feat(baoyu-imagine): add DashScope Wan 2.7 image model support (#141)

* feat(baoyu-imagine): add DashScope Wan 2.7 image model support

Closes #139.

Adds the new `wan2.7-image-pro` and `wan2.7-image` model family to the
DashScope provider so users can call Wan 2.7 directly through the
official Aliyun (Bailian) API instead of going through Replicate.

- Register `wan2.7-image-pro` and `wan2.7-image` as a new `wan27` family
  in the DashScope provider with their own size resolution rules:
  pixel range `[768*768, 4096*4096]` for `wan2.7-image-pro` text-to-image,
  `[768*768, 2048*2048]` for `wan2.7-image-pro` with refs and for the
  base `wan2.7-image` model in any mode, with aspect ratios validated
  against the documented `[1:8, 8:1]` band.
- Allow up to 9 reference images per request (image editing /
  multi-image fusion). Local files are inlined as base64 data URLs;
  `http(s)://` paths are forwarded as-is. Other DashScope models still
  reject `--ref` with a hint to switch to a wan2.7 model or another
  provider.
- Drop `prompt_extend` from the request body for the Wan 2.7 family
  (not part of the Wan 2.7 API surface) and skip the Qwen-only negative
  prompt for this family.
- Allow `--provider dashscope --ref ...` in `detectProvider` so users
  can opt into Wan 2.7 reference workflows, while keeping Wan 2.7 out
  of the auto-detect ref priority list.
- Add provider, reference, and usage-example documentation, plus
  unit tests covering family routing, size derivation across the
  three pixel-budget modes, ratio rejection, explicit-size validation,
  and the new `--provider dashscope` ref opt-in path.

Made-with: Cursor

* fix(baoyu-imagine): force n=1 for DashScope wan2.7 to avoid silent multi-image billing

Cross-checked the implementation against the official Wan 2.7 image
generation & editing API reference and found that the API defaults
`parameters.n` to 4 in non-collage mode (1-4 range, billed per image).
baoyu-imagine has single-image save semantics — only the first image
in the response is kept — so without an explicit `n: 1` users would
silently pay for 3 discarded images per request.

- Always send `parameters.n: 1` in the wan2.7 request body
- Reject `--n > 1` for wan2.7 with a clear error pointing at the
  single-image save semantics
- Add tests asserting the request body shape (n=1, no prompt_extend,
  no negative_prompt) and the --n>1 rejection
- Document the defaults-vs-skill mismatch in the dashscope reference

Made-with: Cursor

* Fix DashScope Wan 2.7 review feedback

skills/baoyu-imagine/SKILL.md

@@ -91,7 +91,7 @@ ${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4
 | `--quality normal\|2k` | Quality preset (default: `2k`) |
 | `--imageSize 1K\|2K\|4K` | Image size for Google/OpenRouter (default: from quality) |
 | `--imageApiDialect openai-native\|ratio-metadata` | OpenAI-compatible endpoint dialect — use `ratio-metadata` for gateways that expect aspect-ratio `size` plus `metadata.resolution` |
-| `--ref <files...>` | Reference images. Supported by Google multimodal, OpenAI GPT Image edits, Azure OpenAI edits (PNG/JPG only), OpenRouter multimodal models, Replicate supported families, MiniMax subject-reference, Seedream 5.0/4.5/4.0. Not supported by Jimeng, Seedream 3.0, SeedEdit 3.0 |
+| `--ref <files...>` | Reference images. Supported by Google multimodal, OpenAI GPT Image edits, Azure OpenAI edits (PNG/JPG only), OpenRouter multimodal models, Replicate supported families, MiniMax subject-reference, Seedream 5.0/4.5/4.0, DashScope `wan2.7-image-pro`/`wan2.7-image`. Not supported by Jimeng, Seedream 3.0, SeedEdit 3.0, or any DashScope model outside the `wan2.7-image*` family |
 | `--n <count>` | Number of images. Replicate requires `--n 1` (single-output save semantics) |
 | `--json` | JSON output |
 

skills/baoyu-imagine/references/config/first-time-setup.md

@@ -271,6 +271,10 @@ options:
     description: "Legacy Qwen model with five fixed output sizes"
   - label: "qwen-image-plus"
     description: "Legacy Qwen model, same current capability as qwen-image"
+  - label: "wan2.7-image-pro"
+    description: "Wan 2.7 Pro — supports up to 4K text-to-image and reference-image editing"
+  - label: "wan2.7-image"
+    description: "Wan 2.7 base — faster generation, up to 2K, supports reference-image editing"
   - label: "z-image-turbo"
     description: "Legacy DashScope model for compatibility"
   - label: "z-image-ultra"
@@ -281,6 +285,7 @@ Notes for DashScope setup:
 
 - Prefer `qwen-image-2.0-pro` when the user needs custom `--size`, uncommon ratios like `21:9`, or strong Chinese/English text rendering.
 - `qwen-image-max` / `qwen-image-plus` / `qwen-image` only support five fixed sizes: `1664*928`, `1472*1104`, `1328*1328`, `1104*1472`, `928*1664`.
+- `wan2.7-image-pro` and `wan2.7-image` are the only DashScope models that accept `--ref`. Pick one of these when the user wants reference-image editing or multi-image fusion via DashScope.
 - In `baoyu-imagine`, `quality` is a compatibility preset. It is not a native DashScope parameter.
 
