chore: release v1.11.0
This commit is contained in:
Jim Liu 宝玉
parent
0d677ea171
commit
776afba5d8
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@ -6,7 +6,7 @@
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},
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"metadata": {
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"description": "Skills shared by Baoyu for improving daily work efficiency",
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"version": "1.10.0"
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"version": "1.11.0"
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},
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"plugins": [
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{
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@ -31,7 +31,8 @@
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"source": "./",
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"strict": false,
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"skills": [
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"./skills/baoyu-danger-gemini-web"
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"./skills/baoyu-danger-gemini-web",
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"./skills/baoyu-image-gen"
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]
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},
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{
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@ -2,6 +2,15 @@
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English | [中文](./CHANGELOG.zh.md)
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## 1.11.0 - 2026-01-21
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### Features
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- `baoyu-image-gen`: new AI SDK-based image generation skill using official OpenAI and Google APIs. Supports text-to-image, reference images (Google multimodal), aspect ratios, and quality presets (`normal`, `2k`). Auto-detects provider based on available API keys.
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- `baoyu-slide-deck`: adds Layout Gallery with 24 layout types—10 slide-specific layouts (`title-hero`, `quote-callout`, `key-stat`, `split-screen`, `icon-grid`, `two-columns`, `three-columns`, `image-caption`, `agenda`, `bullet-list`) and 14 infographic-derived layouts (`linear-progression`, `binary-comparison`, `comparison-matrix`, `hierarchical-layers`, `hub-spoke`, `bento-grid`, `funnel`, `dashboard`, `venn-diagram`, `circular-flow`, `winding-roadmap`, `tree-branching`, `iceberg`, `bridge`).
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### Documentation
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- `README.md`, `README.zh.md`: adds baoyu-image-gen documentation with usage examples, options table, and environment variables; adds Environment Configuration section for API key setup.
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## 1.10.0 - 2026-01-21
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### Features
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@ -2,6 +2,15 @@
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[English](./CHANGELOG.md) | 中文
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## 1.11.0 - 2026-01-21
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### 新功能
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- `baoyu-image-gen`：新增基于 AI SDK 的图像生成技能，使用官方 OpenAI 和 Google API。支持文生图、参考图（Google 多模态）、宽高比和质量预设（`normal`、`2k`）。根据可用的 API 密钥自动选择服务商。
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- `baoyu-slide-deck`：新增布局库（Layout Gallery），包含 24 种布局类型——10 种幻灯片专用布局（`title-hero` 标题主图、`quote-callout` 引用突出、`key-stat` 关键数据、`split-screen` 分屏、`icon-grid` 图标网格、`two-columns` 双栏、`three-columns` 三栏、`image-caption` 图片说明、`agenda` 议程、`bullet-list` 要点列表）和 14 种信息图衍生布局（`linear-progression` 线性流程、`binary-comparison` 二元对比、`comparison-matrix` 对比矩阵、`hierarchical-layers` 层级、`hub-spoke` 中心辐射、`bento-grid` 便当盒、`funnel` 漏斗、`dashboard` 仪表盘、`venn-diagram` 韦恩图、`circular-flow` 循环流程、`winding-roadmap` 蜿蜒路线图、`tree-branching` 树状分支、`iceberg` 冰山、`bridge` 桥接）。
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### 文档
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- `README.md`、`README.zh.md`：新增 baoyu-image-gen 文档，包含用法示例、选项表和环境变量说明；新增环境配置章节，介绍 API 密钥设置方法。
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## 1.10.0 - 2026-01-21
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### 新功能
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89
README.md
89
README.md
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@ -54,7 +54,7 @@ Simply tell Claude Code:
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| Plugin | Description | Skills |
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|--------|-------------|--------|
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| **content-skills** | Content generation and publishing | [xhs-images](#baoyu-xhs-images), [infographic](#baoyu-infographic), [cover-image](#baoyu-cover-image), [slide-deck](#baoyu-slide-deck), [comic](#baoyu-comic), [article-illustrator](#baoyu-article-illustrator), [post-to-x](#baoyu-post-to-x), [post-to-wechat](#baoyu-post-to-wechat) |
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| **ai-generation-skills** | AI-powered generation backends | [danger-gemini-web](#baoyu-danger-gemini-web) |
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| **ai-generation-skills** | AI-powered generation backends | [image-gen](#baoyu-image-gen), [danger-gemini-web](#baoyu-danger-gemini-web) |
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| **utility-skills** | Utility tools for content processing | [danger-x-to-markdown](#baoyu-danger-x-to-markdown), [compress-image](#baoyu-compress-image) |
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## Update Skills
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@ -515,6 +515,55 @@ Prerequisites: Google Chrome installed. First run requires QR code login (sessio
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AI-powered generation backends.
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#### baoyu-image-gen
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AI SDK-based image generation using official OpenAI and Google APIs. Supports text-to-image, reference images, aspect ratios, and quality presets.
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```bash
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# Basic generation (auto-detect provider)
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/baoyu-image-gen --prompt "A cute cat" --image cat.png
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# With aspect ratio
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/baoyu-image-gen --prompt "A landscape" --image landscape.png --ar 16:9
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# High quality (2k)
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/baoyu-image-gen --prompt "A banner" --image banner.png --quality 2k
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# Specific provider
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/baoyu-image-gen --prompt "A cat" --image cat.png --provider openai
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# With reference images (Google multimodal only)
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/baoyu-image-gen --prompt "Make it blue" --image out.png --ref source.png
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```
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**Options**:
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| Option | Description |
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|--------|-------------|
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| `--prompt`, `-p` | Prompt text |
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| `--promptfiles` | Read prompt from files (concatenated) |
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| `--image` | Output image path (required) |
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| `--provider` | `google` or `openai` (default: google) |
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| `--model`, `-m` | Model ID |
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| `--ar` | Aspect ratio (e.g., `16:9`, `1:1`, `4:3`) |
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| `--size` | Size (e.g., `1024x1024`) |
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| `--quality` | `normal` or `2k` (default: normal) |
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| `--ref` | Reference images (Google multimodal only) |
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**Environment Variables** (see [Environment Configuration](#environment-configuration) for setup):
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| Variable | Description | Default |
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|----------|-------------|---------|
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| `OPENAI_API_KEY` | OpenAI API key | - |
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| `GOOGLE_API_KEY` | Google API key | - |
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| `OPENAI_IMAGE_MODEL` | OpenAI model | `gpt-image-1.5` |
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| `GOOGLE_IMAGE_MODEL` | Google model | `gemini-3-pro-image-preview` |
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| `OPENAI_BASE_URL` | Custom OpenAI endpoint | - |
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| `GOOGLE_BASE_URL` | Custom Google endpoint | - |
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**Provider Auto-Selection**:
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1. If `--provider` specified → use it
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2. If only one API key available → use that provider
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3. If both available → default to Google
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#### baoyu-danger-gemini-web
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Interacts with Gemini Web to generate text and images.
