user wants GLM-image output.
+
+Official Z.AI image model options currently documented in the sync image API:
+
+- `glm-image` (recommended default)
+  - Text-to-image only in `baoyu-imagine`
+  - Native `quality` options are `hd` and `standard`; this skill maps `2k -> hd` and `normal -> standard`
+  - Recommended sizes: `1280x1280`, `1568x1056`, `1056x1568`, `1472x1088`, `1088x1472`, `1728x960`, `960x1728`
+  - Custom `--size` requires width and height between `1024` and `2048`, divisible by `32`, with total pixels <= `2^22`
+- `cogview-4-250304`
+  - Legacy Z.AI image model family exposed by the same endpoint
+  - Custom `--size` requires width and height between `512` and `2048`, divisible by `16`, with total pixels <= `2^21`
+
+Notes:
+
+- The official sync API returns a temporary image URL; `baoyu-imagine` downloads that URL and writes the image locally
+- `--ref` is not supported for Z.AI in this skill yet
+- The sync API currently returns a single image, so `--n > 1` is rejected
+
+Official references:
+
+- [GLM-Image Guide](https://docs.z.ai/guides/image/glm-image)
+- [Generate Image API](https://docs.z.ai/api-reference/image/generate-image)
+
 ### MiniMax Models

 Use `--model image-01` or set `default_model.minimax` / `MINIMAX_IMAGE_MODEL` when the user wants MiniMax image generation.
@@ -342,7 +380,7 @@ ${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider r
 1. `--ref` provided + no `--provider` → auto-select Google first, then OpenAI, then Azure, then OpenRouter, then Replicate, then Seedream, then MiniMax (MiniMax subject reference is more specialized toward character/portrait consistency)
 2. `--provider` specified → use it (if `--ref`, must be `google`, `openai`, `azure`, `openrouter`, `replicate`, `seedream`, or `minimax`)
 3. Only one API key available → use that provider
-4. Multiple available → default to Google
+4. Multiple available → default to Google, then OpenAI, Azure, OpenRouter, DashScope, Z.AI, MiniMax, Replicate, Jimeng, Seedream

 ## Quality Presets

@@ -53,6 +53,8 @@ options:
    description: "Router for Gemini/FLUX/OpenAI-compatible image models"
  - label: "DashScope"
    description: "Alibaba Cloud - Qwen-Image, strong Chinese/English text rendering"
+  - label: "Z.AI"
+    description: "GLM-image, strong poster and text-heavy image generation"
  - label: "MiniMax"
    description: "MiniMax image generation with subject-reference character workflows"
  - label: "Replicate"
@@ -119,6 +121,20 @@ options:
    description: "Faster variant, use aspect ratio instead of custom size"
 ```

+### Question 2e: Default Z.AI Model
+
+Only show if user selected Z.AI.
+
+```yaml
+header: "Z.AI Model"
+question: "Default Z.AI image generation model?"
+options:
+  - label: "glm-image (Recommended)"
+    description: "Best default for posters, diagrams, and text-heavy images"
+  - label: "cogview-4-250304"
+    description: "Legacy Z.AI image model on the same endpoint"
+```
+
 ### Question 3: Default Quality

 ```yaml
@@ -165,6 +181,7 @@ default_model:
  azure: [selected azure deployment or null]
  openrouter: [selected openrouter model or null]
  dashscope: null
+  zai: [selected Z.AI model or null]
  minimax: [selected minimax model or null]
  replicate: null
 ---
@@ -257,6 +274,24 @@ Notes for DashScope setup:
 - `qwen-image-max` / `qwen-image-plus` / `qwen-image` only support five fixed sizes: `1664*928`, `1472*1104`, `1328*1328`, `1104*1472`, `928*1664`.
 - In `baoyu-imagine`, `quality` is a compatibility preset. It is not a native DashScope parameter.