 ### Z.AI Model Selection

skills/baoyu-imagine/references/providers/dashscope.md

@@ -17,6 +17,17 @@ Read when the user picks `--provider dashscope`, sets `default_model.dashscope`,
 - Default is `1664*928`
 - `qwen-image` currently has the same capability as `qwen-image-plus`
 
+**`wan2.7-image*`** — multimodal Wan 2.7 family. Members: `wan2.7-image-pro`, `wan2.7-image`.
+
+- Free-form `size` in `宽*高` format, plus aspect-ratio inference
+- `wan2.7-image-pro` text-to-image (no `--ref`): total pixels in `[768*768, 4096*4096]`, ratio in `[1:8, 8:1]`
+- `wan2.7-image-pro` with reference images and `wan2.7-image` (all scenarios): total pixels in `[768*768, 2048*2048]`, ratio in `[1:8, 8:1]`
+- Default: `1024*1024` (`--quality normal`) or `2048*2048` (`--quality 2k`); 4K requires explicit `--size`
+- Supports up to 9 reference images in `--ref` (image editing / multi-image fusion)
+- Reference images are sent inline as base64 (or passed through if the path is an `http(s)://` URL)
+- API does NOT use `prompt_extend`; the skill omits it for this family
+- The Wan 2.7 API defaults `n` to **4** in non-collage mode and bills per generated image. baoyu-imagine forces `n: 1` and rejects `--n > 1` to avoid silently paying for and discarding extra images.
+
 **Legacy** — `z-image-turbo`, `z-image-ultra`, `wanx-v1`. Only use when the user explicitly asks for legacy behavior.
 
 ## Size Resolution
@@ -24,7 +35,8 @@ Read when the user picks `--provider dashscope`, sets `default_model.dashscope`,
 - `--size` wins over `--ar`
 - For `qwen-image-2.0*`: prefer explicit `--size`; otherwise infer from `--ar` using the recommended table below
 - For `qwen-image-max/plus/image`: only use the five fixed sizes; if the requested ratio doesn't fit, switch to `qwen-image-2.0-pro`
-- `--quality` is a baoyu-imagine preset, not an official DashScope field. The mapping of `normal`/`2k` onto the `qwen-image-2.0*` table is an implementation choice, not an API guarantee
+- For `wan2.7-image*`: explicit `--size` is validated against the per-mode pixel/ratio limits; otherwise the size is derived from `--ar` and `--quality` (`normal` ≈ 1K, `2k` ≈ 2K). To request 4K with `wan2.7-image-pro` text-to-image, pass `--size` explicitly (e.g. `4096*4096`, `3840*2160`)
+- `--quality` is a baoyu-imagine preset, not an official DashScope field. The mapping of `normal`/`2k` onto the `qwen-image-2.0*` and `wan2.7-image*` tables is an implementation choice, not an API guarantee
 
 ### Recommended `qwen-image-2.0*` sizes
 
@@ -39,12 +51,19 @@ Read when the user picks `--provider dashscope`, sets `default_model.dashscope`,
 | `16:9` | `1280*720` | `1920*1080` |
 | `21:9` | `1344*576` | `2048*872` |
 
+## Reference Images
+
+- Only `wan2.7-image-pro` and `wan2.7-image` accept `--ref`. Other DashScope models (qwen-image-2.0*, qwen-image-max/plus/image, legacy) reject `--ref` and the user is steered to a different provider/model.
+- Up to 9 reference images per request. Local files are inlined as base64 data URLs; `http(s)://` URLs are forwarded as-is.
+- Supplying any `--ref` automatically clamps the wan2.7-image-pro pixel ceiling from 4K to 2K (the API only supports 4K for pure text-to-image with no image input).
+
 ## Not Exposed
 
-DashScope APIs also support `negative_prompt`, `prompt_extend`, and `watermark`, but `baoyu-imagine` does not expose them as CLI flags today.
+DashScope APIs also support `negative_prompt`, `prompt_extend`, `watermark`, `thinking_mode`, `seed`, `bbox_list`, `enable_sequential`, and `color_palette`. `baoyu-imagine` does not expose them as CLI flags today; the wan2.7 family relies on the API defaults (e.g. `thinking_mode=true`). The skill always sends `n=1` for wan2.7 — if you want grid/collage mode you currently need to call the API directly.
 
 ## Official References
 
 - [Qwen-Image API](https://help.aliyun.com/zh/model-studio/qwen-image-api)
 - [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)
+- [Wan 2.7 image generation & editing API](https://help.aliyun.com/zh/model-studio/wan-image-generation-and-editing-api-reference)

skills/baoyu-imagine/references/usage-examples.md

@@ -51,6 +51,12 @@ ${BUN_X} {baseDir}/scripts/main.ts --prompt "为咖啡品牌设计一张 21:9
 # DashScope legacy fixed-size
 ${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
 