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/baoyu-compress-image path/to/images/ --quality 80
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```
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## Environment Configuration
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Some skills require API keys or custom configuration. Environment variables can be set in `.env` files:
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**Load Priority** (higher priority overrides lower):
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1. CLI environment variables (e.g., `OPENAI_API_KEY=xxx /baoyu-image-gen ...`)
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2. `process.env` (system environment)
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3. `<cwd>/.baoyu-skills/.env` (project-level)
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4. `~/.baoyu-skills/.env` (user-level)
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**Setup**:
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```bash
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# Create user-level config directory
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mkdir -p ~/.baoyu-skills
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# Create .env file
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cat > ~/.baoyu-skills/.env << 'EOF'
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# OpenAI
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OPENAI_API_KEY=sk-xxx
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OPENAI_IMAGE_MODEL=gpt-image-1.5
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# OPENAI_BASE_URL=https://api.openai.com/v1
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# Google
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GOOGLE_API_KEY=xxx
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GOOGLE_IMAGE_MODEL=gemini-3-pro-image-preview
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# GOOGLE_BASE_URL=https://generativelanguage.googleapis.com/v1beta
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EOF
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```
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**Project-level config** (for team sharing):
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```bash
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mkdir -p .baoyu-skills
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# Add .baoyu-skills/.env to .gitignore to avoid committing secrets
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echo ".baoyu-skills/.env" >> .gitignore
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```
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## Customization
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All skills support customization via `EXTEND.md` files. Create an extension file to override default styles, add custom configurations, or define your own presets.
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89
README.zh.md
89
README.zh.md
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@ -54,7 +54,7 @@ npx skills add jimliu/baoyu-skills
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| 插件 | 说明 | 包含技能 |
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|------|------|----------|
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| **content-skills** | 内容生成和发布 | [xhs-images](#baoyu-xhs-images), [infographic](#baoyu-infographic), [cover-image](#baoyu-cover-image), [slide-deck](#baoyu-slide-deck), [comic](#baoyu-comic), [article-illustrator](#baoyu-article-illustrator), [post-to-x](#baoyu-post-to-x), [post-to-wechat](#baoyu-post-to-wechat) |
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| **ai-generation-skills** | AI 生成后端 | [danger-gemini-web](#baoyu-danger-gemini-web) |
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| **ai-generation-skills** | AI 生成后端 | [image-gen](#baoyu-image-gen), [danger-gemini-web](#baoyu-danger-gemini-web) |
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| **utility-skills** | 内容处理工具 | [danger-x-to-markdown](#baoyu-danger-x-to-markdown), [compress-image](#baoyu-compress-image) |
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## 更新技能
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AI 驱动的生成后端。
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#### baoyu-image-gen
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基于 AI SDK 的图像生成，使用官方 OpenAI 和 Google API。支持文生图、参考图、宽高比和质量预设。
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```bash
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# 基础生成（自动检测服务商）
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/baoyu-image-gen --prompt "一只可爱的猫" --image cat.png
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# 指定宽高比
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/baoyu-image-gen --prompt "风景图" --image landscape.png --ar 16:9
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# 高质量（2k 分辨率）
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/baoyu-image-gen --prompt "横幅图" --image banner.png --quality 2k
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# 指定服务商
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/baoyu-image-gen --prompt "一只猫" --image cat.png --provider openai
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# 带参考图（仅 Google 多模态支持）
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/baoyu-image-gen --prompt "把它变成蓝色" --image out.png --ref source.png
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```
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**选项**：
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| 选项 | 说明 |
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|------|------|
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| `--prompt`, `-p` | 提示词文本 |
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| `--promptfiles` | 从文件读取提示词（多文件拼接） |
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| `--image` | 输出图片路径（必需） |
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| `--provider` | `google` 或 `openai`（默认：google） |
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| `--model`, `-m` | 模型 ID |
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| `--ar` | 宽高比（如 `16:9`、`1:1`、`4:3`） |
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| `--size` | 尺寸（如 `1024x1024`） |
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| `--quality` | `normal` 或 `2k`（默认：normal） |
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| `--ref` | 参考图片（仅 Google 多模态支持） |
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**环境变量**（配置方法见[环境配置](#环境配置)）：
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| 变量 | 说明 | 默认值 |
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|------|------|--------|
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| `OPENAI_API_KEY` | OpenAI API 密钥 | - |
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| `GOOGLE_API_KEY` | Google API 密钥 | - |
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| `OPENAI_IMAGE_MODEL` | OpenAI 模型 | `gpt-image-1.5` |
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| `GOOGLE_IMAGE_MODEL` | Google 模型 | `gemini-3-pro-image-preview` |
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| `OPENAI_BASE_URL` | 自定义 OpenAI 端点 | - |
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| `GOOGLE_BASE_URL` | 自定义 Google 端点 | - |
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**服务商自动选择**：
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1. 如果指定了 `--provider` → 使用指定的
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2. 如果只有一个 API 密钥 → 使用对应服务商
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3. 如果两个都有 → 默认使用 Google
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#### baoyu-danger-gemini-web
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与 Gemini Web 交互，生成文本和图片。
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/baoyu-compress-image path/to/images/ --quality 80
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```
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## 环境配置
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部分技能需要 API 密钥或自定义配置。环境变量可以在 `.env` 文件中设置：
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**加载优先级**（高优先级覆盖低优先级）：
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1. 命令行环境变量（如 `OPENAI_API_KEY=xxx /baoyu-image-gen ...`）
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2. `process.env`（系统环境变量）
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3. `<cwd>/.baoyu-skills/.env`（项目级）
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4. `~/.baoyu-skills/.env`（用户级）
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**配置方法**：
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```bash
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# 创建用户级配置目录
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mkdir -p ~/.baoyu-skills
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# 创建 .env 文件
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cat > ~/.baoyu-skills/.env << 'EOF'
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# OpenAI
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OPENAI_API_KEY=sk-xxx
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OPENAI_IMAGE_MODEL=gpt-image-1.5
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# OPENAI_BASE_URL=https://api.openai.com/v1
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# Google
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GOOGLE_API_KEY=xxx
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GOOGLE_IMAGE_MODEL=gemini-3-pro-image-preview
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# GOOGLE_BASE_URL=https://generativelanguage.googleapis.com/v1beta
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EOF
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```
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**项目级配置**（团队共享）：
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```bash
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mkdir -p .baoyu-skills
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# 将 .baoyu-skills/.env 添加到 .gitignore 避免提交密钥
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echo ".baoyu-skills/.env" >> .gitignore
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```
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## 自定义扩展
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所有技能支持通过 `EXTEND.md` 文件自定义。创建扩展文件可覆盖默认样式、添加自定义配置或定义个人预设。
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@ -0,0 +1,219 @@
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---
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name: baoyu-image-gen
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description: AI SDK-based image generation using official OpenAI and Google APIs. Supports text-to-image, reference images, aspect ratios, and quality presets.
