feat(baoyu-imagine): add schema-aware Replicate model family support

README.md

@@ -768,7 +768,7 @@ AI SDK-based image generation using OpenAI, Azure OpenAI, Google, OpenRouter, Da
 | `GOOGLE_IMAGE_MODEL` | Google model | `gemini-3-pro-image-preview` |
 | `DASHSCOPE_IMAGE_MODEL` | DashScope model | `qwen-image-2.0-pro` |
 | `MINIMAX_IMAGE_MODEL` | MiniMax model | `image-01` |
-| `REPLICATE_IMAGE_MODEL` | Replicate model | `google/nano-banana-pro` |
+| `REPLICATE_IMAGE_MODEL` | Replicate model | `google/nano-banana-2` |
 | `JIMENG_IMAGE_MODEL` | Jimeng model | `jimeng_t2i_v40` |
 | `SEEDREAM_IMAGE_MODEL` | Seedream model | `doubao-seedream-5-0-260128` |
 | `OPENAI_BASE_URL` | Custom OpenAI endpoint | - |
@@ -1108,7 +1108,7 @@ MINIMAX_IMAGE_MODEL=image-01
 
 # Replicate
 REPLICATE_API_TOKEN=r8_xxx
-REPLICATE_IMAGE_MODEL=google/nano-banana-pro
+REPLICATE_IMAGE_MODEL=google/nano-banana-2
 # REPLICATE_BASE_URL=https://api.replicate.com
 
 # Jimeng (即梦)

README.zh.md

@@ -768,7 +768,7 @@ AI 驱动的生成后端。
 | `GOOGLE_IMAGE_MODEL` | Google 模型 | `gemini-3-pro-image-preview` |
 | `DASHSCOPE_IMAGE_MODEL` | DashScope 模型 | `qwen-image-2.0-pro` |
 | `MINIMAX_IMAGE_MODEL` | MiniMax 模型 | `image-01` |
-| `REPLICATE_IMAGE_MODEL` | Replicate 模型 | `google/nano-banana-pro` |
+| `REPLICATE_IMAGE_MODEL` | Replicate 模型 | `google/nano-banana-2` |
 | `JIMENG_IMAGE_MODEL` | 即梦模型 | `jimeng_t2i_v40` |
 | `SEEDREAM_IMAGE_MODEL` | 豆包模型 | `doubao-seedream-5-0-260128` |
 | `OPENAI_BASE_URL` | 自定义 OpenAI 端点 | - |
@@ -1108,7 +1108,7 @@ MINIMAX_IMAGE_MODEL=image-01
 
 # Replicate
 REPLICATE_API_TOKEN=r8_xxx
-REPLICATE_IMAGE_MODEL=google/nano-banana-pro
+REPLICATE_IMAGE_MODEL=google/nano-banana-2
 # REPLICATE_BASE_URL=https://api.replicate.com
 
 # 即梦（Jimeng）

skills/baoyu-imagine/SKILL.md

@@ -112,7 +112,7 @@ ${BUN_X} {baseDir}/scripts/main.ts --prompt "A girl stands by the library window
 # MiniMax with custom size (documented for image-01)
 ${BUN_X} {baseDir}/scripts/main.ts --prompt "A cinematic poster" --image out.jpg --provider minimax --model image-01 --size 1536x1024
 
-# Replicate (google/nano-banana-pro)
+# Replicate (google/nano-banana-2)
 ${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate
 
 # Replicate with specific model
@@ -136,7 +136,7 @@ ${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4 --json
       "promptFiles": ["prompts/hero.md"],
       "image": "out/hero.png",
       "provider": "replicate",
-      "model": "google/nano-banana-pro",
+      "model": "google/nano-banana-2",
       "ar": "16:9",
       "quality": "2k"
     },
@@ -192,7 +192,7 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
 | `GOOGLE_IMAGE_MODEL` | Google model override |
 | `DASHSCOPE_IMAGE_MODEL` | DashScope model override (default: `qwen-image-2.0-pro`) |
 | `MINIMAX_IMAGE_MODEL` | MiniMax model override (default: `image-01`) |
-| `REPLICATE_IMAGE_MODEL` | Replicate model override (default: google/nano-banana-pro) |
+| `REPLICATE_IMAGE_MODEL` | Replicate model override (default: google/nano-banana-2) |
 | `JIMENG_IMAGE_MODEL` | Jimeng model override (default: jimeng_t2i_v40) |
 | `SEEDREAM_IMAGE_MODEL` | Seedream model override (default: doubao-seedream-5-0-260128) |
 | `OPENAI_BASE_URL` | Custom OpenAI endpoint |
@@ -324,7 +324,7 @@ Notes:
 
