chore: release v1.84.0

feat(baoyu-imagine): rename baoyu-image-gen to baoyu-imagine
chore: release v1.83.0
2026-07-12 13:59:47 +08:00 · 2026-03-25 16:29:22 -05:00 · 2026-03-25 16:28:06 -05:00 · 2026-03-25 15:40:22 -05:00 · 2026-03-25 15:39:40 -05:00
36 changed files with 789 additions and 101 deletions
@@ -6,7 +6,7 @@
  },
  "metadata": {
    "description": "Skills shared by Baoyu for improving daily work efficiency",
-    "version": "1.82.0"
+    "version": "1.84.0"
  },
  "plugins": [
    {
@@ -22,7 +22,7 @@
        "./skills/baoyu-danger-gemini-web",
        "./skills/baoyu-danger-x-to-markdown",
        "./skills/baoyu-format-markdown",
-        "./skills/baoyu-image-gen",
+        "./skills/baoyu-imagine",
        "./skills/baoyu-infographic",
        "./skills/baoyu-markdown-to-html",
        "./skills/baoyu-post-to-weibo",
@@ -2,6 +2,16 @@

 English | [中文](./CHANGELOG.zh.md)

+## 1.84.0 - 2026-03-25
+
+### Features
+- Rename `baoyu-image-gen` skill to `baoyu-imagine` — shorter command name, all references updated across docs, configs, and dependent skills
+
+## 1.83.0 - 2026-03-25
+
+### Features
+- `baoyu-image-gen`: add MiniMax provider (`image-01` / `image-01-live`) with subject_reference for character/portrait consistency, custom sizes, and aspect ratio support
+
 ## 1.82.0 - 2026-03-24

 ### Features
@@ -2,6 +2,16 @@

 [English](./CHANGELOG.md) | 中文

+## 1.84.0 - 2026-03-25
+
+### 新功能
+- 将 `baoyu-image-gen` 技能重命名为 `baoyu-imagine` — 更简短的命令名，所有文档、配置和依赖技能中的引用已同步更新
+
+## 1.83.0 - 2026-03-25
+
+### 新功能
+- `baoyu-image-gen`：新增 MiniMax 服务商（`image-01` / `image-01-live`），支持 subject_reference 角色/肖像一致性、自定义尺寸和宽高比
+
 ## 1.82.0 - 2026-03-24

 ### 新功能
@@ -1,6 +1,6 @@
 # CLAUDE.md

-Claude Code marketplace plugin providing AI-powered content generation skills. Version: **1.82.0**.
+Claude Code marketplace plugin providing AI-powered content generation skills. Version: **1.84.0**.

 ## Architecture

@@ -31,7 +31,7 @@ Execute: `${BUN_X} skills/<skill>/scripts/main.ts [options]`

 - **Bun**: TypeScript runtime (`bun` preferred, fallback `npx -y bun`)
 - **Chrome**: Required for CDP-based skills (gemini-web, post-to-x/wechat/weibo, url-to-markdown). All CDP skills share a single profile, override via `BAOYU_CHROME_PROFILE_DIR` env var. Platform paths: [docs/chrome-profile.md](docs/chrome-profile.md)
- **Image generation APIs**: `baoyu-image-gen` requires API key (OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, or Replicate) configured in EXTEND.md
+- **Image generation APIs**: `baoyu-imagine` requires API key (OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, or Replicate) configured in EXTEND.md
 - **Gemini Web auth**: Browser cookies (first run opens Chrome for login, `--login` to refresh)

 ## Security
@@ -46,7 +46,7 @@ Execute: `${BUN_X} skills/<skill>/scripts/main.ts [options]`
 | Rule | Description |
 |------|-------------|
 | **Load project skills first** | Project skills override system/user-level skills with same name |
-| **Default image generation** | Use `skills/baoyu-image-gen/SKILL.md` unless user specifies otherwise |
+| **Default image generation** | Use `skills/baoyu-imagine/SKILL.md` unless user specifies otherwise |

 Priority: project `skills/` → `$HOME/.baoyu-skills/` → system-level.

@@ -32,7 +32,7 @@ This repository now supports publishing each `skills/baoyu-*` directory as an in
 ClawHub installs skills individually, not as one marketplace bundle. After publishing, users can install specific skills such as:

 ```bash
-clawhub install baoyu-image-gen
+clawhub install baoyu-imagine
 clawhub install baoyu-markdown-to-html
 ```

@@ -661,43 +661,58 @@ Post content to Weibo (微博). Supports regular posts with text, images, and vi

 AI-powered generation backends.

-#### baoyu-image-gen
+#### baoyu-imagine

-AI SDK-based image generation using OpenAI, Azure OpenAI, Google, OpenRouter, DashScope (Aliyun Tongyi Wanxiang), Jimeng (即梦), Seedream (豆包), and Replicate APIs. Supports text-to-image, reference images, aspect ratios, and quality presets.
+AI SDK-based image generation using OpenAI, Azure OpenAI, Google, OpenRouter, DashScope (Aliyun Tongyi Wanxiang), MiniMax, Jimeng (即梦), Seedream (豆包), and Replicate APIs. Supports text-to-image, reference images, aspect ratios, custom sizes, batch generation, and quality presets.

 ```bash
 # Basic generation (auto-detect provider)
-/baoyu-image-gen --prompt "A cute cat" --image cat.png
+/baoyu-imagine --prompt "A cute cat" --image cat.png

 # With aspect ratio
-/baoyu-image-gen --prompt "A landscape" --image landscape.png --ar 16:9
+/baoyu-imagine --prompt "A landscape" --image landscape.png --ar 16:9

 # High quality (2k)
-/baoyu-image-gen --prompt "A banner" --image banner.png --quality 2k
+/baoyu-imagine --prompt "A banner" --image banner.png --quality 2k

 # Specific provider
-/baoyu-image-gen --prompt "A cat" --image cat.png --provider openai
+/baoyu-imagine --prompt "A cat" --image cat.png --provider openai

 # Azure OpenAI (model = deployment name)
-/baoyu-image-gen --prompt "A cat" --image cat.png --provider azure --model gpt-image-1.5
+/baoyu-imagine --prompt "A cat" --image cat.png --provider azure --model gpt-image-1.5

 # OpenRouter
-/baoyu-image-gen --prompt "A cat" --image cat.png --provider openrouter
+/baoyu-imagine --prompt "A cat" --image cat.png --provider openrouter
+
+# OpenRouter with reference images
+/baoyu-imagine --prompt "Make it blue" --image out.png --provider openrouter --model google/gemini-3.1-flash-image-preview --ref source.png

 # DashScope (Aliyun Tongyi Wanxiang)
-/baoyu-image-gen --prompt "一只可爱的猫" --image cat.png --provider dashscope
+/baoyu-imagine --prompt "一只可爱的猫" --image cat.png --provider dashscope
+
+# DashScope with custom size
+/baoyu-imagine --prompt "为咖啡品牌设计一张 21:9 横幅海报，包含清晰中文标题" --image banner.png --provider dashscope --model qwen-image-2.0-pro --size 2048x872
+
+# MiniMax
+/baoyu-imagine --prompt "A fashion editorial portrait by a bright studio window" --image out.jpg --provider minimax
+
+# MiniMax with subject reference
+/baoyu-imagine --prompt "A girl stands by the library window, cinematic lighting" --image out.jpg --provider minimax --model image-01 --ref portrait.png --ar 16:9

 # Replicate
-/baoyu-image-gen --prompt "A cat" --image cat.png --provider replicate
+/baoyu-imagine --prompt "A cat" --image cat.png --provider replicate

 # Jimeng (即梦)
-/baoyu-image-gen --prompt "一只可爱的猫" --image cat.png --provider jimeng
+/baoyu-imagine --prompt "一只可爱的猫" --image cat.png --provider jimeng

 # Seedream (豆包)
-/baoyu-image-gen --prompt "一只可爱的猫" --image cat.png --provider seedream
+/baoyu-imagine --prompt "一只可爱的猫" --image cat.png --provider seedream

-# With reference images (Google, OpenAI, Azure OpenAI, OpenRouter, Replicate, or Seedream 5.0/4.5/4.0)
-/baoyu-image-gen --prompt "Make it blue" --image out.png --ref source.png
+# With reference images (Google, OpenAI, Azure OpenAI, OpenRouter, Replicate, MiniMax, or Seedream 5.0/4.5/4.0)
+/baoyu-imagine --prompt "Make it blue" --image out.png --ref source.png
+
+# Batch mode
+/baoyu-imagine --batchfile batch.json --jobs 4 --json
 ```

 **Options**:
@@ -706,44 +721,73 @@ AI SDK-based image generation using OpenAI, Azure OpenAI, Google, OpenRouter, Da
 | `--prompt`, `-p` | Prompt text |
 | `--promptfiles` | Read prompt from files (concatenated) |
 | `--image` | Output image path (required) |
-| `--provider` | `google`, `openai`, `openrouter`, `dashscope`, `jimeng`, `seedream` or `replicate` (default: auto-detect; prefers google) |
-| `--model`, `-m` | Model ID |
+| `--batchfile` | JSON batch file for multi-image generation |
+| `--jobs` | Worker count for batch mode |
+| `--provider` | `google`, `openai`, `azure`, `openrouter`, `dashscope`, `minimax`, `jimeng`, `seedream`, or `replicate` |
+| `--model`, `-m` | Model ID or deployment name. Azure uses deployment name; OpenRouter uses full model IDs; MiniMax uses `image-01` / `image-01-live` |
 | `--ar` | Aspect ratio (e.g., `16:9`, `1:1`, `4:3`) |
 | `--size` | Size (e.g., `1024x1024`) |
 | `--quality` | `normal` or `2k` (default: `2k`) |
-| `--ref` | Reference images (Google, OpenAI, OpenRouter, Replicate, or Seedream 5.0/4.5/4.0) |
+| `--imageSize` | `1K`, `2K`, or `4K` for Google/OpenRouter |
+| `--ref` | Reference images (Google, OpenAI, Azure OpenAI, OpenRouter, Replicate, MiniMax, or Seedream 5.0/4.5/4.0) |
+| `--n` | Number of images per request |
+| `--json` | JSON output |