+# DashScope Wan 2.7 Image Pro (4K text-to-image)
+${BUN_X} {baseDir}/scripts/main.ts --prompt "一间有着精致窗户的花店" --image out.png --provider dashscope --model wan2.7-image-pro --size 4096x4096
+
+# DashScope Wan 2.7 Image with reference image (multi-image fusion)
+${BUN_X} {baseDir}/scripts/main.ts --prompt "把图2的涂鸦喷绘在图1的汽车上" --image out.png --provider dashscope --model wan2.7-image-pro --ref car.webp paint.webp
+
 # 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
 

skills/baoyu-imagine/scripts/main.test.ts

@@ -19,6 +19,7 @@ import {
   parseArgs,
   parseOpenAIImageApiDialect,
   parseSimpleYaml,
+  validateReferenceImages,
 } from "./main.ts";
 
 function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
@@ -123,6 +124,15 @@ test("parseArgs falls back to positional prompt and rejects invalid provider", (
   );
 });
 
+test("validateReferenceImages can skip remote URLs for providers that support them", async () => {
+  await validateReferenceImages(["https://example.com/ref.png"], { allowRemoteUrls: true });
+
+  await assert.rejects(
+    () => validateReferenceImages(["https://example.com/ref.png"]),
+    /Reference image not found/,
+  );
+});
+
 test("parseSimpleYaml parses nested defaults and provider limits", () => {
   const yaml = `
 version: 2
@@ -308,7 +318,7 @@ test("detectProvider rejects non-ref-capable providers and prefers Google first
     () =>
       detectProvider(
         makeArgs({
-          provider: "dashscope",
+          provider: "zai",
           referenceImages: ["ref.png"],
         }),
       ),
@@ -426,6 +436,33 @@ test("detectProvider infers Seedream from model id and allows Seedream reference
   );
 });
 
+test("detectProvider allows DashScope reference-image workflows when explicitly chosen for wan2.7 models", (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: "dashscope-key",
+    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({
+        provider: "dashscope",
+        model: "wan2.7-image-pro",
+        referenceImages: ["ref.png"],
+      }),
+    ),
+    "dashscope",
+  );
+});
+
 test("detectProvider selects MiniMax when only MiniMax credentials are configured or the model id matches", (t) => {
   useEnv(t, {
     GOOGLE_API_KEY: null,
@@ -504,7 +541,7 @@ test("loadBatchTasks and createTaskArgs resolve batch-relative paths", async (t)
           id: "hero",
           promptFiles: ["prompts/hero.md"],
           image: "out/hero",
-          ref: ["refs/hero.png"],
+          ref: ["refs/hero.png", "https://example.com/ref.png"],
           ar: "16:9",
         },
       ],
@@ -533,6 +570,7 @@ test("loadBatchTasks and createTaskArgs resolve batch-relative paths", async (t)
   assert.equal(taskArgs.imagePath, path.join(loaded.batchDir, "out/hero"));
   assert.deepEqual(taskArgs.referenceImages, [
     path.join(loaded.batchDir, "refs/hero.png"),
+    "https://example.com/ref.png",
   ]);
   assert.equal(taskArgs.provider, "replicate");
   assert.equal(taskArgs.aspectRatio, "16:9");
@@ -557,5 +595,29 @@ test("path normalization, worker count, and retry classification follow expected
     ),
     false,
   );
+  assert.equal(
+    isRetryableGenerationError(
+      new Error("DashScope wan2.7 image models accept at most 9 reference images. Received 10."),
+    ),
+    false,
+  );
+  assert.equal(
+    isRetryableGenerationError(
+      new Error("DashScope wan2.7 image models in baoyu-imagine support exactly one output image per request."),
+    ),
+    false,
+  );
+  assert.equal(
+    isRetryableGenerationError(
+      new Error("DashScope wan2.7 image models support aspect ratios in [1:8, 8:1]."),
+    ),
+    false,
+  );
+  assert.equal(
+    isRetryableGenerationError(
+      new Error("DashScope wan2.7-image requires total pixels between 768*768 and 2048*2048."),
+    ),
+    false,
+  );
   assert.equal(isRetryableGenerationError(new Error("socket hang up")), true);
 });

skills/baoyu-imagine/scripts/main.ts

@@ -85,7 +85,7 @@ Options:
   --quality normal|2k       Quality preset (default: 2k)
   --imageSize 1K|2K|4K      Image size for Google/OpenRouter (default: from quality)
   --imageApiDialect <id>    OpenAI-compatible image dialect: openai-native|ratio-metadata
-  --ref <files...>          Reference images (Google, OpenAI, Azure, OpenRouter, Replicate supported families, MiniMax, or Seedream 4.0/4.5/5.0)
+  --ref <files...>          Reference images (Google, OpenAI, Azure, OpenRouter, Replicate supported families, MiniMax, Seedream 4.0/4.5/5.0, or DashScope wan2.7-image*)
   --n <count>               Number of images for the current task (default: 1; Replicate currently requires 1)
   --json                    JSON output
   -h, --help                Show help
@@ -698,10 +698,11 @@ export function detectProvider(args: CliArgs): Provider {
     args.provider !== "openrouter" &&
     args.provider !== "replicate" &&
     args.provider !== "seedream" &&
-    args.provider !== "minimax"
+    args.provider !== "minimax" &&
+    args.provider !== "dashscope"
   ) {
     throw new Error(
-      "Reference images require a ref-capable provider. Use --provider google (Gemini multimodal), --provider openai (GPT Image edits), --provider azure (Azure OpenAI), --provider openrouter (OpenRouter multimodal), --provider replicate, --provider seedream for supported Seedream models, or --provider minimax for MiniMax subject-reference workflows."
+      "Reference images require a ref-capable provider. Use --provider google (Gemini multimodal), --provider openai (GPT Image edits), --provider azure (Azure OpenAI), --provider openrouter (OpenRouter multimodal), --provider replicate, --provider dashscope with a wan2.7 image model, --provider seedream for supported Seedream models, or --provider minimax for MiniMax subject-reference workflows."
     );
   }
 
