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Author SHA1 Message Date
Jim Liu 宝玉 7c995fcc24 chore: release v1.80.1 2026-03-24 20:06:02 -05:00
Jim Liu 宝玉 151f1ec2a8 fix(baoyu-image-gen): use correct prompt field name for Jimeng API 2026-03-24 20:04:21 -05:00
Jim Liu 宝玉 12e207dc3f chore: release v1.80.0 2026-03-24 19:27:57 -05:00
Jim Liu 宝玉 00e74ab071 feat(baoyu-image-gen): improve Azure OpenAI provider with flexible endpoint parsing and deployment resolution 2026-03-24 19:19:49 -05:00
优弧 1653b8544b feat(baoyu-image-gen): add Azure OpenAI as independent image generation provider (#111)
Azure OpenAI differs from standard OpenAI in two ways:
1. Auth via api-key header instead of Authorization: Bearer
2. URL requires ?api-version query param with deployment path

Changes:
- New file: scripts/providers/azure.ts (generations + edits, reuses openai utilities)
- types.ts: add "azure" to Provider type and default_model
- main.ts: register azure across rate limits, CLI args, auto-detection,
  provider loading, model resolution, help text, ref validation,
  EXTEND.md parsing, and batch logging

Env vars: AZURE_OPENAI_API_KEY, AZURE_OPENAI_BASE_URL (required),
AZURE_API_VERSION, AZURE_OPENAI_IMAGE_MODEL (optional)

Co-authored-by: CatFly <zw.catfly@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-24 19:04:34 -05:00
16 changed files with 650 additions and 26 deletions
+1 -1
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@@ -6,7 +6,7 @@
},
"metadata": {
"description": "Skills shared by Baoyu for improving daily work efficiency",
"version": "1.79.2"
"version": "1.80.1"
},
"plugins": [
{
+10
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@@ -2,6 +2,16 @@
English | [中文](./CHANGELOG.zh.md)
## 1.80.1 - 2026-03-24
### Fixes
- `baoyu-image-gen`: use correct `prompt` field name for Jimeng API request
## 1.80.0 - 2026-03-24
### Features
- `baoyu-image-gen`: add Azure OpenAI as independent image generation provider with flexible endpoint parsing, deployment-name resolution, quality mapping, and reference image validation
## 1.79.2 - 2026-03-23
### Fixes
+10
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@@ -2,6 +2,16 @@
[English](./CHANGELOG.md) | 中文
## 1.80.1 - 2026-03-24
### 修复
- `baoyu-image-gen`:修正即梦 API 请求中的 `prompt` 字段名
## 1.80.0 - 2026-03-24
### 新功能
- `baoyu-image-gen`:新增 Azure OpenAI 作为独立图像生成服务商,支持灵活的端点解析、部署名称推断、质量映射及参考图片格式校验
## 1.79.2 - 2026-03-23
### 修复
+2 -2
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@@ -1,6 +1,6 @@
# CLAUDE.md
Claude Code marketplace plugin providing AI-powered content generation skills. Version: **1.79.2**.
Claude Code marketplace plugin providing AI-powered content generation skills. Version: **1.80.1**.
## Architecture
@@ -31,7 +31,7 @@ Execute: `${BUN_X} skills/<skill>/scripts/main.ts [options]`
- **Bun**: TypeScript runtime (`bun` preferred, fallback `npx -y bun`)
- **Chrome**: Required for CDP-based skills (gemini-web, post-to-x/wechat/weibo, url-to-markdown). All CDP skills share a single profile, override via `BAOYU_CHROME_PROFILE_DIR` env var. Platform paths: [docs/chrome-profile.md](docs/chrome-profile.md)
- **Image generation APIs**: `baoyu-image-gen` requires API key (OpenAI, Google, OpenRouter, DashScope, or Replicate) configured in EXTEND.md
- **Image generation APIs**: `baoyu-image-gen` requires API key (OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, or Replicate) configured in EXTEND.md
- **Gemini Web auth**: Browser cookies (first run opens Chrome for login, `--login` to refresh)
## Security
+5 -2
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@@ -663,7 +663,7 @@ AI-powered generation backends.
#### baoyu-image-gen
AI SDK-based image generation using OpenAI, Google, OpenRouter, DashScope (Aliyun Tongyi Wanxiang), Jimeng (即梦), Seedream (豆包), and Replicate APIs. Supports text-to-image, reference images, aspect ratios, and quality presets.
AI SDK-based image generation using OpenAI, Azure OpenAI, Google, OpenRouter, DashScope (Aliyun Tongyi Wanxiang), Jimeng (即梦), Seedream (豆包), and Replicate APIs. Supports text-to-image, reference images, aspect ratios, and quality presets.