 **Environment Variables** (see [Environment Configuration](#environment-configuration) for setup):
 | Variable | Description | Default |
 |----------|-------------|---------|
 | `OPENAI_API_KEY` | OpenAI API key | - |
+| `AZURE_OPENAI_API_KEY` | Azure OpenAI API key | - |
 | `OPENROUTER_API_KEY` | OpenRouter API key | - |
 | `GOOGLE_API_KEY` | Google API key | - |
+| `GEMINI_API_KEY` | Alias for `GOOGLE_API_KEY` | - |
 | `DASHSCOPE_API_KEY` | DashScope API key (Aliyun) | - |
+| `MINIMAX_API_KEY` | MiniMax API key | - |
 | `REPLICATE_API_TOKEN` | Replicate API token | - |
 | `JIMENG_ACCESS_KEY_ID` | Jimeng Volcengine access key | - |
 | `JIMENG_SECRET_ACCESS_KEY` | Jimeng Volcengine secret key | - |
 | `ARK_API_KEY` | Seedream Volcengine ARK API key | - |
 | `OPENAI_IMAGE_MODEL` | OpenAI model | `gpt-image-1.5` |
+| `AZURE_OPENAI_DEPLOYMENT` | Azure default deployment name | - |
+| `AZURE_OPENAI_IMAGE_MODEL` | Backward-compatible Azure deployment/model alias | `gpt-image-1.5` |
 | `OPENROUTER_IMAGE_MODEL` | OpenRouter model | `google/gemini-3.1-flash-image-preview` |
 | `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` |
 | `JIMENG_IMAGE_MODEL` | Jimeng model | `jimeng_t2i_v40` |
 | `SEEDREAM_IMAGE_MODEL` | Seedream model | `doubao-seedream-5-0-260128` |
 | `OPENAI_BASE_URL` | Custom OpenAI endpoint | - |
+| `OPENAI_IMAGE_USE_CHAT` | Use `/chat/completions` for OpenAI image generation | `false` |
+| `AZURE_OPENAI_BASE_URL` | Azure resource or deployment endpoint | - |
+| `AZURE_API_VERSION` | Azure image API version | `2025-04-01-preview` |
 | `OPENROUTER_BASE_URL` | Custom OpenRouter endpoint | `https://openrouter.ai/api/v1` |
+| `OPENROUTER_HTTP_REFERER` | Optional app/site URL for OpenRouter attribution | - |
+| `OPENROUTER_TITLE` | Optional app name for OpenRouter attribution | - |
 | `GOOGLE_BASE_URL` | Custom Google endpoint | - |
 | `DASHSCOPE_BASE_URL` | Custom DashScope endpoint | - |
+| `MINIMAX_BASE_URL` | Custom MiniMax endpoint | `https://api.minimax.io` |
 | `REPLICATE_BASE_URL` | Custom Replicate endpoint | - |
 | `JIMENG_BASE_URL` | Custom Jimeng endpoint | `https://visual.volcengineapi.com` |
 | `JIMENG_REGION` | Jimeng region | `cn-north-1` |
 | `SEEDREAM_BASE_URL` | Custom Seedream endpoint | `https://ark.cn-beijing.volces.com/api/v3` |
+| `BAOYU_IMAGE_GEN_MAX_WORKERS` | Override batch worker cap | `10` |
+| `BAOYU_IMAGE_GEN_<PROVIDER>_CONCURRENCY` | Override provider concurrency | provider-specific |
+| `BAOYU_IMAGE_GEN_<PROVIDER>_START_INTERVAL_MS` | Override provider request start gap | provider-specific |
+
+**Provider Notes**:
+- Azure OpenAI: `--model` means Azure deployment name, not the underlying model family.
+- DashScope: `qwen-image-2.0-pro` is the recommended default for custom `--size`, `21:9`, and strong Chinese/English text rendering.
+- MiniMax: `image-01` supports documented custom `width` / `height`; `image-01-live` is lower latency and works best with `--ar`.
+- MiniMax reference images are sent as `subject_reference`; the current API is specialized toward character / portrait consistency.
+- Jimeng does not support reference images.
+- Seedream reference images are supported by Seedream 5.0 / 4.5 / 4.0, not Seedream 3.0.

 **Provider Auto-Selection**:
-1. If `--provider` specified → use it
-2. If only one API key available → use that provider
-3. If multiple available → default to Google
+1. If `--provider` is specified → use it
+2. If `--ref` is provided and no provider is specified → try Google, then OpenAI, Azure, OpenRouter, Replicate, Seedream, and finally MiniMax
+3. If only one API key is available → use that provider
+4. If multiple providers are available → default to Google

 #### baoyu-danger-gemini-web

@@ -1001,7 +1045,7 @@ Custom style descriptions are also accepted, e.g., `--style "poetic and lyrical"
 Some skills require API keys or custom configuration. Environment variables can be set in `.env` files:

 **Load Priority** (higher priority overrides lower):
-1. CLI environment variables (e.g., `OPENAI_API_KEY=xxx /baoyu-image-gen ...`)
+1. CLI environment variables (e.g., `OPENAI_API_KEY=xxx /baoyu-imagine ...`)
 2. `process.env` (system environment)
 3. `<cwd>/.baoyu-skills/.env` (project-level)
 4. `~/.baoyu-skills/.env` (user-level)
@@ -1018,11 +1062,20 @@ cat > ~/.baoyu-skills/.env << 'EOF'
 OPENAI_API_KEY=sk-xxx
 OPENAI_IMAGE_MODEL=gpt-image-1.5
 # OPENAI_BASE_URL=https://api.openai.com/v1
+# OPENAI_IMAGE_USE_CHAT=false
+
+# Azure OpenAI
+AZURE_OPENAI_API_KEY=xxx
+AZURE_OPENAI_BASE_URL=https://your-resource.openai.azure.com
+AZURE_OPENAI_DEPLOYMENT=gpt-image-1.5
+# AZURE_API_VERSION=2025-04-01-preview

 # OpenRouter
 OPENROUTER_API_KEY=sk-or-xxx
 OPENROUTER_IMAGE_MODEL=google/gemini-3.1-flash-image-preview
 # OPENROUTER_BASE_URL=https://openrouter.ai/api/v1
+# OPENROUTER_HTTP_REFERER=https://your-app.example.com
+# OPENROUTER_TITLE=Your App Name

 # Google
 GOOGLE_API_KEY=xxx
@@ -1034,6 +1087,11 @@ DASHSCOPE_API_KEY=sk-xxx
 DASHSCOPE_IMAGE_MODEL=qwen-image-2.0-pro
 # DASHSCOPE_BASE_URL=https://dashscope.aliyuncs.com/api/v1

+# MiniMax
+MINIMAX_API_KEY=xxx
+MINIMAX_IMAGE_MODEL=image-01
+# MINIMAX_BASE_URL=https://api.minimax.io
+
 # Replicate
 REPLICATE_API_TOKEN=r8_xxx
 REPLICATE_IMAGE_MODEL=google/nano-banana-pro
@@ -32,7 +32,7 @@ npx skills add jimliu/baoyu-skills
 ClawHub 按“单个 skill”安装，不是把整个 marketplace 一次性装进去。发布后，用户可以按需安装：

 ```bash
-clawhub install baoyu-image-gen
+clawhub install baoyu-imagine
 clawhub install baoyu-markdown-to-html
 ```

@@ -661,43 +661,58 @@ accounts:

 AI 驱动的生成后端。

-#### baoyu-image-gen
+#### baoyu-imagine

-基于 AI SDK 的图像生成，支持 OpenAI、Azure OpenAI、Google、OpenRouter、DashScope（阿里通义万相）、即梦（Jimeng）、豆包（Seedream）和 Replicate API。支持文生图、参考图、宽高比和质量预设。
+基于 AI SDK 的图像生成，支持 OpenAI、Azure OpenAI、Google、OpenRouter、DashScope（阿里通义万相）、MiniMax、即梦（Jimeng）、豆包（Seedream）和 Replicate API。支持文生图、参考图、宽高比、自定义尺寸、批量生成和质量预设。

 ```bash
 # 基础生成（自动检测服务商）
-/baoyu-image-gen --prompt "一只可爱的猫" --image cat.png
+/baoyu-imagine --prompt "一只可爱的猫" --image cat.png

 # 指定宽高比
-/baoyu-image-gen --prompt "风景图" --image landscape.png --ar 16:9
+/baoyu-imagine --prompt "风景图" --image landscape.png --ar 16:9

 # 高质量（2k 分辨率）
-/baoyu-image-gen --prompt "横幅图" --image banner.png --quality 2k
+/baoyu-imagine --prompt "横幅图" --image banner.png --quality 2k

 # 指定服务商
-/baoyu-image-gen --prompt "一只猫" --image cat.png --provider openai
+/baoyu-imagine --prompt "一只猫" --image cat.png --provider openai

 # Azure OpenAI（model 为部署名称）
-/baoyu-image-gen --prompt "一只猫" --image cat.png --provider azure --model gpt-image-1.5
+/baoyu-imagine --prompt "一只猫" --image cat.png --provider azure --model gpt-image-1.5

 # OpenRouter
-/baoyu-image-gen --prompt "一只猫" --image cat.png --provider openrouter
+/baoyu-imagine --prompt "一只猫" --image cat.png --provider openrouter
+
+# OpenRouter + 参考图
+/baoyu-imagine --prompt "把它变成蓝色" --image out.png --provider openrouter --model google/gemini-3.1-flash-image-preview --ref source.png

 # DashScope（阿里通义万相）
-/baoyu-image-gen --prompt "一只可爱的猫" --image cat.png --provider dashscope
+/baoyu-imagine --prompt "一只可爱的猫" --image cat.png --provider dashscope
+
+# DashScope 自定义尺寸
+/baoyu-imagine --prompt "为咖啡品牌设计一张 21:9 横幅海报，包含清晰中文标题" --image banner.png --provider dashscope --model qwen-image-2.0-pro --size 2048x872
+
+# MiniMax
+/baoyu-imagine --prompt "A fashion editorial portrait by a bright studio window" --image out.jpg --provider minimax
+
+# MiniMax + 角色参考图
+/baoyu-imagine --prompt "A girl stands by the library window, cinematic lighting" --image out.jpg --provider minimax --model image-01 --ref portrait.png --ar 16:9

 # Replicate
-/baoyu-image-gen --prompt "一只猫" --image cat.png --provider replicate
+/baoyu-imagine --prompt "一只猫" --image cat.png --provider replicate

 # 即梦（Jimeng）
-/baoyu-image-gen --prompt "一只可爱的猫" --image cat.png --provider jimeng
+/baoyu-imagine --prompt "一只可爱的猫" --image cat.png --provider jimeng

 # 豆包（Seedream）
-/baoyu-image-gen --prompt "一只可爱的猫" --image cat.png --provider seedream
+/baoyu-imagine --prompt "一只可爱的猫" --image cat.png --provider seedream

-# 带参考图（Google、OpenAI、Azure OpenAI、OpenRouter、Replicate 或 Seedream 5.0/4.5/4.0）
-/baoyu-image-gen --prompt "把它变成蓝色" --image out.png --ref source.png
+# 带参考图（Google、OpenAI、Azure OpenAI、OpenRouter、Replicate、MiniMax 或 Seedream 5.0/4.5/4.0）
+/baoyu-imagine --prompt "把它变成蓝色" --image out.png --ref source.png
+
+# 批量模式
+/baoyu-imagine --batchfile batch.json --jobs 4 --json
 ```

