Image Generation (AI SDK)

Official API-based image generation. Supports OpenAI, Google, DashScope (阿里通义万象) and Replicate providers.

Script Directory

Agent Execution:

1. {baseDir} = this SKILL.md file's directory
2. Script path = {baseDir}/scripts/main.ts
3. 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-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"

# PowerShell (Windows)
if (Test-Path .baoyu-skills/baoyu-image-gen/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" }

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-image-gen/EXTEND.md	Project directory
$HOME/.baoyu-skills/baoyu-image-gen/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

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 multimodal or OpenAI edits)
${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

# 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

# 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|dashscope|replicate	Force provider (default: auto-detect)
--model <id>, -m	Model ID (Google: gemini-3-pro-image-preview, gemini-3.1-flash-image-preview; OpenAI: gpt-image-1.5, gpt-image-1)
--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 (default: from quality)
--ref <files...>	Reference images. Supported by Google multimodal, OpenAI GPT Image edits, and Replicate
--n <count>	Number of images
--json	JSON output

Environment Variables

Variable	Description
OPENAI_API_KEY	OpenAI API key
GOOGLE_API_KEY	Google API key
DASHSCOPE_API_KEY	DashScope API key (阿里云)
REPLICATE_API_TOKEN	Replicate API token
OPENAI_IMAGE_MODEL	OpenAI model override
GOOGLE_IMAGE_MODEL	Google model override
DASHSCOPE_IMAGE_MODEL	DashScope model override (default: z-image-turbo)
REPLICATE_IMAGE_MODEL	Replicate model override (default: google/nano-banana-pro)
OPENAI_BASE_URL	Custom OpenAI endpoint
GOOGLE_BASE_URL	Custom Google endpoint
DASHSCOPE_BASE_URL	Custom DashScope endpoint
REPLICATE_BASE_URL	Custom Replicate endpoint
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:

1. CLI flag: --model <id>
2. EXTEND.md: default_model.[provider]
3. Env var: <PROVIDER>_IMAGE_MODEL (e.g., GOOGLE_IMAGE_MODEL)
4. Built-in default

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

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

1. --ref provided + no --provider → auto-select Google first, then OpenAI, then Replicate
2. --provider specified → use it (if --ref, must be google, openai, or replicate)
3. Only one API key available → use that provider
4. Multiple available → default to Google

Quality Presets

Preset	Google imageSize	OpenAI Size	Replicate resolution	Use Case
normal	1K	1024px	1K	Quick previews
2k (default)	2K	2048px	2K	Covers, illustrations, infographics

Google 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
• Replicate: passes aspect_ratio to model; when --ref is provided without --ar, defaults to match_input_image

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.