+### Z.AI Model Selection
+
+```yaml
+header: "Z.AI Model"
+question: "Choose a default Z.AI image generation model?"
+options:
+  - label: "glm-image (Recommended)"
+    description: "Current flagship image model with better text rendering and poster layouts"
+  - label: "cogview-4-250304"
+    description: "Legacy model on the sync image endpoint"
+```
+
+Notes for Z.AI setup:
+
+- Prefer `glm-image` for posters, diagrams, and Chinese/English text-heavy layouts.
+- In `baoyu-imagine`, Z.AI currently exposes text-to-image only; reference images are not wired for this provider.
+- The sync Z.AI image API returns a downloadable image URL, which the runtime saves locally after download.
+
 ### Replicate Model Selection

 ```yaml
@@ -302,6 +337,7 @@ default_model:
  azure: [value or null]
  openrouter: [value or null]
  dashscope: [value or null]
+  zai: [value or null]
  minimax: [value or null]
  replicate: [value or null]
 ```
@@ -11,7 +11,7 @@ description: EXTEND.md YAML schema for baoyu-imagine user preferences
 ---
 version: 1

-default_provider: null      # google|openai|azure|openrouter|dashscope|minimax|replicate|null (null = auto-detect)
+default_provider: null      # google|openai|azure|openrouter|dashscope|zai|minimax|replicate|null (null = auto-detect)

 default_quality: null       # normal|2k|null (null = use default: 2k)

@@ -25,6 +25,7 @@ default_model:
  azure: null               # Azure deployment name, e.g., "gpt-image-1.5" or "image-prod"
  openrouter: null          # e.g., "google/gemini-3.1-flash-image-preview"
  dashscope: null           # e.g., "qwen-image-2.0-pro"
+  zai: null                 # e.g., "glm-image"
  minimax: null             # e.g., "image-01"
  replicate: null           # e.g., "google/nano-banana-pro"

@@ -49,6 +50,9 @@ batch:
    dashscope:
      concurrency: 3
      start_interval_ms: 1100
+    zai:
+      concurrency: 3
+      start_interval_ms: 1100
    minimax:
      concurrency: 3
      start_interval_ms: 1100
@@ -69,6 +73,7 @@ batch:
 | `default_model.azure` | string\|null | null | Azure default deployment name |
 | `default_model.openrouter` | string\|null | null | OpenRouter default model |
 | `default_model.dashscope` | string\|null | null | DashScope default model |
+| `default_model.zai` | string\|null | null | Z.AI default model |
 | `default_model.minimax` | string\|null | null | MiniMax default model |
 | `default_model.replicate` | string\|null | null | Replicate default model |
 | `batch.max_workers` | int\|null | 10 | Batch worker cap |
@@ -100,6 +105,7 @@ default_model:
  azure: "gpt-image-1.5"
  openrouter: "google/gemini-3.1-flash-image-preview"
  dashscope: "qwen-image-2.0-pro"
+  zai: "glm-image"
  minimax: "image-01"
  replicate: "google/nano-banana-pro"
 batch:
@@ -111,6 +117,9 @@ batch:
    azure:
      concurrency: 3
      start_interval_ms: 1100
+    zai:
+      concurrency: 3
+      start_interval_ms: 1100
    openrouter:
      concurrency: 3
      start_interval_ms: 1100
@@ -78,7 +78,7 @@ test("parseArgs parses the main baoyu-imagine CLI flags", () => {
    "--image",
    "out/hero",
    "--provider",
-    "openai",
+    "zai",
    "--quality",
    "2k",
    "--imageSize",
@@ -95,7 +95,7 @@ test("parseArgs parses the main baoyu-imagine CLI flags", () => {

  assert.deepEqual(args.promptFiles, ["prompts/system.md", "prompts/content.md"]);
  assert.equal(args.imagePath, "out/hero");
-  assert.equal(args.provider, "openai");
+  assert.equal(args.provider, "zai");
  assert.equal(args.quality, "2k");
  assert.equal(args.imageSize, "4K");
  assert.deepEqual(args.referenceImages, ["ref/one.png", "ref/two.jpg"]);
@@ -124,6 +124,7 @@ default_image_size: 2K
 default_model:
  google: gemini-3-pro-image-preview
  openai: gpt-image-1.5
+  zai: glm-image
  azure: image-prod
  minimax: image-01
 batch:
@@ -134,6 +135,9 @@ batch:
      start_interval_ms: 900
    openai:
      concurrency: 4
+    zai:
+      concurrency: 2
+      start_interval_ms: 1000
    minimax:
      concurrency: 2
      start_interval_ms: 1400
@@ -151,6 +155,7 @@ batch:
  assert.equal(config.default_image_size, "2K");
  assert.equal(config.default_model?.google, "gemini-3-pro-image-preview");
  assert.equal(config.default_model?.openai, "gpt-image-1.5");
+  assert.equal(config.default_model?.zai, "glm-image");
  assert.equal(config.default_model?.azure, "image-prod");
  assert.equal(config.default_model?.minimax, "image-01");
  assert.equal(config.batch?.max_workers, 8);
@@ -161,6 +166,10 @@ batch:
  assert.deepEqual(config.batch?.provider_limits?.openai, {
    concurrency: 4,
  });
+  assert.deepEqual(config.batch?.provider_limits?.zai, {
+    concurrency: 2,
+    start_interval_ms: 1000,
+  });
  assert.deepEqual(config.batch?.provider_limits?.minimax, {
    concurrency: 2,
    start_interval_ms: 1400,
@@ -316,6 +325,27 @@ test("detectProvider selects Azure when only Azure credentials are configured",
  );
 });