```bash
# Basic generation (auto-detect provider)
@@ -678,6 +678,9 @@ AI SDK-based image generation using OpenAI, Google, OpenRouter, DashScope (Aliyu
# Specific provider
/baoyu-image-gen --prompt "A cat" --image cat.png --provider openai
# Azure OpenAI (model = deployment name)
/baoyu-image-gen --prompt "A cat" --image cat.png --provider azure --model gpt-image-1.5
# OpenRouter
/baoyu-image-gen --prompt "A cat" --image cat.png --provider openrouter
@@ -693,7 +696,7 @@ AI SDK-based image generation using OpenAI, Google, OpenRouter, DashScope (Aliyu
# Seedream (豆包)
/baoyu-image-gen --prompt "一只可爱的猫" --image cat.png --provider seedream
# With reference images (Google, OpenAI, OpenRouter, Replicate, or Seedream 5.0/4.5/4.0)
# With reference images (Google, OpenAI, Azure OpenAI, OpenRouter, Replicate, or Seedream 5.0/4.5/4.0)
/baoyu-image-gen --prompt "Make it blue" --image out.png --ref source.png
```
+5 -2
View File
@@ -663,7 +663,7 @@ AI 驱动的生成后端。
#### baoyu-image-gen
基于 AI SDK 的图像生成,支持 OpenAI、Google、OpenRouter、DashScope(阿里通义万相)、即梦(Jimeng)、豆包(Seedream)和 Replicate API。支持文生图、参考图、宽高比和质量预设。
基于 AI SDK 的图像生成,支持 OpenAI、Azure OpenAI、Google、OpenRouter、DashScope(阿里通义万相)、即梦(Jimeng)、豆包(Seedream)和 Replicate API。支持文生图、参考图、宽高比和质量预设。
```bash
# 基础生成(自动检测服务商)
@@ -678,6 +678,9 @@ AI 驱动的生成后端。
# 指定服务商
/baoyu-image-gen --prompt "一只猫" --image cat.png --provider openai
# Azure OpenAImodel 为部署名称)
/baoyu-image-gen --prompt "一只猫" --image cat.png --provider azure --model gpt-image-1.5
# OpenRouter
/baoyu-image-gen --prompt "一只猫" --image cat.png --provider openrouter
@@ -693,7 +696,7 @@ AI 驱动的生成后端。
# 豆包(Seedream
/baoyu-image-gen --prompt "一只可爱的猫" --image cat.png --provider seedream
# 带参考图(Google、OpenAI、OpenRouter、Replicate 或 Seedream 5.0/4.5/4.0
# 带参考图(Google、OpenAI、Azure OpenAI、OpenRouter、Replicate 或 Seedream 5.0/4.5/4.0
/baoyu-image-gen --prompt "把它变成蓝色" --image out.png --ref source.png
```
+16 -6
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@@ -1,6 +1,6 @@
---
name: baoyu-image-gen
description: AI image generation with OpenAI, Google, OpenRouter, DashScope, Jimeng, Seedream and Replicate 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.
description: AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, Jimeng, Seedream and Replicate 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.
version: 1.56.3
metadata:
openclaw:
@@ -13,7 +13,7 @@ metadata:
# Image Generation (AI SDK)
Official API-based image generation. Supports OpenAI, Google, OpenRouter, DashScope (阿里通义万象), Jimeng (即梦), Seedream (豆包) and Replicate providers.
Official API-based image generation. Supports OpenAI, Azure OpenAI, Google, OpenRouter, DashScope (阿里通义万象), Jimeng (即梦), Seedream (豆包) and Replicate providers.
## Script Directory
@@ -74,12 +74,15 @@ ${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --quality 2k
# From prompt files
${BUN_X} {baseDir}/scripts/main.ts --promptfiles system.md content.md --image out.png
# With reference images (Google, OpenAI, OpenRouter, Replicate, or Seedream 4.0/4.5/5.0)
# With reference images (Google, OpenAI, Azure OpenAI, OpenRouter, Replicate, or Seedream 4.0/4.5/5.0)
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --ref source.png
# With reference images (explicit provider/model)
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --provider google --model gemini-3-pro-image-preview --ref source.png
# Azure OpenAI (model means deployment name)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider azure --model gpt-image-1.5
# OpenRouter (recommended default model)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openrouter
@@ -147,13 +150,13 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
| `--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\|openrouter\|dashscope\|jimeng\|seedream\|replicate` | Force provider (default: auto-detect) |
| `--model <id>`, `-m` | Model ID (Google: `gemini-3-pro-image-preview`; OpenAI: `gpt-image-1.5`; OpenRouter: `google/gemini-3.1-flash-image-preview`; DashScope: `qwen-image-2.0-pro`) |
| `--provider google\|openai\|azure\|openrouter\|dashscope\|jimeng\|seedream\|replicate` | Force provider (default: auto-detect) |
| `--model <id>`, `-m` | Model ID (Google: `gemini-3-pro-image-preview`; OpenAI: `gpt-image-1.5`; Azure: deployment name such as `gpt-image-1.5` or `image-prod`; OpenRouter: `google/gemini-3.1-flash-image-preview`; DashScope: `qwen-image-2.0-pro`) |
| `--ar <ratio>` | Aspect ratio (e.g., `16:9`, `1:1`, `4:3`) |
| `--size <WxH>` | Size (e.g., `1024x1024`) |
| `--quality normal\|2k` | Quality preset (default: `2k`) |
| `--imageSize 1K\|2K\|4K` | Image size for Google/OpenRouter (default: from quality) |