 **选项**：
@@ -706,44 +721,73 @@ AI 驱动的生成后端。
 | `--prompt`, `-p` | 提示词文本 |
 | `--promptfiles` | 从文件读取提示词（多文件拼接） |
 | `--image` | 输出图片路径（必需） |
-| `--provider` | `google`、`openai`、`openrouter`、`dashscope`、`jimeng`、`seedream` 或 `replicate`（默认：自动检测，优先 google） |
-| `--model`, `-m` | 模型 ID |
+| `--batchfile` | 多图批量生成的 JSON 文件 |
+| `--jobs` | 批量模式的并发 worker 数 |
+| `--provider` | `google`、`openai`、`azure`、`openrouter`、`dashscope`、`minimax`、`jimeng`、`seedream` 或 `replicate` |
+| `--model`, `-m` | 模型 ID 或部署名。Azure 使用部署名；OpenRouter 使用完整模型 ID；MiniMax 使用 `image-01` / `image-01-live` |
 | `--ar` | 宽高比（如 `16:9`、`1:1`、`4:3`） |
 | `--size` | 尺寸（如 `1024x1024`） |
 | `--quality` | `normal` 或 `2k`（默认：`2k`） |
-| `--ref` | 参考图片（Google、OpenAI、OpenRouter、Replicate 或 Seedream 5.0/4.5/4.0） |
+| `--imageSize` | Google/OpenRouter 使用的 `1K`、`2K`、`4K` |
+| `--ref` | 参考图片（Google、OpenAI、Azure OpenAI、OpenRouter、Replicate、MiniMax 或 Seedream 5.0/4.5/4.0） |
+| `--n` | 单次请求生成图片数量 |
+| `--json` | 输出 JSON 结果 |

 **环境变量**（配置方法见[环境配置](#环境配置)）：
 | 变量 | 说明 | 默认值 |
 |------|------|--------|
 | `OPENAI_API_KEY` | OpenAI API 密钥 | - |
+| `AZURE_OPENAI_API_KEY` | Azure OpenAI API 密钥 | - |
 | `OPENROUTER_API_KEY` | OpenRouter API 密钥 | - |
 | `GOOGLE_API_KEY` | Google API 密钥 | - |
+| `GEMINI_API_KEY` | `GOOGLE_API_KEY` 的别名 | - |
 | `DASHSCOPE_API_KEY` | DashScope API 密钥（阿里云） | - |
+| `MINIMAX_API_KEY` | MiniMax API 密钥 | - |
 | `REPLICATE_API_TOKEN` | Replicate API Token | - |
 | `JIMENG_ACCESS_KEY_ID` | 即梦火山引擎 Access Key | - |
 | `JIMENG_SECRET_ACCESS_KEY` | 即梦火山引擎 Secret Key | - |
 | `ARK_API_KEY` | 豆包火山引擎 ARK API 密钥 | - |
 | `OPENAI_IMAGE_MODEL` | OpenAI 模型 | `gpt-image-1.5` |
+| `AZURE_OPENAI_DEPLOYMENT` | Azure 默认部署名 | - |
+| `AZURE_OPENAI_IMAGE_MODEL` | 兼容旧配置的 Azure 部署/模型别名 | `gpt-image-1.5` |
 | `OPENROUTER_IMAGE_MODEL` | OpenRouter 模型 | `google/gemini-3.1-flash-image-preview` |
 | `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` |
 | `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 | - |
+| `OPENAI_IMAGE_USE_CHAT` | OpenAI 改走 `/chat/completions` | `false` |
+| `AZURE_OPENAI_BASE_URL` | Azure 资源或部署端点 | - |
+| `AZURE_API_VERSION` | Azure 图像 API 版本 | `2025-04-01-preview` |
 | `OPENROUTER_BASE_URL` | 自定义 OpenRouter 端点 | `https://openrouter.ai/api/v1` |
+| `OPENROUTER_HTTP_REFERER` | OpenRouter 归因用站点 URL | - |
+| `OPENROUTER_TITLE` | OpenRouter 归因用应用名 | - |
 | `GOOGLE_BASE_URL` | 自定义 Google 端点 | - |
 | `DASHSCOPE_BASE_URL` | 自定义 DashScope 端点 | - |
+| `MINIMAX_BASE_URL` | 自定义 MiniMax 端点 | `https://api.minimax.io` |
 | `REPLICATE_BASE_URL` | 自定义 Replicate 端点 | - |
 | `JIMENG_BASE_URL` | 自定义即梦端点 | `https://visual.volcengineapi.com` |
 | `JIMENG_REGION` | 即梦区域 | `cn-north-1` |
 | `SEEDREAM_BASE_URL` | 自定义豆包端点 | `https://ark.cn-beijing.volces.com/api/v3` |
+| `BAOYU_IMAGE_GEN_MAX_WORKERS` | 批量模式最大 worker 数 | `10` |
+| `BAOYU_IMAGE_GEN_<PROVIDER>_CONCURRENCY` | 覆盖 provider 并发数 | provider 默认值 |
+| `BAOYU_IMAGE_GEN_<PROVIDER>_START_INTERVAL_MS` | 覆盖 provider 请求启动间隔 | provider 默认值 |
+
+**Provider 说明**：
+- Azure OpenAI：`--model` 表示 Azure deployment name，不是底层模型家族名。
+- DashScope：`qwen-image-2.0-pro` 是自定义 `--size`、`21:9` 和中英文排版的推荐默认模型。
+- MiniMax：`image-01` 支持官方文档里的自定义 `width` / `height`；`image-01-live` 更偏低延迟，适合配合 `--ar` 使用。
+- MiniMax 参考图会走 `subject_reference`，当前能力更偏角色 / 人像一致性。
+- 即梦不支持参考图。
+- 豆包参考图能力仅适用于 Seedream 5.0 / 4.5 / 4.0，不适用于 Seedream 3.0。

 **服务商自动选择**：
 1. 如果指定了 `--provider` → 使用指定的
-2. 如果只有一个 API 密钥 → 使用对应服务商
-3. 如果多个可用 → 默认使用 Google
+2. 如果传了 `--ref` 且未指定 provider → 依次尝试 Google、OpenAI、Azure、OpenRouter、Replicate、Seedream，最后是 MiniMax
+3. 如果只有一个 API 密钥 → 使用对应服务商
+4. 如果多个可用 → 默认使用 Google

 #### baoyu-danger-gemini-web

@@ -1001,7 +1045,7 @@ AI 驱动的生成后端。
 部分技能需要 API 密钥或自定义配置。环境变量可以在 `.env` 文件中设置：

 **加载优先级**（高优先级覆盖低优先级）：
-1. 命令行环境变量（如 `OPENAI_API_KEY=xxx /baoyu-image-gen ...`）
+1. 命令行环境变量（如 `OPENAI_API_KEY=xxx /baoyu-imagine ...`）
 2. `process.env`（系统环境变量）
 3. `<cwd>/.baoyu-skills/.env`（项目级）
 4. `~/.baoyu-skills/.env`（用户级）
@@ -1018,11 +1062,20 @@ cat > ~/.baoyu-skills/.env << 'EOF'
 OPENAI_API_KEY=sk-xxx
 OPENAI_IMAGE_MODEL=gpt-image-1.5
 # OPENAI_BASE_URL=https://api.openai.com/v1
+# OPENAI_IMAGE_USE_CHAT=false
+
+# Azure OpenAI
+AZURE_OPENAI_API_KEY=xxx
+AZURE_OPENAI_BASE_URL=https://your-resource.openai.azure.com
+AZURE_OPENAI_DEPLOYMENT=gpt-image-1.5
+# AZURE_API_VERSION=2025-04-01-preview

 # OpenRouter
 OPENROUTER_API_KEY=sk-or-xxx
 OPENROUTER_IMAGE_MODEL=google/gemini-3.1-flash-image-preview
 # OPENROUTER_BASE_URL=https://openrouter.ai/api/v1
+# OPENROUTER_HTTP_REFERER=https://your-app.example.com
+# OPENROUTER_TITLE=你的应用名

 # Google
 GOOGLE_API_KEY=xxx
@@ -1034,6 +1087,11 @@ DASHSCOPE_API_KEY=sk-xxx
 DASHSCOPE_IMAGE_MODEL=qwen-image-2.0-pro
 # DASHSCOPE_BASE_URL=https://dashscope.aliyuncs.com/api/v1

+# MiniMax
+MINIMAX_API_KEY=xxx
+MINIMAX_IMAGE_MODEL=image-01
+# MINIMAX_BASE_URL=https://api.minimax.io
+
 # Replicate
 REPLICATE_API_TOKEN=r8_xxx
 REPLICATE_IMAGE_MODEL=google/nano-banana-pro
@@ -4,7 +4,7 @@ Skills that require image generation MUST delegate to available image generation

 ## Skill Selection

-**Default**: `skills/baoyu-image-gen/SKILL.md` (unless user specifies otherwise).
+**Default**: `skills/baoyu-imagine/SKILL.md` (unless user specifies otherwise).