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---
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# Image Generation (AI SDK)
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Official API-based image generation via AI SDK. Supports OpenAI (DALL-E, GPT Image) and Google (Imagen, Gemini multimodal).
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## Script Directory
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**Important**: All scripts are located in the `scripts/` subdirectory of this skill.
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**Agent Execution Instructions**:
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1. Determine this SKILL.md file's directory path as `SKILL_DIR`
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2. Script path = `${SKILL_DIR}/scripts/<script-name>.ts`
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3. Replace all `${SKILL_DIR}` in this document with the actual path
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**Script Reference**:
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| Script | Purpose |
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|--------|---------|
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| `scripts/main.ts` | CLI entry point for image generation |
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## Quick Start
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```bash
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# Basic generation (auto-detect provider)
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npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png
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# With aspect ratio
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npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A landscape" --image landscape.png --ar 16:9
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# High quality (2k)
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npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png --quality 2k
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# Specific provider
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npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png --provider openai
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# From prompt files
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npx -y bun ${SKILL_DIR}/scripts/main.ts --promptfiles system.md content.md --image out.png
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# With reference images (Google multimodal only)
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npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "Make blue" --image out.png --ref source.png
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```
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## Commands
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### Basic Image Generation
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```bash
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# Generate with prompt
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npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A sunset over mountains" --image sunset.png
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# Shorthand
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npx -y bun ${SKILL_DIR}/scripts/main.ts -p "A cute robot" --image robot.png
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```
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### Aspect Ratios
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```bash
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# Common ratios: 1:1, 16:9, 9:16, 4:3, 3:4, 2.35:1
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npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A portrait" --image portrait.png --ar 3:4
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# Or specify exact size
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npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "Banner" --image banner.png --size 1792x1024
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```
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### Reference Images (Google Multimodal)
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```bash
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# Image editing with reference
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npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "Make it blue" --image blue.png --ref original.png
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# Multiple references
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npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "Combine these styles" --image out.png --ref a.png b.png
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```
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### Quality Presets
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```bash
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# Normal quality (default)
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npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png --quality normal
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# High quality (2k resolution)
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npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png --quality 2k
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```
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### Output Formats
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```bash
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||||
# Plain output (prints saved path)
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png
|
||||
|
||||
# JSON output
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png --json
|
||||
```
|
||||
|
||||
## Options
|
||||
|
||||
| Option | Description |
|
||||
|--------|-------------|
|
||||
| `--prompt <text>`, `-p` | Prompt text |
|
||||
| `--promptfiles <files...>` | Read prompt from files (concatenated) |
|
||||
| `--image <path>` | Output image path (required) |
|
||||
| `--provider google\|openai` | Force provider (default: google) |
|
||||
| `--model <id>`, `-m` | Model ID |
|
||||
| `--ar <ratio>` | Aspect ratio (e.g., `16:9`, `1:1`, `4:3`) |
|
||||
| `--size <WxH>` | Size (e.g., `1024x1024`) |
