
baoyu-image-gen
热门AI image generation with OpenAI GPT Image 2, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream, Replicate and Agnes 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.
AI image generation with OpenAI GPT Image 2, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream, Replicate and Agnes 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.
Image Generation (AI SDK)
Official API-based image generation. Supports OpenAI GPT Image 2, Azure OpenAI, Google, OpenRouter, DashScope (阿里通义万象), Z.AI GLM-Image, MiniMax, Jimeng (即梦), Seedream (豆包), Replicate and Agnes.
User Input Tools
When this skill prompts the user, follow this tool-selection rule (priority order):
- Prefer built-in user-input tools exposed by the current agent runtime — e.g.,
AskUserQuestion,request_user_input,clarify,ask_user, or any equivalent. - Fallback: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question.
- Batching: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.
Concrete AskUserQuestion references below are examples — substitute the local equivalent in other runtimes.
Script Directory
{baseDir} = this SKILL.md's directory. All scripts/... paths below are relative to {baseDir}. Main script: {baseDir}/scripts/main.ts. Batch payload helper: {baseDir}/scripts/build-batch.ts. Resolve ${BUN_X}: prefer bun; else npx -y bun; else suggest brew install oven-sh/bun/bun.
Step 0: Load Preferences ⛔ BLOCKING
This step MUST complete before any image generation — generation is blocked until EXTEND.md exists.
Check these paths in order; first hit wins:
| Path | Scope |
|---|---|
.baoyu-skills/baoyu-image-gen/EXTEND.md |
Project |
${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-image-gen/EXTEND.md |
XDG |
$HOME/.baoyu-skills/baoyu-image-gen/EXTEND.md |
User home |
- Found → load, parse, apply. If
default_model.[provider]is null → ask model only. - Not found → run first-time setup (
references/config/first-time-setup.md) using AskUserQuestion to collect provider + model + quality + save location. Save EXTEND.md, then continue. Do not generate images before this completes.
Legacy compatibility: if .baoyu-skills/baoyu-imagine/EXTEND.md exists and the new path doesn't, the runtime renames it to baoyu-image-gen. If both exist, the runtime leaves them alone and uses the new path.
EXTEND.md keys: default provider, default quality, default aspect ratio, default image size, OpenAI image API dialect, default models, batch worker cap, provider-specific batch limits. Schema: references/config/preferences-schema.md.
Usage
Minimum working examples — see references/usage-examples.md for the full set including per-provider invocations and batch mode.
Identity-preserving reference prompts
When the user wants a real person/character/object preserved from reference images, do not replace the reference with a long generic description. Prefer short, hard identity-preservation language:
- "Use the person/object in the reference image(s) as the same identity. Do not redesign it or create a similar-looking new subject."
- "Only change scene, clothing, pose, lighting, rendering style, and composition. Keep the face/proportions/hair/key accessories/overall identity from the references."
- If using multiple references, state that they are the same subject and should jointly define identity.
Pitfall: long descriptions like "young East Asian woman, oval face, clear eyes..." can cause the model to synthesize a new person matching the description instead of preserving the referenced person.
# Basic
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image cat.png
# With aspect ratio and high quality
${BUN_X} {baseDir}/scripts/main.ts --prompt "A landscape" --image out.png --ar 16:9 --quality 2k
# Prompt from files
${BUN_X} {baseDir}/scripts/main.ts --promptfiles system.md content.md --image out.png
# With reference image
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --ref source.png
# Specific provider
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider dashscope --model qwen-image-2.0-pro
# OpenAI GPT Image 2
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openai --model gpt-image-2
# Codex CLI (uses logged-in Codex subscription — no OPENAI_API_KEY required; requires `codex` on PATH)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider codex-cli --ar 16:9
# Batch mode
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4
# Build a batch file from outline.md + prompts/ (e.g. baoyu-article-illustrator output)
${BUN_X} {baseDir}/scripts/build-batch.ts --outline outline.md --prompts prompts --output batch.json --images-dir attachments
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4
Reference-Image Identity Preservation
When the user wants a person/object preserved from reference images:
- Prefer a small curated set of existing source references (usually 2–4) over many images; large multi-megabyte refs can destabilize streaming providers.
- Make the prompt say the references are the same subject and the output must use that identity. Avoid long generic facial-feature descriptions that can cause the model to synthesize a new similar-looking person.
- Do not use newly generated outputs as references unless the user explicitly asks; generated refs compound drift.
- If results become too polished or influencer-like, reduce stylized refs and add explicit anti-beautification constraints (no face slimming, eye enlargement, heavy makeup, commercial travel shoot, over-smoothing).