@@ -775,8 +776,24 @@ export function detectProvider(args: CliArgs): Provider {
   );
 }
 
-export async function validateReferenceImages(referenceImages: string[]): Promise<void> {
+export type ReferenceImageValidationOptions = {
+  allowRemoteUrls?: boolean;
+};
+
+function isRemoteReferenceImage(refPath: string): boolean {
+  return /^https?:\/\//i.test(refPath);
+}
+
+function shouldAllowRemoteReferenceImages(provider: Provider | null): boolean {
+  return provider === "dashscope";
+}
+
+export async function validateReferenceImages(
+  referenceImages: string[],
+  options: ReferenceImageValidationOptions = {},
+): Promise<void> {
   for (const refPath of referenceImages) {
+    if (options.allowRemoteUrls && isRemoteReferenceImage(refPath)) continue;
     const fullPath = path.resolve(refPath);
     try {
       await access(fullPath);
@@ -803,6 +820,11 @@ export function isRetryableGenerationError(error: unknown): boolean {
     "API error (404)",
     "temporarily disabled",
     "supports saving exactly one image",
+    "supports only",
+    "support exactly one output image",
+    "support aspect ratios in",
+    "requires total pixels between",
+    "accept at most",
   ];
   return !nonRetryableMarkers.some((marker) => msg.includes(marker));
 }
@@ -858,7 +880,11 @@ async function prepareSingleTask(args: CliArgs, extendConfig: Partial<ExtendConf
   const prompt = (await loadPromptForArgs(args)) ?? (await readPromptFromStdin());
   if (!prompt) throw new Error("Prompt is required");
   if (!args.imagePath) throw new Error("--image is required");
-  if (args.referenceImages.length > 0) await validateReferenceImages(args.referenceImages);
+  if (args.referenceImages.length > 0) {
+    await validateReferenceImages(args.referenceImages, {
+      allowRemoteUrls: shouldAllowRemoteReferenceImages(args.provider),
+    });
+  }
 
   const provider = detectProvider(args);
   const providerModule = await loadProviderModule(provider);
@@ -907,6 +933,10 @@ export function resolveBatchPath(batchDir: string, filePath: string): string {
   return path.isAbsolute(filePath) ? filePath : path.resolve(batchDir, filePath);
 }
 
+function resolveBatchReferencePath(batchDir: string, filePath: string): string {
+  return isRemoteReferenceImage(filePath) ? filePath : resolveBatchPath(batchDir, filePath);
+}
+
 export function createTaskArgs(baseArgs: CliArgs, task: BatchTaskInput, batchDir: string): CliArgs {
   return {
     ...baseArgs,
@@ -922,7 +952,7 @@ export function createTaskArgs(baseArgs: CliArgs, task: BatchTaskInput, batchDir
     imageSize: task.imageSize ?? baseArgs.imageSize ?? null,
     imageSizeSource: task.imageSize != null ? "task" : (baseArgs.imageSizeSource ?? null),
     imageApiDialect: task.imageApiDialect ?? baseArgs.imageApiDialect ?? null,
-    referenceImages: task.ref ? task.ref.map((filePath) => resolveBatchPath(batchDir, filePath)) : [],
+    referenceImages: task.ref ? task.ref.map((filePath) => resolveBatchReferencePath(batchDir, filePath)) : [],
     n: task.n ?? baseArgs.n,
     batchFile: null,
     jobs: baseArgs.jobs,
@@ -946,7 +976,11 @@ async function prepareBatchTasks(
     const prompt = await loadPromptForArgs(taskArgs);
     if (!prompt) throw new Error(`Task ${i + 1} is missing prompt or promptFiles.`);
     if (!taskArgs.imagePath) throw new Error(`Task ${i + 1} is missing image output path.`);
-    if (taskArgs.referenceImages.length > 0) await validateReferenceImages(taskArgs.referenceImages);
+    if (taskArgs.referenceImages.length > 0) {
+      await validateReferenceImages(taskArgs.referenceImages, {
+        allowRemoteUrls: shouldAllowRemoteReferenceImages(taskArgs.provider),
+      });
+    }
 
     const provider = detectProvider(taskArgs);
     const providerModule = await loadProviderModule(provider);

skills/baoyu-imagine/scripts/providers/dashscope.test.ts

@@ -2,15 +2,42 @@ import assert from "node:assert/strict";
 import test, { type TestContext } from "node:test";
 