 1. Read skill's SKILL.md for parameters and capabilities
 2. If user requests different skill, check `skills/` for alternatives
@@ -16,7 +16,7 @@ Skills that require image generation MUST delegate to available image generation
 ### Step N: Generate Images

 **Skill Selection**:
-1. Check available skills (`baoyu-image-gen` default, or `baoyu-danger-gemini-web`)
+1. Check available skills (`baoyu-imagine` default, or `baoyu-danger-gemini-web`)
 2. Read selected skill's SKILL.md for parameters
 3. If multiple skills available, ask user to choose

@@ -27,7 +27,7 @@ Skills that require image generation MUST delegate to available image generation
 4. On failure, auto-retry once before reporting error
 ```

-**Batch Parallel** (`baoyu-image-gen` only): concurrent workers with per-provider throttling via `batch.max_workers` in EXTEND.md.
+**Batch Parallel** (`baoyu-imagine` only): concurrent workers with per-provider throttling via `batch.max_workers` in EXTEND.md.

 ## Output Path Convention

@@ -118,7 +118,7 @@ Full template: [references/workflow.md](references/workflow.md#step-4-generate-o

 ⛔ **BLOCKING: Prompt files MUST be saved before ANY image generation.**

-**Execution strategy**: When multiple illustrations have saved prompt files and the task is now plain generation, prefer `baoyu-image-gen` batch mode (`build-batch.ts` → `--batchfile`) over spawning subagents. Use subagents only when each image still needs separate prompt iteration or creative exploration.
+**Execution strategy**: When multiple illustrations have saved prompt files and the task is now plain generation, prefer `baoyu-imagine` batch mode (`build-batch.ts` → `--batchfile`) over spawning subagents. Use subagents only when each image still needs separate prompt iteration or creative exploration.

 1. For each illustration, create a prompt file per [references/prompt-construction.md](references/prompt-construction.md)
 2. Save to `prompts/NN-{type}-{slug}.md` with YAML frontmatter
@@ -316,7 +316,7 @@ Prompt Files:
 **DO NOT** pass ad-hoc inline text to `--prompt` without first saving prompt files. The generation command should either use `--promptfiles prompts/NN-{type}-{slug}.md` or read the saved file content for `--prompt`.

 **Execution choice**:
- If multiple illustrations already have saved prompt files and the task is now plain generation, prefer `baoyu-image-gen` batch mode (`build-batch.ts` -> `main.ts --batchfile`)
+- If multiple illustrations already have saved prompt files and the task is now plain generation, prefer `baoyu-imagine` batch mode (`build-batch.ts` -> `main.ts --batchfile`)
 - Use subagents only when each illustration still needs separate prompt rewriting, style exploration, or other per-image reasoning before generation

 **CRITICAL - References in Frontmatter**:
@@ -352,7 +352,7 @@ Check available skills. If multiple, ask user.

 | Skill Supports `--ref` | Action |
 |------------------------|--------|
-| Yes (e.g., baoyu-image-gen with Google) | Pass reference images via `--ref` |
+| Yes (e.g., baoyu-imagine with Google) | Pass reference images via `--ref` |
 | No | Convert to text description, append to prompt |

 **Verification**: Before generating, confirm reference processing:
@@ -29,8 +29,8 @@ Options:
  --prompts <path>     Path to prompts directory
  --output <path>      Path to output batch.json
  --images-dir <path>  Directory for generated images
-  --provider <name>    Provider for baoyu-image-gen batch tasks (default: replicate)
-  --model <id>         Model for baoyu-image-gen batch tasks (default: google/nano-banana-pro)
+  --provider <name>    Provider for baoyu-imagine batch tasks (default: replicate)
+  --model <id>         Model for baoyu-imagine batch tasks (default: google/nano-banana-pro)
  --ar <ratio>         Aspect ratio for all tasks (default: 16:9)
  --quality <level>    Quality for all tasks (default: 2k)
  --jobs <count>       Recommended worker count metadata (optional)
@@ -216,7 +216,7 @@ Analyze → [Check Existing?] → [Confirm: Style + Reviews] → Storyboard →

 **7.1 Generate character sheet first**:
 - **Backup rule**: If `characters/characters.png` exists, rename to `characters/characters-backup-YYYYMMDD-HHMMSS.png`
- Invoke an installed image generation skill such as `baoyu-image-gen`
+- Invoke an installed image generation skill such as `baoyu-imagine`
 - Read that skill's `SKILL.md` and follow its documented interface rather than calling its scripts directly
 - Use `characters/characters.md` as the prompt-file input
 - Save output to `characters/characters.png`
@@ -433,7 +433,7 @@ With confirmed prompts from Step 5/6:
 | Supports `--ref` | **Strategy A** | Pass `characters/characters.png` with EVERY page |
 | Does NOT support `--ref` | **Strategy B** | Prepend character descriptions to EVERY prompt |

-**Strategy A: Using `--ref` parameter** (e.g., baoyu-image-gen)
+**Strategy A: Using `--ref` parameter** (e.g., baoyu-imagine)

 - Read the chosen image generation skill's `SKILL.md`
 - Invoke that installed skill via its documented interface, not by calling its scripts directly
@@ -1,10 +1,10 @@
 ---
-name: baoyu-image-gen
-description: AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, 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: 1.56.3
+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
 metadata:
  openclaw:
-    homepage: https://github.com/JimLiu/baoyu-skills#baoyu-image-gen
+    homepage: https://github.com/JimLiu/baoyu-skills#baoyu-imagine
    requires:
      anyBins:
        - bun
@@ -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), 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), MiniMax, Jimeng (即梦), Seedream (豆包) and Replicate providers.

 ## Script Directory

@@ -30,17 +30,17 @@ Check EXTEND.md existence (priority: project → user):

 ```bash
 # macOS, Linux, WSL, Git Bash
-test -f .baoyu-skills/baoyu-image-gen/EXTEND.md && echo "project"
-test -f "${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-image-gen/EXTEND.md" && echo "xdg"
-test -f "$HOME/.baoyu-skills/baoyu-image-gen/EXTEND.md" && echo "user"
+test -f .baoyu-skills/baoyu-imagine/EXTEND.md && echo "project"
+test -f "${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-imagine/EXTEND.md" && echo "xdg"
+test -f "$HOME/.baoyu-skills/baoyu-imagine/EXTEND.md" && echo "user"
 ```