| `--ref <files...>` | Reference images. Supported by Google multimodal, OpenAI GPT Image edits, OpenRouter multimodal models, Replicate, and Seedream 5.0/4.5/4.0. Not supported by Jimeng, Seedream 3.0, or removed SeedEdit 3.0 |
| `--ref <files...>` | Reference images. Supported by Google multimodal, OpenAI GPT Image edits, Azure OpenAI edits (PNG/JPG only), OpenRouter multimodal models, Replicate, and Seedream 5.0/4.5/4.0. Not supported by Jimeng, Seedream 3.0, or removed SeedEdit 3.0 |
| `--n <count>` | Number of images |
| `--json` | JSON output |
@@ -162,6 +165,7 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
| Variable | Description |
|----------|-------------|
| `OPENAI_API_KEY` | OpenAI API key |
| `AZURE_OPENAI_API_KEY` | Azure OpenAI API key |
| `OPENROUTER_API_KEY` | OpenRouter API key |
| `GOOGLE_API_KEY` | Google API key |
| `DASHSCOPE_API_KEY` | DashScope API key (阿里云) |
@@ -170,6 +174,8 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
| `JIMENG_SECRET_ACCESS_KEY` | Jimeng (即梦) Volcengine secret key |
| `ARK_API_KEY` | Seedream (豆包) Volcengine ARK API key |
| `OPENAI_IMAGE_MODEL` | OpenAI model override |
| `AZURE_OPENAI_DEPLOYMENT` | Azure default deployment name |
| `AZURE_OPENAI_IMAGE_MODEL` | Backward-compatible alias for Azure default deployment/model name |
| `OPENROUTER_IMAGE_MODEL` | OpenRouter model override (default: `google/gemini-3.1-flash-image-preview`) |
| `GOOGLE_IMAGE_MODEL` | Google model override |
| `DASHSCOPE_IMAGE_MODEL` | DashScope model override (default: `qwen-image-2.0-pro`) |
@@ -177,6 +183,8 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
| `JIMENG_IMAGE_MODEL` | Jimeng model override (default: jimeng_t2i_v40) |
| `SEEDREAM_IMAGE_MODEL` | Seedream model override (default: doubao-seedream-5-0-260128) |
| `OPENAI_BASE_URL` | Custom OpenAI endpoint |
| `AZURE_OPENAI_BASE_URL` | Azure resource endpoint or deployment endpoint |
| `AZURE_API_VERSION` | Azure image API version (default: `2025-04-01-preview`) |
| `OPENROUTER_BASE_URL` | Custom OpenRouter endpoint (default: `https://openrouter.ai/api/v1`) |
| `OPENROUTER_HTTP_REFERER` | Optional app/site URL for OpenRouter attribution |
| `OPENROUTER_TITLE` | Optional app name for OpenRouter attribution |
@@ -201,6 +209,8 @@ Model priority (highest → lowest), applies to all providers:
3. Env var: `<PROVIDER>_IMAGE_MODEL` (e.g., `GOOGLE_IMAGE_MODEL`)
4. Built-in default
For Azure, `--model` / `default_model.azure` should be the Azure deployment name. `AZURE_OPENAI_DEPLOYMENT` is the preferred env var, and `AZURE_OPENAI_IMAGE_MODEL` remains as a backward-compatible alias.
**EXTEND.md overrides env vars**. If both EXTEND.md `default_model.google: "gemini-3-pro-image-preview"` and env var `GOOGLE_IMAGE_MODEL=gemini-3.1-flash-image-preview` exist, EXTEND.md wins.
**Agent MUST display model info** before each generation:
@@ -47,6 +47,8 @@ options:
description: "Gemini multimodal - high quality, reference images, flexible sizes"
- label: "OpenAI"
description: "GPT Image - consistent quality, reliable output"
- label: "Azure OpenAI"
description: "Azure-hosted GPT Image deployments with resource-specific routing"
- label: "OpenRouter"
description: "Router for Gemini/FLUX/OpenAI-compatible image models"
- label: "DashScope"
@@ -87,6 +89,20 @@ options:
description: "Strong text-to-image quality through OpenRouter"
```
### Question 2c: Default Azure Deployment
Only show if user selected Azure OpenAI.
```yaml
header: "Azure Deploy"
question: "Default Azure image deployment name?"
options:
- label: "gpt-image-1.5 (Recommended)"
description: "Best default if your Azure deployment uses the same name"
- label: "gpt-image-1"
description: "Previous GPT Image deployment name"
```
### Question 3: Default Quality
```yaml
@@ -130,6 +146,7 @@ default_image_size: null
default_model:
google: [selected google model or null]
openai: null
azure: [selected azure deployment or null]
openrouter: [selected openrouter model or null]
dashscope: null
replicate: null
@@ -166,6 +183,23 @@ options:
description: "Previous generation GPT Image model"
```
### Azure Deployment Selection
```yaml
header: "Azure Deploy"
question: "Choose a default Azure image deployment name?"
options:
- label: "gpt-image-1.5 (Recommended)"
description: "Use when your Azure deployment name matches the GPT-image-1.5 model"
- label: "gpt-image-1"
description: "Use when your Azure deployment name matches GPT-image-1"
```
Notes for Azure setup:
- In `baoyu-image-gen`, Azure `--model` / `default_model.azure` should be the Azure deployment name, not just the underlying model family.
- If the deployment name is custom, save that exact deployment name in `default_model.azure`.