 import {
+  generateImage,
   getDefaultModel,
   getModelFamily,
   getQwen2SizeFromAspectRatio,
   getSizeFromAspectRatio,
+  getWan27SizeFromAspectRatio,
   normalizeSize,
   parseAspectRatio,
   parseSize,
   resolveSizeForModel,
 } from "./dashscope.ts";
+import type { CliArgs } from "../types.ts";
+
+function makeCliArgs(overrides: Partial<CliArgs> = {}): CliArgs {
+  return {
+    prompt: null,
+    promptFiles: [],
+    imagePath: null,
+    provider: "dashscope",
+    model: null,
+    aspectRatio: null,
+    aspectRatioSource: null,
+    size: null,
+    quality: "2k",
+    imageSize: null,
+    imageSizeSource: null,
+    imageApiDialect: null,
+    referenceImages: [],
+    n: 1,
+    batchFile: null,
+    jobs: null,
+    json: false,
+    help: false,
+    ...overrides,
+  };
+}
 
 function useEnv(
   t: TestContext,
@@ -51,9 +78,11 @@ test("DashScope aspect-ratio parsing accepts numeric ratios only", () => {
   assert.equal(parseAspectRatio("-1:2"), null);
 });
 
-test("DashScope model family routing distinguishes qwen-2.0, fixed-size qwen, and legacy models", () => {
+test("DashScope model family routing distinguishes qwen-2.0, fixed-size qwen, wan2.7, and legacy models", () => {
   assert.equal(getModelFamily("qwen-image-2.0-pro"), "qwen2");
   assert.equal(getModelFamily("qwen-image"), "qwenFixed");
+  assert.equal(getModelFamily("wan2.7-image"), "wan27");
+  assert.equal(getModelFamily("wan2.7-image-pro"), "wan27");
   assert.equal(getModelFamily("z-image-turbo"), "legacy");
   assert.equal(getModelFamily("wanx-v1"), "legacy");
 });
@@ -146,3 +175,218 @@ test("DashScope size normalization converts WxH into provider format", () => {
   assert.equal(normalizeSize("1024x1024"), "1024*1024");
   assert.equal(normalizeSize("2048*1152"), "2048*1152");
 });
+
+test("Wan 2.7 derives sizes that match the requested ratio at the chosen pixel budget", () => {
+  const square2k = getWan27SizeFromAspectRatio(null, "2k", 2048 * 2048);
+  const parsedSquare = parseSize(square2k);
+  assert.ok(parsedSquare);
+  assert.equal(parsedSquare.width, parsedSquare.height);
+  assert.ok(parsedSquare.width * parsedSquare.height <= 2048 * 2048);
+
+  const widescreen = getWan27SizeFromAspectRatio("16:9", "2k", 2048 * 2048);
+  const parsedWide = parseSize(widescreen);
+  assert.ok(parsedWide);
+  assert.ok(Math.abs(parsedWide.width / parsedWide.height - 16 / 9) < 0.05);
+  assert.ok(parsedWide.width * parsedWide.height <= 2048 * 2048);
+
+  const pro4k = getWan27SizeFromAspectRatio("16:9", "2k", 4096 * 4096);
+  const parsed4k = parseSize(pro4k);
+  assert.ok(parsed4k);
+  assert.ok(parsed4k.width * parsed4k.height > 2048 * 2048);
+  assert.ok(parsed4k.width * parsed4k.height <= 4096 * 4096);
+});
+
+test("Wan 2.7 rejects aspect ratios outside the [1:8, 8:1] range", () => {
+  assert.throws(
+    () => getWan27SizeFromAspectRatio("9:1", "2k", 2048 * 2048),
+    /1:8, 8:1/,
+  );
+  assert.throws(
+    () => getWan27SizeFromAspectRatio("1:9", "normal", 2048 * 2048),
+    /1:8, 8:1/,
+  );
+});
+
+test("Wan 2.7 derived sizes stay inside the boundary ratio limits after rounding", () => {
+  for (const ar of ["8:1", "1:8"]) {
+    const size = getWan27SizeFromAspectRatio(ar, "2k", 2048 * 2048);
+    const parsed = parseSize(size);
+    assert.ok(parsed);
+    const ratio = parsed.width / parsed.height;
+    assert.ok(ratio >= 1 / 8);
+    assert.ok(ratio <= 8);
+    assert.ok(parsed.width * parsed.height <= 2048 * 2048);
+  }
+});
+
+test("resolveSizeForModel routes wan2.7-image to the 2K-capped derivation", () => {
+  const size = resolveSizeForModel("wan2.7-image", {
+    size: null,
+    aspectRatio: "16:9",
+    quality: "2k",
+  });
+  const parsed = parseSize(size);
+  assert.ok(parsed);
+  assert.ok(parsed.width * parsed.height <= 2048 * 2048);
+  assert.ok(Math.abs(parsed.width / parsed.height - 16 / 9) < 0.05);
+});
+
+test("resolveSizeForModel allows wan2.7-image-pro 4K only when there are no reference images", () => {
+  assert.equal(
+    resolveSizeForModel("wan2.7-image-pro", {
+      size: "4096*4096",
+      aspectRatio: null,
+      quality: "2k",
+    }),
+    "4096*4096",
+  );
+
+  assert.throws(
+    () =>
+      resolveSizeForModel("wan2.7-image-pro", {
+        size: "4096*4096",
+        aspectRatio: null,
+        quality: "2k",
+        referenceImages: ["a.png"],