 ```powershell
 # PowerShell (Windows)
-if (Test-Path .baoyu-skills/baoyu-image-gen/EXTEND.md) { "project" }
+if (Test-Path .baoyu-skills/baoyu-imagine/EXTEND.md) { "project" }
 $xdg = if ($env:XDG_CONFIG_HOME) { $env:XDG_CONFIG_HOME } else { "$HOME/.config" }
-if (Test-Path "$xdg/baoyu-skills/baoyu-image-gen/EXTEND.md") { "xdg" }
-if (Test-Path "$HOME/.baoyu-skills/baoyu-image-gen/EXTEND.md") { "user" }
+if (Test-Path "$xdg/baoyu-skills/baoyu-imagine/EXTEND.md") { "xdg" }
+if (Test-Path "$HOME/.baoyu-skills/baoyu-imagine/EXTEND.md") { "user" }
 ```

 | Result | Action |
@@ -52,8 +52,8 @@ if (Test-Path "$HOME/.baoyu-skills/baoyu-image-gen/EXTEND.md") { "user" }

 | Path | Location |
 |------|----------|
-| `.baoyu-skills/baoyu-image-gen/EXTEND.md` | Project directory |
-| `$HOME/.baoyu-skills/baoyu-image-gen/EXTEND.md` | User home |
+| `.baoyu-skills/baoyu-imagine/EXTEND.md` | Project directory |
+| `$HOME/.baoyu-skills/baoyu-imagine/EXTEND.md` | User home |

 **EXTEND.md Supports**: Default provider | Default quality | Default aspect ratio | Default image size | Default models | Batch worker cap | Provider-specific batch limits

@@ -74,7 +74,7 @@ ${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --quality 2k
 # From prompt files
 ${BUN_X} {baseDir}/scripts/main.ts --promptfiles system.md content.md --image out.png

-# With reference images (Google, OpenAI, Azure OpenAI, OpenRouter, Replicate, or Seedream 4.0/4.5/5.0)
+# With reference images (Google, OpenAI, Azure OpenAI, OpenRouter, Replicate, MiniMax, or Seedream 4.0/4.5/5.0)
 ${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --ref source.png

 # With reference images (explicit provider/model)
@@ -101,6 +101,15 @@ ${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

+# MiniMax
+${BUN_X} {baseDir}/scripts/main.ts --prompt "A fashion editorial portrait by a bright studio window" --image out.jpg --provider minimax
+
+# MiniMax with subject reference (best for character/portrait consistency)
+${BUN_X} {baseDir}/scripts/main.ts --prompt "A girl stands by the library window, cinematic lighting" --image out.jpg --provider minimax --model image-01 --ref portrait.png --ar 16:9
+
+# 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)
 ${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate

@@ -150,13 +159,13 @@ 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\|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`) |
+| `--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`) |
 | `--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`) |
 | `--imageSize 1K\|2K\|4K` | Image size for Google/OpenRouter (default: from quality) |
-| `--ref <files...>` | Reference images. Supported by Google multimodal, OpenAI GPT Image edits, Azure OpenAI edits (PNG/JPG only), OpenRouter multimodal models, Replicate, and Seedream 5.0/4.5/4.0. Not supported by Jimeng, Seedream 3.0, or removed 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, MiniMax subject-reference, and Seedream 5.0/4.5/4.0. Not supported by Jimeng, Seedream 3.0, or removed SeedEdit 3.0 |
 | `--n <count>` | Number of images |
 | `--json` | JSON output |

@@ -169,6 +178,7 @@ 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) |
+| `MINIMAX_API_KEY` | MiniMax API key |
 | `REPLICATE_API_TOKEN` | Replicate API token |
 | `JIMENG_ACCESS_KEY_ID` | Jimeng (即梦) Volcengine access key |
 | `JIMENG_SECRET_ACCESS_KEY` | Jimeng (即梦) Volcengine secret key |
@@ -179,6 +189,7 @@ 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`) |
+| `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) |
 | `SEEDREAM_IMAGE_MODEL` | Seedream model override (default: doubao-seedream-5-0-260128) |
@@ -190,6 +201,7 @@ 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 |
+| `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`) |
 | `JIMENG_REGION` | Jimeng region (default: `cn-north-1`) |
@@ -240,7 +252,7 @@ When translating CLI args into DashScope behavior:
 - `--size` wins over `--ar`
 - For `qwen-image-2.0*`, prefer explicit `--size`; otherwise infer from `--ar` and use the official recommended resolutions below
 - For `qwen-image-max/plus/image`, only use the five official fixed sizes; if the requested ratio is not covered, switch to `qwen-image-2.0-pro`
- `--quality` is a baoyu-image-gen compatibility preset, not a native DashScope API field. Mapping `normal` / `2k` onto the `qwen-image-2.0*` table below is an implementation inference, not an official API guarantee
+- `--quality` is a baoyu-imagine compatibility preset, not a native DashScope API field. Mapping `normal` / `2k` onto the `qwen-image-2.0*` table below is an implementation inference, not an official API guarantee

 Recommended `qwen-image-2.0*` sizes for common aspect ratios:

@@ -255,7 +267,7 @@ Recommended `qwen-image-2.0*` sizes for common aspect ratios:
 | `16:9` | `1280*720` | `1920*1080` |
 | `21:9` | `1344*576` | `2048*872` |

-DashScope official APIs also expose `negative_prompt`, `prompt_extend`, and `watermark`, but `baoyu-image-gen` does not expose them as dedicated CLI flags today.
+DashScope official APIs also expose `negative_prompt`, `prompt_extend`, and `watermark`, but `baoyu-imagine` does not expose them as dedicated CLI flags today.

 Official references:

@@ -263,6 +275,34 @@ 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)

+### MiniMax Models
+
+Use `--model image-01` or set `default_model.minimax` / `MINIMAX_IMAGE_MODEL` when the user wants MiniMax image generation.
+
+Official MiniMax image model options currently documented in the API reference:
+
+- `image-01` (recommended default)
+  - Supports text-to-image and subject-reference image generation
+  - Supports official `aspect_ratio` values: `1:1`, `16:9`, `4:3`, `3:2`, `2:3`, `3:4`, `9:16`, `21:9`
+  - Supports documented custom `width` / `height` output sizes when using `--size <WxH>`
+  - `width` and `height` must both be between `512` and `2048`, and both must be divisible by `8`
+- `image-01-live`
+  - Lower-latency variant
+  - Use `--ar` for sizing; MiniMax documents custom `width` / `height` as only effective for `image-01`
+
+MiniMax subject reference notes:
+
+- `--ref` files are sent as MiniMax `subject_reference`
+- MiniMax docs currently describe `subject_reference[].type` as `character`
+- Official docs say `image_file` supports public URLs or Base64 Data URLs; `baoyu-imagine` sends local refs as Data URLs
+- Official docs recommend front-facing portrait references in JPG/JPEG/PNG under 10MB
+
+Official references:
+
+- [MiniMax Image Generation Guide](https://platform.minimax.io/docs/guides/image-generation)
+- [MiniMax Text-to-Image API](https://platform.minimax.io/docs/api-reference/image-generation-t2i)
+- [MiniMax Image-to-Image API](https://platform.minimax.io/docs/api-reference/image-generation-i2i)
+
 ### OpenRouter Models

 Use full OpenRouter model IDs, e.g.:
@@ -297,8 +337,8 @@ ${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider r

 ## Provider Selection

-1. `--ref` provided + no `--provider` → auto-select Google first, then OpenAI, then OpenRouter, then Replicate (Jimeng and Seedream do not support reference images)
-2. `--provider` specified → use it (if `--ref`, must be `google`, `openai`, `openrouter`, or `replicate`)
+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

@@ -319,6 +359,7 @@ Supported: `1:1`, `16:9`, `9:16`, `4:3`, `3:4`, `2.35:1`
 - OpenAI: maps to closest supported size
 - OpenRouter: sends `imageGenerationOptions.aspect_ratio`; if only `--size <WxH>` is given, aspect ratio is inferred automatically
 - Replicate: passes `aspect_ratio` to model; when `--ref` is provided without `--ar`, defaults to `match_input_image`
+- MiniMax: sends official `aspect_ratio` values directly; if `--size <WxH>` is given without `--ar`, `width` / `height` are sent for `image-01`

 ## Generation Mode

@@ -1,6 +1,6 @@
 ---
 name: first-time-setup
-description: First-time setup and default model selection flow for baoyu-image-gen
+description: First-time setup and default model selection flow for baoyu-imagine
 ---

 # First-Time Setup
@@ -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: "MiniMax"
+    description: "MiniMax image generation with subject-reference character workflows"
  - label: "Replicate"
    description: "Community models - nano-banana-pro, flexible model selection"
 ```
@@ -103,6 +105,20 @@ options:
    description: "Previous GPT Image deployment name"
 ```

+### Question 2d: Default MiniMax Model
+
+Only show if user selected MiniMax.
+
+```yaml
+header: "MiniMax Model"
+question: "Default MiniMax image generation model?"
+options:
+  - label: "image-01 (Recommended)"
+    description: "Best default, supports aspect ratios and custom width/height"
+  - label: "image-01-live"
+    description: "Faster variant, use aspect ratio instead of custom size"
+```
+
 ### Question 3: Default Quality

 ```yaml
@@ -131,8 +147,8 @@ options:

 | Choice | Path | Scope |
 |--------|------|-------|
-| Project | `.baoyu-skills/baoyu-image-gen/EXTEND.md` | Current project |
-| User | `$HOME/.baoyu-skills/baoyu-image-gen/EXTEND.md` | All projects |
+| Project | `.baoyu-skills/baoyu-imagine/EXTEND.md` | Current project |
+| User | `$HOME/.baoyu-skills/baoyu-imagine/EXTEND.md` | All projects |

 ### EXTEND.md Template

@@ -149,6 +165,7 @@ default_model:
  azure: [selected azure deployment or null]
  openrouter: [selected openrouter model or null]
  dashscope: null
+  minimax: [selected minimax model or null]
  replicate: null
 ---
 ```
@@ -197,7 +214,7 @@ options:

 Notes for Azure setup:

- In `baoyu-image-gen`, Azure `--model` / `default_model.azure` should be the Azure deployment name, not just the underlying model family.
+- In `baoyu-imagine`, Azure `--model` / `default_model.azure` should be the Azure deployment name, not just the underlying model family.
 - If the deployment name is custom, save that exact deployment name in `default_model.azure`.

 ### OpenRouter Model Selection
@@ -238,7 +255,7 @@ 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`.
- In `baoyu-image-gen`, `quality` is a compatibility preset. It is not a native DashScope parameter.
+- In `baoyu-imagine`, `quality` is a compatibility preset. It is not a native DashScope parameter.

 ### Replicate Model Selection

@@ -252,6 +269,24 @@ options:
    description: "Google's base image model on Replicate"
 ```

+### MiniMax Model Selection
+
+```yaml
+header: "MiniMax Model"
+question: "Choose a default MiniMax image generation model?"
+options:
+  - label: "image-01 (Recommended)"
+    description: "Best general-purpose MiniMax image model with custom width/height support"
+  - label: "image-01-live"
+    description: "Lower-latency MiniMax image model using aspect ratios"
+```
+
+Notes for MiniMax setup:
+
+- `image-01` is the safest default. It supports official `aspect_ratio` values and documented custom `width` / `height` output sizes.
+- `image-01-live` is useful when the user prefers faster generation and can work with aspect-ratio-based sizing.
+- MiniMax subject reference currently uses `subject_reference[].type = character`; docs recommend front-facing portrait references in JPG/JPEG/PNG under 10MB.
+
 ### Update EXTEND.md

 After user selects a model:
@@ -267,6 +302,7 @@ default_model:
  azure: [value or null]
  openrouter: [value or null]
  dashscope: [value or null]
+  minimax: [value or null]
  replicate: [value or null]
 ```

@@ -1,6 +1,6 @@
 ---
 name: preferences-schema
-description: EXTEND.md YAML schema for baoyu-image-gen user preferences
+description: EXTEND.md YAML schema for baoyu-imagine user preferences
 ---

 # Preferences Schema
@@ -11,7 +11,7 @@ description: EXTEND.md YAML schema for baoyu-image-gen user preferences
 ---
 version: 1

-default_provider: null      # google|openai|azure|openrouter|dashscope|replicate|null (null = auto-detect)
+default_provider: null      # google|openai|azure|openrouter|dashscope|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"
+  minimax: null             # e.g., "image-01"
  replicate: null           # e.g., "google/nano-banana-pro"

 batch:
@@ -48,6 +49,9 @@ batch:
    dashscope:
      concurrency: 3
      start_interval_ms: 1100
+    minimax:
+      concurrency: 3
+      start_interval_ms: 1100
 ---
 ```