 Supported model formats:
 
-- `owner/name` (recommended for official models), e.g. `google/nano-banana-pro`
+- `owner/name` (recommended for official models), e.g. `google/nano-banana-2`
 - `owner/name:version` (community models by version), e.g. `stability-ai/sdxl:<version>`
 
 Examples:

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

@@ -56,7 +56,7 @@ options:
   - label: "MiniMax"
     description: "MiniMax image generation with subject-reference character workflows"
   - label: "Replicate"
-    description: "Community models - nano-banana-pro, flexible model selection"
+    description: "Community models - nano-banana-2, flexible model selection"
 ```
 
 ### Question 2: Default Google Model
@@ -263,7 +263,7 @@ Notes for DashScope setup:
 header: "Replicate Model"
 question: "Choose a default Replicate image generation model?"
 options:
-  - label: "google/nano-banana-pro (Recommended)"
+  - label: "google/nano-banana-2 (Recommended)"
     description: "Google's fast image model on Replicate"
   - label: "google/nano-banana"
     description: "Google's base image model on Replicate"

skills/baoyu-imagine/references/config/preferences-schema.md

@@ -26,7 +26,7 @@ default_model:
   openrouter: null          # e.g., "google/gemini-3.1-flash-image-preview"
   dashscope: null           # e.g., "qwen-image-2.0-pro"
   minimax: null             # e.g., "image-01"
-  replicate: null           # e.g., "google/nano-banana-pro"
+  replicate: null           # e.g., "google/nano-banana-2"
 
 batch:
   max_workers: 10
@@ -101,7 +101,7 @@ default_model:
   openrouter: "google/gemini-3.1-flash-image-preview"
   dashscope: "qwen-image-2.0-pro"
   minimax: "image-01"
-  replicate: "google/nano-banana-pro"
+  replicate: "google/nano-banana-2"
 batch:
   max_workers: 10
   provider_limits:

skills/baoyu-imagine/scripts/main.ts

@@ -96,7 +96,7 @@ Batch file format:
         "promptFiles": ["prompts/hero.md"],
         "image": "out/hero.png",
         "provider": "replicate",
-        "model": "google/nano-banana-pro",
+        "model": "google/nano-banana-2",
         "ar": "16:9"
       }
     ]
@@ -123,7 +123,7 @@ Environment variables:
   GOOGLE_IMAGE_MODEL        Default Google model (gemini-3-pro-image-preview)
   DASHSCOPE_IMAGE_MODEL     Default DashScope model (qwen-image-2.0-pro)
   MINIMAX_IMAGE_MODEL       Default MiniMax model (image-01)
-  REPLICATE_IMAGE_MODEL     Default Replicate model (google/nano-banana-pro)
+  REPLICATE_IMAGE_MODEL     Default Replicate model (google/nano-banana-2)
   JIMENG_IMAGE_MODEL        Default Jimeng model (jimeng_t2i_v40)
   SEEDREAM_IMAGE_MODEL      Default Seedream model (doubao-seedream-5-0-260128)
   OPENAI_BASE_URL           Custom OpenAI endpoint

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

@@ -5,7 +5,9 @@ import type { CliArgs } from "../types.ts";
 import {
   buildInput,
   extractOutputUrl,
+  generateImage,
   parseModelId,
+  validateArgs,
 } from "./replicate.ts";
 
 function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
@@ -47,21 +49,20 @@ test("Replicate model parsing accepts official formats and rejects malformed one
   );
 });
 
-test("Replicate input builder maps aspect ratio, image count, quality, and refs", () => {
+test("Replicate input builder keeps nano-banana mapping for compatible models", () => {
   assert.deepEqual(
     buildInput(
       "A robot painter",
+      "google/nano-banana-2",
       makeArgs({
         aspectRatio: "16:9",
         quality: "2k",
-        n: 3,
       }),