- If the subject should look younger/older, preserve the face and express age through clothing, posture, scene, and styling; do not ask the model to change facial identity.
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|zai|minimax|jimeng|seedream|replicate|codex-cli|agnes |
Force provider (default: auto-detect; codex-cli is never auto-selected — must be pinned via CLI or EXTEND.md) |
--model <id>, -m |
Model ID — see provider references for defaults and allowed values |
--ar <ratio> |
Aspect ratio (16:9, 1:1, 4:3, …) |
--size <WxH> |
Explicit size (e.g., 1024x1024; for gpt-image-2, width/height must be multiples of 16, max edge 3840px, ratio no wider than 3:1) |
--quality normal|2k |
Quality preset (default: 2k) |
--imageSize 1K|2K|4K |
Image size for Google/OpenRouter (default: from quality) |
--imageApiDialect openai-native|ratio-metadata |
OpenAI-compatible endpoint dialect — use ratio-metadata for gateways that expect aspect-ratio size plus metadata.resolution |
--ref <files...> |
Reference images. Supported by Google multimodal, OpenAI GPT Image edits, Azure OpenAI edits (PNG/JPG only), OpenRouter multimodal models, Replicate supported families, MiniMax subject-reference, Seedream 5.0/4.5/4.0, DashScope wan2.7-image-pro/wan2.7-image. Not supported by Jimeng, Seedream 3.0, SeedEdit 3.0, or any DashScope model outside the wan2.7-image* family |
--n <count> |
Number of images. Replicate requires --n 1 (single-output save semantics) |
--json |
JSON output |
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 |
ZAI_API_KEY (alias BIGMODEL_API_KEY) |
Z.AI API key |
MINIMAX_API_KEY |
MiniMax API key |
REPLICATE_API_TOKEN |
Replicate API token |
JIMENG_ACCESS_KEY_ID, JIMENG_SECRET_ACCESS_KEY |
Jimeng (即梦) Volcengine credentials |
ARK_API_KEY |
Seedream (豆包) Volcengine ARK API key |
<PROVIDER>_IMAGE_MODEL |
Per-provider model override (OPENAI_IMAGE_MODEL, GOOGLE_IMAGE_MODEL, DASHSCOPE_IMAGE_MODEL, ZAI_IMAGE_MODEL/BIGMODEL_IMAGE_MODEL, MINIMAX_IMAGE_MODEL, OPENROUTER_IMAGE_MODEL, REPLICATE_IMAGE_MODEL, JIMENG_IMAGE_MODEL, SEEDREAM_IMAGE_MODEL, AGNES_IMAGE_MODEL) |
AZURE_OPENAI_DEPLOYMENT (alias AZURE_OPENAI_IMAGE_MODEL) |
Azure default deployment |
<PROVIDER>_BASE_URL |
Per-provider endpoint override |
AZURE_API_VERSION |
Azure image API version (default 2025-04-01-preview) |
JIMENG_REGION |
Jimeng region (default cn-north-1) |
OPENAI_IMAGE_API_DIALECT |
openai-native | ratio-metadata |
OPENROUTER_HTTP_REFERER, OPENROUTER_TITLE |
Optional OpenRouter attribution |
BAOYU_IMAGE_GEN_MAX_WORKERS |
Override batch worker cap |
BAOYU_IMAGE_GEN_<PROVIDER>_CONCURRENCY |
Per-provider concurrency (e.g., BAOYU_IMAGE_GEN_REPLICATE_CONCURRENCY; for codex-cli use BAOYU_IMAGE_GEN_CODEX_CLI_CONCURRENCY) |
BAOYU_IMAGE_GEN_<PROVIDER>_START_INTERVAL_MS |
Per-provider start-gap |
BAOYU_CODEX_IMAGEGEN_BIN |
Override the codex-imagegen wrapper path for the codex-cli provider (default: bundled scripts/codex-imagegen/main.ts; accepts .ts or legacy .sh/binary) |
BAOYU_CODEX_IMAGEGEN_CACHE_DIR |
Enable idempotency cache for the codex-cli provider (off by default) |
BAOYU_CODEX_IMAGEGEN_TIMEOUT_MS |
Per-attempt codex exec timeout for the codex-cli provider (default: 300000 ms) |
BAOYU_CODEX_IMAGEGEN_RETRIES |
Wrapper-side retry attempts on retryable errors for the codex-cli provider (default: 2) |
BAOYU_CODEX_IMAGEGEN_LOG_FILE |
Append JSONL diagnostic log for the codex-cli provider |
Load priority: CLI args > EXTEND.md > env vars > <cwd>/.baoyu-skills/.env > ~/.baoyu-skills/.env
Codex/ChatGPT OAuth is not an OpenAI API key
--provider openai --model gpt-image-2 uses the standard OpenAI Images API (/v1/images/generations or /v1/images/edits) and requires OPENAI_API_KEY. A Codex or ChatGPT desktop login is a different entitlement and is not a drop-in replacement for OPENAI_API_KEY; do not paste a Codex OAuth token into OPENAI_API_KEY or only set OPENAI_BASE_URL to a Codex backend.