+      }),
+    /total pixels between 768\*768 and 2048\*2048/,
+  );
+
+  const proWithRef = resolveSizeForModel("wan2.7-image-pro", {
+    size: null,
+    aspectRatio: "1:1",
+    quality: "2k",
+    referenceImages: ["a.png"],
+  });
+  const parsedRef = parseSize(proWithRef);
+  assert.ok(parsedRef);
+  assert.ok(parsedRef.width * parsedRef.height <= 2048 * 2048);
+});
+
+test("Wan 2.7 request body forces n=1 and omits prompt_extend / negative_prompt", async (t) => {
+  useEnv(t, { DASHSCOPE_API_KEY: "fake-key" });
+
+  const originalFetch = globalThis.fetch;
+  let capturedBody: any = null;
+  globalThis.fetch = (async (_url: string, init?: RequestInit) => {
+    capturedBody = JSON.parse(String(init?.body));
+    return new Response(
+      JSON.stringify({
+        output: {
+          choices: [
+            {
+              message: {
+                content: [{ image: "data:image/png;base64,iVBORw0KGgo=" }],
+              },
+            },
+          ],
+        },
+      }),
+      { status: 200, headers: { "content-type": "application/json" } },
+    );
+  }) as typeof fetch;
+  t.after(() => {
+    globalThis.fetch = originalFetch;
+  });
+
+  await generateImage("hello", "wan2.7-image-pro", makeCliArgs({ aspectRatio: "1:1" }));
+
+  assert.equal(capturedBody.model, "wan2.7-image-pro");
+  assert.deepEqual(Object.keys(capturedBody.parameters).sort(), ["n", "size", "watermark"]);
+  assert.equal(capturedBody.parameters.n, 1);
+  assert.equal(capturedBody.parameters.watermark, false);
+  assert.equal(typeof capturedBody.parameters.size, "string");
+  assert.ok(!("prompt_extend" in capturedBody.parameters));
+  assert.ok(!("negative_prompt" in capturedBody.parameters));
+
+  assert.deepEqual(capturedBody.input.messages[0].content, [{ text: "hello" }]);
+});
+
+test("Wan 2.7 request body forwards remote reference image URLs", async (t) => {
+  useEnv(t, { DASHSCOPE_API_KEY: "fake-key" });
+
+  const originalFetch = globalThis.fetch;
+  let capturedBody: any = null;
+  globalThis.fetch = (async (_url: string, init?: RequestInit) => {
+    capturedBody = JSON.parse(String(init?.body));
+    return new Response(
+      JSON.stringify({
+        output: {
+          choices: [
+            {
+              message: {
+                content: [{ image: "data:image/png;base64,iVBORw0KGgo=" }],
+              },
+            },
+          ],
+        },
+      }),
+      { status: 200, headers: { "content-type": "application/json" } },
+    );
+  }) as typeof fetch;
+  t.after(() => {
+    globalThis.fetch = originalFetch;
+  });
+
+  await generateImage(
+    "combine these",
+    "wan2.7-image-pro",
+    makeCliArgs({ referenceImages: ["https://example.com/ref.png"] }),
+  );
+
+  assert.deepEqual(capturedBody.input.messages[0].content, [
+    { image: "https://example.com/ref.png" },
+    { text: "combine these" },
+  ]);
+});
+
+test("Wan 2.7 rejects --n > 1 to prevent silent multi-image billing", async (t) => {
+  useEnv(t, { DASHSCOPE_API_KEY: "fake-key" });
+
+  await assert.rejects(
+    () => generateImage("hi", "wan2.7-image-pro", makeCliArgs({ n: 2 })),
+    /support exactly one output image/,
+  );
+});
+
+test("resolveSizeForModel validates explicit wan2.7 sizes by pixel budget and ratio", () => {
+  assert.equal(
+    resolveSizeForModel("wan2.7-image-pro", {
+      size: "3840x2160",
+      aspectRatio: null,
+      quality: "2k",
+    }),
+    "3840*2160",
+  );
+
+  assert.throws(
+    () =>
+      resolveSizeForModel("wan2.7-image-pro", {
+        size: "3840x2160",
+        aspectRatio: null,
+        quality: "2k",
+        referenceImages: ["a.png"],
+      }),
+    /total pixels between 768\*768 and 2048\*2048/,
+  );
+
+  assert.throws(
+    () =>
+      resolveSizeForModel("wan2.7-image", {
+        size: "4096x4096",
+        aspectRatio: null,
+        quality: "2k",
+      }),
+    /total pixels between 768\*768 and 2048\*2048/,
+  );
+
+  assert.throws(
+    () =>
+      resolveSizeForModel("wan2.7-image-pro", {
+        size: "3072*256",
+        aspectRatio: null,
+        quality: "2k",
+      }),
+    /1:8, 8:1/,
+  );
+});

skills/baoyu-imagine/scripts/providers/dashscope.ts

@@ -1,6 +1,8 @@
+import path from "node:path";
+import { readFile } from "node:fs/promises";
 import type { CliArgs, Quality } from "../types";
 