|
||||
| `--quality normal\|2k` | Quality preset (default: normal) |
|
||||
| `--ref <files...>` | Reference images (Google multimodal only) |
|
||||
| `--n <count>` | Number of images |
|
||||
| `--json` | JSON output |
|
||||
| `--help`, `-h` | Show help |
|
||||
|
||||
## Environment Variables
|
||||
|
||||
| Variable | Description | Default |
|
||||
|----------|-------------|---------|
|
||||
| `OPENAI_API_KEY` | OpenAI API key | - |
|
||||
| `GOOGLE_API_KEY` | Google API key | - |
|
||||
| `OPENAI_IMAGE_MODEL` | OpenAI model | `gpt-image-1.5` |
|
||||
| `GOOGLE_IMAGE_MODEL` | Google model | `gemini-3-pro-image-preview` |
|
||||
| `OPENAI_BASE_URL` | Custom OpenAI endpoint | - |
|
||||
| `GOOGLE_BASE_URL` | Custom Google endpoint | - |
|
||||
|
||||
**Load Priority**: CLI args > `process.env` > `<cwd>/.baoyu-skills/.env` > `~/.baoyu-skills/.env`
|
||||
|
||||
## Provider & Model Strategy
|
||||
|
||||
### Auto-Selection
|
||||
|
||||
1. If `--provider` specified → use it
|
||||
2. If only one API key available → use that provider
|
||||
3. If both available → default to Google (multimodal LLMs more versatile)
|
||||
|
||||
### API Selection by Model Type
|
||||
|
||||
| Model Category | API Function | Example Models |
|
||||
|----------------|--------------|----------------|
|
||||
| Google Multimodal | `generateText` | `gemini-2.0-flash-exp-image-generation` |
|
||||
| Google Imagen | `experimental_generateImage` | `imagen-3.0-generate-002` |
|
||||
| OpenAI | `experimental_generateImage` | `gpt-image-1`, `dall-e-3` |
|
||||
|
||||
### Available Models
|
||||
|
||||
**Google**:
|
||||
- `gemini-3-pro-image-preview` - Default, multimodal generation
|
||||
- `gemini-2.0-flash-exp-image-generation` - Gemini 2.0 Flash
|
||||
- `imagen-3.0-generate-002` - Imagen 3
|
||||
|
||||
**OpenAI**:
|
||||
- `gpt-image-1.5` - Default, GPT Image 1.5
|
||||
- `gpt-image-1` - GPT Image 1
|
||||
- `dall-e-3` - DALL-E 3
|
||||
|
||||
## Quality Presets
|
||||
|
||||
| Preset | OpenAI | Google | Use Case |
|
||||
|--------|--------|--------|----------|
|
||||
| `normal` | 1024x1024 | Default | Covers, illustrations |
|
||||
| `2k` | 2048x2048 | "2048px" in prompt | Infographics, slides |
|
||||
|
||||
## Aspect Ratio Handling
|
||||
|
||||
- **Multimodal LLMs**: Embedded in prompt (e.g., `"... aspect ratio 16:9"`)
|
||||
- **Image-only models**: Uses `aspectRatio` or `size` parameter
|
||||
- **Common ratios**: 1:1, 16:9, 9:16, 4:3, 3:4, 2.35:1
|
||||
|
||||
## Examples
|
||||
|
||||
### Generate Cover Image
|
||||
|
||||
```bash
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts \
|
||||
--prompt "A minimalist tech illustration with blue gradients" \
|
||||
--image cover.png --ar 2.35:1 --quality 2k
|
||||
```
|
||||
|
||||
### Generate Social Media Post
|
||||
|
||||
```bash
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts \
|
||||
--prompt "Instagram post about coffee" \
|
||||
--image post.png --ar 1:1
|
||||
```
|
||||
|
||||
### Edit Image with Reference
|
||||
|
||||
```bash
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts \
|
||||
--prompt "Change the background to sunset" \
|
||||
--image edited.png --ref original.png --provider google
|
||||
```
|
||||
|
||||
### Batch Generation from Prompt File
|
||||
|
||||
```bash
|
||||
# Create prompt file with detailed instructions
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts \
|
||||
--promptfiles style-guide.md scene-description.md \
|
||||
--image scene.png
|
||||
```
|
||||
|
||||
## Error Handling
|
||||
|
||||
- **Missing API key**: Clear error with setup instructions
|
||||
- **Generation failure**: Auto-retry once, then error
|
||||
- **Invalid aspect ratio**: Warning, proceed with default
|
||||
- **Reference images with image-only model**: Warning, ignore refs
|
||||
|
||||
## Extension Support
|
||||
|
||||
Custom configurations via EXTEND.md.
|
||||
|
||||
**Check paths** (priority order):
|
||||
1. `.baoyu-skills/baoyu-image-gen/EXTEND.md` (project)
|
||||
2. `~/.baoyu-skills/baoyu-image-gen/EXTEND.md` (user)
|
||||
|
||||
If found, load before workflow. Extension content overrides defaults.
|
||||
|
|
@ -0,0 +1,576 @@
|
|||
import fs from "node:fs";
|
||||
import path from "node:path";
|
||||
import process from "node:process";
|
||||
import { homedir } from "node:os";
|
||||
import { mkdir, readFile, writeFile } from "node:fs/promises";
|
||||
|
||||
type Provider = "google" | "openai";
|
||||
type Quality = "normal" | "2k";
|
||||
|
||||
type CliArgs = {
|
||||
prompt: string | null;
|
||||
promptFiles: string[];
|
||||
imagePath: string | null;
|
||||
provider: Provider | null;
|
||||
model: string | null;
|
||||
aspectRatio: string | null;
|
||||
size: string | null;
|
||||
quality: Quality;
|
||||
referenceImages: string[];
|
||||
n: number;
|
||||
json: boolean;
|
||||
help: boolean;
|
||||
};
|
||||
|
||||
const GOOGLE_MULTIMODAL_MODELS = [
|
||||
"gemini-3-pro-image-preview",
|
||||
"gemini-2.0-flash-exp-image-generation",
|
||||
"gemini-2.5-flash-preview-native-audio-dialog",
|
||||
];
|
||||
|
||||
const GOOGLE_IMAGEN_MODELS = ["imagen-3.0-generate-002", "imagen-3.0-generate-001"];
|
||||
|
||||
const OPENAI_IMAGE_MODELS = ["gpt-image-1.5", "gpt-image-1", "dall-e-3", "dall-e-2"];
|
||||
|
||||
function printUsage(): void {
|
||||
console.log(`Usage:
|
||||
npx -y bun scripts/main.ts --prompt "A cat" --image cat.png
|
||||
npx -y bun scripts/main.ts --prompt "A landscape" --image landscape.png --ar 16:9
|
||||
npx -y bun scripts/main.ts --promptfiles system.md content.md --image out.png
|
||||
|
||||
Options:
|
||||
-p, --prompt <text> Prompt text
|
||||
--promptfiles <files...> Read prompt from files (concatenated)
|
||||
--image <path> Output image path (required)
|
||||
--provider google|openai Force provider (auto-detect by default)
|
||||
-m, --model <id> Model ID
|
||||
--ar <ratio> Aspect ratio (e.g., 16:9, 1:1, 4:3)
|
||||
--size <WxH> Size (e.g., 1024x1024)
|
||||
--quality normal|2k Quality preset (default: normal)
|
||||
--ref <files...> Reference images (Google multimodal only)
|
||||
--n <count> Number of images (default: 1)
|
||||
--json JSON output
|
||||
-h, --help Show help
|
||||
|
||||
Environment variables:
|
||||
OPENAI_API_KEY OpenAI API key
|
||||
GOOGLE_API_KEY Google API key
|
||||
OPENAI_IMAGE_MODEL Default OpenAI model (gpt-image-1.5)
