mirror of
https://github.com/JimLiu/baoyu-skills.git
synced 2026-07-14 06:39:48 +08:00
Jim Liu 宝玉
49e9c46ca4
Expose Codex CLI's built-in image_gen tool through baoyu-image-gen's
standard CLI + batch flow as a dedicated provider. The provider spawns
the bundled scripts/codex-imagegen/main.ts (synced from
packages/baoyu-codex-imagegen/src/) so the skill remains self-contained
and inherits retry, cache, file-lock, and JSONL logging. No
OPENAI_API_KEY required — uses the user's Codex subscription.
New env vars: BAOYU_CODEX_IMAGEGEN_{BIN,CACHE_DIR,TIMEOUT_MS,RETRIES,LOG_FILE}.
Hyphenated provider names now resolve under-scored env vars (e.g.,
BAOYU_IMAGE_GEN_CODEX_CLI_CONCURRENCY). codex-cli is never auto-selected
— pin via --provider or default_provider in EXTEND.md.
129 lines
5.5 KiB
Markdown
129 lines
5.5 KiB
Markdown
# Usage Examples
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Extended CLI examples. SKILL.md shows the minimum set; read this file when the user asks about provider-specific invocation, batch generation, or less-common flags.
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## Core Patterns
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```bash
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# Basic text-to-image
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image cat.png
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# With aspect ratio
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A landscape" --image out.png --ar 16:9
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# High quality
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --quality 2k
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# Prompt from files
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${BUN_X} {baseDir}/scripts/main.ts --promptfiles system.md content.md --image out.png
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# With reference images (any provider family that supports refs)
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${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --ref source.png
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```
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## Per-Provider
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```bash
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# OpenAI
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openai --model gpt-image-2
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# Azure OpenAI (model = deployment name)
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider azure --model gpt-image-2
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# OpenAI GPT Image 2 custom 4K size
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A cinematic landscape" --image out.png --provider openai --model gpt-image-2 --size 3840x2160
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# Google with explicit model
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${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --provider google --model gemini-3-pro-image-preview --ref source.png
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# OpenRouter (recommended default)
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openrouter
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# OpenRouter with reference
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${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --provider openrouter --model google/gemini-3.1-flash-image-preview --ref source.png
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# DashScope (default model)
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${BUN_X} {baseDir}/scripts/main.ts --prompt "一只可爱的猫" --image out.png --provider dashscope
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# DashScope Qwen-Image 2.0 Pro (custom size, Chinese text)
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${BUN_X} {baseDir}/scripts/main.ts --prompt "为咖啡品牌设计一张 21:9 横幅海报，包含清晰中文标题" --image out.png --provider dashscope --model qwen-image-2.0-pro --size 2048x872
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# DashScope legacy fixed-size
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${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
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# DashScope Wan 2.7 Image Pro (4K text-to-image)
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${BUN_X} {baseDir}/scripts/main.ts --prompt "一间有着精致窗户的花店" --image out.png --provider dashscope --model wan2.7-image-pro --size 4096x4096
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# DashScope Wan 2.7 Image with reference image (multi-image fusion)
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${BUN_X} {baseDir}/scripts/main.ts --prompt "把图2的涂鸦喷绘在图1的汽车上" --image out.png --provider dashscope --model wan2.7-image-pro --ref car.webp paint.webp
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# Z.AI GLM-image
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${BUN_X} {baseDir}/scripts/main.ts --prompt "一张带清晰中文标题的科技海报" --image out.png --provider zai
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# Z.AI with custom size
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A science illustration with labels" --image out.png --provider zai --model glm-image --size 1472x1088
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# MiniMax
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A fashion editorial portrait" --image out.jpg --provider minimax
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# MiniMax with subject reference (character/portrait consistency)
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A girl by the library window" --image out.jpg --provider minimax --model image-01 --ref portrait.png --ar 16:9
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# Replicate (default: google/nano-banana-2)
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate
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# Replicate Seedream 4.5
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A cinematic portrait" --image out.png --provider replicate --model bytedance/seedream-4.5 --ar 3:2
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# Replicate Wan 2.7 Image Pro
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A concept frame" --image out.png --provider replicate --model wan-video/wan-2.7-image-pro --size 2048x1152
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# Codex CLI (uses Codex / ChatGPT subscription — no OPENAI_API_KEY; requires `codex` on PATH and `codex login`)
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A cinematic portrait" --image out.png --provider codex-cli --ar 16:9
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# Codex CLI with reference images (style/composition guidance)
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${BUN_X} {baseDir}/scripts/main.ts --prompt "Match this color palette" --image out.png --provider codex-cli --ref source.png --ar 1:1
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```
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Notes on `codex-cli`:
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- Never auto-selected — pin via `--provider codex-cli` or `default_provider: codex-cli` in EXTEND.md.
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- Only `n=1` supported (Codex `image_gen` returns one image per call); `--size`, `--imageSize`, `--quality`, and `--imageApiDialect` are ignored or rejected.
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- Typically 5–10× slower than direct OpenAI / Google API calls (except on cache hits). Tune via `BAOYU_CODEX_IMAGEGEN_TIMEOUT_MS`, `BAOYU_CODEX_IMAGEGEN_RETRIES`, and `BAOYU_CODEX_IMAGEGEN_CACHE_DIR`.
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## Batch Mode
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```bash
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# Batch from saved prompt files
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${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json
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# Batch with explicit worker count
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${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4 --json
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```
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### Batch File Format
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```json
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{
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"jobs": 4,
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"tasks": [
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{
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"id": "hero",
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"promptFiles": ["prompts/hero.md"],
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"image": "out/hero.png",
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"provider": "replicate",
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"model": "google/nano-banana-2",
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"ar": "16:9",
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"quality": "2k"
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},
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{
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"id": "diagram",
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"promptFiles": ["prompts/diagram.md"],
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"image": "out/diagram.png",
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"ref": ["references/original.png"]
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}
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]
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}
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```
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Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch file's directory. `jobs` is optional (overridden by CLI `--jobs`). A top-level array without the `jobs` wrapper is also accepted.
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