-type DashScopeModelFamily = "qwen2" | "qwenFixed" | "legacy";
+type DashScopeModelFamily = "qwen2" | "qwenFixed" | "wan27" | "legacy";
 
 type DashScopeModelSpec = {
   family: DashScopeModelFamily;
@@ -19,6 +21,16 @@ const QWEN_2_TARGET_PIXELS: Record<Quality, number> = {
   "2k": 1536 * 1536,
 };
 
+const MIN_WAN27_TOTAL_PIXELS = 768 * 768;
+const MAX_WAN27_PRO_T2I_PIXELS = 4096 * 4096;
+const MAX_WAN27_GENERAL_PIXELS = 2048 * 2048;
+const WAN27_MAX_REFERENCE_IMAGES = 9;
+
+const WAN27_TARGET_PIXELS: Record<Quality, number> = {
+  normal: 1024 * 1024,
+  "2k": 2048 * 2048,
+};
+
 const QWEN_2_RECOMMENDED: Record<string, Record<Quality, string>> = {
   "1:1": { normal: "1024*1024", "2k": "1536*1536" },
   "2:3": { normal: "768*1152", "2k": "1024*1536" },
@@ -73,6 +85,11 @@ const QWEN_FIXED_SPEC: DashScopeModelSpec = {
   defaultSize: QWEN_FIXED_SIZES_BY_RATIO["16:9"],
 };
 
+const WAN27_SPEC: DashScopeModelSpec = {
+  family: "wan27",
+  defaultSize: "2048*2048",
+};
+
 const LEGACY_SPEC: DashScopeModelSpec = {
   family: "legacy",
   defaultSize: "1536*1536",
@@ -88,12 +105,31 @@ const MODEL_SPEC_ALIASES: Record<string, DashScopeModelSpec> = {
   "qwen-image-plus": QWEN_FIXED_SPEC,
   "qwen-image-plus-2026-01-09": QWEN_FIXED_SPEC,
   "qwen-image": QWEN_FIXED_SPEC,
+  "wan2.7-image-pro": WAN27_SPEC,
+  "wan2.7-image": WAN27_SPEC,
 };
 
 export function getDefaultModel(): string {
   return process.env.DASHSCOPE_IMAGE_MODEL || DEFAULT_MODEL;
 }
 
+function getReferenceImageMime(filePath: string): string {
+  const ext = path.extname(filePath).toLowerCase();
+  if (ext === ".jpg" || ext === ".jpeg") return "image/jpeg";
+  if (ext === ".webp") return "image/webp";
+  if (ext === ".bmp") return "image/bmp";
+  return "image/png";
+}
+
+async function loadReferenceImage(refPath: string): Promise<string> {
+  if (/^https?:\/\//i.test(refPath)) {
+    return refPath;
+  }
+  const fullPath = path.resolve(refPath);
+  const bytes = await readFile(fullPath);
+  return `data:${getReferenceImageMime(fullPath)};base64,${bytes.toString("base64")}`;
+}
+
 function getApiKey(): string | null {
   return process.env.DASHSCOPE_API_KEY || null;
 }
@@ -173,6 +209,10 @@ function roundToStep(value: number): number {
   return Math.max(SIZE_STEP, Math.round(value / SIZE_STEP) * SIZE_STEP);
 }
 
+function floorToStep(value: number): number {
+  return Math.max(SIZE_STEP, Math.floor(value / SIZE_STEP) * SIZE_STEP);
+}
+
 function fitToPixelBudget(
   width: number,
   height: number,
@@ -220,6 +260,21 @@ function fitToPixelBudget(
   return { width: roundedWidth, height: roundedHeight };
 }
 
+function clampWan27DerivedSizeToRatioBounds(
+  size: { width: number; height: number },
+): { width: number; height: number } {
+  let { width, height } = size;
+  const ratio = width / height;
+
+  if (ratio > 8) {
+    width = floorToStep(height * 8);
+  } else if (ratio < 1 / 8) {
+    height = floorToStep(width * 8);
+  }
+
+  return { width, height };
+}
+
 export function getSizeFromAspectRatio(ar: string | null, quality: CliArgs["quality"]): string {
   const normalizedQuality = normalizeQuality(quality);
   const sizes = normalizedQuality === "2k" ? LEGACY_STANDARD_SIZES_2K : LEGACY_STANDARD_SIZES;
@@ -276,6 +331,77 @@ export function getQwen2SizeFromAspectRatio(ar: string | null, quality: CliArgs[
   return formatSize(fitted.width, fitted.height);
 }
 