@@ -65,6 +69,7 @@ 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.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 |
 | `batch.provider_limits.<provider>.concurrency` | int\|null | provider default | Max simultaneous requests per provider |
@@ -95,6 +100,7 @@ default_model:
  azure: "gpt-image-1.5"
  openrouter: "google/gemini-3.1-flash-image-preview"
  dashscope: "qwen-image-2.0-pro"
+  minimax: "image-01"
  replicate: "google/nano-banana-pro"
 batch:
  max_workers: 10
@@ -108,5 +114,8 @@ batch:
    openrouter:
      concurrency: 3
      start_interval_ms: 1100
+    minimax:
+      concurrency: 3
+      start_interval_ms: 1100
 ---
 ```
@@ -69,7 +69,7 @@ async function makeTempDir(prefix: string): Promise<string> {
  return fs.mkdtemp(path.join(os.tmpdir(), prefix));
 }

-test("parseArgs parses the main image-gen CLI flags", () => {
+test("parseArgs parses the main baoyu-imagine CLI flags", () => {
  const args = parseArgs([
    "--promptfiles",
    "prompts/system.md",
@@ -124,6 +124,7 @@ default_model:
  google: gemini-3-pro-image-preview
  openai: gpt-image-1.5
  azure: image-prod
+  minimax: image-01
 batch:
  max_workers: 8
  provider_limits:
@@ -132,6 +133,9 @@ batch:
      start_interval_ms: 900
    openai:
      concurrency: 4
+    minimax:
+      concurrency: 2
+      start_interval_ms: 1400
    azure:
      concurrency: 1
      start_interval_ms: 1500
@@ -147,6 +151,7 @@ batch:
  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?.azure, "image-prod");
+  assert.equal(config.default_model?.minimax, "image-01");
  assert.equal(config.batch?.max_workers, 8);
  assert.deepEqual(config.batch?.provider_limits?.google, {
    concurrency: 2,
@@ -155,6 +160,10 @@ batch:
  assert.deepEqual(config.batch?.provider_limits?.openai, {
    concurrency: 4,
  });
+  assert.deepEqual(config.batch?.provider_limits?.minimax, {
+    concurrency: 2,
+    start_interval_ms: 1400,
+  });
  assert.deepEqual(config.batch?.provider_limits?.azure, {
    concurrency: 1,
    start_interval_ms: 1500,
@@ -200,6 +209,7 @@ test("detectProvider rejects non-ref-capable providers and prefers Google first
    OPENAI_API_KEY: "openai-key",
    OPENROUTER_API_KEY: null,
    DASHSCOPE_API_KEY: null,
+    MINIMAX_API_KEY: null,
    REPLICATE_API_TOKEN: null,
    JIMENG_ACCESS_KEY_ID: null,
    JIMENG_SECRET_ACCESS_KEY: null,
@@ -216,6 +226,7 @@ test("detectProvider selects an available ref-capable provider for reference-ima
    AZURE_OPENAI_BASE_URL: null,
    OPENROUTER_API_KEY: null,
    DASHSCOPE_API_KEY: null,
+    MINIMAX_API_KEY: null,
    REPLICATE_API_TOKEN: null,
    JIMENG_ACCESS_KEY_ID: null,
    JIMENG_SECRET_ACCESS_KEY: null,
@@ -235,6 +246,7 @@ test("detectProvider selects Azure when only Azure credentials are configured",
    AZURE_OPENAI_BASE_URL: "https://example.openai.azure.com",
    OPENROUTER_API_KEY: null,
    DASHSCOPE_API_KEY: null,
+    MINIMAX_API_KEY: null,
    REPLICATE_API_TOKEN: null,
    JIMENG_ACCESS_KEY_ID: null,
    JIMENG_SECRET_ACCESS_KEY: null,
@@ -254,6 +266,7 @@ test("detectProvider infers Seedream from model id and allows Seedream reference
    OPENAI_API_KEY: null,
    OPENROUTER_API_KEY: null,
    DASHSCOPE_API_KEY: null,
+    MINIMAX_API_KEY: null,
    REPLICATE_API_TOKEN: null,
    JIMENG_ACCESS_KEY_ID: null,
    JIMENG_SECRET_ACCESS_KEY: null,
@@ -281,6 +294,26 @@ test("detectProvider infers Seedream from model id and allows Seedream reference
  );
 });

+test("detectProvider selects MiniMax when only MiniMax credentials are configured 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,
+    MINIMAX_API_KEY: "minimax-key",
+    REPLICATE_API_TOKEN: null,
+    JIMENG_ACCESS_KEY_ID: null,
+    JIMENG_SECRET_ACCESS_KEY: null,
+    ARK_API_KEY: null,
+  });
+
+  assert.equal(detectProvider(makeArgs()), "minimax");
+  assert.equal(detectProvider(makeArgs({ referenceImages: ["ref.png"] })), "minimax");
+  assert.equal(detectProvider(makeArgs({ model: "image-01-live" })), "minimax");
+});
+
 test("batch worker and provider-rate-limit configuration prefer env over EXTEND config", (t) => {
  useEnv(t, {
    BAOYU_IMAGE_GEN_MAX_WORKERS: "12",
@@ -296,6 +329,10 @@ test("batch worker and provider-rate-limit configuration prefer env over EXTEND
          concurrency: 2,
          start_interval_ms: 900,
        },
+        minimax: {
+          concurrency: 1,
+          start_interval_ms: 1500,
+        },
      },
    },
  };
@@ -305,10 +342,14 @@ test("batch worker and provider-rate-limit configuration prefer env over EXTEND
    concurrency: 5,
    startIntervalMs: 450,
  });
+  assert.deepEqual(getConfiguredProviderRateLimits(extendConfig).minimax, {
+    concurrency: 1,
+    startIntervalMs: 1500,
+  });
 });

 test("loadBatchTasks and createTaskArgs resolve batch-relative paths", async (t) => {
-  const root = await makeTempDir("baoyu-image-gen-batch-");
+  const root = await makeTempDir("baoyu-imagine-batch-");
  t.after(() => fs.rm(root, { recursive: true, force: true }));

  const batchFile = path.join(root, "jobs", "batch.json");
@@ -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 },
+  minimax: { concurrency: 3, startIntervalMs: 1100 },
  jimeng: { concurrency: 3, startIntervalMs: 1100 },
  seedream: { concurrency: 3, startIntervalMs: 1100 },
  azure: { concurrency: 3, startIntervalMs: 1100 },
@@ -75,13 +76,13 @@ 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|replicate|jimeng|seedream|azure  Force provider (auto-detect by default)
+  --provider google|openai|openrouter|dashscope|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)
  --quality normal|2k       Quality preset (default: 2k)
  --imageSize 1K|2K|4K      Image size for Google/OpenRouter (default: from quality)
-  --ref <files...>          Reference images (Google, OpenAI, Azure, OpenRouter, Replicate, or Seedream 4.0/4.5/5.0)
+  --ref <files...>          Reference images (Google, OpenAI, Azure, OpenRouter, Replicate, MiniMax, or Seedream 4.0/4.5/5.0)
  --n <count>               Number of images for the current task (default: 1)
  --json                    JSON output
  -h, --help                Show help
@@ -112,6 +113,7 @@ 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
+  MINIMAX_API_KEY           MiniMax API key
  REPLICATE_API_TOKEN       Replicate API token
  JIMENG_ACCESS_KEY_ID      Jimeng Access Key ID
  JIMENG_SECRET_ACCESS_KEY  Jimeng Secret Access Key
@@ -120,6 +122,7 @@ 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)
+  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)
  SEEDREAM_IMAGE_MODEL      Default Seedream model (doubao-seedream-5-0-260128)
@@ -130,6 +133,7 @@ Environment variables:
  OPENROUTER_TITLE          Optional app name for OpenRouter attribution
  GOOGLE_BASE_URL           Custom Google endpoint
  DASHSCOPE_BASE_URL        Custom DashScope endpoint
+  MINIMAX_BASE_URL          Custom MiniMax endpoint
  REPLICATE_BASE_URL        Custom Replicate endpoint
  JIMENG_BASE_URL           Custom Jimeng endpoint
  AZURE_OPENAI_API_KEY      Azure OpenAI API key
@@ -235,6 +239,7 @@ export function parseArgs(argv: string[]): CliArgs {
        v !== "openai" &&
        v !== "openrouter" &&
        v !== "dashscope" &&
+        v !== "minimax" &&
        v !== "replicate" &&
        v !== "jimeng" &&
        v !== "seedream" &&
@@ -390,6 +395,7 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
          openai: null,
          openrouter: null,
          dashscope: null,
+          minimax: null,
          replicate: null,
          jimeng: null,
          seedream: null,
@@ -417,6 +423,7 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
          key === "openai" ||
          key === "openrouter" ||
          key === "dashscope" ||
+          key === "minimax" ||
          key === "replicate" ||
          key === "jimeng" ||
          key === "seedream" ||
@@ -434,6 +441,7 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
          key === "openai" ||
          key === "openrouter" ||
          key === "dashscope" ||
+          key === "minimax" ||
          key === "replicate" ||
          key === "jimeng" ||
          key === "seedream" ||
@@ -468,8 +476,8 @@ async function loadExtendConfig(): Promise<Partial<ExtendConfig>> {
  const cwd = process.cwd();

  const paths = [
-    path.join(cwd, ".baoyu-skills", "baoyu-image-gen", "EXTEND.md"),
-    path.join(home, ".baoyu-skills", "baoyu-image-gen", "EXTEND.md"),
+    path.join(cwd, ".baoyu-skills", "baoyu-imagine", "EXTEND.md"),
+    path.join(home, ".baoyu-skills", "baoyu-imagine", "EXTEND.md"),
  ];

  for (const p of paths) {