|
||||
GOOGLE_IMAGE_MODEL Default Google model (gemini-3-pro-image-preview)
|
||||
OPENAI_BASE_URL Custom OpenAI endpoint
|
||||
GOOGLE_BASE_URL Custom Google endpoint
|
||||
|
||||
Env file load order: CLI args > process.env > <cwd>/.baoyu-skills/.env > ~/.baoyu-skills/.env`);
|
||||
}
|
||||
|
||||
function parseArgs(argv: string[]): CliArgs {
|
||||
const out: CliArgs = {
|
||||
prompt: null,
|
||||
promptFiles: [],
|
||||
imagePath: null,
|
||||
provider: null,
|
||||
model: null,
|
||||
aspectRatio: null,
|
||||
size: null,
|
||||
quality: "normal",
|
||||
referenceImages: [],
|
||||
n: 1,
|
||||
json: false,
|
||||
help: false,
|
||||
};
|
||||
|
||||
const positional: string[] = [];
|
||||
|
||||
const takeMany = (i: number): { items: string[]; next: number } => {
|
||||
const items: string[] = [];
|
||||
let j = i + 1;
|
||||
while (j < argv.length) {
|
||||
const v = argv[j]!;
|
||||
if (v.startsWith("-")) break;
|
||||
items.push(v);
|
||||
j++;
|
||||
}
|
||||
return { items, next: j - 1 };
|
||||
};
|
||||
|
||||
for (let i = 0; i < argv.length; i++) {
|
||||
const a = argv[i]!;
|
||||
|
||||
if (a === "--help" || a === "-h") {
|
||||
out.help = true;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--json") {
|
||||
out.json = true;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--prompt" || a === "-p") {
|
||||
const v = argv[++i];
|
||||
if (!v) throw new Error(`Missing value for ${a}`);
|
||||
out.prompt = v;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--promptfiles") {
|
||||
const { items, next } = takeMany(i);
|
||||
if (items.length === 0) throw new Error("Missing files for --promptfiles");
|
||||
out.promptFiles.push(...items);
|
||||
i = next;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--image") {
|
||||
const v = argv[++i];
|
||||
if (!v) throw new Error("Missing value for --image");
|
||||
out.imagePath = v;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--provider") {
|
||||
const v = argv[++i];
|
||||
if (v !== "google" && v !== "openai") throw new Error(`Invalid provider: ${v}`);
|
||||
out.provider = v;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--model" || a === "-m") {
|
||||
const v = argv[++i];
|
||||
if (!v) throw new Error(`Missing value for ${a}`);
|
||||
out.model = v;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--ar") {
|
||||
const v = argv[++i];
|
||||
if (!v) throw new Error("Missing value for --ar");
|
||||
out.aspectRatio = v;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--size") {
|
||||
const v = argv[++i];
|
||||
if (!v) throw new Error("Missing value for --size");
|
||||
out.size = v;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--quality") {
|
||||
const v = argv[++i];
|
||||
if (v !== "normal" && v !== "2k") throw new Error(`Invalid quality: ${v}`);
|
||||
out.quality = v;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--ref" || a === "--reference") {
|
||||
const { items, next } = takeMany(i);
|
||||
if (items.length === 0) throw new Error(`Missing files for ${a}`);
|
||||
out.referenceImages.push(...items);
|
||||
i = next;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--n") {
|
||||
const v = argv[++i];
|
||||
if (!v) throw new Error("Missing value for --n");
|
||||
out.n = parseInt(v, 10);
|
||||
if (isNaN(out.n) || out.n < 1) throw new Error(`Invalid count: ${v}`);
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a.startsWith("-")) {
|
||||
throw new Error(`Unknown option: ${a}`);
|
||||
}
|
||||
|
||||
positional.push(a);
|
||||
}
|
||||
|
||||
if (!out.prompt && out.promptFiles.length === 0 && positional.length > 0) {
|
||||
out.prompt = positional.join(" ");
|
||||
}
|
||||
|
||||
return out;
|
||||
}
|
||||
|
||||
async function loadEnvFile(p: string): Promise<Record<string, string>> {
|
||||
try {
|
||||
const content = await readFile(p, "utf8");
|
||||
const env: Record<string, string> = {};
|
||||
for (const line of content.split("\n")) {
|
||||
const trimmed = line.trim();
|
||||
if (!trimmed || trimmed.startsWith("#")) continue;
|
||||
const idx = trimmed.indexOf("=");
|
||||
if (idx === -1) continue;
|
||||
const key = trimmed.slice(0, idx).trim();
|
||||
let val = trimmed.slice(idx + 1).trim();
|
||||
if ((val.startsWith('"') && val.endsWith('"')) || (val.startsWith("'") && val.endsWith("'"))) {
|
||||
val = val.slice(1, -1);
|
||||
}
|
||||
env[key] = val;
|
||||
}
|
||||
return env;
|
||||
} catch {
|
||||
return {};
|
||||
}
|
||||
}
|
||||
|
||||
async function loadEnv(): Promise<void> {
|
||||
const home = homedir();
|
||||
const cwd = process.cwd();
|
||||
|
||||
const homeEnv = await loadEnvFile(path.join(home, ".baoyu-skills", ".env"));
|
||||
const cwdEnv = await loadEnvFile(path.join(cwd, ".baoyu-skills", ".env"));
|
||||
|
||||
for (const [k, v] of Object.entries(homeEnv)) {
|
||||
if (!process.env[k]) process.env[k] = v;
|
||||
}
|
||||
for (const [k, v] of Object.entries(cwdEnv)) {
|
||||
if (!process.env[k]) process.env[k] = v;
|
||||
}
|
||||
}
|
||||
|
||||
async function readPromptFromFiles(files: string[]): Promise<string> {
|
||||
const parts: string[] = [];
|
||||
for (const f of files) {
|
||||
parts.push(await readFile(f, "utf8"));
|
||||
}
|
||||
return parts.join("\n\n");
|
||||
}
|
||||
|
||||
async function readPromptFromStdin(): Promise<string | null> {
|
||||
if (process.stdin.isTTY) return null;
|
||||
try {
|
||||
const t = await Bun.stdin.text();
|
||||
const v = t.trim();
|
||||
return v.length > 0 ? v : null;
|
||||
} catch {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
function normalizeOutputImagePath(p: string): string {
|
||||
const full = path.resolve(p);
|
||||
const ext = path.extname(full);
|
||||
if (ext) return full;
|
||||
return `${full}.png`;
|
||||
}
|
||||
|
||||
function detectProvider(args: CliArgs): Provider {
|
||||
if (args.provider) return args.provider;
|
||||
|
||||
const hasGoogle = !!process.env.GOOGLE_API_KEY;
|
||||
const hasOpenai = !!process.env.OPENAI_API_KEY;
|
||||
|
||||
if (hasGoogle && !hasOpenai) return "google";
|
||||
if (hasOpenai && !hasGoogle) return "openai";
|
||||
if (hasGoogle && hasOpenai) return "google";
|
||||
|
||||
throw new Error(
|
||||
"No API key found. Set GOOGLE_API_KEY or OPENAI_API_KEY.\n" +
|
||||
"Create ~/.baoyu-skills/.env or <cwd>/.baoyu-skills/.env with your keys."
