首页/多媒体与音视频/baoyu-imagine
B

baoyu-imagine

by @jimliuv
4.5(20)

整合 OpenAI、通义万象、即梦等多家 AI 图像生成 API，通过统一接口快速实现文本到图像的转换

image-generationgenerative-aiapi-integrationGitHub
安装方式
npx skills add jimliu/baoyu-skills --skill baoyu-imagine
compare_arrows

Before / After 效果对比

1 组
使用前

需要分别注册和配置多个图像生成服务的账号，学习各自的 API 文档，编写不同的调用代码，调试参数格式，一个项目需要 2-3 天才能对接完成

使用后

统一接口调用 8 家主流图像生成服务，一次配置即可切换不同提供商，输入提示词自动生成高质量图像，30 分钟完成多平台对比测试

SKILL.md

baoyu-imagine

Image Generation (AI SDK)

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

Script Directory

Agent Execution:

  • {baseDir} = this SKILL.md file's directory

  • Script path = {baseDir}/scripts/main.ts

  • Resolve ${BUN_X} runtime: if bun installed → bun; if npx available → npx -y bun; else suggest installing bun

Step 0: Load Preferences ⛔ BLOCKING

CRITICAL: This step MUST complete BEFORE any image generation. Do NOT skip or defer.

Check EXTEND.md existence (priority: project → user):

# macOS, Linux, WSL, Git Bash
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 (Windows)
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 "$xdg/baoyu-skills/baoyu-imagine/EXTEND.md") { "xdg" }
if (Test-Path "$HOME/.baoyu-skills/baoyu-imagine/EXTEND.md") { "user" }

Result Action

Found Load, parse, apply settings. If default_model.[provider] is null → ask model only (Flow 2)

Not found ⛔ Run first-time setup (references/config/first-time-setup.md) → Save EXTEND.md → Then continue

CRITICAL: If not found, complete the full setup (provider + model + quality + save location) using AskUserQuestion BEFORE generating any images. Generation is BLOCKED until EXTEND.md is created.

Path Location

.baoyu-skills/baoyu-imagine/EXTEND.md Project directory

$HOME/.baoyu-skills/baoyu-imagine/EXTEND.md User home

Legacy compatibility: if .baoyu-skills/baoyu-image-gen/EXTEND.md exists and the new path does not, runtime renames it to baoyu-imagine. If both files exist, runtime leaves them unchanged and uses the new path.

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

Schema: references/config/preferences-schema.md

Usage

# Basic
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image cat.png

# With aspect ratio
${BUN_X} {baseDir}/scripts/main.ts --prompt "A landscape" --image out.png --ar 16:9

# High quality
${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, 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)
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --provider google --model gemini-3-pro-image-preview --ref source.png

# Azure OpenAI (model means deployment name)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider azure --model gpt-image-1.5

# OpenRouter (recommended default model)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openrouter

# OpenRouter with reference images
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --provider openrouter --model google/gemini-3.1-flash-image-preview --ref source.png

# Specific provider
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openai

# DashScope (阿里通义万象)
${BUN_X} {baseDir}/scripts/main.ts --prompt "一只可爱的猫" --image out.png --provider dashscope

# DashScope Qwen-Image 2.0 Pro (recommended for custom sizes and text rendering)
${BUN_X} {baseDir}/scripts/main.ts --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 out.png --provider dashscope --model qwen-image-2.0-pro --size 2048x872

# 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

# Replicate with specific model
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate --model google/nano-banana

# Batch mode with saved prompt files
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json

# Batch mode with explicit worker count
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4 --json

Batch File Format

{
  "jobs": 4,
  "tasks": [
    {
      "id": "hero",
      "promptFiles": ["prompts/hero.md"],
      "image": "out/hero.png",
      "provider": "replicate",
      "model": "google/nano-banana-pro",
      "ar": "16:9",
      "quality": "2k"
    },
    {
      "id": "diagram",
      "promptFiles": ["prompts/diagram.md"],
      "image": "out/diagram.png",
      "ref": ["references/original.png"]
    }
  ]
}

Paths in promptFiles, image, and ref are resolved relative to the batch file's directory. jobs is optional (overridden by CLI --jobs). Top-level array format (without jobs wrapper) is also accepted.

Options

Option Description

--prompt <text>, -p Prompt text

--promptfiles <files...> Read prompt from files (concatenated)

--image <path> Output image path (required in single-image mode)

--batchfile <path> JSON batch file for multi-image generation

--jobs <count> Worker count for batch mode (default: auto, max from config, built-in default 10)

--provider google|openai|azure|openrouter|dashscope|minimax|jimeng|seedream|replicate Force provider (default: auto-detect)

--model <id>, -m Model ID (Google: gemini-3-pro-image-preview; OpenAI: gpt-image-1.5; Azure: deployment name such as gpt-image-1.5 or image-prod; OpenRouter: google/gemini-3.1-flash-image-preview; DashScope: qwen-image-2.0-pro; MiniMax: image-01)

--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, 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

Environment Variables

Variable Description

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

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

ARK_API_KEY Seedream (豆包) Volcengine ARK API key

OPENAI_IMAGE_MODEL OpenAI model override

AZURE_OPENAI_DEPLOYMENT Azure default deployment name

AZURE_OPENAI_IMAGE_MODEL Backward-compatible alias for Azure default deployment/model name

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)

OPENAI_BASE_URL Custom OpenAI endpoint

AZURE_OPENAI_BASE_URL Azure resource endpoint or deployment endpoint

AZURE_API_VERSION Azure image API version (default: 2025-04-01-preview)

OPENROUTER_BASE_URL Custom OpenRouter endpoint (default: 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 (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)

SEEDREAM_BASE_URL Custom Seedream endpoint (default: https://ark.cn-beijing.volces.com/api/v3)

BAOYU_IMAGE_GEN_MAX_WORKERS Override batch worker cap

BAOYU_IMAGE_GEN_<PROVIDER>_CONCURRENCY Override provider concurrency, e.g. BAOYU_IMAGE_GEN_REPLICATE_CONCURRENCY

BAOYU_IMAGE_GEN_<PROVIDER>_START_INTERVAL_MS Override provider start gap, e.g. BAOYU_IMAGE_GEN_REPLICATE_START_INTERVAL_MS

Load Priority: CLI args > EXTEND.md > env vars > <cwd>/.baoyu-skills/.env > ~/.baoyu-skills/.env

Model Resolution

Model priority (highest → lowest), applies to all providers:

  • CLI flag: --model <id>

  • EXTEND.md: default_model.[provider]

  • Env var: <PROVIDER>_IMAGE_MODEL (e.g., GOOGLE_IMAGE_MODEL)

  • Built-in default

For Azure, --model / default_model.azure should be the Azure deployment name. AZURE_OPENAI_DEPLOYMENT is the preferred env var, and AZURE_OPENAI_IMAGE_MODEL remains as a backward-compatible alias.

EXTEND.md overrides env vars. If both EXTEND.md default_model.google: "gemini-3-pro-image-preview" and env var GOOGLE_IMAGE_MODEL=gemini-3.1-flash-image-preview exist, EXTEND.md wins.

Agent MUST display model info before each generation:

  • Show: Using [provider] / [model]

  • Show switch hint: Switch model: --model <id> | EXTEND.md default_model.[provider] | env <PROVIDER>_IMAGE_MODEL

DashScope Models

Use --model qwen-image-2.0-pro or set default_model.dashscope / DASHSCOPE_IMAGE_MODEL when the user wants official Qwen-Image behavior.

Official DashScope model families:

  • qwen-image-2.0-pro, qwen-image-2.0-pro-2026-03-03, qwen-image-2.0, qwen-image-2.0-2026-03-03

Free-form size in 宽*高 format

  • Total pixels must stay between 512*512 and 2048*2048

  • Default size is approximately 1024*1024

  • Best choice for custom ratios such as 21:9 and text-heavy Chinese/English layouts

  • qwen-image-max, qwen-image-max-2025-12-30, qwen-image-plus, qwen-image-plus-2026-01-09, qwen-image

Fixed sizes only: 1664*928, 1472*1104, 1328*1328, 1104*1472, 928*1664

  • Default size is 1664*928

  • qwen-image currently has the same capability as qwen-image-plus

  • Legacy DashScope models such as z-image-turbo, z-image-ultra, wanx-v1

Keep using them only when the user explicitly asks for legacy behavior or compatibility

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-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:

Ratio normal 2k

1:1 1024*1024 1536*1536

2:3 768*1152 1024*1536

3:2 1152*768 1536*1024

3:4 960*1280 1080*1440

4:3 1280*960 1440*1080

9:16 720*1280 1080*1920

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-imagine does not expose them as dedicated CLI flags today.

Official references:

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:

OpenRouter Models

Use full OpenRouter model IDs, e.g.:

  • google/gemini-3.1-flash-image-preview (recommended, supports image output and reference-image workflows)

  • google/gemini-2.5-flash-image-preview

  • black-forest-labs/flux.2-pro

  • Other OpenRouter image-capable model IDs

Notes:

  • OpenRouter image generation uses /chat/completions, not the OpenAI /images endpoints

  • If --ref is used, choose a multimodal model that supports image input and image output

  • --imageSize maps to OpenRouter `imageGener

...

用户评价 (0)

发表评价

效果
易用性
文档
兼容性

暂无评价

统计数据

安装量8.9K
评分4.5 / 5.0
版本
更新日期2026年5月23日
对比案例1 组

用户评分

4.5(20)
5
20%
4
50%
3
25%
2
5%
1
0%

为此 Skill 评分

0.0

兼容平台

🔧Claude Code

时间线

创建2026年3月28日
最后更新2026年5月23日