baoyu-imagine
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
npx skills add jimliu/baoyu-skills --skill baoyu-imagineBefore / After 效果对比
1 组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
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
description 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
${BUN_X}runtime: ifbuninstalled →bun; ifnpxavailable →npx -y bun; else suggest installing bun
Step 0: Load Preferences ⛔ BLOCKING
CRITICAL: This step MUST complete BEFORE any image generation. Do NOT skip or defer.
Check EXTEND.md existence (priority: project → user):
# macOS, Linux, WSL, Git Bash
test -f .baoyu-skills/baoyu-imagine/EXTEND.md && echo "project"
test -f "${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*512and2048*2048 -
Default size is approximately
1024*1024 -
Best choice for custom ratios such as
21:9and 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-imagecurrently has the same capability asqwen-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:
-
--sizewins over--ar -
For
qwen-image-2.0*, prefer explicit--size; otherwise infer from--arand 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 toqwen-image-2.0-pro -
--qualityis a baoyu-imagine compatibility preset, not a native DashScope API field. Mappingnormal/2konto theqwen-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_ratiovalues:1:1,16:9,4:3,3:2,2:3,3:4,9:16,21:9 -
Supports documented custom
width/heightoutput sizes when using--size <WxH> -
widthandheightmust both be between512and2048, and both must be divisible by8 -
image-01-live
Lower-latency variant
- Use
--arfor sizing; MiniMax documents customwidth/heightas only effective forimage-01
MiniMax subject reference notes:
-
--reffiles are sent as MiniMaxsubject_reference -
MiniMax docs currently describe
subject_reference[].typeascharacter -
Official docs say
image_filesupports public URLs or Base64 Data URLs;baoyu-imaginesends 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/imagesendpoints -
If
--refis used, choose a multimodal model that supports image input and image output -
--imageSizemaps to OpenRouterimageGenerationOptions.size;--size <WxH>is converted to the nearest OpenRouter size and inferred aspect ratio when possible
Replicate Models
Supported model formats:
-
owner/name(recommended for official models), e.g.google/nano-banana-pro -
owner/name:version(community models by version), e.g.stability-ai/sdxl:<version>
Examples:
# Use Replicate default model
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate
# Override model explicitly
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate --model google/nano-banana
Provider Selection
-
--refprovided + 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) -
--providerspecified → use it (if--ref, must begoogle,openai,azure,openrouter,replicate,seedream, orminimax) -
Only one API key available → use that provider
-
Multiple available → default to Google
Quality Presets
Preset Google imageSize OpenAI Size OpenRouter size Replicate resolution Use Case
normal
1K
1024px
1K
1K
Quick previews
2k (default)
2K
2048px
2K
2K
Covers, illustrations, infographics
Google/OpenRouter imageSize: Can be overridden with --imageSize 1K|2K|4K
Aspect Ratios
Supported: 1:1, 16:9, 9:16, 4:3, 3:4, 2.35:1
-
Google multimodal: uses
imageConfig.aspectRatio -
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_ratioto model; when--refis provided without--ar, defaults tomatch_input_image -
MiniMax: sends official
aspect_ratiovalues directly; if--size <WxH>is given without--ar,width/heightare sent forimage-01
Generation Mode
Default: Sequential generation.
Batch Parallel Generation: When --batchfile contains 2 or more pending tasks, the script automatically enables parallel generation.
Mode When to Use
Sequential (default) Normal usage, single images, small batches
Parallel batch Batch mode with 2+ tasks
Execution choice:
Situation Preferred approach Why
One image, or 1-2 simple images Sequential Lower coordination overhead and easier debugging
Multiple images already have saved prompt files
Batch (--batchfile)
Reuses finalized prompts, applies shared throttling/retries, and gives predictable throughput
Each image still needs separate reasoning, prompt writing, or style exploration Subagents The work is still exploratory, so each image may need independent analysis before generation
Output comes from baoyu-article-illustrator with outline.md + prompts/
Batch (build-batch.ts -> --batchfile)
That workflow already produces prompt files, so direct batch execution is the intended path
Rule of thumb:
-
Prefer batch over subagents once prompt files are already saved and the task is "generate all of these"
-
Use subagents only when generation is coupled with per-image thinking, rewriting, or divergent creative exploration
Parallel behavior:
-
Default worker count is automatic, capped by config, built-in default 10
-
Provider-specific throttling is applied only in batch mode, and the built-in defaults are tuned for faster throughput while still avoiding obvious RPM bursts
-
You can override worker count with
--jobs <count> -
Each image retries automatically up to 3 attempts
-
Final output includes success count, failure count, and per-image failure reasons
Error Handling
-
Missing API key → error with setup instructions
-
Generation failure → auto-retry up to 3 attempts per image
-
Invalid aspect ratio → warning, proceed with default
-
Reference images with unsupported provider/model → error with fix hint
Extension Support
Custom configurations via EXTEND.md. See Preferences section for paths and supported options. Weekly Installs407Repositoryjimliu/baoyu-skillsGitHub Stars11.8KFirst Seen2 days agoSecurity AuditsGen Agent Trust HubPassSocketPassSnykPassInstalled oncodex398gemini-cli398opencode398kimi-cli397github-copilot397cursor397
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