### OpenRouter Model Selection
```yaml
@@ -230,6 +264,7 @@ After user selects a model:
default_model:
google: [value or null]
openai: [value or null]
azure: [value or null]
openrouter: [value or null]
dashscope: [value or null]
replicate: [value or null]
@@ -11,7 +11,7 @@ description: EXTEND.md YAML schema for baoyu-image-gen user preferences
---
version: 1
default_provider: null # google|openai|openrouter|dashscope|replicate|null (null = auto-detect)
default_provider: null # google|openai|azure|openrouter|dashscope|replicate|null (null = auto-detect)
default_quality: null # normal|2k|null (null = use default: 2k)
@@ -22,6 +22,7 @@ default_image_size: null # 1K|2K|4K|null (Google/OpenRouter, overrides qualit
default_model:
google: null # e.g., "gemini-3-pro-image-preview", "gemini-3.1-flash-image-preview"
openai: null # e.g., "gpt-image-1.5", "gpt-image-1"
azure: null # Azure deployment name, e.g., "gpt-image-1.5" or "image-prod"
openrouter: null # e.g., "google/gemini-3.1-flash-image-preview"
dashscope: null # e.g., "qwen-image-2.0-pro"
replicate: null # e.g., "google/nano-banana-pro"
@@ -38,6 +39,9 @@ batch:
openai:
concurrency: 3
start_interval_ms: 1100
azure:
concurrency: 3
start_interval_ms: 1100
openrouter:
concurrency: 3
start_interval_ms: 1100
@@ -58,6 +62,7 @@ batch:
| `default_image_size` | string\|null | null | Google/OpenRouter image size (overrides quality) |
| `default_model.google` | string\|null | null | Google default model |
| `default_model.openai` | string\|null | null | OpenAI default model |
| `default_model.azure` | string\|null | null | Azure default deployment name |
| `default_model.openrouter` | string\|null | null | OpenRouter default model |
| `default_model.dashscope` | string\|null | null | DashScope default model |
| `default_model.replicate` | string\|null | null | Replicate default model |
@@ -87,6 +92,7 @@ default_image_size: 2K
default_model:
google: "gemini-3-pro-image-preview"
openai: "gpt-image-1.5"
azure: "gpt-image-1.5"
openrouter: "google/gemini-3.1-flash-image-preview"
dashscope: "qwen-image-2.0-pro"
replicate: "google/nano-banana-pro"
@@ -96,6 +102,9 @@ batch:
replicate:
concurrency: 5
start_interval_ms: 700
azure:
concurrency: 3
start_interval_ms: 1100
openrouter:
concurrency: 3
start_interval_ms: 1100
@@ -123,6 +123,7 @@ default_image_size: 2K
default_model:
google: gemini-3-pro-image-preview
openai: gpt-image-1.5
azure: image-prod
batch:
max_workers: 8
provider_limits:
@@ -131,6 +132,9 @@ batch:
start_interval_ms: 900
openai:
concurrency: 4
azure:
concurrency: 1
start_interval_ms: 1500
`;
const config = parseSimpleYaml(yaml);
@@ -142,6 +146,7 @@ batch:
assert.equal(config.default_image_size, "2K");
assert.equal(config.default_model?.google, "gemini-3-pro-image-preview");
assert.equal(config.default_model?.openai, "gpt-image-1.5");
assert.equal(config.default_model?.azure, "image-prod");
assert.equal(config.batch?.max_workers, 8);
assert.deepEqual(config.batch?.provider_limits?.google, {
concurrency: 2,
@@ -150,6 +155,10 @@ batch:
assert.deepEqual(config.batch?.provider_limits?.openai, {
concurrency: 4,
});
assert.deepEqual(config.batch?.provider_limits?.azure, {
concurrency: 1,
start_interval_ms: 1500,
});
});
test("mergeConfig only fills values missing from CLI args", () => {
@@ -203,6 +212,8 @@ test("detectProvider selects an available ref-capable provider for reference-ima
useEnv(t, {
GOOGLE_API_KEY: null,
OPENAI_API_KEY: "openai-key",
AZURE_OPENAI_API_KEY: null,
AZURE_OPENAI_BASE_URL: null,
OPENROUTER_API_KEY: null,
DASHSCOPE_API_KEY: null,
REPLICATE_API_TOKEN: null,
@@ -216,6 +227,27 @@ test("detectProvider selects an available ref-capable provider for reference-ima
);
});
test("detectProvider selects Azure when only Azure credentials are configured", (t) => {
useEnv(t, {
GOOGLE_API_KEY: null,
OPENAI_API_KEY: null,
AZURE_OPENAI_API_KEY: "azure-key",
AZURE_OPENAI_BASE_URL: "https://example.openai.azure.com",
OPENROUTER_API_KEY: null,
DASHSCOPE_API_KEY: null,
REPLICATE_API_TOKEN: null,
JIMENG_ACCESS_KEY_ID: null,
JIMENG_SECRET_ACCESS_KEY: null,
ARK_API_KEY: null,
});
assert.equal(detectProvider(makeArgs()), "azure");
assert.equal(
detectProvider(makeArgs({ referenceImages: ["ref.png"] })),
"azure",
);
});
test("detectProvider infers Seedream from model id and allows Seedream reference-image workflows", (t) => {
useEnv(t, {
GOOGLE_API_KEY: null,
+27 -10
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@@ -60,6 +60,7 @@ const DEFAULT_PROVIDER_RATE_LIMITS: Record<Provider, ProviderRateLimit> = {
dashscope: { concurrency: 3, startIntervalMs: 1100 },
jimeng: { concurrency: 3, startIntervalMs: 1100 },
seedream: { concurrency: 3, startIntervalMs: 1100 },
azure: { concurrency: 3, startIntervalMs: 1100 },
};
function printUsage(): void {
@@ -74,13 +75,13 @@ Options:
--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|openrouter|dashscope|replicate|jimeng|seedream Force provider (auto-detect by default)
--provider google|openai|openrouter|dashscope|replicate|jimeng|seedream|azure 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: 2k)
--imageSize 1K|2K|4K Image size for Google/OpenRouter (default: from quality)
--ref <files...> Reference images (Google, OpenAI, OpenRouter, Replicate, or Seedream 4.0/4.5/5.0)