+function isWan27ProModel(model: string): boolean {
+  return model.trim().toLowerCase() === "wan2.7-image-pro";
+}
+
+function getWan27MaxPixels(model: string, hasReferenceImages: boolean): number {
+  if (isWan27ProModel(model) && !hasReferenceImages) {
+    return MAX_WAN27_PRO_T2I_PIXELS;
+  }
+  return MAX_WAN27_GENERAL_PIXELS;
+}
+
+export function getWan27SizeFromAspectRatio(
+  ar: string | null,
+  quality: CliArgs["quality"],
+  maxPixels: number,
+): string {
+  const normalizedQuality = normalizeQuality(quality);
+  const targetPixels = Math.min(WAN27_TARGET_PIXELS[normalizedQuality], maxPixels);
+
+  if (!ar) {
+    const side = roundToStep(Math.sqrt(targetPixels));
+    return formatSize(side, side);
+  }
+
+  const parsed = parseAspectRatio(ar);
+  if (!parsed) {
+    const side = roundToStep(Math.sqrt(targetPixels));
+    return formatSize(side, side);
+  }
+
+  const ratio = parsed.width / parsed.height;
+  if (ratio < 1 / 8 || ratio > 8) {
+    throw new Error(
+      `DashScope wan2.7 image models support aspect ratios in [1:8, 8:1]. Received "${ar}".`
+    );
+  }
+
+  const rawWidth = Math.sqrt(targetPixels * ratio);
+  const rawHeight = Math.sqrt(targetPixels / ratio);
+  const fitted = fitToPixelBudget(
+    rawWidth,
+    rawHeight,
+    MIN_WAN27_TOTAL_PIXELS,
+    maxPixels,
+  );
+  const bounded = clampWan27DerivedSizeToRatioBounds(fitted);
+
+  return formatSize(bounded.width, bounded.height);
+}
+
+function validateWan27Size(size: string, maxPixels: number, model: string): string {
+  const normalized = normalizeSize(size);
+  const parsed = validateSizeFormat(normalized);
+  const totalPixels = parsed.width * parsed.height;
+  if (totalPixels < MIN_WAN27_TOTAL_PIXELS || totalPixels > maxPixels) {
+    const limit = maxPixels === MAX_WAN27_PRO_T2I_PIXELS ? "4096*4096" : "2048*2048";
+    throw new Error(
+      `DashScope ${model} requires total pixels between 768*768 and ${limit} ` +
+      `for the current request. Received ${normalized} (${totalPixels} pixels).`
+    );
+  }
+  const ratio = parsed.width / parsed.height;
+  if (ratio < 1 / 8 || ratio > 8) {
+    throw new Error(
+      `DashScope wan2.7 image models support aspect ratios in [1:8, 8:1]. ` +
+      `Received ${normalized} (ratio ${ratio.toFixed(3)}).`
+    );
+  }
+  return normalized;
+}
+
 function getQwenFixedSizeFromAspectRatio(ar: string | null, quality: CliArgs["quality"]): string {
   if (quality === "normal") {
     console.warn(
@@ -331,9 +457,16 @@ function validateQwenFixedSize(size: string): string {
 
 export function resolveSizeForModel(
   model: string,
-  args: Pick<CliArgs, "size" | "aspectRatio" | "quality">,
+  args: Pick<CliArgs, "size" | "aspectRatio" | "quality"> & { referenceImages?: string[] },
 ): string {
   const spec = getModelSpec(model);
+  const referenceCount = args.referenceImages?.length ?? 0;
+
+  if (spec.family === "wan27") {
+    const maxPixels = getWan27MaxPixels(model, referenceCount > 0);
+    if (args.size) return validateWan27Size(args.size, maxPixels, model);
+    return getWan27SizeFromAspectRatio(args.aspectRatio, args.quality, maxPixels);
+  }
 
   if (args.size) {
     if (spec.family === "qwen2") return validateQwen2Size(args.size);
@@ -357,6 +490,14 @@ function buildParameters(
   family: DashScopeModelFamily,
   size: string,
 ): Record<string, unknown> {
+  if (family === "wan27") {
+    return {
+      size,
+      n: 1,
+      watermark: false,
+    };
+  }
+
   const parameters: Record<string, unknown> = {
     prompt_extend: false,
     size,
@@ -419,23 +560,44 @@ export async function generateImage(
   const apiKey = getApiKey();
   if (!apiKey) throw new Error("DASHSCOPE_API_KEY is required");
 
-  if (args.referenceImages.length > 0) {
+  const spec = getModelSpec(model);
+
+  if (args.referenceImages.length > 0 && spec.family !== "wan27") {
     throw new Error(
-      "Reference images are not supported with DashScope provider in baoyu-imagine. Use --provider google with a Gemini multimodal model."
+      "Reference images are not supported with this DashScope model. Use a wan2.7 image model (--model wan2.7-image-pro or wan2.7-image), or switch to --provider google with a Gemini multimodal model."
+    );
+  }
+
+  if (args.referenceImages.length > WAN27_MAX_REFERENCE_IMAGES) {
+    throw new Error(
+      `DashScope wan2.7 image models accept at most ${WAN27_MAX_REFERENCE_IMAGES} reference images. Received ${args.referenceImages.length}.`
+    );
+  }
+
+  if (spec.family === "wan27" && args.n !== 1) {
+    throw new Error(
+      "DashScope wan2.7 image models in baoyu-imagine support exactly one output image per request (extra images would be billed but discarded). Remove --n or use --n 1."
     );
   }
 
-  const spec = getModelSpec(model);
   const size = resolveSizeForModel(model, args);
   const url = `${getBaseUrl()}/api/v1/services/aigc/multimodal-generation/generation`;
 
+  const content: Array<Record<string, unknown>> = [];
+  if (spec.family === "wan27" && args.referenceImages.length > 0) {
+    for (const refPath of args.referenceImages) {
+      content.push({ image: await loadReferenceImage(refPath) });
+    }
+  }
+  content.push({ text: prompt });
+
   const body = {
     model,
     input: {
       messages: [
         {
           role: "user",
-          content: [{ text: prompt }],
+          content,
         },
       ],
     },