@@ -528,12 +536,13 @@ export function getConfiguredProviderRateLimits(
    openai: { ...DEFAULT_PROVIDER_RATE_LIMITS.openai },
    openrouter: { ...DEFAULT_PROVIDER_RATE_LIMITS.openrouter },
    dashscope: { ...DEFAULT_PROVIDER_RATE_LIMITS.dashscope },
+    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", "jimeng", "seedream", "azure"] as Provider[]) {
+  for (const provider of ["replicate", "google", "openai", "openrouter", "dashscope", "minimax", "jimeng", "seedream", "azure"] as Provider[]) {
    const envPrefix = `BAOYU_IMAGE_GEN_${provider.toUpperCase()}`;
    const extendLimit = extendConfig.batch?.provider_limits?.[provider];
    configured[provider] = {
@@ -582,7 +591,9 @@ export function normalizeOutputImagePath(p: string, defaultExtension = ".png"):

 function inferProviderFromModel(model: string | null): Provider | null {
  if (!model) return null;
-  if (model.includes("seedream") || model.includes("seededit")) return "seedream";
+  const normalized = model.trim();
+  if (normalized.includes("seedream") || normalized.includes("seededit")) return "seedream";
+  if (normalized === "image-01" || normalized === "image-01-live") return "minimax";
  return null;
 }

@@ -595,10 +606,11 @@ export function detectProvider(args: CliArgs): Provider {
    args.provider !== "azure" &&
    args.provider !== "openrouter" &&
    args.provider !== "replicate" &&
-    args.provider !== "seedream"
+    args.provider !== "seedream" &&
+    args.provider !== "minimax"
  ) {
    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, or --provider seedream for supported Seedream models."
+      "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."
    );
  }

@@ -609,6 +621,7 @@ 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 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);
  const hasSeedream = !!process.env.ARK_API_KEY;
@@ -621,6 +634,13 @@ export function detectProvider(args: CliArgs): Provider {
    return "seedream";
  }

+  if (modelProvider === "minimax") {
+    if (!hasMinimax) {
+      throw new Error("Model looks like a MiniMax image model, but MINIMAX_API_KEY is not set.");
+    }
+    return "minimax";
+  }
+
  if (args.referenceImages.length > 0) {
    if (hasGoogle) return "google";
    if (hasOpenai) return "openai";
@@ -628,8 +648,9 @@ export function detectProvider(args: CliArgs): Provider {
    if (hasOpenrouter) return "openrouter";
    if (hasReplicate) return "replicate";
    if (hasSeedream) return "seedream";
+    if (hasMinimax) return "minimax";
    throw new Error(
-      "Reference images require Google, OpenAI, Azure, OpenRouter, Replicate, or supported Seedream models. Set GOOGLE_API_KEY/GEMINI_API_KEY, OPENAI_API_KEY, AZURE_OPENAI_API_KEY+AZURE_OPENAI_BASE_URL, OPENROUTER_API_KEY, REPLICATE_API_TOKEN, or ARK_API_KEY, or remove --ref."
+      "Reference images require Google, OpenAI, Azure, OpenRouter, Replicate, supported Seedream models, or MiniMax. Set GOOGLE_API_KEY/GEMINI_API_KEY, OPENAI_API_KEY, AZURE_OPENAI_API_KEY+AZURE_OPENAI_BASE_URL, OPENROUTER_API_KEY, REPLICATE_API_TOKEN, ARK_API_KEY, or MINIMAX_API_KEY, or remove --ref."
    );
  }

@@ -639,6 +660,7 @@ export function detectProvider(args: CliArgs): Provider {
    hasAzure && "azure",
    hasOpenrouter && "openrouter",
    hasDashscope && "dashscope",
+    hasMinimax && "minimax",
    hasReplicate && "replicate",
    hasJimeng && "jimeng",
    hasSeedream && "seedream",
@@ -648,7 +670,7 @@ 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, REPLICATE_API_TOKEN, JIMENG keys, or ARK_API_KEY.\n" +
+    "No API key found. Set GOOGLE_API_KEY, GEMINI_API_KEY, OPENAI_API_KEY, AZURE_OPENAI_API_KEY+AZURE_OPENAI_BASE_URL, OPENROUTER_API_KEY, DASHSCOPE_API_KEY, MINIMAX_API_KEY, REPLICATE_API_TOKEN, JIMENG keys, or ARK_API_KEY.\n" +
      "Create ~/.baoyu-skills/.env or <cwd>/.baoyu-skills/.env with your keys."
  );
 }
@@ -687,6 +709,7 @@ 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 === "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;
  if (provider === "jimeng") return (await import("./providers/jimeng")) as ProviderModule;
@@ -717,6 +740,7 @@ function getModelForProvider(
      return extendConfig.default_model.openrouter;
    }
    if (provider === "dashscope" && extendConfig.default_model.dashscope) return extendConfig.default_model.dashscope;
+    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;
    if (provider === "seedream" && extendConfig.default_model.seedream) return extendConfig.default_model.seedream;
@@ -136,7 +136,7 @@ test("Azure image generation routes model to deployment and sends mapped quality
 });

 test("Azure image edits include quality in multipart requests", async (t) => {
-  const root = await makeTempDir("baoyu-image-gen-azure-");
+  const root = await makeTempDir("baoyu-imagine-azure-");
  t.after(() => fs.rm(root, { recursive: true, force: true }));

  const pngPath = path.join(root, "ref.png");
@@ -421,7 +421,7 @@ export async function generateImage(

  if (args.referenceImages.length > 0) {
    throw new Error(
-      "Reference images are not supported with DashScope provider in baoyu-image-gen. Use --provider google with a Gemini multimodal model."
+      "Reference images are not supported with DashScope provider in baoyu-imagine. Use --provider google with a Gemini multimodal model."
    );
  }

@@ -0,0 +1,171 @@
+import assert from "node:assert/strict";
+import fs from "node:fs/promises";
+import os from "node:os";
+import path from "node:path";
+import test, { type TestContext } from "node:test";
+
+import type { CliArgs } from "../types.ts";
+import {
+  buildMinimaxUrl,
+  buildRequestBody,
+  buildSubjectReference,
+  extractImageFromResponse,
+  parsePixelSize,
+  validateArgs,
+} from "./minimax.ts";
+
+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;
+      }
+    }
+  });
+}
+
+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,
+  };
+}
+
+test("MiniMax URL builder normalizes /v1 suffixes", (t) => {
+  useEnv(t, { MINIMAX_BASE_URL: "https://api.minimax.io" });
+  assert.equal(buildMinimaxUrl(), "https://api.minimax.io/v1/image_generation");
+
+  process.env.MINIMAX_BASE_URL = "https://proxy.example.com/custom/v1/";
+  assert.equal(buildMinimaxUrl(), "https://proxy.example.com/custom/v1/image_generation");
+});
+
+test("MiniMax size parsing and validation follow documented constraints", () => {
+  assert.deepEqual(parsePixelSize("1536x1024"), { width: 1536, height: 1024 });
+  assert.deepEqual(parsePixelSize("1536*1024"), { width: 1536, height: 1024 });
+  assert.equal(parsePixelSize("wide"), null);
+
+  validateArgs("image-01", makeArgs({ size: "1536x1024", n: 9 }));
+
+  assert.throws(
+    () => validateArgs("image-01-live", makeArgs({ size: "1536x1024" })),
+    /only supported with model image-01/,
+  );
+  assert.throws(
+    () => validateArgs("image-01", makeArgs({ size: "1537x1024" })),
+    /divisible by 8/,
+  );
+  assert.throws(
+    () => validateArgs("image-01", makeArgs({ aspectRatio: "2.35:1" })),
+    /aspect_ratio must be one of/,
+  );
+  assert.throws(
+    () => validateArgs("image-01", makeArgs({ n: 10 })),
+    /at most 9 images/,
+  );
+});
+
+test("MiniMax request body maps aspect ratio, size, n, and subject references", async (t) => {
+  const dir = await fs.mkdtemp(path.join(os.tmpdir(), "minimax-test-"));
+  t.after(() => fs.rm(dir, { recursive: true, force: true }));
+
+  const refPath = path.join(dir, "portrait.png");
+  await fs.writeFile(refPath, Buffer.from("portrait"));
+
+  const ratioBody = await buildRequestBody(
+    "A portrait by the window",
+    "image-01",
+    makeArgs({ aspectRatio: "16:9", n: 2, referenceImages: [refPath] }),
+  );
+  assert.equal(ratioBody.aspect_ratio, "16:9");
+  assert.equal(ratioBody.n, 2);
+  assert.equal(ratioBody.response_format, "base64");
+  assert.match(ratioBody.subject_reference?.[0]?.image_file || "", /^data:image\/png;base64,/);
+
+  const sizeBody = await buildRequestBody(
+    "A portrait by the window",
+    "image-01",
+    makeArgs({ size: "1536x1024" }),
+  );
+  assert.equal(sizeBody.width, 1536);
+  assert.equal(sizeBody.height, 1024);
+  assert.equal(sizeBody.aspect_ratio, undefined);
+});
+
+test("MiniMax subject references require supported file types", async (t) => {
+  const dir = await fs.mkdtemp(path.join(os.tmpdir(), "minimax-ref-"));
+  t.after(() => fs.rm(dir, { recursive: true, force: true }));
+
+  const good = path.join(dir, "portrait.jpg");
+  const bad = path.join(dir, "portrait.webp");
+  await fs.writeFile(good, Buffer.from("portrait"));
+  await fs.writeFile(bad, Buffer.from("portrait"));