       ["data:image/png;base64,AAAA"],
     ),
     {
       prompt: "A robot painter",
       aspect_ratio: "16:9",
-      number_of_images: 3,
       resolution: "2K",
       output_format: "png",
       image_input: ["data:image/png;base64,AAAA"],
@@ -69,7 +70,7 @@ test("Replicate input builder maps aspect ratio, image count, quality, and refs"
   );
 
   assert.deepEqual(
-    buildInput("A robot painter", makeArgs({ quality: "normal" }), ["ref"]),
+    buildInput("A robot painter", "google/nano-banana-pro", makeArgs({ quality: "normal" }), ["ref"]),
     {
       prompt: "A robot painter",
       aspect_ratio: "match_input_image",
@@ -80,6 +81,146 @@ test("Replicate input builder maps aspect ratio, image count, quality, and refs"
   );
 });
 
+test("Replicate input builder maps Seedream models to size-based schema", () => {
+  assert.deepEqual(
+    buildInput(
+      "A robot painter",
+      "bytedance/seedream-4.5",
+      makeArgs({
+        quality: "2k",
+        aspectRatio: "16:9",
+        n: 4,
+      }),
+      ["data:image/png;base64,AAAA"],
+    ),
+    {
+      prompt: "A robot painter",
+      size: "2K",
+      aspect_ratio: "16:9",
+      sequential_image_generation: "auto",
+      max_images: 4,
+      image_input: ["data:image/png;base64,AAAA"],
+    },
+  );
+
+  assert.deepEqual(
+    buildInput(
+      "A robot painter",
+      "bytedance/seedream-5-lite",
+      makeArgs({
+        size: "3K",
+        aspectRatio: "4:3",
+      }),
+      [],
+    ),
+    {
+      prompt: "A robot painter",
+      size: "3K",
+      aspect_ratio: "4:3",
+      output_format: "png",
+    },
+  );
+});
+
+test("Replicate input builder maps Wan models to their native schema", () => {
+  assert.deepEqual(
+    buildInput(
+      "A robot painter",
+      "wan-video/wan-2.7-image-pro",
+      makeArgs({
+        quality: "2k",
+        n: 2,
+      }),
+      ["data:image/png;base64,AAAA"],
+    ),
+    {
+      prompt: "A robot painter",
+      size: "2K",
+      num_outputs: 2,
+      images: ["data:image/png;base64,AAAA"],
+    },
+  );
+
+  assert.deepEqual(
+    buildInput(
+      "A robot painter",
+      "wan-video/wan-2.7-image",
+      makeArgs({
+        size: "2048x1152",
+      }),
+      [],
+    ),
+    {
+      prompt: "A robot painter",
+      size: "2048*1152",
+      thinking_mode: true,
+    },
+  );
+});
+
+test("Replicate input builder falls back to nano-banana schema for unknown models", () => {
+  assert.deepEqual(
+    buildInput(
+      "A robot painter",
+      "unknown-owner/unknown-model",
+      makeArgs({
+        aspectRatio: "16:9",
+        quality: "2k",
+      }),
+      ["ref"],
+    ),
+    {
+      prompt: "A robot painter",
+      aspect_ratio: "16:9",
+      resolution: "2K",
+      output_format: "png",
+      image_input: ["ref"],
+    },
+  );
+});
+
+test("Replicate validation catches unsupported Seedream and Wan argument combinations", () => {
+  assert.throws(
+    () => validateArgs("bytedance/seedream-4.5", makeArgs({ size: "large" })),
+    /Seedream on Replicate requires --size/,
+  );
+
+  assert.throws(
+    () => validateArgs("bytedance/seedream-5-lite", makeArgs({ size: "4K" })),
+    /Seedream on Replicate requires --size to be one of 2K, 3K/,
+  );
+
+  assert.throws(
+    () => validateArgs("google/nano-banana-2", makeArgs({ n: 2 })),
+    /Nano Banana models on Replicate do not support --n yet/,
+  );
+
+  assert.throws(
+    () => validateArgs("wan-video/wan-2.7-image-pro", makeArgs({ aspectRatio: "16:9" })),