+test("detectProvider selects Z.AI when credentials are present or the model id matches", (t) => {
+  useEnv(t, {
+    GOOGLE_API_KEY: null,
+    OPENAI_API_KEY: null,
+    AZURE_OPENAI_API_KEY: null,
+    AZURE_OPENAI_BASE_URL: null,
+    OPENROUTER_API_KEY: null,
+    DASHSCOPE_API_KEY: null,
+    ZAI_API_KEY: "zai-key",
+    BIGMODEL_API_KEY: null,
+    MINIMAX_API_KEY: null,
+    REPLICATE_API_TOKEN: null,
+    JIMENG_ACCESS_KEY_ID: null,
+    JIMENG_SECRET_ACCESS_KEY: null,
+    ARK_API_KEY: null,
+  });
+
+  assert.equal(detectProvider(makeArgs()), "zai");
+  assert.equal(detectProvider(makeArgs({ model: "glm-image" })), "zai");
+});
+
 test("detectProvider infers Seedream from model id and allows Seedream reference-image workflows", (t) => {
  useEnv(t, {
    GOOGLE_API_KEY: null,
@@ -375,6 +405,7 @@ test("batch worker and provider-rate-limit configuration prefer env over EXTEND
    BAOYU_IMAGE_GEN_MAX_WORKERS: "12",
    BAOYU_IMAGE_GEN_GOOGLE_CONCURRENCY: "5",
    BAOYU_IMAGE_GEN_GOOGLE_START_INTERVAL_MS: "450",
+    BAOYU_IMAGE_GEN_ZAI_CONCURRENCY: "4",
  });