--ref <files...> Reference images (Google, OpenAI, Azure, OpenRouter, Replicate, or Seedream 4.0/4.5/5.0)
--n <count> Number of images for the current task (default: 1)
--json JSON output
-h, --help Show help
@@ -131,6 +132,11 @@ Environment variables:
DASHSCOPE_BASE_URL Custom DashScope endpoint
REPLICATE_BASE_URL Custom Replicate endpoint
JIMENG_BASE_URL Custom Jimeng endpoint
AZURE_OPENAI_API_KEY Azure OpenAI API key
AZURE_OPENAI_BASE_URL Azure OpenAI resource or deployment endpoint
AZURE_OPENAI_DEPLOYMENT Default Azure deployment name
AZURE_API_VERSION Azure API version (default: 2025-04-01-preview)
AZURE_OPENAI_IMAGE_MODEL Backward-compatible Azure deployment/model alias (defaults to gpt-image-1.5)
SEEDREAM_BASE_URL Custom Seedream endpoint
BAOYU_IMAGE_GEN_MAX_WORKERS Override batch worker cap
BAOYU_IMAGE_GEN_<PROVIDER>_CONCURRENCY Override provider concurrency
@@ -231,7 +237,8 @@ export function parseArgs(argv: string[]): CliArgs {
v !== "dashscope" &&
v !== "replicate" &&
v !== "jimeng" &&
v !== "seedream"
v !== "seedream" &&
v !== "azure"
) {
throw new Error(`Invalid provider: ${v}`);
}
@@ -386,6 +393,7 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
replicate: null,
jimeng: null,
seedream: null,
azure: null,
};
currentKey = "default_model";
currentProvider = null;
@@ -411,7 +419,8 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
key === "dashscope" ||
key === "replicate" ||
key === "jimeng" ||
key === "seedream"
key === "seedream" ||
key === "azure"
)
) {
config.batch ??= {};
@@ -427,7 +436,8 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
key === "dashscope" ||
key === "replicate" ||
key === "jimeng" ||
key === "seedream"
key === "seedream" ||
key === "azure"
)
) {
const cleaned = value.replace(/['"]/g, "");
@@ -520,9 +530,10 @@ export function getConfiguredProviderRateLimits(
dashscope: { ...DEFAULT_PROVIDER_RATE_LIMITS.dashscope },
jimeng: { ...DEFAULT_PROVIDER_RATE_LIMITS.jimeng },
seedream: { ...DEFAULT_PROVIDER_RATE_LIMITS.seedream },
azure: { ...DEFAULT_PROVIDER_RATE_LIMITS.azure },
};
for (const provider of ["replicate", "google", "openai", "openrouter", "dashscope", "jimeng", "seedream"] as Provider[]) {
for (const provider of ["replicate", "google", "openai", "openrouter", "dashscope", "jimeng", "seedream", "azure"] as Provider[]) {
const envPrefix = `BAOYU_IMAGE_GEN_${provider.toUpperCase()}`;
const extendLimit = extendConfig.batch?.provider_limits?.[provider];
configured[provider] = {
@@ -581,18 +592,20 @@ export function detectProvider(args: CliArgs): Provider {
args.provider &&
args.provider !== "google" &&
args.provider !== "openai" &&
args.provider !== "azure" &&
args.provider !== "openrouter" &&
args.provider !== "replicate" &&
args.provider !== "seedream"
) {
throw new Error(
"Reference images require a ref-capable provider. Use --provider google (Gemini multimodal), --provider openai (GPT Image edits), --provider openrouter (OpenRouter multimodal), --provider replicate, or --provider seedream for supported Seedream models."
"Reference images require a ref-capable provider. Use --provider google (Gemini multimodal), --provider openai (GPT Image edits), --provider azure (Azure OpenAI), --provider openrouter (OpenRouter multimodal), --provider replicate, or --provider seedream for supported Seedream models."
);
}
if (args.provider) return args.provider;
const hasGoogle = !!(process.env.GOOGLE_API_KEY || process.env.GEMINI_API_KEY);
const hasAzure = !!(process.env.AZURE_OPENAI_API_KEY && process.env.AZURE_OPENAI_BASE_URL);
const hasOpenai = !!process.env.OPENAI_API_KEY;
const hasOpenrouter = !!process.env.OPENROUTER_API_KEY;
const hasDashscope = !!process.env.DASHSCOPE_API_KEY;
@@ -611,17 +624,19 @@ export function detectProvider(args: CliArgs): Provider {
if (args.referenceImages.length > 0) {
if (hasGoogle) return "google";
if (hasOpenai) return "openai";
if (hasAzure) return "azure";
if (hasOpenrouter) return "openrouter";
if (hasReplicate) return "replicate";
if (hasSeedream) return "seedream";
throw new Error(
"Reference images require Google, OpenAI, OpenRouter, Replicate, or supported Seedream models. Set GOOGLE_API_KEY/GEMINI_API_KEY, OPENAI_API_KEY, OPENROUTER_API_KEY, REPLICATE_API_TOKEN, or ARK_API_KEY, or remove --ref."
"Reference images require Google, OpenAI, Azure, OpenRouter, Replicate, or supported Seedream models. Set GOOGLE_API_KEY/GEMINI_API_KEY, OPENAI_API_KEY, AZURE_OPENAI_API_KEY+AZURE_OPENAI_BASE_URL, OPENROUTER_API_KEY, REPLICATE_API_TOKEN, or ARK_API_KEY, or remove --ref."
);
}
const available = [
hasGoogle && "google",
hasOpenai && "openai",
hasAzure && "azure",
hasOpenrouter && "openrouter",
hasDashscope && "dashscope",
hasReplicate && "replicate",
@@ -633,7 +648,7 @@ export function detectProvider(args: CliArgs): Provider {
if (available.length > 1) return available[0]!;
throw new Error(
"No API key found. Set GOOGLE_API_KEY, GEMINI_API_KEY, OPENAI_API_KEY, OPENROUTER_API_KEY, DASHSCOPE_API_KEY, REPLICATE_API_TOKEN, JIMENG keys, or ARK_API_KEY.\n" +
"No API key found. Set GOOGLE_API_KEY, GEMINI_API_KEY, OPENAI_API_KEY, AZURE_OPENAI_API_KEY+AZURE_OPENAI_BASE_URL, OPENROUTER_API_KEY, DASHSCOPE_API_KEY, REPLICATE_API_TOKEN, JIMENG keys, or ARK_API_KEY.\n" +
"Create ~/.baoyu-skills/.env or <cwd>/.baoyu-skills/.env with your keys."
);
}
@@ -676,6 +691,7 @@ async function loadProviderModule(provider: Provider): Promise<ProviderModule> {
if (provider === "openrouter") return (await import("./providers/openrouter")) as ProviderModule;
if (provider === "jimeng") return (await import("./providers/jimeng")) as ProviderModule;
if (provider === "seedream") return (await import("./providers/seedream")) as ProviderModule;
if (provider === "azure") return (await import("./providers/azure")) as ProviderModule;
return (await import("./providers/openai")) as ProviderModule;
}
@@ -704,6 +720,7 @@ function getModelForProvider(
if (provider === "replicate" && extendConfig.default_model.replicate) return extendConfig.default_model.replicate;
if (provider === "jimeng" && extendConfig.default_model.jimeng) return extendConfig.default_model.jimeng;
if (provider === "seedream" && extendConfig.default_model.seedream) return extendConfig.default_model.seedream;
if (provider === "azure" && extendConfig.default_model.azure) return extendConfig.default_model.azure;
}
return providerModule.getDefaultModel();
}
@@ -923,7 +940,7 @@ async function runBatchTasks(
const acquireProvider = createProviderGate(providerRateLimits);
const workerCount = getWorkerCount(tasks.length, jobs, maxWorkers);
console.error(`Batch mode: ${tasks.length} tasks, ${workerCount} workers, parallel mode enabled.`);
for (const provider of ["replicate", "google", "openai", "openrouter", "dashscope", "jimeng", "seedream"] as Provider[]) {
for (const provider of ["replicate", "google", "openai", "openrouter", "dashscope", "jimeng", "seedream", "azure"] as Provider[]) {
const limit = providerRateLimits[provider];
console.error(`- ${provider}: concurrency=${limit.concurrency}, startIntervalMs=${limit.startIntervalMs}`);
}
@@ -0,0 +1,188 @@
import assert from "node:assert/strict";
import fs from "node:fs/promises";
import os from "node:os";
import path from "node:path";
import test, { type TestContext } from "node:test";
import type { CliArgs } from "../types.ts";
import {
generateImage,
getDefaultModel,
parseAzureBaseURL,
validateArgs,
} from "./azure.ts";
function useEnv(
t: TestContext,
values: Record<string, string | null>,
): void {
const previous = new Map<string, string | undefined>();
for (const [key, value] of Object.entries(values)) {
previous.set(key, process.env[key]);
if (value == null) {
delete process.env[key];
} else {
process.env[key] = value;
}
}
t.after(() => {
for (const [key, value] of previous.entries()) {
if (value == null) {
delete process.env[key];
} else {
process.env[key] = value;
}
}
});
}
function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
return {
prompt: null,
promptFiles: [],
imagePath: null,
provider: null,
model: null,
aspectRatio: null,
size: null,
quality: null,
imageSize: null,
referenceImages: [],
n: 1,
batchFile: null,
jobs: null,
json: false,
help: false,
...overrides,
};
}
async function makeTempDir(prefix: string): Promise<string> {
return fs.mkdtemp(path.join(os.tmpdir(), prefix));
}
test("Azure endpoint parsing and default deployment selection follow env precedence", (t) => {
assert.deepEqual(parseAzureBaseURL("https://example.openai.azure.com"), {
resourceBaseURL: "https://example.openai.azure.com/openai",
deployment: null,
});
assert.deepEqual(
parseAzureBaseURL("https://example.openai.azure.com/openai/deployments/from-url"),
{
resourceBaseURL: "https://example.openai.azure.com/openai",
deployment: "from-url",
},
);
useEnv(t, {
AZURE_OPENAI_BASE_URL: "https://example.openai.azure.com/openai/deployments/from-url",
AZURE_OPENAI_DEPLOYMENT: "explicit-deploy",
AZURE_OPENAI_IMAGE_MODEL: "env-fallback",
});
assert.equal(getDefaultModel(), "explicit-deploy");
});
test("Azure validateArgs rejects unsupported edit input formats before the API call", () => {
assert.doesNotThrow(() =>
validateArgs("demo-deployment", makeArgs({ referenceImages: ["hero.png", "photo.jpeg"] })),
);
assert.throws(
() => validateArgs("demo-deployment", makeArgs({ referenceImages: ["hero.webp"] })),
/PNG or JPG\/JPEG/,
);
});
test("Azure image generation routes model to deployment and sends mapped quality", async (t) => {
useEnv(t, {
AZURE_OPENAI_API_KEY: "azure-key",
AZURE_OPENAI_BASE_URL: "https://example.openai.azure.com/openai/deployments/default-deploy",
AZURE_API_VERSION: null,
AZURE_OPENAI_DEPLOYMENT: null,
AZURE_OPENAI_IMAGE_MODEL: null,
});
const originalFetch = globalThis.fetch;
t.after(() => {
globalThis.fetch = originalFetch;
});
const calls: Array<{ url: string; body: string }> = [];
globalThis.fetch = async (input, init) => {
calls.push({
url: String(input),
body: String(init?.body ?? ""),
});
return Response.json({
data: [{ b64_json: Buffer.from("azure-image").toString("base64") }],
});
};
const bytes = await generateImage(
"A calm lake at sunset",
"custom-deploy",
makeArgs({ quality: "normal" }),
);
assert.equal(Buffer.from(bytes).toString("utf8"), "azure-image");
assert.equal(
calls[0]?.url,
"https://example.openai.azure.com/openai/deployments/custom-deploy/images/generations?api-version=2025-04-01-preview",
);
const body = JSON.parse(calls[0]!.body) as Record<string, string>;
assert.equal(body.quality, "medium");
assert.equal(body.size, "1024x1024");
});
test("Azure image edits include quality in multipart requests", async (t) => {
const root = await makeTempDir("baoyu-image-gen-azure-");
t.after(() => fs.rm(root, { recursive: true, force: true }));
const pngPath = path.join(root, "ref.png");
const jpgPath = path.join(root, "ref.jpg");
await fs.writeFile(pngPath, "png-bytes");
await fs.writeFile(jpgPath, "jpg-bytes");
useEnv(t, {
AZURE_OPENAI_API_KEY: "azure-key",
AZURE_OPENAI_BASE_URL: "https://example.openai.azure.com",
AZURE_API_VERSION: "2025-04-01-preview",
AZURE_OPENAI_DEPLOYMENT: null,
AZURE_OPENAI_IMAGE_MODEL: null,
});
const originalFetch = globalThis.fetch;
t.after(() => {
globalThis.fetch = originalFetch;
});
const calls: Array<{ url: string; form: FormData }> = [];
globalThis.fetch = async (input, init) => {
calls.push({
url: String(input),
form: init?.body as FormData,
});
return Response.json({
data: [{ b64_json: Buffer.from("edited-image").toString("base64") }],
});
};
const bytes = await generateImage(
"Add warm lighting",
"edit-deploy",
makeArgs({
quality: "2k",
referenceImages: [pngPath, jpgPath],
}),
);
assert.equal(Buffer.from(bytes).toString("utf8"), "edited-image");
assert.equal(
calls[0]?.url,
"https://example.openai.azure.com/openai/deployments/edit-deploy/images/edits?api-version=2025-04-01-preview",
);
assert.equal(calls[0]?.form.get("quality"), "high");
assert.equal(calls[0]?.form.get("size"), "1024x1024");
assert.equal(calls[0]?.form.getAll("image[]").length, 2);
});
@@ -0,0 +1,192 @@
import path from "node:path";
import { readFile } from "node:fs/promises";
import type { CliArgs } from "../types";
import { getOpenAISize, extractImageFromResponse } from "./openai.ts";
type OpenAIImageResponse = { data: Array<{ url?: string; b64_json?: string }> };
type AzureEndpoint = {
resourceBaseURL: string;
deployment: string | null;
};
const DEFAULT_AZURE_API_VERSION = "2025-04-01-preview";
const AZURE_EDIT_IMAGE_EXTENSIONS = new Set([".png", ".jpg", ".jpeg"]);
export function parseAzureBaseURL(url: string): AzureEndpoint {
const parsed = new URL(url);
const trimmedPath = parsed.pathname.replace(/\/+$/, "");
const deploymentMatch = trimmedPath.match(/^(.*?)(?:\/openai)?\/deployments\/([^/]+)$/);
if (deploymentMatch) {
parsed.pathname = `${deploymentMatch[1] || ""}/openai`;
return {
resourceBaseURL: parsed.toString().replace(/\/+$/, ""),
deployment: decodeURIComponent(deploymentMatch[2]!),
};
}
parsed.pathname = trimmedPath.endsWith("/openai") ? trimmedPath : `${trimmedPath}/openai`;
return {
resourceBaseURL: parsed.toString().replace(/\/+$/, ""),
deployment: null,
};
}
export function getDefaultModel(): string {
const explicitDeployment = process.env.AZURE_OPENAI_DEPLOYMENT?.trim();
if (explicitDeployment) return explicitDeployment;
const baseURL = process.env.AZURE_OPENAI_BASE_URL;
if (baseURL) {
try {
const { deployment } = parseAzureBaseURL(baseURL);
if (deployment) return deployment;
} catch {
// Ignore invalid URLs here so the required-env check can raise the user-facing error later.
}
}
return process.env.AZURE_OPENAI_IMAGE_MODEL || "gpt-image-1.5";
}
function getEndpoint(): AzureEndpoint {
const url = process.env.AZURE_OPENAI_BASE_URL;
if (!url) {
throw new Error(
"AZURE_OPENAI_BASE_URL is required. Set it to your Azure resource or deployment endpoint, e.g.: https://your-resource.openai.azure.com or https://your-resource.openai.azure.com/openai/deployments/your-deployment"
);
}
return parseAzureBaseURL(url);
}
function getApiKey(): string {
const key = process.env.AZURE_OPENAI_API_KEY;
if (!key) {
throw new Error(
"AZURE_OPENAI_API_KEY is required. Get it from Azure Portal → your OpenAI resource → Keys and Endpoint."
);
}
return key;
}
function getApiVersion(): string {
return process.env.AZURE_API_VERSION || DEFAULT_AZURE_API_VERSION;
}
function getDeployment(model: string): string {
const deployment = model.trim();
if (!deployment) {
throw new Error(
"Azure deployment name is required. Use --model <deployment>, AZURE_OPENAI_DEPLOYMENT, AZURE_OPENAI_IMAGE_MODEL, or embed the deployment in AZURE_OPENAI_BASE_URL."