|
||||
);
|
||||
}
|
||||
|
||||
function getDefaultModel(provider: Provider): string {
|
||||
if (provider === "google") {
|
||||
return process.env.GOOGLE_IMAGE_MODEL || "gemini-3-pro-image-preview";
|
||||
}
|
||||
return process.env.OPENAI_IMAGE_MODEL || "gpt-image-1.5";
|
||||
}
|
||||
|
||||
function isGoogleMultimodal(model: string): boolean {
|
||||
return GOOGLE_MULTIMODAL_MODELS.some((m) => model.includes(m));
|
||||
}
|
||||
|
||||
function isGoogleImagen(model: string): boolean {
|
||||
return GOOGLE_IMAGEN_MODELS.some((m) => model.includes(m));
|
||||
}
|
||||
|
||||
function buildPromptWithAspect(prompt: string, ar: string | null, quality: Quality): string {
|
||||
let result = prompt;
|
||||
if (ar) {
|
||||
result += ` Aspect ratio: ${ar}.`;
|
||||
}
|
||||
if (quality === "2k") {
|
||||
result += " High resolution 2048px.";
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
function parseAspectRatio(ar: string): { width: number; height: number } | null {
|
||||
const match = ar.match(/^(\d+(?:\.\d+)?):(\d+(?:\.\d+)?)$/);
|
||||
if (!match) return null;
|
||||
const w = parseFloat(match[1]!);
|
||||
const h = parseFloat(match[2]!);
|
||||
if (w <= 0 || h <= 0) return null;
|
||||
return { width: w, height: h };
|
||||
}
|
||||
|
||||
function getOpenAISize(ar: string | null, quality: Quality): string {
|
||||
const base = quality === "2k" ? 2048 : 1024;
|
||||
|
||||
if (!ar) return `${base}x${base}`;
|
||||
|
||||
const parsed = parseAspectRatio(ar);
|
||||
if (!parsed) return `${base}x${base}`;
|
||||
|
||||
const ratio = parsed.width / parsed.height;
|
||||
|
||||
if (Math.abs(ratio - 1) < 0.1) return `${base}x${base}`;
|
||||
if (ratio > 1.5) return quality === "2k" ? "2048x1024" : "1792x1024";
|
||||
if (ratio < 0.67) return quality === "2k" ? "1024x2048" : "1024x1792";
|
||||
return `${base}x${base}`;
|
||||
}
|
||||
|
||||
async function readImageAsBase64(p: string): Promise<{ data: string; mimeType: string }> {
|
||||
const buf = await readFile(p);
|
||||
const ext = path.extname(p).toLowerCase();
|
||||
let mimeType = "image/png";
|
||||
if (ext === ".jpg" || ext === ".jpeg") mimeType = "image/jpeg";
|
||||
else if (ext === ".gif") mimeType = "image/gif";
|
||||
else if (ext === ".webp") mimeType = "image/webp";
|
||||
return { data: buf.toString("base64"), mimeType };
|
||||
}
|
||||
|
||||
async function generateWithGoogleMultimodal(
|
||||
prompt: string,
|
||||
model: string,
|
||||
args: CliArgs
|
||||
): Promise<Uint8Array> {
|
||||
const { generateText } = await import("ai");
|
||||
const { createGoogleGenerativeAI } = await import("@ai-sdk/google");
|
||||
|
||||
const google = createGoogleGenerativeAI({
|
||||
apiKey: process.env.GOOGLE_API_KEY,
|
||||
baseURL: process.env.GOOGLE_BASE_URL,
|
||||
});
|
||||
|
||||
const fullPrompt = buildPromptWithAspect(prompt, args.aspectRatio, args.quality);
|
||||
|
||||
const messages: any[] = [];
|
||||
const content: any[] = [];
|
||||
|
||||
for (const refPath of args.referenceImages) {
|
||||
const { data, mimeType } = await readImageAsBase64(refPath);
|
||||
content.push({ type: "image", image: data, mimeType });
|
||||
}
|
||||
content.push({ type: "text", text: fullPrompt });
|
||||
|
||||
messages.push({ role: "user", content });
|
||||
|
||||
const result = await generateText({
|
||||
model: google(model, { useSearchGrounding: false }),
|
||||
messages,
|
||||
providerOptions: {
|
||||
google: {
|
||||
responseModalities: ["TEXT", "IMAGE"],
|
||||
},
|
||||
},
|
||||
});
|
||||
|
||||
const files = (result as any).files;
|
||||
if (!files || files.length === 0) {
|
||||
const expRes = (result as any).response?.body?.candidates?.[0]?.content?.parts;
|
||||
if (expRes) {
|
||||
for (const part of expRes) {
|
||||
if (part.inlineData?.data) {
|
||||
return Uint8Array.from(Buffer.from(part.inlineData.data, "base64"));
|
||||
}
|
||||
}
|
||||
}
|
||||
throw new Error("No image in response");
|
||||
}
|
||||
|
||||
const img = files[0];
|
||||
if (img.uint8Array) return img.uint8Array;
|
||||
if (img.base64) return Uint8Array.from(Buffer.from(img.base64, "base64"));
|
||||
|
||||
throw new Error("Cannot extract image data");
|
||||
}
|
||||
|
||||
async function generateWithGoogleImagen(
|
||||
prompt: string,
|
||||
model: string,
|
||||
args: CliArgs
|
||||
): Promise<Uint8Array> {
|
||||
const { experimental_generateImage: generateImage } = await import("ai");
|
||||
const { createGoogleGenerativeAI } = await import("@ai-sdk/google");
|
||||
|
||||
const google = createGoogleGenerativeAI({
|
||||
apiKey: process.env.GOOGLE_API_KEY,
|
||||
baseURL: process.env.GOOGLE_BASE_URL,
|
||||
});
|
||||
|
||||
const fullPrompt = buildPromptWithAspect(prompt, args.aspectRatio, args.quality);
|
||||
|
||||
const result = await generateImage({
|
||||
model: google.image(model),
|
||||
prompt: fullPrompt,
|
||||
n: args.n,
|
||||
aspectRatio: args.aspectRatio || undefined,
|
||||
});
|
||||
|
||||