  const extendConfig: Partial<ExtendConfig> = {
@@ -385,6 +416,10 @@ test("batch worker and provider-rate-limit configuration prefer env over EXTEND
          concurrency: 2,
          start_interval_ms: 900,
        },
+        zai: {
+          concurrency: 1,
+          start_interval_ms: 1200,
+        },
        minimax: {
          concurrency: 1,
          start_interval_ms: 1500,
@@ -398,6 +433,10 @@ test("batch worker and provider-rate-limit configuration prefer env over EXTEND
    concurrency: 5,
    startIntervalMs: 450,
  });
+  assert.deepEqual(getConfiguredProviderRateLimits(extendConfig).zai, {
+    concurrency: 4,
+    startIntervalMs: 1200,
+  });
  assert.deepEqual(getConfiguredProviderRateLimits(extendConfig).minimax, {
    concurrency: 1,
    startIntervalMs: 1500,
@@ -58,6 +58,7 @@ const DEFAULT_PROVIDER_RATE_LIMITS: Record<Provider, ProviderRateLimit> = {
  openai: { concurrency: 3, startIntervalMs: 1100 },
  openrouter: { concurrency: 3, startIntervalMs: 1100 },
  dashscope: { concurrency: 3, startIntervalMs: 1100 },
+  zai: { concurrency: 3, startIntervalMs: 1100 },
  minimax: { concurrency: 3, startIntervalMs: 1100 },
  jimeng: { concurrency: 3, startIntervalMs: 1100 },
  seedream: { concurrency: 3, startIntervalMs: 1100 },
@@ -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|zai|minimax|replicate|jimeng|seedream|azure  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)
@@ -113,6 +114,8 @@ Environment variables:
  GOOGLE_API_KEY            Google API key
  GEMINI_API_KEY            Gemini API key (alias for GOOGLE_API_KEY)
  DASHSCOPE_API_KEY         DashScope API key
+  ZAI_API_KEY               Z.AI API key
+  BIGMODEL_API_KEY          Backward-compatible alias for Z.AI API key
  MINIMAX_API_KEY           MiniMax API key
  REPLICATE_API_TOKEN       Replicate API token
  JIMENG_ACCESS_KEY_ID      Jimeng Access Key ID
@@ -122,6 +125,8 @@ Environment variables:
  OPENROUTER_IMAGE_MODEL    Default OpenRouter model (google/gemini-3.1-flash-image-preview)
  GOOGLE_IMAGE_MODEL        Default Google model (gemini-3-pro-image-preview)
  DASHSCOPE_IMAGE_MODEL     Default DashScope model (qwen-image-2.0-pro)
+  ZAI_IMAGE_MODEL           Default Z.AI model (glm-image)
+  BIGMODEL_IMAGE_MODEL      Backward-compatible alias for Z.AI model (glm-image)
  MINIMAX_IMAGE_MODEL       Default MiniMax model (image-01)
  REPLICATE_IMAGE_MODEL     Default Replicate model (google/nano-banana-pro)
  JIMENG_IMAGE_MODEL        Default Jimeng model (jimeng_t2i_v40)
@@ -133,6 +138,8 @@ Environment variables:
  OPENROUTER_TITLE          Optional app name for OpenRouter attribution
  GOOGLE_BASE_URL           Custom Google endpoint
  DASHSCOPE_BASE_URL        Custom DashScope endpoint
+  ZAI_BASE_URL              Custom Z.AI endpoint
+  BIGMODEL_BASE_URL         Backward-compatible alias for Z.AI endpoint
  MINIMAX_BASE_URL          Custom MiniMax endpoint
  REPLICATE_BASE_URL        Custom Replicate endpoint
  JIMENG_BASE_URL           Custom Jimeng endpoint
@@ -239,6 +246,7 @@ export function parseArgs(argv: string[]): CliArgs {
        v !== "openai" &&
        v !== "openrouter" &&
        v !== "dashscope" &&
+        v !== "zai" &&
        v !== "minimax" &&
        v !== "replicate" &&
        v !== "jimeng" &&
@@ -395,6 +403,7 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
          openai: null,
          openrouter: null,
          dashscope: null,
+          zai: null,
          minimax: null,
          replicate: null,
          jimeng: null,
@@ -423,6 +432,7 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
          key === "openai" ||
          key === "openrouter" ||
          key === "dashscope" ||
+          key === "zai" ||
          key === "minimax" ||
          key === "replicate" ||
          key === "jimeng" ||
@@ -441,6 +451,7 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
          key === "openai" ||
          key === "openrouter" ||
          key === "dashscope" ||
+          key === "zai" ||
          key === "minimax" ||
          key === "replicate" ||
          key === "jimeng" ||
@@ -571,13 +582,14 @@ export function getConfiguredProviderRateLimits(
    openai: { ...DEFAULT_PROVIDER_RATE_LIMITS.openai },
    openrouter: { ...DEFAULT_PROVIDER_RATE_LIMITS.openrouter },
    dashscope: { ...DEFAULT_PROVIDER_RATE_LIMITS.dashscope },
+    zai: { ...DEFAULT_PROVIDER_RATE_LIMITS.zai },
    minimax: { ...DEFAULT_PROVIDER_RATE_LIMITS.minimax },
    jimeng: { ...DEFAULT_PROVIDER_RATE_LIMITS.jimeng },
    seedream: { ...DEFAULT_PROVIDER_RATE_LIMITS.seedream },
    azure: { ...DEFAULT_PROVIDER_RATE_LIMITS.azure },
  };

-  for (const provider of ["replicate", "google", "openai", "openrouter", "dashscope", "minimax", "jimeng", "seedream", "azure"] as Provider[]) {
+  for (const provider of ["replicate", "google", "openai", "openrouter", "dashscope", "zai", "minimax", "jimeng", "seedream", "azure"] as Provider[]) {
    const envPrefix = `BAOYU_IMAGE_GEN_${provider.toUpperCase()}`;
    const extendLimit = extendConfig.batch?.provider_limits?.[provider];
    configured[provider] = {
@@ -629,6 +641,7 @@ function inferProviderFromModel(model: string | null): Provider | null {
  const normalized = model.trim();
  if (normalized.includes("seedream") || normalized.includes("seededit")) return "seedream";
  if (normalized === "image-01" || normalized === "image-01-live") return "minimax";
+  if (normalized === "glm-image" || normalized === "cogview-4-250304") return "zai";
  return null;
 }