If the user wants to use their Codex subscription / GPT Image 2 entitlement without an OpenAI API key, route through a Codex-native backend instead of this skill's openai provider:
- In Codex runtime: use the native
imagegenskill/tool. - In non-Codex runtimes with
codexCLI installed and logged in: usebaoyu-image-gen --provider codex-cli(preferred — it gives you the same retry / cache / batch flow as every other provider). The provider spawns the bundledscripts/codex-imagegen/main.ts; the same code lives upstream atpackages/baoyu-codex-imagegen/src/main.tsfor standalone callers. - In Hermes runtimes with a native
image_generatetool: use that tool as a fallback, and state whether reference images were passed directly or reconstructed from extracted traits.
Do not modify the existing openai provider to silently consume Codex OAuth. The first-class Codex-CLI path is the dedicated codex-cli provider, which has its own auth (Codex login), route (codex exec), request shape, and tests. See references/codex-oauth-vs-openai-api-key.md.
Model Resolution
Priority (highest → lowest) applies to every provider:
- CLI flag
--model <id> - EXTEND.md
default_model.[provider] - Env var
<PROVIDER>_IMAGE_MODEL - Built-in default
For OpenAI, the built-in default is gpt-image-2. gpt-image-1.5, gpt-image-1, and GPT Image snapshots remain selectable with --model or OPENAI_IMAGE_MODEL.
For Azure, --model / default_model.azure is the Azure deployment name. AZURE_OPENAI_DEPLOYMENT is the preferred env var; AZURE_OPENAI_IMAGE_MODEL is kept as a backward-compatible alias. If your Azure deployment is named after the underlying model, use gpt-image-2; otherwise use the exact custom deployment name.
EXTEND.md overrides env vars: if EXTEND.md sets default_model.google: "gemini-3-pro-image" and the env var sets GOOGLE_IMAGE_MODEL=gemini-3.1-flash-image, EXTEND.md wins.
Display model info before each generation:
Using [provider] / [model]Switch model: --model <id> | EXTEND.md default_model.[provider] | env <PROVIDER>_IMAGE_MODEL
OpenAI-Compatible Gateway Dialects
provider=openai means the auth and routing entrypoint is OpenAI-compatible. It does not guarantee the upstream image API uses OpenAI native semantics. When a gateway expects a different wire format, set default_image_api_dialect in EXTEND.md, OPENAI_IMAGE_API_DIALECT, or --imageApiDialect:
openai-native: pixelsize(1536x1024) and native OpenAI quality fieldsratio-metadata: aspect-ratiosize(16:9) plusmetadata.resolution(1K|2K|4K) andmetadata.orientation
Use openai-native for the OpenAI native API or strict clones; try ratio-metadata for compatibility gateways in front of Gemini or similar models. Current limitation: ratio-metadata applies only to text-to-image; reference-image edits still need openai-native or a provider with first-class edit support.
Provider-Specific Guides
Each provider has its own quirks (model families, size rules, ref support, limits). Read these when the user picks that provider or asks for non-default behavior:
| Provider | Reference |
|---|---|
| DashScope (Qwen-Image families, custom sizes) | references/providers/dashscope.md |
| Z.AI (GLM-Image, cogview-4) | references/providers/zai.md |
| MiniMax (image-01, subject-reference) | references/providers/minimax.md |
OpenRouter (multimodal models, /chat/completions flow) |
references/providers/openrouter.md |
| Replicate (nano-banana, Seedream, Wan) | references/providers/replicate.md |
Codex CLI (wraps bundled scripts/codex-imagegen/; Codex login, no OPENAI_API_KEY) |
references/providers/codex-cli.md |
| Agnes (agnes-image-2.1-flash, reference-image support) | references/providers/agnes.md |
Provider Selection
--refprovided + no--provider→ auto-select Google → OpenAI → Azure → OpenRouter → Replicate → Seedream → MiniMax → Agnes (MiniMax's subject reference is more specialized toward character/portrait consistency)--providerspecified → use it (if--ref, must be google/openai/azure/openrouter/replicate/seedream/minimax/codex-cli/agnes)- Only one API key present → use that provider
- Multiple keys → default priority: Google → OpenAI → Azure → OpenRouter → DashScope → Z.AI → MiniMax → Replicate → Jimeng → Seedream → Agnes
codex-cliis never auto-selected — setdefault_provider: codex-cliin EXTEND.md or pass--provider codex-cli. It spawnscodex execvia the bundledscripts/codex-imagegen/main.tsTS entrypoint (run withbun) and uses the user's Codex subscription (noOPENAI_API_KEY). RequirescodexonPATHwith an activecodex login.
Quality Presets
| Preset | Google imageSize | OpenAI size | OpenRouter size | Replicate resolution | Use case |
|---|---|---|---|---|---|
normal |
1K | 1024px target | 1K | 1K | Quick previews |
2k (default) |
2K | 2048px target | 2K | 2K | Covers, illustrations, infographics |
Google/OpenRouter imageSize can be overridden with --imageSize 1K|2K|4K.
For OpenAI native gpt-image-2, normal maps to quality=medium and a low-latency valid size near the requested aspect ratio; 2k maps to quality=high and 2048px-class sizes such as 2048x2048, 2048x1152, or 1152x2048. Use explicit --size for valid custom or 4K outputs, e.g. 3840x2160.
Aspect Ratios
Supported: 1:1, 16:9, 9:16, 4:3, 3:4, 2.35:1.
- Google multimodal:
imageConfig.aspectRatio - OpenAI:
gpt-image-2uses the closest valid custom size for the requested ratio; older GPT Image and DALL·E models use their closest supported fixed size - OpenRouter:
imageGenerationOptions.aspect_ratio; if only--size <WxH>is given, the ratio is inferred - Replicate: behavior is model-specific —
google/nano-banana*usesaspect_ratio,bytedance/seedream-*uses documented Replicate ratios, Wan 2.7 maps--arto a concretesize - MiniMax: official
aspect_ratiovalues; if--size <WxH>is given without--ar, sendswidth/heightforimage-01
Generation Mode
Default: sequential. Batch parallel: enabled automatically when --batchfile contains 2+ pending tasks.
| Situation | Prefer | Why |
|---|---|---|
| One image, or 1-2 simple images | Sequential | Lower coordination overhead, easier debugging |
| Multiple images with saved prompt files | Batch (--batchfile) |
Reuses finalized prompts, applies shared throttling/retries, predictable throughput |
| Each image still needs its own reasoning / prompt writing / style exploration | Subagents | Work is still exploratory, each needs independent analysis |
Input is outline.md + prompts/ (e.g. from baoyu-article-illustrator) |
Batch — use {baseDir}/scripts/build-batch.ts to assemble the payload |
The outline + prompt files already contain everything needed |
Rule of thumb: once prompt files are saved and the task is "generate all of these", prefer batch over subagents. Use subagents only when generation is coupled with per-image thinking or divergent creative exploration.
Parallel behavior:
- Default worker count is automatic, capped by config, built-in default 10
- Provider-specific throttling applies only in batch mode; defaults are tuned for throughput while avoiding RPM bursts
- Override with
--jobs <count> - Each image retries 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
Codex image2 fallback
If --provider openai --model gpt-image-2 fails because OPENAI_API_KEY is missing but the current runtime has a native image-generation backend or the repo-level codex-imagegen wrapper is available, use that path rather than leaving the user waiting. Be explicit about whether the fallback is true reference-image generation or only a text-prompt reconstruction from extracted visual traits. See references/codex-image2-fallback.md.
References
| File | Content |
|---|---|
references/usage-examples.md |
Extended CLI examples across providers and batch mode |
references/codex-oauth-vs-openai-api-key.md |
Why Codex/ChatGPT OAuth image2 entitlement is not usable through baoyu-image-gen's standard OpenAI API-key provider |
references/codex-image2-fallback.md |
Practical fallback behavior when OpenAI API credentials are absent but Codex/native image generation is available |
references/providers/dashscope.md |
DashScope families, sizes, limits |
references/providers/zai.md |
Z.AI GLM-image / cogview-4 |
references/providers/minimax.md |
MiniMax image-01 + subject reference |
references/providers/openrouter.md |
OpenRouter multimodal flow |
references/providers/replicate.md |
Replicate supported families + guardrails |
references/providers/agnes.md |
Agnes (agnes-image-2.1-flash) sizing, refs, and limits |
references/config/preferences-schema.md |
EXTEND.md schema |
references/config/first-time-setup.md |
First-time setup flow |
Extension Support
Custom configurations via EXTEND.md. See Step 0 for paths and schema.
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