const img = result.images[0];
|
||||
if (!img) throw new Error("No image in response");
|
||||
|
||||
if (img.uint8Array) return img.uint8Array;
|
||||
if (img.base64) return Uint8Array.from(Buffer.from(img.base64, "base64"));
|
||||
|
||||
throw new Error("Cannot extract image data");
|
||||
}
|
||||
|
||||
async function generateWithOpenAI(
|
||||
prompt: string,
|
||||
model: string,
|
||||
args: CliArgs
|
||||
): Promise<Uint8Array> {
|
||||
const baseURL = process.env.OPENAI_BASE_URL || "https://api.openai.com/v1";
|
||||
const apiKey = process.env.OPENAI_API_KEY;
|
||||
|
||||
if (!apiKey) throw new Error("OPENAI_API_KEY is required");
|
||||
|
||||
const size = args.size || getOpenAISize(args.aspectRatio, args.quality);
|
||||
|
||||
const body: Record<string, any> = {
|
||||
model,
|
||||
prompt,
|
||||
size,
|
||||
};
|
||||
|
||||
if (model.includes("dall-e-3")) {
|
||||
body.quality = args.quality === "2k" ? "hd" : "standard";
|
||||
}
|
||||
|
||||
const res = await fetch(`${baseURL}/images/generations`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: `Bearer ${apiKey}`,
|
||||
},
|
||||
body: JSON.stringify(body),
|
||||
});
|
||||
|
||||
if (!res.ok) {
|
||||
const err = await res.text();
|
||||
throw new Error(`OpenAI API error: ${err}`);
|
||||
}
|
||||
|
||||
const result = (await res.json()) as { data: Array<{ url?: string; b64_json?: string }> };
|
||||
const img = result.data[0];
|
||||
|
||||
if (img?.b64_json) {
|
||||
return Uint8Array.from(Buffer.from(img.b64_json, "base64"));
|
||||
}
|
||||
|
||||
if (img?.url) {
|
||||
const imgRes = await fetch(img.url);
|
||||
if (!imgRes.ok) throw new Error("Failed to download image");
|
||||
const buf = await imgRes.arrayBuffer();
|
||||
return new Uint8Array(buf);
|
||||
}
|
||||
|
||||
throw new Error("No image in response");
|
||||
}
|
||||
|
||||
async function generate(
|
||||
provider: Provider,
|
||||
model: string,
|
||||
prompt: string,
|
||||
args: CliArgs
|
||||
): Promise<Uint8Array> {
|
||||
if (provider === "google") {
|
||||
if (isGoogleMultimodal(model)) {
|
||||
return generateWithGoogleMultimodal(prompt, model, args);
|
||||
}
|
||||
if (isGoogleImagen(model)) {
|
||||
if (args.referenceImages.length > 0) {
|
||||
console.error("Warning: Reference images not supported with Imagen models, ignoring.");
|
||||
}
|
||||
return generateWithGoogleImagen(prompt, model, args);
|
||||
}
|
||||
return generateWithGoogleMultimodal(prompt, model, args);
|
||||
}
|
||||
|
||||
if (args.referenceImages.length > 0) {
|
||||
console.error("Warning: Reference images not supported with OpenAI, ignoring.");
|
||||
}
|
||||
return generateWithOpenAI(prompt, model, args);
|
||||
}
|
||||
|
||||
async function main(): Promise<void> {
|
||||
const args = parseArgs(process.argv.slice(2));
|
||||
|
||||
if (args.help) {
|
||||
printUsage();
|
||||
return;
|
||||
}
|
||||
|
||||
await loadEnv();
|
||||
|
||||
let prompt: string | null = args.prompt;
|
||||
if (!prompt && args.promptFiles.length > 0) prompt = await readPromptFromFiles(args.promptFiles);
|
||||
if (!prompt) prompt = await readPromptFromStdin();
|
||||
|
||||
if (!prompt) {
|
||||
console.error("Error: Prompt is required");
|
||||
printUsage();
|
||||
process.exitCode = 1;
|
||||
return;
|
||||
}
|
||||
|
||||
if (!args.imagePath) {
|
||||
console.error("Error: --image is required");
|
||||
printUsage();
|
||||
process.exitCode = 1;
|
||||
return;
|
||||
}
|
||||
|
||||
const provider = detectProvider(args);
|
||||
const model = args.model || getDefaultModel(provider);
|
||||
const outputPath = normalizeOutputImagePath(args.imagePath);
|
||||
|
||||
let imageData: Uint8Array;
|
||||
let retried = false;
|
||||
|
||||
while (true) {
|
||||
try {
|
||||
imageData = await generate(provider, model, prompt, args);
|
||||
break;
|
||||
} catch (e) {
|
||||
if (!retried) {
|
||||
retried = true;
|
||||
console.error("Generation failed, retrying...");
|
||||
continue;
|
||||
}
|
||||
throw e;
|
||||
}
|
||||
}
|
||||
|
||||
const dir = path.dirname(outputPath);
|
||||
await mkdir(dir, { recursive: true });
|
||||
await writeFile(outputPath, imageData);
|
||||
|
||||
if (args.json) {
|
||||
console.log(
|
||||
JSON.stringify(
|
||||
{
|
||||
savedImage: outputPath,
|
||||
provider,
|
||||
model,
|
||||
prompt: prompt.slice(0, 200),
|
||||
},
|
||||
null,
|
||||
2
|
||||
)
|
||||
);
|
||||
} else {
|
||||
console.log(outputPath);
|
||||
}
|
||||
}
|
||||
|
||||
main().catch((e) => {
|
||||
const msg = e instanceof Error ? e.message : String(e);
|
||||
console.error(msg);
|
||||
process.exit(1);
|
||||
});
|
||||
|
|
@ -87,6 +87,46 @@ Transform content into professional slide deck images with flexible style option
|
|||
| lifestyle, wellness, travel, artistic, natural | `watercolor` |
|
||||
| Default | `blueprint` |
|
||||
|
||||
## Layout Gallery
|
||||
|
||||
Optional layout hints for individual slides. Specify in outline's `// LAYOUT` section.