+    /Wan image models on Replicate require --size when using --ar/,
+  );
+
+  assert.throws(
+    () => validateArgs("wan-video/wan-2.7-image", makeArgs({ size: "wide" })),
+    /Wan image models on Replicate require --size/,
+  );
+
+  assert.throws(
+    () => validateArgs("wan-video/wan-2.7-image", makeArgs({ size: "4K" })),
+    /Wan image models on Replicate require --size to be one of/,
+  );
+
+  assert.throws(
+    () => validateArgs("wan-video/wan-2.7-image-pro", makeArgs({ size: "4K", referenceImages: ["ref"] })),
+    /only supports 4K for text-to-image requests without input images/,
+  );
+
+  assert.throws(
+    () => validateArgs("wan-video/wan-2.7-image-pro", makeArgs({ n: 5 })),
+    /support --n values from 1 to 4/,
+  );
+});
+
 test("Replicate output extraction supports string, array, and object URLs", () => {
   assert.equal(
     extractOutputUrl({ output: "https://example.com/a.png" } as never),
@@ -99,3 +240,25 @@ test("Replicate output extraction supports string, array, and object URLs", () =
     /Unexpected Replicate output format/,
   );
 });
+
+test("Replicate generateImage validates arguments before making API requests", async () => {
+  const previousToken = process.env.REPLICATE_API_TOKEN;
+  process.env.REPLICATE_API_TOKEN = "test-token";
+
+  try {
+    await assert.rejects(
+      generateImage(
+        "A robot painter",
+        "wan-video/wan-2.7-image-pro",
+        makeArgs({ aspectRatio: "16:9" }),
+      ),
+      /Wan image models on Replicate require --size when using --ar/,
+    );
+  } finally {
+    if (previousToken === undefined) {
+      delete process.env.REPLICATE_API_TOKEN;
+    } else {
+      process.env.REPLICATE_API_TOKEN = previousToken;
+    }
+  }
+});

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

@@ -2,10 +2,31 @@ import path from "node:path";
 import { readFile } from "node:fs/promises";
 import type { CliArgs } from "../types";
 
-const DEFAULT_MODEL = "google/nano-banana-pro";
+const DEFAULT_MODEL = "google/nano-banana-2";
 const SYNC_WAIT_SECONDS = 60;
 const POLL_INTERVAL_MS = 2000;
 const MAX_POLL_MS = 300_000;
+const SIZE_PRESET_PATTERN = /^\d+K$/i;
+const SEEDREAM_45_SIZES = new Set(["2K", "4K"]);
+const SEEDREAM_5_LITE_SIZES = new Set(["2K", "3K"]);
+const WAN_PRO_SIZES = new Set([
+  "1K", "2K", "4K",
+  "1024*1024", "2048*2048", "4096*4096",
+  "1280*720", "720*1280",
+  "2048*1152", "1152*2048",
+  "4096*2304", "2304*4096",
+  "1024*768", "768*1024",
+  "2048*1536", "1536*2048",
+  "4096*3072", "3072*4096",
+]);
+const WAN_SIZES = new Set([
+  "1K", "2K",
+  "1024*1024", "2048*2048",
+  "1280*720", "720*1280",
+  "2048*1152", "1152*2048",
+  "1024*768", "768*1024",
+  "2048*1536", "1536*2048",
+]);
 
 export function getDefaultModel(): string {
   return process.env.REPLICATE_IMAGE_MODEL || DEFAULT_MODEL;
@@ -31,7 +52,78 @@ export function parseModelId(model: string): { owner: string; name: string; vers
   return { owner: parts[0], name: parts[1], version: version || null };
 }
 
-export function buildInput(prompt: string, args: CliArgs, referenceImages: string[]): Record<string, unknown> {
+function isNanoBananaModel(model: string): boolean {
+  return model.startsWith("google/nano-banana");
+}
+
+function isSeedreamModel(model: string): boolean {
+  return model.startsWith("bytedance/seedream-4.5") || model.startsWith("bytedance/seedream-5-lite");
+}
+
+function isSeedream45Model(model: string): boolean {
+  return model.startsWith("bytedance/seedream-4.5");
+}
+
+function isSeedream5LiteModel(model: string): boolean {
+  return model.startsWith("bytedance/seedream-5-lite");
+}
+
+function isWanModel(model: string): boolean {
+  return model.startsWith("wan-video/wan-2.7-image");
+}
+
+function isWanProModel(model: string): boolean {
+  return model.startsWith("wan-video/wan-2.7-image-pro");
+}
+
+function parsePixelSize(size: string): { width: number; height: number } | null {
+  const match = size.trim().match(/^(\d+)\s*[xX*]\s*(\d+)$/);
+  if (!match) return null;
+
+  const width = Number.parseInt(match[1]!, 10);
+  const height = Number.parseInt(match[2]!, 10);
+
+  if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
+    return null;
+  }
+
+  return { width, height };
+}
+
+function normalizePixelSize(size: string): string {
+  const parsed = parsePixelSize(size);
+  if (!parsed) return size;
+  return `${parsed.width}*${parsed.height}`;
+}
+
+function isPresetSize(size: string): boolean {
+  return SIZE_PRESET_PATTERN.test(size.trim());
+}
+
+function getSeedreamDefaultSize(model: string, quality: CliArgs["quality"]): string | null {
+  if (!isSeedreamModel(model) || !quality) return null;
+  return "2K";
+}
+
+function getWanDefaultSize(quality: CliArgs["quality"]): string | null {
+  if (quality === "normal") return "1K";
+  if (quality === "2k") return "2K";
+  return null;
+}
+
+function getAllowedSeedreamSizes(model: string): Set<string> {
+  return isSeedream45Model(model) ? SEEDREAM_45_SIZES : SEEDREAM_5_LITE_SIZES;
+}
+
+function getAllowedWanSizes(model: string): Set<string> {
+  return isWanProModel(model) ? WAN_PRO_SIZES : WAN_SIZES;
+}
+
+function normalizePresetSize(size: string): string {
+  return size.trim().toUpperCase();
+}
+
+function buildNanoBananaInput(prompt: string, args: CliArgs, referenceImages: string[]): Record<string, unknown> {
   const input: Record<string, unknown> = { prompt };
 
   if (args.aspectRatio) {
@@ -40,10 +132,6 @@ export function buildInput(prompt: string, args: CliArgs, referenceImages: strin
     input.aspect_ratio = "match_input_image";
   }
 
-  if (args.n > 1) {
-    input.number_of_images = args.n;
-  }
-
   if (args.quality === "normal") {
     input.resolution = "1K";
   } else if (args.quality === "2k") {
@@ -59,6 +147,123 @@ export function buildInput(prompt: string, args: CliArgs, referenceImages: strin
   return input;
 }
 
+function buildSeedreamInput(prompt: string, model: string, args: CliArgs, referenceImages: string[]): Record<string, unknown> {
+  const input: Record<string, unknown> = { prompt };
+  const requestedSize = args.size || getSeedreamDefaultSize(model, args.quality);
+
+  if (requestedSize) {
+    input.size = normalizePresetSize(requestedSize);
+  }
+
+  if (args.aspectRatio) {
+    input.aspect_ratio = args.aspectRatio;
+  }
+
+  if (args.n > 1) {
+    input.sequential_image_generation = "auto";
+    input.max_images = args.n;
+  }
+
+  if (referenceImages.length > 0) {
+    input.image_input = referenceImages;
+  }
+
+  if (isSeedream5LiteModel(model)) {
+    input.output_format = "png";
+  }
+
+  return input;
+}
+
+function buildWanInput(prompt: string, model: string, args: CliArgs, referenceImages: string[]): Record<string, unknown> {
+  const input: Record<string, unknown> = { prompt };
+  const requestedSize = args.size || getWanDefaultSize(args.quality);
+
+  if (requestedSize) {
+    input.size = parsePixelSize(requestedSize) ? normalizePixelSize(requestedSize) : normalizePresetSize(requestedSize);
+  }
+
+  if (args.n > 1) {
+    input.num_outputs = args.n;
+  }
+
+  if (referenceImages.length > 0) {
+    input.images = referenceImages;
+  }
+
+  // thinking_mode only applies to pure text-to-image.
+  // image_set_mode is not exposed by the current CLI, so no extra check is needed here yet.
+  if (referenceImages.length === 0) {
+    input.thinking_mode = true;
+  }
+
+  return input;
+}
+
+export function validateArgs(model: string, args: CliArgs): void {
+  if (isNanoBananaModel(model) && args.n > 1) {
+    throw new Error("Nano Banana models on Replicate do not support --n yet because their current schema does not expose a multi-image count field.");
+  }
+
+  if (isSeedreamModel(model)) {
+    if (args.size) {
+      const normalizedSize = normalizePresetSize(args.size);
+      if (!getAllowedSeedreamSizes(model).has(normalizedSize)) {
+        throw new Error(
+          `Seedream on Replicate requires --size to be one of ${Array.from(getAllowedSeedreamSizes(model)).join(", ")}. Received: ${args.size}`
+        );
+      }
+    }
+
+    if (args.n < 1 || args.n > 15) {
+      throw new Error("Seedream on Replicate supports --n values from 1 to 15.");
+    }
+  }
+
+  if (isWanModel(model)) {
+    if (args.aspectRatio && !args.size) {
+      throw new Error("Wan image models on Replicate require --size when using --ar. This provider does not infer size from aspect ratio.");
+    }
+
+    if (args.size) {
+      const normalizedSize = parsePixelSize(args.size) ? normalizePixelSize(args.size) : normalizePresetSize(args.size);
+      if (!getAllowedWanSizes(model).has(normalizedSize)) {
+        throw new Error(
+          `Wan image models on Replicate require --size to be one of ${Array.from(getAllowedWanSizes(model)).join(", ")}. Received: ${args.size}`
+        );
+      }
+    }
+
+    if (args.n < 1 || args.n > 4) {
+      throw new Error("Wan image models on Replicate support --n values from 1 to 4 in standard mode.");
+    }
+
+    if (args.size && normalizePresetSize(args.size) === "4K" && args.referenceImages.length > 0) {
+      throw new Error("Wan 2.7 Image Pro on Replicate only supports 4K for text-to-image requests without input images.");
+    }
+  }
+}
+
+export function buildInput(
+  prompt: string,
+  model: string,
+  args: CliArgs,
+  referenceImages: string[]
+): Record<string, unknown> {
+  if (isSeedreamModel(model)) {
+    return buildSeedreamInput(prompt, model, args, referenceImages);
+  }
+
+  if (isWanModel(model)) {
+    return buildWanInput(prompt, model, args, referenceImages);
+  }
+
+  // Fall back to nano-banana schema for unknown Replicate models.
+  // This preserves backward compatibility; unsupported models will fail
+  // at API validation time if they reject nano-banana-style fields.
+  return buildNanoBananaInput(prompt, args, referenceImages);
+}
+
 async function readImageAsDataUrl(p: string): Promise<string> {
   const buf = await readFile(p);
   const ext = path.extname(p).toLowerCase();
@@ -177,6 +382,8 @@ export async function generateImage(
   const apiToken = getApiToken();
   if (!apiToken) throw new Error("REPLICATE_API_TOKEN is required. Get one at https://replicate.com/account/api-tokens");
 
+  validateArgs(model, args);
+
   const parsedModel = parseModelId(model);
 
   const refDataUrls: string[] = [];
@@ -184,7 +391,7 @@ export async function generateImage(
     refDataUrls.push(await readImageAsDataUrl(refPath));
   }
 
-  const input = buildInput(prompt, args, refDataUrls);
+  const input = buildInput(prompt, model, args, refDataUrls);
 
   console.log(`Generating image with Replicate (${model})...`);