+
+  const subjectReference = await buildSubjectReference([good]);
+  assert.equal(subjectReference?.[0]?.type, "character");
+
+  await assert.rejects(
+    () => buildSubjectReference([bad]),
+    /only supports JPG, JPEG, or PNG/,
+  );
+});
+
+test("MiniMax response extraction supports base64 and URL payloads", async (t) => {
+  const originalFetch = globalThis.fetch;
+  t.after(() => {
+    globalThis.fetch = originalFetch;
+  });
+
+  const fromBase64 = await extractImageFromResponse({
+    data: {
+      image_base64: [Buffer.from("hello").toString("base64")],
+    },
+  });
+  assert.equal(Buffer.from(fromBase64).toString("utf8"), "hello");
+
+  globalThis.fetch = async () =>
+    new Response(Uint8Array.from([1, 2, 3]), {
+      status: 200,
+      headers: { "Content-Type": "image/jpeg" },
+    });
+
+  const fromUrl = await extractImageFromResponse({
+    data: {
+      image_urls: ["https://example.com/output.jpg"],
+    },
+  });
+  assert.deepEqual([...fromUrl], [1, 2, 3]);
+
+  await assert.rejects(
+    () => extractImageFromResponse({ base_resp: { status_code: 1001, status_msg: "blocked" } }),
+    /blocked/,
+  );
+});
@@ -0,0 +1,220 @@
+import path from "node:path";
+import { readFile } from "node:fs/promises";
+
+import type { CliArgs } from "../types";
+
+const DEFAULT_MODEL = "image-01";
+const MAX_REFERENCE_IMAGE_BYTES = 10 * 1024 * 1024;
+const SUPPORTED_ASPECT_RATIOS = new Set(["1:1", "16:9", "4:3", "3:2", "2:3", "3:4", "9:16", "21:9"]);
+
+type MinimaxSubjectReference = {
+  type: "character";
+  image_file: string;
+};
+
+type MinimaxRequestBody = {
+  model: string;
+  prompt: string;
+  response_format: "base64";
+  aspect_ratio?: string;
+  width?: number;
+  height?: number;
+  n?: number;
+  subject_reference?: MinimaxSubjectReference[];
+};
+
+type MinimaxResponse = {
+  id?: string;
+  data?: {
+    image_urls?: string[];
+    image_base64?: string[];
+  };
+  base_resp?: {
+    status_code?: number;
+    status_msg?: string;
+  };
+};
+
+export function getDefaultModel(): string {
+  return process.env.MINIMAX_IMAGE_MODEL || DEFAULT_MODEL;
+}
+
+function getApiKey(): string | null {
+  return process.env.MINIMAX_API_KEY || null;
+}
+
+export function buildMinimaxUrl(): string {
+  const base = (process.env.MINIMAX_BASE_URL || "https://api.minimax.io").replace(/\/+$/g, "");
+  return base.endsWith("/v1") ? `${base}/image_generation` : `${base}/v1/image_generation`;
+}
+
+function getMimeType(filename: string): "image/jpeg" | "image/png" {
+  const ext = path.extname(filename).toLowerCase();
+  if (ext === ".jpg" || ext === ".jpeg") return "image/jpeg";
+  if (ext === ".png") return "image/png";
+  throw new Error(
+    `MiniMax subject_reference only supports JPG, JPEG, or PNG files: ${filename}`
+  );
+}
+
+export function parsePixelSize(size: string): { width: number; height: number } | null {
+  const match = size.trim().match(/^(\d+)\s*[xX*]\s*(\d+)$/);
+  if (!match) return null;
+
+  const width = 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 validatePixelSize(width: number, height: number): void {
+  if (width < 512 || width > 2048 || height < 512 || height > 2048) {
+    throw new Error("MiniMax custom size must keep width and height between 512 and 2048.");
+  }
+  if (width % 8 !== 0 || height % 8 !== 0) {
+    throw new Error("MiniMax custom size requires width and height divisible by 8.");
+  }
+}
+
+export function validateArgs(model: string, args: CliArgs): void {
+  if (args.n > 9) {
+    throw new Error("MiniMax supports at most 9 images per request.");
+  }
+
+  if (args.aspectRatio && !SUPPORTED_ASPECT_RATIOS.has(args.aspectRatio)) {
+    throw new Error(
+      `MiniMax aspect_ratio must be one of: ${Array.from(SUPPORTED_ASPECT_RATIOS).join(", ")}.`
+    );
+  }
+
+  if (args.size && !args.aspectRatio) {
+    if (model !== "image-01") {
+      throw new Error("MiniMax custom --size is only supported with model image-01. Use --model image-01 or pass --ar instead.");
+    }
+    const parsed = parsePixelSize(args.size);
+    if (!parsed) {
+      throw new Error("MiniMax --size must be in WxH format, for example 1536x1024.");
+    }
+    validatePixelSize(parsed.width, parsed.height);
+  }
+}
+
+export async function buildSubjectReference(
+  referenceImages: string[],
+): Promise<MinimaxSubjectReference[] | undefined> {
+  if (referenceImages.length === 0) return undefined;
+
+  const subjectReference: MinimaxSubjectReference[] = [];
+  for (const refPath of referenceImages) {
+    const bytes = await readFile(refPath);
+    if (bytes.length > MAX_REFERENCE_IMAGE_BYTES) {
+      throw new Error(`MiniMax subject_reference images must be smaller than 10MB: ${refPath}`);
+    }
+
+    subjectReference.push({
+      type: "character",
+      image_file: `data:${getMimeType(refPath)};base64,${bytes.toString("base64")}`,
+    });
+  }
+
+  return subjectReference;
+}
+
+export async function buildRequestBody(
+  prompt: string,
+  model: string,
+  args: CliArgs,
+): Promise<MinimaxRequestBody> {
+  validateArgs(model, args);
+
+  const body: MinimaxRequestBody = {
+    model,
+    prompt,
+    response_format: "base64",
+  };
+
+  if (args.aspectRatio) {
+    body.aspect_ratio = args.aspectRatio;
+  } else if (args.size) {
+    const parsed = parsePixelSize(args.size);
+    if (!parsed) {
+      throw new Error("MiniMax --size must be in WxH format, for example 1536x1024.");
+    }
+    body.width = parsed.width;
+    body.height = parsed.height;
+  }
+
+  if (args.n > 1) {
+    body.n = args.n;
+  }
+
+  const subjectReference = await buildSubjectReference(args.referenceImages);
+  if (subjectReference) {
+    body.subject_reference = subjectReference;
+  }
+
+  return body;
+}
+
+async function downloadImage(url: string): Promise<Uint8Array> {
+  const response = await fetch(url);
+  if (!response.ok) {
+    throw new Error(`Failed to download image from MiniMax: ${response.status}`);
+  }
+  return new Uint8Array(await response.arrayBuffer());
+}
+
+export async function extractImageFromResponse(result: MinimaxResponse): Promise<Uint8Array> {
+  const baseResp = result.base_resp;
+  if (baseResp && baseResp.status_code !== undefined && baseResp.status_code !== 0) {
+    throw new Error(baseResp.status_msg || `MiniMax API returned status_code=${baseResp.status_code}`);
+  }
+
+  const base64Image = result.data?.image_base64?.[0];
+  if (base64Image) {
+    return Uint8Array.from(Buffer.from(base64Image, "base64"));
+  }
+
+  const url = result.data?.image_urls?.[0];
+  if (url) {
+    return downloadImage(url);
+  }
+
+  throw new Error("No image data in MiniMax response");
+}
+
+export function getDefaultOutputExtension(): ".jpg" {
+  return ".jpg";
+}
+
+export async function generateImage(
+  prompt: string,
+  model: string,
+  args: CliArgs
+): Promise<Uint8Array> {
+  const apiKey = getApiKey();
+  if (!apiKey) {
+    throw new Error("MINIMAX_API_KEY is required. Get one from https://platform.minimax.io/");
+  }
+
+  const body = await buildRequestBody(prompt, model, args);
+  const response = await fetch(buildMinimaxUrl(), {
+    method: "POST",
+    headers: {
+      "Content-Type": "application/json",
+      Authorization: `Bearer ${apiKey}`,
+    },
+    body: JSON.stringify(body),
+  });
+
+  if (!response.ok) {
+    const err = await response.text();
+    throw new Error(`MiniMax API error (${response.status}): ${err}`);
+  }
+
+  const result = (await response.json()) as MinimaxResponse;
+  return extractImageFromResponse(result);
+}
@@ -1,4 +1,13 @@
-export type Provider = "google" | "openai" | "openrouter" | "dashscope" | "replicate" | "jimeng" | "seedream" | "azure";
+export type Provider =
+  | "google"
+  | "openai"
+  | "openrouter"
+  | "dashscope"
+  | "minimax"
+  | "replicate"
+  | "jimeng"
+  | "seedream"
+  | "azure";
 export type Quality = "normal" | "2k";

 export type CliArgs = {
@@ -52,6 +61,7 @@ export type ExtendConfig = {
    openai: string | null;
    openrouter: string | null;
    dashscope: string | null;
+    minimax: string | null;
    replicate: string | null;
    jimeng: string | null;
    seedream: string | null;
Author	SHA1	Message	Date
Jim Liu 宝玉	7a0ffd9533	chore: release v1.84.0	2026-03-25 16:29:22 -05:00
Jim Liu 宝玉	69355b4ee1	feat(baoyu-imagine): rename baoyu-image-gen to baoyu-imagine	2026-03-25 16:28:06 -05:00
Jim Liu 宝玉	23b7487321	chore: release v1.83.0	2026-03-25 15:40:22 -05:00
Jim Liu 宝玉	ad8781c1c5	feat(baoyu-image-gen): add MiniMax provider with subject reference and custom sizes	2026-03-25 15:39:40 -05:00