@@ -656,6 +669,7 @@ export function detectProvider(args: CliArgs): Provider {
  const hasOpenai = !!process.env.OPENAI_API_KEY;
  const hasOpenrouter = !!process.env.OPENROUTER_API_KEY;
  const hasDashscope = !!process.env.DASHSCOPE_API_KEY;
+  const hasZai = !!(process.env.ZAI_API_KEY || process.env.BIGMODEL_API_KEY);
  const hasMinimax = !!process.env.MINIMAX_API_KEY;
  const hasReplicate = !!process.env.REPLICATE_API_TOKEN;
  const hasJimeng = !!(process.env.JIMENG_ACCESS_KEY_ID && process.env.JIMENG_SECRET_ACCESS_KEY);
@@ -676,6 +690,13 @@ export function detectProvider(args: CliArgs): Provider {
    return "minimax";
  }

+  if (modelProvider === "zai") {
+    if (!hasZai) {
+      throw new Error("Model looks like a Z.AI image model, but ZAI_API_KEY is not set.");
+    }
+    return "zai";
+  }
+
  if (args.referenceImages.length > 0) {
    if (hasGoogle) return "google";
    if (hasOpenai) return "openai";
@@ -695,6 +716,7 @@ export function detectProvider(args: CliArgs): Provider {
    hasAzure && "azure",
    hasOpenrouter && "openrouter",
    hasDashscope && "dashscope",
+    hasZai && "zai",
    hasMinimax && "minimax",
    hasReplicate && "replicate",
    hasJimeng && "jimeng",
@@ -705,7 +727,7 @@ export function detectProvider(args: CliArgs): Provider {
  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, ZAI_API_KEY, MINIMAX_API_KEY, REPLICATE_API_TOKEN, JIMENG keys, or ARK_API_KEY.\n" +
      "Create ~/.baoyu-skills/.env or <cwd>/.baoyu-skills/.env with your keys."
  );
 }
@@ -744,6 +766,7 @@ export function isRetryableGenerationError(error: unknown): boolean {
 async function loadProviderModule(provider: Provider): Promise<ProviderModule> {
  if (provider === "google") return (await import("./providers/google")) as ProviderModule;
  if (provider === "dashscope") return (await import("./providers/dashscope")) as ProviderModule;
+  if (provider === "zai") return (await import("./providers/zai")) as ProviderModule;
  if (provider === "minimax") return (await import("./providers/minimax")) as ProviderModule;
  if (provider === "replicate") return (await import("./providers/replicate")) as ProviderModule;
  if (provider === "openrouter") return (await import("./providers/openrouter")) as ProviderModule;
@@ -775,6 +798,7 @@ function getModelForProvider(
      return extendConfig.default_model.openrouter;
    }
    if (provider === "dashscope" && extendConfig.default_model.dashscope) return extendConfig.default_model.dashscope;
+    if (provider === "zai" && extendConfig.default_model.zai) return extendConfig.default_model.zai;
    if (provider === "minimax" && extendConfig.default_model.minimax) return extendConfig.default_model.minimax;
    if (provider === "replicate" && extendConfig.default_model.replicate) return extendConfig.default_model.replicate;
    if (provider === "jimeng" && extendConfig.default_model.jimeng) return extendConfig.default_model.jimeng;
@@ -999,7 +1023,7 @@ 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", "zai", "minimax", "jimeng", "seedream", "azure"] 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-imagine. 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-imagine.");
+  }
+}
+
+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);
+}
@@ -3,6 +3,7 @@ export type Provider =
  | "openai"
  | "openrouter"
  | "dashscope"
+  | "zai"
  | "minimax"
  | "replicate"
  | "jimeng"
@@ -61,6 +62,7 @@ export type ExtendConfig = {
    openai: string | null;
    openrouter: string | null;
    dashscope: string | null;
+    zai: string | null;
    minimax: string | null;
    replicate: string | null;
    jimeng: string | null;