);
}
return deployment;
}
function buildURL(deployment: string, pathSuffix: string): string {
const { resourceBaseURL } = getEndpoint();
return `${resourceBaseURL}/deployments/${encodeURIComponent(deployment)}${pathSuffix}?api-version=${getApiVersion()}`;
}
function authHeaders(): Record<string, string> {
return { "api-key": getApiKey() };
}
function getAzureQuality(quality: CliArgs["quality"]): "medium" | "high" {
return quality === "2k" ? "high" : "medium";
}
export function validateArgs(_model: string, args: CliArgs): void {
for (const refPath of args.referenceImages) {
const ext = path.extname(refPath).toLowerCase();
if (!AZURE_EDIT_IMAGE_EXTENSIONS.has(ext)) {
throw new Error(
`Azure OpenAI reference images must be PNG or JPG/JPEG. Unsupported file: ${refPath}`
);
}
}
}
export async function generateImage(
prompt: string,
model: string,
args: CliArgs
): Promise<Uint8Array> {
const deployment = getDeployment(model);
const size = args.size || getOpenAISize(model, args.aspectRatio, args.quality);
if (args.referenceImages.length > 0) {
return generateWithAzureEdits(prompt, deployment, size, args.referenceImages, args.quality);
}
return generateWithAzureGenerations(prompt, deployment, size, args.quality);
}
async function generateWithAzureGenerations(
prompt: string,
deployment: string,
size: string,
quality: CliArgs["quality"]
): Promise<Uint8Array> {
const body: Record<string, any> = {
prompt,
size,
n: 1,
quality: getAzureQuality(quality),
};
const res = await fetch(buildURL(deployment, "/images/generations"), {
method: "POST",
headers: {
"Content-Type": "application/json",
...authHeaders(),
},
body: JSON.stringify(body),
});
if (!res.ok) {
const err = await res.text();
throw new Error(`Azure OpenAI API error: ${err}`);
}
const result = (await res.json()) as OpenAIImageResponse;
return extractImageFromResponse(result);
}
async function generateWithAzureEdits(
prompt: string,
deployment: string,
size: string,
referenceImages: string[],
quality: CliArgs["quality"]
): Promise<Uint8Array> {
const form = new FormData();
form.append("prompt", prompt);
form.append("size", size);
form.append("n", "1");
form.append("quality", getAzureQuality(quality));
for (const refPath of referenceImages) {
const bytes = await readFile(refPath);
const filename = path.basename(refPath);
const mimeType = path.extname(filename).toLowerCase() === ".png" ? "image/png" : "image/jpeg";
const blob = new Blob([bytes], { type: mimeType });
form.append("image[]", blob, filename);
}
const res = await fetch(buildURL(deployment, "/images/edits"), {
method: "POST",
headers: {
...authHeaders(),
},
body: form,
});
if (!res.ok) {
const err = await res.text();
throw new Error(`Azure OpenAI edits API error: ${err}`);
}
const result = (await res.json()) as OpenAIImageResponse;
return extractImageFromResponse(result);
}
@@ -0,0 +1,114 @@
import assert from "node:assert/strict";
import test, { type TestContext } from "node:test";
import type { CliArgs } from "../types.ts";
import { generateImage } from "./jimeng.ts";
function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
return {
prompt: null,
promptFiles: [],
imagePath: null,
provider: null,
model: null,
aspectRatio: null,
size: null,
quality: null,
imageSize: null,
referenceImages: [],
n: 1,
batchFile: null,
jobs: null,
json: false,
help: false,
...overrides,
};
}
function useEnv(
t: TestContext,
values: Record<string, string | null>,
): void {
const previous = new Map<string, string | undefined>();
for (const [key, value] of Object.entries(values)) {
previous.set(key, process.env[key]);
if (value == null) {
delete process.env[key];
} else {
process.env[key] = value;
}
}
t.after(() => {
for (const [key, value] of previous.entries()) {
if (value == null) {
delete process.env[key];
} else {
process.env[key] = value;
}
}
});
}
test("Jimeng submit request uses prompt field expected by current API", async (t) => {
useEnv(t, {
JIMENG_ACCESS_KEY_ID: "test-access-key",
JIMENG_SECRET_ACCESS_KEY: "test-secret-key",
JIMENG_BASE_URL: null,
JIMENG_REGION: null,
});
const originalFetch = globalThis.fetch;
t.after(() => {
globalThis.fetch = originalFetch;
});
const calls: Array<{
input: string;
init?: RequestInit;
}> = [];
globalThis.fetch = async (input, init) => {
calls.push({
input: String(input),
init,
});
if (calls.length === 1) {
return Response.json({
code: 10000,
data: {
task_id: "task-123",
},
});
}
return Response.json({
code: 10000,
data: {
status: "done",
binary_data_base64: [Buffer.from("jimeng-image").toString("base64")],
},
});
};
const image = await generateImage(
"A quiet bamboo forest",
"jimeng_t2i_v40",
makeArgs({ quality: "normal" }),
);
assert.equal(Buffer.from(image).toString("utf8"), "jimeng-image");
assert.equal(calls.length, 2);
assert.equal(
calls[0]?.input,
"https://visual.volcengineapi.com/?Action=CVSync2AsyncSubmitTask&Version=2022-08-31",
);
const submitBody = JSON.parse(String(calls[0]?.init?.body)) as Record<string, unknown>;
assert.equal(submitBody.req_key, "jimeng_t2i_v40");
assert.equal(submitBody.prompt, "A quiet bamboo forest");
assert.ok(!("prompt_text" in submitBody));
assert.equal(submitBody.width, 1024);
assert.equal(submitBody.height, 1024);
});
@@ -246,7 +246,7 @@ async function submitTask(
const [width, height] = size.split("x").map(Number);
const bodyObj = {
req_key: model,
prompt_text: prompt,
prompt,
// Use separate width and height parameters instead of size string
width: width,
height: height,
+2 -1
View File
@@ -1,4 +1,4 @@
export type Provider = "google" | "openai" | "openrouter" | "dashscope" | "replicate" | "jimeng" | "seedream";
export type Provider = "google" | "openai" | "openrouter" | "dashscope" | "replicate" | "jimeng" | "seedream" | "azure";
export type Quality = "normal" | "2k";
export type CliArgs = {
@@ -55,6 +55,7 @@ export type ExtendConfig = {
replicate: string | null;
jimeng: string | null;
seedream: string | null;
azure: string | null;
};
batch?: {
max_workers?: number | null;