|
||||
|
||||
### Slide-Specific Layouts
|
||||
|
||||
| Layout | Description | Best For |
|
||||
|--------|-------------|----------|
|
||||
| `title-hero` | Large centered title + subtitle | Cover slides, section breaks |
|
||||
| `quote-callout` | Featured quote with attribution | Testimonials, key insights |
|
||||
| `key-stat` | Single large number as focal point | Impact statistics, metrics |
|
||||
| `split-screen` | Half image, half text | Feature highlights, comparisons |
|
||||
| `icon-grid` | Grid of icons with labels | Features, capabilities, benefits |
|
||||
| `two-columns` | Content in balanced columns | Paired information, dual points |
|
||||
| `three-columns` | Content in three columns | Triple comparisons, categories |
|
||||
| `image-caption` | Full-bleed image + text overlay | Visual storytelling, emotional |
|
||||
| `agenda` | Numbered list with highlights | Session overview, roadmap |
|
||||
| `bullet-list` | Structured bullet points | Simple content, lists |
|
||||
|
||||
### Infographic-Derived Layouts
|
||||
|
||||
| Layout | Description | Best For |
|
||||
|--------|-------------|----------|
|
||||
| `linear-progression` | Sequential flow left-to-right | Timelines, step-by-step |
|
||||
| `binary-comparison` | Side-by-side A vs B | Before/after, pros-cons |
|
||||
| `comparison-matrix` | Multi-factor grid | Feature comparisons |
|
||||
| `hierarchical-layers` | Pyramid or stacked levels | Priority, importance |
|
||||
| `hub-spoke` | Central node with radiating items | Concept maps, ecosystems |
|
||||
| `bento-grid` | Varied-size tiles | Overview, summary |
|
||||
| `funnel` | Narrowing stages | Conversion, filtering |
|
||||
| `dashboard` | Metrics with charts/numbers | KPIs, data display |
|
||||
| `venn-diagram` | Overlapping circles | Relationships, intersections |
|
||||
| `circular-flow` | Continuous cycle | Recurring processes |
|
||||
| `winding-roadmap` | Curved path with milestones | Journey, timeline |
|
||||
| `tree-branching` | Parent-child hierarchy | Org charts, taxonomies |
|
||||
| `iceberg` | Visible vs hidden layers | Surface vs depth |
|
||||
| `bridge` | Gap with connection | Problem-solution |
|
||||
|
||||
**Usage**: Add `Layout: <name>` in slide's `// LAYOUT` section to guide visual composition.
|
||||
|
||||
## Design Philosophy
|
||||
|
||||
This deck is designed for **reading and sharing**, not live presentation:
|
||||
|
|
@ -169,7 +209,10 @@ If `--outline-only`, stop here.
|
|||
1. Read `references/base-prompt.md`
|
||||
2. Combine with style instructions from outline
|
||||
3. Add slide-specific content
|
||||
4. Save to `prompts/` directory
|
||||
4. If `Layout:` specified in outline, include layout guidance in prompt:
|
||||
- Reference layout characteristics for image composition
|
||||
- Example: `Layout: hub-spoke` → "Central concept in middle with related items radiating outward"
|
||||
5. Save to `prompts/` directory
|
||||
|
||||
### Step 5: Generate Images
|
||||
|
||||
|
|
|
|||
|
|
@ -67,6 +67,7 @@ Sub-headline: [supporting tagline]
|
|||
[Detailed visual description - specific elements, composition, mood]
|
||||
|
||||
// LAYOUT
|
||||
Layout: [optional: layout name from gallery, e.g., title-hero]
|
||||
[Composition, hierarchy, spatial arrangement]
|
||||
```
|
||||
|
||||
|
|
@ -93,6 +94,7 @@ Body:
|
|||
[Detailed visual description]
|
||||
|
||||
// LAYOUT
|
||||
Layout: [optional: layout name from gallery]
|
||||
[Composition, hierarchy, spatial arrangement]
|
||||
```
|
||||
|
||||
|
|
@ -115,6 +117,7 @@ Body: [optional summary points or next steps]
|
|||
[Visual that reinforces the core message]
|
||||
|
||||
// LAYOUT
|
||||
Layout: [optional: layout name from gallery]
|
||||
[Clean, impactful composition]
|
||||
```
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue