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Author SHA1 Message Date
Jim Liu 宝玉 4d465d55d0 chore: release v1.102.0 2026-04-12 02:15:47 -05:00
Jim Liu 宝玉 11d80eeaa9 feat(baoyu-imagine): add OpenAI-compatible image API dialect support
Add --imageApiDialect flag, OPENAI_IMAGE_API_DIALECT env var, and
default_image_api_dialect config for gateways that expect aspect-ratio
size plus metadata.resolution instead of pixel size.
2026-04-12 02:14:18 -05:00
Jim Liu 宝玉 58ba4579ef chore: release v1.101.0 2026-04-12 01:20:43 -05:00
Jim Liu 宝玉 67a45a57a0 Improve baoyu-imagine Replicate compatibility (#125)
* Align Replicate image behavior with the models we actually support

Replicate image generation in baoyu-imagine no longer assumes that every model
accepts the nano-banana request schema. The Replicate provider now defaults to
google/nano-banana-2, routes supported model families through family-specific
builders and validators, blocks misleading multi-output requests before they
reach the API, and updates user-facing docs/config guidance to match the actual
contract.

Constraint: Replicate model families expose different input schemas
Constraint: Current Replicate path only saves one output image per request
Constraint: Must not change non-Replicate providers
Rejected: Keep one nano-banana-style payload for all Replicate models | triggers remote schema errors on Seedream and Wan
Rejected: Continue accepting multi-image Replicate requests and save only the first result | silently drops outputs
Confidence: high
Scope-risk: narrow
Reversibility: clean
Directive: Add a family-specific validator and input builder before exposing more Replicate model IDs or multi-output flags
Tested: npm test
Tested: node --test skills/baoyu-imagine/scripts/providers/replicate.test.ts skills/baoyu-imagine/scripts/main.test.ts
Not-tested: Live Replicate API calls against production models
Co-authored-by: justnode <justnode@users.noreply.github.com>

* Preserve Replicate compatibility when shared defaults leak across providers

Addressed the new PR review findings by teaching baoyu-imagine to track
where aspect-ratio defaults came from, mirroring the earlier imageSize fix,
so unsupported Replicate models can still run prompt-only requests when the
value was inherited from shared config. Also corrected Seedream 4.5 custom
size encoding to use the API's custom width/height schema instead of sending
literal WxH strings.

Constraint: Shared EXTEND defaults still need to apply globally for providers that support them
Constraint: Seedream 4.5 custom sizes must follow Replicate's documented custom size schema
Rejected: Ignore all aspect ratios for unknown Replicate models | would hide explicit unsupported CLI/task input
Rejected: Keep Seedream custom sizes as literal strings | validated locally but fails against the provider API
Confidence: high
Scope-risk: narrow
Reversibility: clean
Directive: Any future inherited-default validation for provider-specific flags should record the source explicitly before rejecting it
Tested: node --import tsx --test skills/baoyu-imagine/scripts/main.test.ts skills/baoyu-imagine/scripts/providers/replicate.test.ts
Tested: npm test
Not-tested: Live Replicate API calls for Seedream 4.5 custom-size requests

---------

Co-authored-by: justnode <justnode@users.noreply.github.com>
2026-04-12 01:16:32 -05:00
Jim Liu 宝玉 0b8ac256f4 chore: release v1.100.0 2026-04-12 00:30:55 -05:00
Jim Liu 宝玉 eaa0f1aa11 feat(baoyu-imagine): add Z.AI GLM-Image provider
Adds the Z.AI (智谱) provider supporting glm-image and cogview-4-250304
models via the Z.AI sync image API. Configure with ZAI_API_KEY (or
BIGMODEL_API_KEY for backward compat). Reference images are not supported yet.
2026-04-12 00:30:49 -05:00
23 changed files with 1784 additions and 97 deletions
+1 -1
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@@ -6,7 +6,7 @@
},
"metadata": {
"description": "Skills shared by Baoyu for improving daily work efficiency",
"version": "1.99.1"
"version": "1.102.0"
},
"plugins": [
{
+15
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@@ -2,6 +2,21 @@
English | [中文](./CHANGELOG.zh.md)
## 1.102.0 - 2026-04-12
### Features
- `baoyu-imagine`: add OpenAI-compatible image API dialect — new `--imageApiDialect` flag, `OPENAI_IMAGE_API_DIALECT` env var, and `default_image_api_dialect` config for gateways that expect aspect-ratio `size` plus `metadata.resolution` instead of pixel `size`
## 1.101.0 - 2026-04-12
### Features
- `baoyu-imagine`: improve Replicate provider compatibility — route models through family-specific input builders and validators (nano-banana, Seedream 4.5, Seedream 5 Lite, Wan 2.7 Image); update default model to `google/nano-banana-2`; fix Seedream 4.5 custom size encoding to use width/height schema; fix aspect-ratio default inheritance for unsupported Replicate models; block multi-output requests before they reach the API (by @justnode)
## 1.100.0 - 2026-04-12
### Features
- `baoyu-imagine`: add Z.AI GLM-Image provider — supports `glm-image` and `cogview-4-250304` models via the Z.AI sync image API; configure with `ZAI_API_KEY` (or `BIGMODEL_API_KEY` for backward compatibility)
## 1.99.1 - 2026-04-11
### Fixes
+15
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@@ -2,6 +2,21 @@
[English](./CHANGELOG.md) | 中文
## 1.102.0 - 2026-04-12
### 新功能
- `baoyu-imagine`:新增 OpenAI 兼容图像 API 方言支持 —— 新增 `--imageApiDialect` 参数、`OPENAI_IMAGE_API_DIALECT` 环境变量及 `default_image_api_dialect` 配置项,用于对接期望宽高比格式 `size``metadata.resolution` 的兼容网关
## 1.101.0 - 2026-04-12
### 新功能
- `baoyu-imagine`:改进 Replicate 服务商兼容性 —— 针对不同模型系列(nano-banana、Seedream 4.5、Seedream 5 Lite、Wan 2.7 Image)实现专属输入构建器和验证器;将默认模型更新为 `google/nano-banana-2`;修复 Seedream 4.5 自定义尺寸编码(改用 width/height schema);修复不支持的 Replicate 模型的宽高比默认值继承问题;在请求到达 API 前拦截多图请求 (by @justnode)
## 1.100.0 - 2026-04-12
### 新功能
- `baoyu-imagine`:新增 Z.AI GLM-Image 服务商支持,支持 `glm-image``cogview-4-250304` 模型,通过 Z.AI 同步图像 API 调用;配置 `ZAI_API_KEY`(或 `BIGMODEL_API_KEY` 向后兼容)
## 1.99.1 - 2026-04-11
### 修复
+34 -8
View File
@@ -745,15 +745,24 @@ AI SDK-based image generation using OpenAI, Azure OpenAI, Google, OpenRouter, Da
# DashScope with custom size
/baoyu-imagine --prompt "为咖啡品牌设计一张 21:9 横幅海报,包含清晰中文标题" --image banner.png --provider dashscope --model qwen-image-2.0-pro --size 2048x872
# Z.AI GLM-Image
/baoyu-imagine --prompt "一张带清晰中文标题的科技海报" --image out.png --provider zai
# MiniMax
/baoyu-imagine --prompt "A fashion editorial portrait by a bright studio window" --image out.jpg --provider minimax
# MiniMax with subject reference
/baoyu-imagine --prompt "A girl stands by the library window, cinematic lighting" --image out.jpg --provider minimax --model image-01 --ref portrait.png --ar 16:9
# Replicate
# Replicate (default: google/nano-banana-2)
/baoyu-imagine --prompt "A cat" --image cat.png --provider replicate
# Replicate Seedream 4.5
/baoyu-imagine --prompt "A studio portrait" --image portrait.png --provider replicate --model bytedance/seedream-4.5 --ar 3:2
# Replicate Wan 2.7 Image Pro
/baoyu-imagine --prompt "A concept frame" --image frame.png --provider replicate --model wan-video/wan-2.7-image-pro --size 2048x1152
# Jimeng (即梦)
/baoyu-imagine --prompt "一只可爱的猫" --image cat.png --provider jimeng
@@ -775,14 +784,15 @@ AI SDK-based image generation using OpenAI, Azure OpenAI, Google, OpenRouter, Da
| `--image` | Output image path (required) |
| `--batchfile` | JSON batch file for multi-image generation |
| `--jobs` | Worker count for batch mode |
| `--provider` | `google`, `openai`, `azure`, `openrouter`, `dashscope`, `minimax`, `jimeng`, `seedream`, or `replicate` |
| `--model`, `-m` | Model ID or deployment name. Azure uses deployment name; OpenRouter uses full model IDs; MiniMax uses `image-01` / `image-01-live` |
| `--provider` | `google`, `openai`, `azure`, `openrouter`, `dashscope`, `zai`, `minimax`, `jimeng`, `seedream`, or `replicate` |
| `--model`, `-m` | Model ID or deployment name. Azure uses deployment name; OpenRouter uses full model IDs; Z.AI uses `glm-image`; MiniMax uses `image-01` / `image-01-live` |
| `--ar` | Aspect ratio (e.g., `16:9`, `1:1`, `4:3`) |
| `--size` | Size (e.g., `1024x1024`) |
| `--quality` | `normal` or `2k` (default: `2k`) |
| `--imageSize` | `1K`, `2K`, or `4K` for Google/OpenRouter |
| `--ref` | Reference images (Google, OpenAI, Azure OpenAI, OpenRouter, Replicate, MiniMax, or Seedream 5.0/4.5/4.0) |
| `--n` | Number of images per request |
| `--imageApiDialect` | `openai-native` or `ratio-metadata` for OpenAI-compatible gateways |
| `--ref` | Reference images (Google, OpenAI, Azure OpenAI, OpenRouter, Replicate supported families, MiniMax, or Seedream 5.0/4.5/4.0) |
| `--n` | Number of images per request (`replicate` currently requires `--n 1`) |
| `--json` | JSON output |
**Environment Variables** (see [Environment Configuration](#environment-configuration) for setup):
@@ -794,6 +804,8 @@ AI SDK-based image generation using OpenAI, Azure OpenAI, Google, OpenRouter, Da
| `GOOGLE_API_KEY` | Google API key | - |
| `GEMINI_API_KEY` | Alias for `GOOGLE_API_KEY` | - |
| `DASHSCOPE_API_KEY` | DashScope API key (Aliyun) | - |
| `ZAI_API_KEY` | Z.AI API key | - |
| `BIGMODEL_API_KEY` | Backward-compatible alias for Z.AI API key | - |
| `MINIMAX_API_KEY` | MiniMax API key | - |
| `REPLICATE_API_TOKEN` | Replicate API token | - |
| `JIMENG_ACCESS_KEY_ID` | Jimeng Volcengine access key | - |
@@ -805,11 +817,14 @@ AI SDK-based image generation using OpenAI, Azure OpenAI, Google, OpenRouter, Da
| `OPENROUTER_IMAGE_MODEL` | OpenRouter model | `google/gemini-3.1-flash-image-preview` |
| `GOOGLE_IMAGE_MODEL` | Google model | `gemini-3-pro-image-preview` |
| `DASHSCOPE_IMAGE_MODEL` | DashScope model | `qwen-image-2.0-pro` |
| `ZAI_IMAGE_MODEL` | Z.AI model | `glm-image` |
| `BIGMODEL_IMAGE_MODEL` | Backward-compatible alias for Z.AI model | `glm-image` |
| `MINIMAX_IMAGE_MODEL` | MiniMax model | `image-01` |
| `REPLICATE_IMAGE_MODEL` | Replicate model | `google/nano-banana-pro` |
| `REPLICATE_IMAGE_MODEL` | Replicate model | `google/nano-banana-2` |
| `JIMENG_IMAGE_MODEL` | Jimeng model | `jimeng_t2i_v40` |
| `SEEDREAM_IMAGE_MODEL` | Seedream model | `doubao-seedream-5-0-260128` |
| `OPENAI_BASE_URL` | Custom OpenAI endpoint | - |
| `OPENAI_IMAGE_API_DIALECT` | OpenAI-compatible image API dialect (`openai-native` or `ratio-metadata`) | `openai-native` |
| `OPENAI_IMAGE_USE_CHAT` | Use `/chat/completions` for OpenAI image generation | `false` |
| `AZURE_OPENAI_BASE_URL` | Azure resource or deployment endpoint | - |
| `AZURE_API_VERSION` | Azure image API version | `2025-04-01-preview` |
@@ -818,6 +833,8 @@ AI SDK-based image generation using OpenAI, Azure OpenAI, Google, OpenRouter, Da
| `OPENROUTER_TITLE` | Optional app name for OpenRouter attribution | - |
| `GOOGLE_BASE_URL` | Custom Google endpoint | - |
| `DASHSCOPE_BASE_URL` | Custom DashScope endpoint | - |
| `ZAI_BASE_URL` | Custom Z.AI endpoint | `https://api.z.ai/api/paas/v4` |
| `BIGMODEL_BASE_URL` | Backward-compatible alias for Z.AI endpoint | - |
| `MINIMAX_BASE_URL` | Custom MiniMax endpoint | `https://api.minimax.io` |
| `REPLICATE_BASE_URL` | Custom Replicate endpoint | - |
| `JIMENG_BASE_URL` | Custom Jimeng endpoint | `https://visual.volcengineapi.com` |
@@ -830,16 +847,20 @@ AI SDK-based image generation using OpenAI, Azure OpenAI, Google, OpenRouter, Da
**Provider Notes**:
- Azure OpenAI: `--model` means Azure deployment name, not the underlying model family.
- DashScope: `qwen-image-2.0-pro` is the recommended default for custom `--size`, `21:9`, and strong Chinese/English text rendering.
- Z.AI: `glm-image` is recommended for posters, diagrams, and text-heavy Chinese/English images. Reference images are not supported.
- MiniMax: `image-01` supports documented custom `width` / `height`; `image-01-live` is lower latency and works best with `--ar`.
- MiniMax reference images are sent as `subject_reference`; the current API is specialized toward character / portrait consistency.
- Jimeng does not support reference images.
- Seedream reference images are supported by Seedream 5.0 / 4.5 / 4.0, not Seedream 3.0.
- Replicate defaults to `google/nano-banana-2`. `baoyu-imagine` only enables Replicate advanced options for `google/nano-banana*`, `bytedance/seedream-4.5`, `bytedance/seedream-5-lite`, `wan-video/wan-2.7-image`, and `wan-video/wan-2.7-image-pro`.
- Replicate currently saves exactly one output image per request. `--n > 1` is blocked locally instead of silently dropping extra results.
- Replicate model behavior is family-specific: nano-banana uses `--quality` / `--ar`, Seedream uses validated `--size` / `--ar`, and Wan uses validated `--size` (with `--ar` converted locally to a concrete size).
**Provider Auto-Selection**:
1. If `--provider` is specified → use it
2. If `--ref` is provided and no provider is specified → try Google, then OpenAI, Azure, OpenRouter, Replicate, Seedream, and finally MiniMax
3. If only one API key is available → use that provider
4. If multiple providers are available → default to Google
4. If multiple providers are available → default to Google, then OpenAI, Azure, OpenRouter, DashScope, Z.AI, MiniMax, Replicate, Jimeng, Seedream
#### baoyu-danger-gemini-web
@@ -1139,6 +1160,11 @@ DASHSCOPE_API_KEY=sk-xxx
DASHSCOPE_IMAGE_MODEL=qwen-image-2.0-pro
# DASHSCOPE_BASE_URL=https://dashscope.aliyuncs.com/api/v1
# Z.AI
ZAI_API_KEY=xxx
ZAI_IMAGE_MODEL=glm-image
# ZAI_BASE_URL=https://api.z.ai/api/paas/v4
# MiniMax
MINIMAX_API_KEY=xxx
MINIMAX_IMAGE_MODEL=image-01
@@ -1146,7 +1172,7 @@ MINIMAX_IMAGE_MODEL=image-01
# Replicate
REPLICATE_API_TOKEN=r8_xxx
REPLICATE_IMAGE_MODEL=google/nano-banana-pro
REPLICATE_IMAGE_MODEL=google/nano-banana-2
# REPLICATE_BASE_URL=https://api.replicate.com
# Jimeng (即梦)
+34 -8
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@@ -745,15 +745,24 @@ AI 驱动的生成后端。
# DashScope 自定义尺寸
/baoyu-imagine --prompt "为咖啡品牌设计一张 21:9 横幅海报,包含清晰中文标题" --image banner.png --provider dashscope --model qwen-image-2.0-pro --size 2048x872
# Z.AI GLM-Image
/baoyu-imagine --prompt "一张带清晰中文标题的科技海报" --image out.png --provider zai
# MiniMax
/baoyu-imagine --prompt "A fashion editorial portrait by a bright studio window" --image out.jpg --provider minimax
# MiniMax + 角色参考图
/baoyu-imagine --prompt "A girl stands by the library window, cinematic lighting" --image out.jpg --provider minimax --model image-01 --ref portrait.png --ar 16:9
# Replicate
# Replicate(默认:google/nano-banana-2
/baoyu-imagine --prompt "一只猫" --image cat.png --provider replicate
# Replicate Seedream 4.5
/baoyu-imagine --prompt "一张影棚人像" --image portrait.png --provider replicate --model bytedance/seedream-4.5 --ar 3:2
# Replicate Wan 2.7 Image Pro
/baoyu-imagine --prompt "一张概念分镜" --image frame.png --provider replicate --model wan-video/wan-2.7-image-pro --size 2048x1152
# 即梦(Jimeng
/baoyu-imagine --prompt "一只可爱的猫" --image cat.png --provider jimeng
@@ -775,14 +784,15 @@ AI 驱动的生成后端。
| `--image` | 输出图片路径(必需) |
| `--batchfile` | 多图批量生成的 JSON 文件 |
| `--jobs` | 批量模式的并发 worker 数 |
| `--provider` | `google``openai``azure``openrouter``dashscope``minimax``jimeng``seedream``replicate` |
| `--model`, `-m` | 模型 ID 或部署名。Azure 使用部署名;OpenRouter 使用完整模型 IDMiniMax 使用 `image-01` / `image-01-live` |
| `--provider` | `google``openai``azure``openrouter``dashscope``zai``minimax``jimeng``seedream``replicate` |
| `--model`, `-m` | 模型 ID 或部署名。Azure 使用部署名;OpenRouter 使用完整模型 IDZ.AI 使用 `glm-image`MiniMax 使用 `image-01` / `image-01-live` |
| `--ar` | 宽高比(如 `16:9``1:1``4:3` |
| `--size` | 尺寸(如 `1024x1024` |
| `--quality` | `normal``2k`(默认:`2k` |
| `--imageSize` | Google/OpenRouter 使用的 `1K``2K``4K` |
| `--ref` | 参考图片(Google、OpenAI、Azure OpenAI、OpenRouter、Replicate、MiniMax 或 Seedream 5.0/4.5/4.0 |
| `--n` | 单次请求生成图片数量 |
| `--imageApiDialect` | OpenAI 兼容网关的图像 API 方言(`openai-native``ratio-metadata` |
| `--ref` | 参考图片(Google、OpenAI、Azure OpenAI、OpenRouter、Replicate 支持的模型家族、MiniMax 或 Seedream 5.0/4.5/4.0 |
| `--n` | 单次请求生成图片数量(`replicate` 当前只支持 `--n 1` |
| `--json` | 输出 JSON 结果 |
**环境变量**(配置方法见[环境配置](#环境配置)):
@@ -794,6 +804,8 @@ AI 驱动的生成后端。
| `GOOGLE_API_KEY` | Google API 密钥 | - |
| `GEMINI_API_KEY` | `GOOGLE_API_KEY` 的别名 | - |
| `DASHSCOPE_API_KEY` | DashScope API 密钥(阿里云) | - |
| `ZAI_API_KEY` | Z.AI API 密钥 | - |
| `BIGMODEL_API_KEY` | Z.AI API 密钥向后兼容别名 | - |
| `MINIMAX_API_KEY` | MiniMax API 密钥 | - |
| `REPLICATE_API_TOKEN` | Replicate API Token | - |
| `JIMENG_ACCESS_KEY_ID` | 即梦火山引擎 Access Key | - |
@@ -805,11 +817,14 @@ AI 驱动的生成后端。
| `OPENROUTER_IMAGE_MODEL` | OpenRouter 模型 | `google/gemini-3.1-flash-image-preview` |
| `GOOGLE_IMAGE_MODEL` | Google 模型 | `gemini-3-pro-image-preview` |
| `DASHSCOPE_IMAGE_MODEL` | DashScope 模型 | `qwen-image-2.0-pro` |
| `ZAI_IMAGE_MODEL` | Z.AI 模型 | `glm-image` |
| `BIGMODEL_IMAGE_MODEL` | Z.AI 模型向后兼容别名 | `glm-image` |
| `MINIMAX_IMAGE_MODEL` | MiniMax 模型 | `image-01` |
| `REPLICATE_IMAGE_MODEL` | Replicate 模型 | `google/nano-banana-pro` |
| `REPLICATE_IMAGE_MODEL` | Replicate 模型 | `google/nano-banana-2` |
| `JIMENG_IMAGE_MODEL` | 即梦模型 | `jimeng_t2i_v40` |
| `SEEDREAM_IMAGE_MODEL` | 豆包模型 | `doubao-seedream-5-0-260128` |
| `OPENAI_BASE_URL` | 自定义 OpenAI 端点 | - |
| `OPENAI_IMAGE_API_DIALECT` | OpenAI 兼容图像 API 方言(`openai-native``ratio-metadata` | `openai-native` |
| `OPENAI_IMAGE_USE_CHAT` | OpenAI 改走 `/chat/completions` | `false` |
| `AZURE_OPENAI_BASE_URL` | Azure 资源或部署端点 | - |
| `AZURE_API_VERSION` | Azure 图像 API 版本 | `2025-04-01-preview` |
@@ -818,6 +833,8 @@ AI 驱动的生成后端。
| `OPENROUTER_TITLE` | OpenRouter 归因用应用名 | - |
| `GOOGLE_BASE_URL` | 自定义 Google 端点 | - |
| `DASHSCOPE_BASE_URL` | 自定义 DashScope 端点 | - |
| `ZAI_BASE_URL` | 自定义 Z.AI 端点 | `https://api.z.ai/api/paas/v4` |
| `BIGMODEL_BASE_URL` | Z.AI 端点向后兼容别名 | - |
| `MINIMAX_BASE_URL` | 自定义 MiniMax 端点 | `https://api.minimax.io` |
| `REPLICATE_BASE_URL` | 自定义 Replicate 端点 | - |
| `JIMENG_BASE_URL` | 自定义即梦端点 | `https://visual.volcengineapi.com` |
@@ -830,16 +847,20 @@ AI 驱动的生成后端。
**Provider 说明**
- Azure OpenAI`--model` 表示 Azure deployment name,不是底层模型家族名。
- DashScope`qwen-image-2.0-pro` 是自定义 `--size``21:9` 和中英文排版的推荐默认模型。
- Z.AI`glm-image` 适合海报、图表和中英文排版密集的图片生成,暂不支持参考图。
- MiniMax`image-01` 支持官方文档里的自定义 `width` / `height``image-01-live` 更偏低延迟,适合配合 `--ar` 使用。
- MiniMax 参考图会走 `subject_reference`,当前能力更偏角色 / 人像一致性。
- 即梦不支持参考图。
- 豆包参考图能力仅适用于 Seedream 5.0 / 4.5 / 4.0,不适用于 Seedream 3.0。
- Replicate 默认模型改为 `google/nano-banana-2``baoyu-imagine` 目前只对 `google/nano-banana*``bytedance/seedream-4.5``bytedance/seedream-5-lite``wan-video/wan-2.7-image``wan-video/wan-2.7-image-pro` 开启本地能力识别与校验。
- Replicate 当前只保存单张输出图,`--n > 1` 会在本地直接报错,避免多图结果被静默丢弃。
- Replicate 的参数能力按模型家族区分:nano-banana 走 `--quality` / `--ar`Seedream 走校验后的 `--size` / `--ar`Wan 走校验后的 `--size``--ar` 会先在本地换算成具体尺寸)。
**服务商自动选择**
1. 如果指定了 `--provider` → 使用指定的
2. 如果传了 `--ref` 且未指定 provider → 依次尝试 Google、OpenAI、Azure、OpenRouter、Replicate、Seedream,最后是 MiniMax
3. 如果只有一个 API 密钥 → 使用对应服务商
4. 如果多个可用 → 默认使用 Google
4. 如果多个可用 → 默认使用 Google,然后依次为 OpenAI、Azure、OpenRouter、DashScope、Z.AI、MiniMax、Replicate、即梦、豆包
#### baoyu-danger-gemini-web
@@ -1139,6 +1160,11 @@ DASHSCOPE_API_KEY=sk-xxx
DASHSCOPE_IMAGE_MODEL=qwen-image-2.0-pro
# DASHSCOPE_BASE_URL=https://dashscope.aliyuncs.com/api/v1
# Z.AI
ZAI_API_KEY=xxx
ZAI_IMAGE_MODEL=glm-image
# ZAI_BASE_URL=https://api.z.ai/api/paas/v4
# MiniMax
MINIMAX_API_KEY=xxx
MINIMAX_IMAGE_MODEL=image-01
@@ -1146,7 +1172,7 @@ MINIMAX_IMAGE_MODEL=image-01
# Replicate
REPLICATE_API_TOKEN=r8_xxx
REPLICATE_IMAGE_MODEL=google/nano-banana-pro
REPLICATE_IMAGE_MODEL=google/nano-banana-2
# REPLICATE_BASE_URL=https://api.replicate.com
# 即梦(Jimeng
+101 -19
View File
@@ -1,7 +1,7 @@
---
name: baoyu-imagine
description: AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, 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: 1.56.4
description: AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, 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: 1.57.0
metadata:
openclaw:
homepage: https://github.com/JimLiu/baoyu-skills#baoyu-imagine
@@ -13,7 +13,7 @@ metadata:
# Image Generation (AI SDK)
Official API-based image generation. Supports OpenAI, Azure OpenAI, Google, OpenRouter, DashScope (阿里通义万象), MiniMax, 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), Z.AI GLM-Image, MiniMax, Jimeng (即梦), Seedream (豆包) and Replicate providers.
## Script Directory
@@ -57,7 +57,7 @@ if (Test-Path "$HOME/.baoyu-skills/baoyu-imagine/EXTEND.md") { "user" }
Legacy compatibility: if `.baoyu-skills/baoyu-image-gen/EXTEND.md` exists and the new path does not, runtime renames it to `baoyu-imagine`. If both files exist, runtime leaves them unchanged and uses the new path.
**EXTEND.md Supports**: Default provider | Default quality | Default aspect ratio | Default image size | Default models | Batch worker cap | Provider-specific batch limits
**EXTEND.md Supports**: Default provider | Default quality | Default aspect ratio | Default image size | OpenAI image API dialect | Default models | Batch worker cap | Provider-specific batch limits
Schema: `references/config/preferences-schema.md`
@@ -76,7 +76,7 @@ ${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, Azure OpenAI, OpenRouter, Replicate, MiniMax, or Seedream 4.0/4.5/5.0)
# With reference images (Google, OpenAI, Azure OpenAI, OpenRouter, Replicate supported families, MiniMax, 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)
@@ -103,6 +103,12 @@ ${BUN_X} {baseDir}/scripts/main.ts --prompt "为咖啡品牌设计一张 21:9
# DashScope legacy Qwen fixed-size model
${BUN_X} {baseDir}/scripts/main.ts --prompt "一张电影感海报" --image out.png --provider dashscope --model qwen-image-max --size 1664x928
# Z.AI GLM-image
${BUN_X} {baseDir}/scripts/main.ts --prompt "一张带清晰中文标题的科技海报" --image out.png --provider zai
# Z.AI GLM-image with explicit custom size
${BUN_X} {baseDir}/scripts/main.ts --prompt "A science illustration with labels" --image out.png --provider zai --model glm-image --size 1472x1088
# MiniMax
${BUN_X} {baseDir}/scripts/main.ts --prompt "A fashion editorial portrait by a bright studio window" --image out.jpg --provider minimax
@@ -112,11 +118,14 @@ ${BUN_X} {baseDir}/scripts/main.ts --prompt "A girl stands by the library window
# MiniMax with custom size (documented for image-01)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cinematic poster" --image out.jpg --provider minimax --model image-01 --size 1536x1024
# Replicate (google/nano-banana-pro)
# Replicate (default: google/nano-banana-2)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate
# Replicate with specific model
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate --model google/nano-banana
# Replicate Seedream 4.5
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cinematic portrait" --image out.png --provider replicate --model bytedance/seedream-4.5 --ar 3:2
# Replicate Wan 2.7 Image Pro
${BUN_X} {baseDir}/scripts/main.ts --prompt "A concept frame" --image out.png --provider replicate --model wan-video/wan-2.7-image-pro --size 2048x1152
# Batch mode with saved prompt files
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json
@@ -136,7 +145,7 @@ ${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4 --json
"promptFiles": ["prompts/hero.md"],
"image": "out/hero.png",
"provider": "replicate",
"model": "google/nano-banana-pro",
"model": "google/nano-banana-2",
"ar": "16:9",
"quality": "2k"
},
@@ -161,14 +170,15 @@ 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\|azure\|openrouter\|dashscope\|minimax\|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`; MiniMax: `image-01`) |
| `--provider google\|openai\|azure\|openrouter\|dashscope\|zai\|minimax\|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`; Z.AI: `glm-image`; MiniMax: `image-01`) |
| `--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, Azure OpenAI edits (PNG/JPG only), OpenRouter multimodal models, Replicate, MiniMax subject-reference, 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 |
| `--imageApiDialect openai-native\|ratio-metadata` | OpenAI-compatible image API dialect. Use `ratio-metadata` when the endpoint is OpenAI-compatible but expects aspect-ratio `size` plus `metadata.resolution` instead of pixel `size` |
| `--ref <files...>` | Reference images. Supported by Google multimodal, OpenAI GPT Image edits, Azure OpenAI edits (PNG/JPG only), OpenRouter multimodal models, Replicate supported families, MiniMax subject-reference, 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. Replicate currently supports only `--n 1` because this path saves exactly one output image |
| `--json` | JSON output |
## Environment Variables
@@ -180,6 +190,8 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
| `OPENROUTER_API_KEY` | OpenRouter API key |
| `GOOGLE_API_KEY` | Google API key |
| `DASHSCOPE_API_KEY` | DashScope API key (阿里云) |
| `ZAI_API_KEY` | Z.AI API key |
| `BIGMODEL_API_KEY` | Backward-compatible alias for Z.AI API key |
| `MINIMAX_API_KEY` | MiniMax API key |
| `REPLICATE_API_TOKEN` | Replicate API token |
| `JIMENG_ACCESS_KEY_ID` | Jimeng (即梦) Volcengine access key |
@@ -191,11 +203,14 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
| `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`) |
| `ZAI_IMAGE_MODEL` | Z.AI model override (default: `glm-image`) |
| `BIGMODEL_IMAGE_MODEL` | Backward-compatible alias for Z.AI model override |
| `MINIMAX_IMAGE_MODEL` | MiniMax model override (default: `image-01`) |
| `REPLICATE_IMAGE_MODEL` | Replicate model override (default: google/nano-banana-pro) |
| `REPLICATE_IMAGE_MODEL` | Replicate model override (default: google/nano-banana-2) |
| `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 |
| `OPENAI_IMAGE_API_DIALECT` | OpenAI-compatible image API dialect override (`openai-native` or `ratio-metadata`) |
| `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`) |
@@ -203,6 +218,8 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
| `OPENROUTER_TITLE` | Optional app name for OpenRouter attribution |
| `GOOGLE_BASE_URL` | Custom Google endpoint |
| `DASHSCOPE_BASE_URL` | Custom DashScope endpoint |
| `ZAI_BASE_URL` | Custom Z.AI endpoint (default: `https://api.z.ai/api/paas/v4`) |
| `BIGMODEL_BASE_URL` | Backward-compatible alias for Z.AI endpoint |
| `MINIMAX_BASE_URL` | Custom MiniMax endpoint (default: `https://api.minimax.io`) |
| `REPLICATE_BASE_URL` | Custom Replicate endpoint |
| `JIMENG_BASE_URL` | Custom Jimeng endpoint (default: `https://visual.volcengineapi.com`) |
@@ -227,6 +244,22 @@ For Azure, `--model` / `default_model.azure` should be the Azure deployment name
**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.
### OpenAI-Compatible Gateway Dialects
`provider=openai` means the auth and routing entrypoint is OpenAI-compatible. It does **not** guarantee that the upstream image API uses OpenAI native image-request semantics.
Use `default_image_api_dialect` in `EXTEND.md`, `OPENAI_IMAGE_API_DIALECT`, or `--imageApiDialect` when the endpoint expects a different wire format:
- `openai-native`: Sends pixel `size` such as `1536x1024` and native OpenAI quality fields when supported
- `ratio-metadata`: Sends aspect-ratio `size` such as `16:9` and maps quality/size intent into `metadata.resolution` (`1K|2K|4K`) plus `metadata.orientation`
Recommended use:
- OpenAI native Images API or strict clones: keep `openai-native`
- OpenAI-compatible gateways in front of Gemini or similar models: try `ratio-metadata`
Current limitation: `ratio-metadata` only applies to text-to-image generation. Reference-image edit flows still require `openai-native` or another provider with first-class edit support.
**Agent MUST display model info** before each generation:
- Show: `Using [provider] / [model]`
- Show switch hint: `Switch model: --model <id> | EXTEND.md default_model.[provider] | env <PROVIDER>_IMAGE_MODEL`
@@ -277,6 +310,32 @@ Official references:
- [Text-to-image guide](https://help.aliyun.com/zh/model-studio/text-to-image)
- [Qwen-Image Edit API](https://help.aliyun.com/zh/model-studio/qwen-image-edit-api)
### Z.AI Models
Use `--model glm-image` or set `default_model.zai` / `ZAI_IMAGE_MODEL` when the user wants GLM-image output.
Official Z.AI image model options currently documented in the sync image API:
- `glm-image` (recommended default)
- Text-to-image only in `baoyu-imagine`
- Native `quality` options are `hd` and `standard`; this skill maps `2k -> hd` and `normal -> standard`
- Recommended sizes: `1280x1280`, `1568x1056`, `1056x1568`, `1472x1088`, `1088x1472`, `1728x960`, `960x1728`
- Custom `--size` requires width and height between `1024` and `2048`, divisible by `32`, with total pixels <= `2^22`
- `cogview-4-250304`
- Legacy Z.AI image model family exposed by the same endpoint
- Custom `--size` requires width and height between `512` and `2048`, divisible by `16`, with total pixels <= `2^21`
Notes:
- The official sync API returns a temporary image URL; `baoyu-imagine` downloads that URL and writes the image locally
- `--ref` is not supported for Z.AI in this skill yet
- The sync API currently returns a single image, so `--n > 1` is rejected
Official references:
- [GLM-Image Guide](https://docs.z.ai/guides/image/glm-image)
- [Generate Image API](https://docs.z.ai/api-reference/image/generate-image)
### MiniMax Models
Use `--model image-01` or set `default_model.minimax` / `MINIMAX_IMAGE_MODEL` when the user wants MiniMax image generation.
@@ -322,10 +381,33 @@ Notes:
### Replicate Models
Supported model formats:
Replicate support in `baoyu-imagine` is intentionally scoped to the model families that the tool can validate locally and save without dropping outputs:
- `owner/name` (recommended for official models), e.g. `google/nano-banana-pro`
- `owner/name:version` (community models by version), e.g. `stability-ai/sdxl:<version>`
- `google/nano-banana*` (default: `google/nano-banana-2`)
- Supports prompt-only and reference-image generation
- Uses Replicate `aspect_ratio`, `resolution`, and `output_format`
- `--size <WxH>` is accepted only as a shorthand for a documented aspect ratio plus `1K` / `2K`
- `bytedance/seedream-4.5`
- Supports prompt-only and reference-image generation
- Uses Replicate `size`, `aspect_ratio`, and `image_input`
- Local validation blocks unsupported `1K` requests before the API call
- `bytedance/seedream-5-lite`
- Supports prompt-only and reference-image generation
- Uses Replicate `size`, `aspect_ratio`, and `image_input`
- Local validation currently accepts `2K` / `3K` only
- `wan-video/wan-2.7-image`
- Supports prompt-only and reference-image generation
- Uses Replicate `size` and `images`
- Max output size is 2K
- `wan-video/wan-2.7-image-pro`
- Supports prompt-only and reference-image generation
- Uses Replicate `size` and `images`
- 4K is allowed only for text-to-image; local validation blocks `4K + --ref`
Guardrails:
- Replicate currently supports only single-output save semantics in this tool. Keep `--n 1`.
- If a Replicate model is outside the compatibility list above, `baoyu-imagine` only treats it as prompt-only and rejects advanced local options instead of guessing a nano-banana-style schema.
Examples:
@@ -342,7 +424,7 @@ ${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider r
1. `--ref` provided + no `--provider` → auto-select Google first, then OpenAI, then Azure, then OpenRouter, then Replicate, then Seedream, then MiniMax (MiniMax subject reference is more specialized toward character/portrait consistency)
2. `--provider` specified → use it (if `--ref`, must be `google`, `openai`, `azure`, `openrouter`, `replicate`, `seedream`, or `minimax`)
3. Only one API key available → use that provider
4. Multiple available → default to Google
4. Multiple available → default to Google, then OpenAI, Azure, OpenRouter, DashScope, Z.AI, MiniMax, Replicate, Jimeng, Seedream
## Quality Presets
@@ -360,7 +442,7 @@ Supported: `1:1`, `16:9`, `9:16`, `4:3`, `3:4`, `2.35:1`
- Google multimodal: uses `imageConfig.aspectRatio`
- OpenAI: maps to closest supported size
- OpenRouter: sends `imageGenerationOptions.aspect_ratio`; if only `--size <WxH>` is given, aspect ratio is inferred automatically
- Replicate: passes `aspect_ratio` to model; when `--ref` is provided without `--ar`, defaults to `match_input_image`
- Replicate: behavior is model-family-specific. `google/nano-banana*` uses `aspect_ratio`; `bytedance/seedream-*` uses documented Replicate aspect ratios; Wan 2.7 maps `--ar` to a concrete `size`
- MiniMax: sends official `aspect_ratio` values directly; if `--size <WxH>` is given without `--ar`, `width` / `height` are sent for `image-01`
## Generation Mode
@@ -53,10 +53,12 @@ options:
description: "Router for Gemini/FLUX/OpenAI-compatible image models"
- label: "DashScope"
description: "Alibaba Cloud - Qwen-Image, strong Chinese/English text rendering"
- label: "Z.AI"
description: "GLM-image, strong poster and text-heavy image generation"
- label: "MiniMax"
description: "MiniMax image generation with subject-reference character workflows"
- label: "Replicate"
description: "Community models - nano-banana-pro, flexible model selection"
description: "Curated Replicate image families - nano-banana-2, Seedream, and Wan image models"
```
### Question 2: Default Google Model
@@ -119,6 +121,20 @@ options:
description: "Faster variant, use aspect ratio instead of custom size"
```
### Question 2e: Default Z.AI Model
Only show if user selected Z.AI.
```yaml
header: "Z.AI Model"
question: "Default Z.AI image generation model?"
options:
- label: "glm-image (Recommended)"
description: "Best default for posters, diagrams, and text-heavy images"
- label: "cogview-4-250304"
description: "Legacy Z.AI image model on the same endpoint"
```
### Question 3: Default Quality
```yaml
@@ -159,17 +175,21 @@ default_provider: [selected provider or null]
default_quality: [selected quality]
default_aspect_ratio: null
default_image_size: null
default_image_api_dialect: 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
zai: [selected Z.AI model or null]
minimax: [selected minimax model or null]
replicate: null
---
```
If the user selects `OpenAI` but says their endpoint is only OpenAI-compatible and fronts another image model family, save `default_image_api_dialect: ratio-metadata` when they explicitly confirm the gateway expects aspect-ratio `size` plus metadata-based resolution. Otherwise leave it `null` / `openai-native`.
## Flow 2: EXTEND.md Exists, Model Null
When EXTEND.md exists but `default_model.[current_provider]` is null, ask ONLY the model question for the current provider.
@@ -257,16 +277,38 @@ Notes for DashScope setup:
- `qwen-image-max` / `qwen-image-plus` / `qwen-image` only support five fixed sizes: `1664*928`, `1472*1104`, `1328*1328`, `1104*1472`, `928*1664`.
- In `baoyu-imagine`, `quality` is a compatibility preset. It is not a native DashScope parameter.
### Z.AI Model Selection
```yaml
header: "Z.AI Model"
question: "Choose a default Z.AI image generation model?"
options:
- label: "glm-image (Recommended)"
description: "Current flagship image model with better text rendering and poster layouts"
- label: "cogview-4-250304"
description: "Legacy model on the sync image endpoint"
```
Notes for Z.AI setup:
- Prefer `glm-image` for posters, diagrams, and Chinese/English text-heavy layouts.
- In `baoyu-imagine`, Z.AI currently exposes text-to-image only; reference images are not wired for this provider.
- The sync Z.AI image API returns a downloadable image URL, which the runtime saves locally after download.
### Replicate Model Selection
```yaml
header: "Replicate Model"
question: "Choose a default Replicate image generation model?"
options:
- label: "google/nano-banana-pro (Recommended)"
description: "Google's fast image model on Replicate"
- label: "google/nano-banana"
description: "Google's base image model on Replicate"
- label: "google/nano-banana-2 (Recommended)"
description: "Current default for general Replicate image generation in baoyu-imagine"
- label: "bytedance/seedream-4.5"
description: "Replicate Seedream 4.5 with validated local size/ref guardrails"
- label: "bytedance/seedream-5-lite"
description: "Replicate Seedream 5 Lite with validated local size/ref guardrails"
- label: "wan-video/wan-2.7-image-pro"
description: "Replicate Wan 2.7 Image Pro with 4K text-to-image support"
```
### MiniMax Model Selection
@@ -302,6 +344,7 @@ default_model:
azure: [value or null]
openrouter: [value or null]
dashscope: [value or null]
zai: [value or null]
minimax: [value or null]
replicate: [value or null]
```
@@ -11,7 +11,7 @@ description: EXTEND.md YAML schema for baoyu-imagine user preferences
---
version: 1
default_provider: null # google|openai|azure|openrouter|dashscope|minimax|replicate|null (null = auto-detect)
default_provider: null # google|openai|azure|openrouter|dashscope|zai|minimax|replicate|null (null = auto-detect)
default_quality: null # normal|2k|null (null = use default: 2k)
@@ -19,14 +19,17 @@ default_aspect_ratio: null # "16:9"|"1:1"|"4:3"|"3:4"|"2.35:1"|null
default_image_size: null # 1K|2K|4K|null (Google/OpenRouter, overrides quality)
default_image_api_dialect: null # openai-native|ratio-metadata|null (OpenAI-compatible gateways; null = use env/default)
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"
zai: null # e.g., "glm-image"
minimax: null # e.g., "image-01"
replicate: null # e.g., "google/nano-banana-pro"
replicate: null # e.g., "google/nano-banana-2"
batch:
max_workers: 10
@@ -49,6 +52,9 @@ batch:
dashscope:
concurrency: 3
start_interval_ms: 1100
zai:
concurrency: 3
start_interval_ms: 1100
minimax:
concurrency: 3
start_interval_ms: 1100
@@ -64,11 +70,13 @@ batch:
| `default_quality` | string\|null | null | Default quality (null = 2k) |
| `default_aspect_ratio` | string\|null | null | Default aspect ratio |
| `default_image_size` | string\|null | null | Google/OpenRouter image size (overrides quality) |
| `default_image_api_dialect` | string\|null | null | OpenAI-compatible image dialect (`openai-native` or `ratio-metadata`) |
| `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.zai` | string\|null | null | Z.AI default model |
| `default_model.minimax` | string\|null | null | MiniMax default model |
| `default_model.replicate` | string\|null | null | Replicate default model |
| `batch.max_workers` | int\|null | 10 | Batch worker cap |
@@ -83,6 +91,7 @@ batch:
version: 1
default_provider: google
default_quality: 2k
default_image_api_dialect: null
---
```
@@ -94,14 +103,16 @@ default_provider: google
default_quality: 2k
default_aspect_ratio: "16:9"
default_image_size: 2K
default_image_api_dialect: null
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"
zai: "glm-image"
minimax: "image-01"
replicate: "google/nano-banana-pro"
replicate: "google/nano-banana-2"
batch:
max_workers: 10
provider_limits:
@@ -111,6 +122,9 @@ batch:
azure:
concurrency: 3
start_interval_ms: 1100
zai:
concurrency: 3
start_interval_ms: 1100
openrouter:
concurrency: 3
start_interval_ms: 1100
+95 -2
View File
@@ -17,6 +17,7 @@ import {
mergeConfig,
normalizeOutputImagePath,
parseArgs,
parseOpenAIImageApiDialect,
parseSimpleYaml,
} from "./main.ts";
@@ -28,9 +29,12 @@ function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
provider: null,
model: null,
aspectRatio: null,
aspectRatioSource: null,
size: null,
quality: null,
imageSize: null,
imageSizeSource: null,
imageApiDialect: null,
referenceImages: [],
n: 1,
batchFile: null,
@@ -78,11 +82,13 @@ test("parseArgs parses the main baoyu-imagine CLI flags", () => {
"--image",
"out/hero",
"--provider",
"openai",
"zai",
"--quality",
"2k",
"--imageSize",
"4k",
"--imageApiDialect",
"ratio-metadata",
"--ref",
"ref/one.png",
"ref/two.jpg",
@@ -95,9 +101,12 @@ test("parseArgs parses the main baoyu-imagine CLI flags", () => {
assert.deepEqual(args.promptFiles, ["prompts/system.md", "prompts/content.md"]);
assert.equal(args.imagePath, "out/hero");
assert.equal(args.provider, "openai");
assert.equal(args.provider, "zai");
assert.equal(args.quality, "2k");
assert.equal(args.aspectRatioSource, null);
assert.equal(args.imageSize, "4K");
assert.equal(args.imageSizeSource, "cli");
assert.equal(args.imageApiDialect, "ratio-metadata");
assert.deepEqual(args.referenceImages, ["ref/one.png", "ref/two.jpg"]);
assert.equal(args.n, 3);
assert.equal(args.jobs, 5);
@@ -121,9 +130,11 @@ default_provider: openrouter
default_quality: normal
default_aspect_ratio: '16:9'
default_image_size: 2K
default_image_api_dialect: ratio-metadata
default_model:
google: gemini-3-pro-image-preview
openai: gpt-image-1.5
zai: glm-image
azure: image-prod
minimax: image-01
batch:
@@ -134,6 +145,9 @@ batch:
start_interval_ms: 900
openai:
concurrency: 4
zai:
concurrency: 2
start_interval_ms: 1000
minimax:
concurrency: 2
start_interval_ms: 1400
@@ -149,8 +163,10 @@ batch:
assert.equal(config.default_quality, "normal");
assert.equal(config.default_aspect_ratio, "16:9");
assert.equal(config.default_image_size, "2K");
assert.equal(config.default_image_api_dialect, "ratio-metadata");
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?.zai, "glm-image");
assert.equal(config.default_model?.azure, "image-prod");
assert.equal(config.default_model?.minimax, "image-01");
assert.equal(config.batch?.max_workers, 8);
@@ -161,6 +177,10 @@ batch:
assert.deepEqual(config.batch?.provider_limits?.openai, {
concurrency: 4,
});
assert.deepEqual(config.batch?.provider_limits?.zai, {
concurrency: 2,
start_interval_ms: 1000,
});
assert.deepEqual(config.batch?.provider_limits?.minimax, {
concurrency: 2,
start_interval_ms: 1400,
@@ -239,13 +259,48 @@ test("mergeConfig only fills values missing from CLI args", () => {
default_quality: "2k",
default_aspect_ratio: "3:2",
default_image_size: "2K",
default_image_api_dialect: "ratio-metadata",
} satisfies Partial<ExtendConfig>,
);
assert.equal(merged.provider, "openai");
assert.equal(merged.quality, "2k");
assert.equal(merged.aspectRatio, "3:2");
assert.equal(merged.aspectRatioSource, "config");
assert.equal(merged.imageSize, "4K");
assert.equal(merged.imageSizeSource, "cli");
assert.equal(merged.imageApiDialect, "ratio-metadata");
});
test("mergeConfig tags inherited imageSize defaults so providers can ignore incompatible config", () => {
const merged = mergeConfig(
makeArgs(),
{
default_image_size: "2K",
} satisfies Partial<ExtendConfig>,
);
assert.equal(merged.imageSize, "2K");
assert.equal(merged.imageSizeSource, "config");
});
test("mergeConfig falls back to OPENAI_IMAGE_API_DIALECT when CLI and EXTEND are unset", (t) => {
useEnv(t, {
OPENAI_IMAGE_API_DIALECT: "ratio-metadata",
});
const merged = mergeConfig(makeArgs(), {});
assert.equal(merged.imageApiDialect, "ratio-metadata");
});
test("parseOpenAIImageApiDialect validates supported values", () => {
assert.equal(parseOpenAIImageApiDialect("openai-native"), "openai-native");
assert.equal(parseOpenAIImageApiDialect("ratio-metadata"), "ratio-metadata");
assert.equal(parseOpenAIImageApiDialect(null), null);
assert.throws(
() => parseOpenAIImageApiDialect("gateway-magic"),
/Invalid OpenAI image API dialect/,
);
});
test("detectProvider rejects non-ref-capable providers and prefers Google first when multiple keys exist", (t) => {
@@ -316,6 +371,27 @@ test("detectProvider selects Azure when only Azure credentials are configured",
);
});
test("detectProvider selects Z.AI when credentials are present or the model id matches", (t) => {
useEnv(t, {
GOOGLE_API_KEY: null,
OPENAI_API_KEY: null,
AZURE_OPENAI_API_KEY: null,
AZURE_OPENAI_BASE_URL: null,
OPENROUTER_API_KEY: null,
DASHSCOPE_API_KEY: null,
ZAI_API_KEY: "zai-key",
BIGMODEL_API_KEY: null,
MINIMAX_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()), "zai");
assert.equal(detectProvider(makeArgs({ model: "glm-image" })), "zai");
});
test("detectProvider infers Seedream from model id and allows Seedream reference-image workflows", (t) => {
useEnv(t, {
GOOGLE_API_KEY: null,
@@ -375,6 +451,7 @@ test("batch worker and provider-rate-limit configuration prefer env over EXTEND
BAOYU_IMAGE_GEN_MAX_WORKERS: "12",
BAOYU_IMAGE_GEN_GOOGLE_CONCURRENCY: "5",
BAOYU_IMAGE_GEN_GOOGLE_START_INTERVAL_MS: "450",
BAOYU_IMAGE_GEN_ZAI_CONCURRENCY: "4",
});
const extendConfig: Partial<ExtendConfig> = {
@@ -385,6 +462,10 @@ test("batch worker and provider-rate-limit configuration prefer env over EXTEND
concurrency: 2,
start_interval_ms: 900,
},
zai: {
concurrency: 1,
start_interval_ms: 1200,
},
minimax: {
concurrency: 1,
start_interval_ms: 1500,
@@ -398,6 +479,10 @@ test("batch worker and provider-rate-limit configuration prefer env over EXTEND
concurrency: 5,
startIntervalMs: 450,
});
assert.deepEqual(getConfiguredProviderRateLimits(extendConfig).zai, {
concurrency: 4,
startIntervalMs: 1200,
});
assert.deepEqual(getConfiguredProviderRateLimits(extendConfig).minimax, {
concurrency: 1,
startIntervalMs: 1500,
@@ -435,6 +520,7 @@ test("loadBatchTasks and createTaskArgs resolve batch-relative paths", async (t)
makeArgs({
provider: "replicate",
quality: "2k",
imageApiDialect: "ratio-metadata",
json: true,
}),
loaded.tasks[0]!,
@@ -451,6 +537,7 @@ test("loadBatchTasks and createTaskArgs resolve batch-relative paths", async (t)
assert.equal(taskArgs.provider, "replicate");
assert.equal(taskArgs.aspectRatio, "16:9");
assert.equal(taskArgs.quality, "2k");
assert.equal(taskArgs.imageApiDialect, "ratio-metadata");
assert.equal(taskArgs.json, true);
});
@@ -464,5 +551,11 @@ test("path normalization, worker count, and retry classification follow expected
assert.equal(getWorkerCount(5, 0, 4), 1);
assert.equal(isRetryableGenerationError(new Error("API error (401): denied")), false);
assert.equal(
isRetryableGenerationError(
new Error("Replicate returned 2 outputs, but baoyu-imagine currently supports saving exactly one image per request."),
),
false,
);
assert.equal(isRetryableGenerationError(new Error("socket hang up")), true);
});
+81 -10
View File
@@ -8,6 +8,7 @@ import type {
BatchTaskInput,
CliArgs,
ExtendConfig,
OpenAIImageApiDialect,
Provider,
} from "./types";
@@ -58,6 +59,7 @@ const DEFAULT_PROVIDER_RATE_LIMITS: Record<Provider, ProviderRateLimit> = {
openai: { concurrency: 3, startIntervalMs: 1100 },
openrouter: { concurrency: 3, startIntervalMs: 1100 },
dashscope: { concurrency: 3, startIntervalMs: 1100 },
zai: { concurrency: 3, startIntervalMs: 1100 },
minimax: { concurrency: 3, startIntervalMs: 1100 },
jimeng: { concurrency: 3, startIntervalMs: 1100 },
seedream: { concurrency: 3, startIntervalMs: 1100 },
@@ -76,14 +78,15 @@ 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|minimax|replicate|jimeng|seedream|azure Force provider (auto-detect by default)
--provider google|openai|openrouter|dashscope|zai|minimax|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, Azure, OpenRouter, Replicate, MiniMax, or Seedream 4.0/4.5/5.0)
--n <count> Number of images for the current task (default: 1)
--imageApiDialect <id> OpenAI-compatible image dialect: openai-native|ratio-metadata
--ref <files...> Reference images (Google, OpenAI, Azure, OpenRouter, Replicate supported families, MiniMax, or Seedream 4.0/4.5/5.0)
--n <count> Number of images for the current task (default: 1; Replicate currently requires 1)
--json JSON output
-h, --help Show help
@@ -96,7 +99,7 @@ Batch file format:
"promptFiles": ["prompts/hero.md"],
"image": "out/hero.png",
"provider": "replicate",
"model": "google/nano-banana-pro",
"model": "google/nano-banana-2",
"ar": "16:9"
}
]
@@ -106,6 +109,7 @@ Behavior:
- Batch mode automatically runs in parallel when pending tasks >= 2
- Each image retries automatically up to 3 attempts
- Batch summary reports success count, failure count, and per-image errors
- Replicate currently supports single-image save semantics only; --n must stay at 1
Environment variables:
OPENAI_API_KEY OpenAI API key
@@ -113,6 +117,8 @@ Environment variables:
GOOGLE_API_KEY Google API key
GEMINI_API_KEY Gemini API key (alias for GOOGLE_API_KEY)
DASHSCOPE_API_KEY DashScope API key
ZAI_API_KEY Z.AI API key
BIGMODEL_API_KEY Backward-compatible alias for Z.AI API key
MINIMAX_API_KEY MiniMax API key
REPLICATE_API_TOKEN Replicate API token
JIMENG_ACCESS_KEY_ID Jimeng Access Key ID
@@ -122,17 +128,22 @@ Environment variables:
OPENROUTER_IMAGE_MODEL Default OpenRouter model (google/gemini-3.1-flash-image-preview)
GOOGLE_IMAGE_MODEL Default Google model (gemini-3-pro-image-preview)
DASHSCOPE_IMAGE_MODEL Default DashScope model (qwen-image-2.0-pro)
ZAI_IMAGE_MODEL Default Z.AI model (glm-image)
BIGMODEL_IMAGE_MODEL Backward-compatible alias for Z.AI model (glm-image)
MINIMAX_IMAGE_MODEL Default MiniMax model (image-01)
REPLICATE_IMAGE_MODEL Default Replicate model (google/nano-banana-pro)
REPLICATE_IMAGE_MODEL Default Replicate model (google/nano-banana-2)
JIMENG_IMAGE_MODEL Default Jimeng model (jimeng_t2i_v40)
SEEDREAM_IMAGE_MODEL Default Seedream model (doubao-seedream-5-0-260128)
OPENAI_BASE_URL Custom OpenAI endpoint
OPENAI_IMAGE_API_DIALECT OpenAI-compatible image dialect (openai-native|ratio-metadata)
OPENAI_IMAGE_USE_CHAT Use /chat/completions instead of /images/generations (true|false)
OPENROUTER_BASE_URL Custom OpenRouter endpoint
OPENROUTER_HTTP_REFERER Optional app URL for OpenRouter attribution
OPENROUTER_TITLE Optional app name for OpenRouter attribution
GOOGLE_BASE_URL Custom Google endpoint
DASHSCOPE_BASE_URL Custom DashScope endpoint
ZAI_BASE_URL Custom Z.AI endpoint
BIGMODEL_BASE_URL Backward-compatible alias for Z.AI endpoint
MINIMAX_BASE_URL Custom MiniMax endpoint
REPLICATE_BASE_URL Custom Replicate endpoint
JIMENG_BASE_URL Custom Jimeng endpoint
@@ -157,9 +168,12 @@ export function parseArgs(argv: string[]): CliArgs {
provider: null,
model: null,
aspectRatio: null,
aspectRatioSource: null,
size: null,
quality: null,
imageSize: null,
imageSizeSource: null,
imageApiDialect: null,
referenceImages: [],
n: 1,
batchFile: null,
@@ -239,6 +253,7 @@ export function parseArgs(argv: string[]): CliArgs {
v !== "openai" &&
v !== "openrouter" &&
v !== "dashscope" &&
v !== "zai" &&
v !== "minimax" &&
v !== "replicate" &&
v !== "jimeng" &&
@@ -262,6 +277,7 @@ export function parseArgs(argv: string[]): CliArgs {
const v = argv[++i];
if (!v) throw new Error("Missing value for --ar");
out.aspectRatio = v;
out.aspectRatioSource = "cli";
continue;
}
@@ -283,6 +299,16 @@ export function parseArgs(argv: string[]): CliArgs {
const v = argv[++i]?.toUpperCase();
if (v !== "1K" && v !== "2K" && v !== "4K") throw new Error(`Invalid imageSize: ${v}`);
out.imageSize = v;
out.imageSizeSource = "cli";
continue;
}
if (a === "--imageApiDialect") {
const v = argv[++i];
if (v !== "openai-native" && v !== "ratio-metadata") {
throw new Error(`Invalid imageApiDialect: ${v}`);
}
out.imageApiDialect = v;
continue;
}
@@ -389,12 +415,16 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
config.default_aspect_ratio = cleaned === "null" ? null : cleaned;
} else if (key === "default_image_size") {
config.default_image_size = value === "null" ? null : value as "1K" | "2K" | "4K";
} else if (key === "default_image_api_dialect") {
config.default_image_api_dialect =
value === "null" ? null : parseOpenAIImageApiDialect(value);
} else if (key === "default_model") {
config.default_model = {
google: null,
openai: null,
openrouter: null,
dashscope: null,
zai: null,
minimax: null,
replicate: null,
jimeng: null,
@@ -423,6 +453,7 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
key === "openai" ||
key === "openrouter" ||
key === "dashscope" ||
key === "zai" ||
key === "minimax" ||
key === "replicate" ||
key === "jimeng" ||
@@ -441,6 +472,7 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
key === "openai" ||
key === "openrouter" ||
key === "dashscope" ||
key === "zai" ||
key === "minimax" ||
key === "replicate" ||
key === "jimeng" ||
@@ -471,6 +503,15 @@ export function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
return config;
}
export function parseOpenAIImageApiDialect(
value: string | undefined | null
): OpenAIImageApiDialect | null {
if (!value) return null;
const normalized = value.replace(/['"]/g, "").trim();
if (normalized === "openai-native" || normalized === "ratio-metadata") return normalized;
throw new Error(`Invalid OpenAI image API dialect: ${value}`);
}
type ExtendConfigPathPair = {
current: string;
legacy: string;
@@ -530,12 +571,25 @@ export async function loadExtendConfig(
}
export function mergeConfig(args: CliArgs, extend: Partial<ExtendConfig>): CliArgs {
const aspectRatio = args.aspectRatio ?? extend.default_aspect_ratio ?? null;
const imageSize = args.imageSize ?? extend.default_image_size ?? null;
const imageApiDialect =
args.imageApiDialect ??
extend.default_image_api_dialect ??
parseOpenAIImageApiDialect(process.env.OPENAI_IMAGE_API_DIALECT);
return {
...args,
provider: args.provider ?? extend.default_provider ?? null,
quality: args.quality ?? extend.default_quality ?? null,
aspectRatio: args.aspectRatio ?? extend.default_aspect_ratio ?? null,
imageSize: args.imageSize ?? extend.default_image_size ?? null,
aspectRatio,
aspectRatioSource:
args.aspectRatioSource ??
(args.aspectRatio !== null ? "cli" : (aspectRatio !== null ? "config" : null)),
imageSize,
imageSizeSource:
args.imageSizeSource ??
(args.imageSize !== null ? "cli" : (imageSize !== null ? "config" : null)),
imageApiDialect,
};
}
@@ -571,13 +625,14 @@ export function getConfiguredProviderRateLimits(
openai: { ...DEFAULT_PROVIDER_RATE_LIMITS.openai },
openrouter: { ...DEFAULT_PROVIDER_RATE_LIMITS.openrouter },
dashscope: { ...DEFAULT_PROVIDER_RATE_LIMITS.dashscope },
zai: { ...DEFAULT_PROVIDER_RATE_LIMITS.zai },
minimax: { ...DEFAULT_PROVIDER_RATE_LIMITS.minimax },
jimeng: { ...DEFAULT_PROVIDER_RATE_LIMITS.jimeng },
seedream: { ...DEFAULT_PROVIDER_RATE_LIMITS.seedream },
azure: { ...DEFAULT_PROVIDER_RATE_LIMITS.azure },
};
for (const provider of ["replicate", "google", "openai", "openrouter", "dashscope", "minimax", "jimeng", "seedream", "azure"] as Provider[]) {
for (const provider of ["replicate", "google", "openai", "openrouter", "dashscope", "zai", "minimax", "jimeng", "seedream", "azure"] as Provider[]) {
const envPrefix = `BAOYU_IMAGE_GEN_${provider.toUpperCase()}`;
const extendLimit = extendConfig.batch?.provider_limits?.[provider];
configured[provider] = {
@@ -629,6 +684,7 @@ function inferProviderFromModel(model: string | null): Provider | null {
const normalized = model.trim();
if (normalized.includes("seedream") || normalized.includes("seededit")) return "seedream";
if (normalized === "image-01" || normalized === "image-01-live") return "minimax";
if (normalized === "glm-image" || normalized === "cogview-4-250304") return "zai";
return null;
}
@@ -656,6 +712,7 @@ export function detectProvider(args: CliArgs): Provider {
const hasOpenai = !!process.env.OPENAI_API_KEY;
const hasOpenrouter = !!process.env.OPENROUTER_API_KEY;
const hasDashscope = !!process.env.DASHSCOPE_API_KEY;
const hasZai = !!(process.env.ZAI_API_KEY || process.env.BIGMODEL_API_KEY);
const hasMinimax = !!process.env.MINIMAX_API_KEY;
const hasReplicate = !!process.env.REPLICATE_API_TOKEN;
const hasJimeng = !!(process.env.JIMENG_ACCESS_KEY_ID && process.env.JIMENG_SECRET_ACCESS_KEY);
@@ -676,6 +733,13 @@ export function detectProvider(args: CliArgs): Provider {
return "minimax";
}
if (modelProvider === "zai") {
if (!hasZai) {
throw new Error("Model looks like a Z.AI image model, but ZAI_API_KEY is not set.");
}
return "zai";
}
if (args.referenceImages.length > 0) {
if (hasGoogle) return "google";
if (hasOpenai) return "openai";
@@ -695,6 +759,7 @@ export function detectProvider(args: CliArgs): Provider {
hasAzure && "azure",
hasOpenrouter && "openrouter",
hasDashscope && "dashscope",
hasZai && "zai",
hasMinimax && "minimax",
hasReplicate && "replicate",
hasJimeng && "jimeng",
@@ -705,7 +770,7 @@ 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, AZURE_OPENAI_API_KEY+AZURE_OPENAI_BASE_URL, OPENROUTER_API_KEY, DASHSCOPE_API_KEY, MINIMAX_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, ZAI_API_KEY, MINIMAX_API_KEY, REPLICATE_API_TOKEN, JIMENG keys, or ARK_API_KEY.\n" +
"Create ~/.baoyu-skills/.env or <cwd>/.baoyu-skills/.env with your keys."
);
}
@@ -737,6 +802,7 @@ export function isRetryableGenerationError(error: unknown): boolean {
"API error (403)",
"API error (404)",
"temporarily disabled",
"supports saving exactly one image",
];
return !nonRetryableMarkers.some((marker) => msg.includes(marker));
}
@@ -744,6 +810,7 @@ export function isRetryableGenerationError(error: unknown): boolean {
async function loadProviderModule(provider: Provider): Promise<ProviderModule> {
if (provider === "google") return (await import("./providers/google")) as ProviderModule;
if (provider === "dashscope") return (await import("./providers/dashscope")) as ProviderModule;
if (provider === "zai") return (await import("./providers/zai")) as ProviderModule;
if (provider === "minimax") return (await import("./providers/minimax")) as ProviderModule;
if (provider === "replicate") return (await import("./providers/replicate")) as ProviderModule;
if (provider === "openrouter") return (await import("./providers/openrouter")) as ProviderModule;
@@ -775,6 +842,7 @@ function getModelForProvider(
return extendConfig.default_model.openrouter;
}
if (provider === "dashscope" && extendConfig.default_model.dashscope) return extendConfig.default_model.dashscope;
if (provider === "zai" && extendConfig.default_model.zai) return extendConfig.default_model.zai;
if (provider === "minimax" && extendConfig.default_model.minimax) return extendConfig.default_model.minimax;
if (provider === "replicate" && extendConfig.default_model.replicate) return extendConfig.default_model.replicate;
if (provider === "jimeng" && extendConfig.default_model.jimeng) return extendConfig.default_model.jimeng;
@@ -848,9 +916,12 @@ export function createTaskArgs(baseArgs: CliArgs, task: BatchTaskInput, batchDir
provider: task.provider ?? baseArgs.provider ?? null,
model: task.model ?? baseArgs.model ?? null,
aspectRatio: task.ar ?? baseArgs.aspectRatio ?? null,
aspectRatioSource: task.ar != null ? "task" : (baseArgs.aspectRatioSource ?? null),
size: task.size ?? baseArgs.size ?? null,
quality: task.quality ?? baseArgs.quality ?? null,
imageSize: task.imageSize ?? baseArgs.imageSize ?? null,
imageSizeSource: task.imageSize != null ? "task" : (baseArgs.imageSizeSource ?? null),
imageApiDialect: task.imageApiDialect ?? baseArgs.imageApiDialect ?? null,
referenceImages: task.ref ? task.ref.map((filePath) => resolveBatchPath(batchDir, filePath)) : [],
n: task.n ?? baseArgs.n,
batchFile: null,
@@ -999,7 +1070,7 @@ 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", "azure"] as Provider[]) {
for (const provider of ["replicate", "google", "openai", "openrouter", "dashscope", "zai", "minimax", "jimeng", "seedream", "azure"] as Provider[]) {
const limit = providerRateLimits[provider];
console.error(`- ${provider}: concurrency=${limit.concurrency}, startIntervalMs=${limit.startIntervalMs}`);
}
@@ -48,6 +48,7 @@ function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
size: null,
quality: null,
imageSize: null,
imageApiDialect: null,
referenceImages: [],
n: 1,
batchFile: null,
@@ -50,6 +50,7 @@ function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
size: null,
quality: null,
imageSize: null,
imageApiDialect: null,
referenceImages: [],
n: 1,
batchFile: null,
@@ -15,6 +15,7 @@ function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
size: null,
quality: null,
imageSize: null,
imageApiDialect: null,
referenceImages: [],
n: 1,
batchFile: null,
@@ -50,6 +50,7 @@ function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
size: null,
quality: null,
imageSize: null,
imageApiDialect: null,
referenceImages: [],
n: 1,
batchFile: null,
@@ -2,9 +2,16 @@ import assert from "node:assert/strict";
import test from "node:test";
import {
buildOpenAIGenerationsBody,
extractImageFromResponse,
getOpenAIAspectRatio,
getOpenAIImageApiDialect,
getOpenAIResolution,
getMimeType,
getOpenAISize,
getOrientationFromAspectRatio,
inferAspectRatioFromSize,
inferResolutionFromSize,
parseAspectRatio,
} from "./openai.ts";
@@ -18,6 +25,69 @@ test("OpenAI aspect-ratio parsing and size selection match model families", () =
assert.equal(getOpenAISize("dall-e-2", "16:9", "2k"), "1024x1024");
assert.equal(getOpenAISize("gpt-image-1.5", "16:9", "2k"), "1536x1024");
assert.equal(getOpenAISize("gpt-image-1.5", "4:3", "2k"), "1024x1024");
assert.equal(inferAspectRatioFromSize("1536x1024"), "3:2");
assert.equal(inferResolutionFromSize("1536x1024"), "2K");
assert.equal(getOpenAIAspectRatio({ aspectRatio: null, size: "2048x1152" }), "16:9");
assert.equal(getOpenAIResolution({ imageSize: null, size: "2048x1152", quality: "normal" }), "2K");
assert.equal(getOrientationFromAspectRatio("16:9"), "landscape");
assert.equal(getOrientationFromAspectRatio("9:16"), "portrait");
assert.equal(getOrientationFromAspectRatio("1:1"), null);
assert.equal(getOpenAIImageApiDialect({ imageApiDialect: null }), "openai-native");
});
test("OpenAI generations body switches between native and ratio-metadata dialects", () => {
assert.deepEqual(
buildOpenAIGenerationsBody("Draw a skyline", "gpt-image-1.5", {
aspectRatio: "16:9",
size: null,
quality: "2k",
imageSize: null,
imageApiDialect: null,
}),
{
model: "gpt-image-1.5",
prompt: "Draw a skyline",
size: "1536x1024",
},
);
assert.deepEqual(
buildOpenAIGenerationsBody("Draw a skyline", "gemini-3-pro-image-preview", {
aspectRatio: "16:9",
size: null,
quality: "2k",
imageSize: null,
imageApiDialect: "ratio-metadata",
}),
{
model: "gemini-3-pro-image-preview",
prompt: "Draw a skyline",
size: "16:9",
metadata: {
resolution: "2K",
orientation: "landscape",
},
},
);
assert.deepEqual(
buildOpenAIGenerationsBody("Draw a portrait", "gemini-3-pro-image-preview", {
aspectRatio: null,
size: "1152x2048",
quality: "normal",
imageSize: null,
imageApiDialect: "ratio-metadata",
}),
{
model: "gemini-3-pro-image-preview",
prompt: "Draw a portrait",
size: "9:16",
metadata: {
resolution: "2K",
orientation: "portrait",
},
},
);
});
test("OpenAI mime-type detection covers supported reference image extensions", () => {
+124 -13
View File
@@ -1,6 +1,6 @@
import path from "node:path";
import { readFile } from "node:fs/promises";
import type { CliArgs } from "../types";
import type { CliArgs, OpenAIImageApiDialect } from "../types";
export function getDefaultModel(): string {
return process.env.OPENAI_IMAGE_MODEL || "gpt-image-1.5";
@@ -23,6 +23,8 @@ type SizeMapping = {
portrait: string;
};
type OpenAIGenerationsBody = Record<string, unknown>;
export function getOpenAISize(
model: string,
ar: string | null,
@@ -60,6 +62,114 @@ export function getOpenAISize(
return sizes.square;
}
function parsePixelSize(value: string): { width: number; height: number } | null {
const match = value.match(/^(\d+)\s*[xX]\s*(\d+)$/);
if (!match) return null;
const width = parseInt(match[1]!, 10);
const height = parseInt(match[2]!, 10);
if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
return null;
}
return { width, height };
}
function gcd(a: number, b: number): number {
let x = Math.abs(a);
let y = Math.abs(b);
while (y !== 0) {
const next = x % y;
x = y;
y = next;
}
return x || 1;
}
export function getOpenAIImageApiDialect(args: Pick<CliArgs, "imageApiDialect">): OpenAIImageApiDialect {
return args.imageApiDialect ?? "openai-native";
}
export function inferAspectRatioFromSize(size: string | null): string | null {
if (!size) return null;
const parsed = parsePixelSize(size);
if (!parsed) return null;
const divisor = gcd(parsed.width, parsed.height);
return `${parsed.width / divisor}:${parsed.height / divisor}`;
}
export function inferResolutionFromSize(size: string | null): "1K" | "2K" | "4K" | null {
if (!size) return null;
const parsed = parsePixelSize(size);
if (!parsed) return null;
const longestEdge = Math.max(parsed.width, parsed.height);
if (longestEdge <= 1024) return "1K";
if (longestEdge <= 2048) return "2K";
return "4K";
}
export function getOpenAIAspectRatio(args: Pick<CliArgs, "aspectRatio" | "size">): string {
return args.aspectRatio ?? inferAspectRatioFromSize(args.size) ?? "1:1";
}
export function getOpenAIResolution(
args: Pick<CliArgs, "imageSize" | "size" | "quality">
): "1K" | "2K" | "4K" {
if (args.imageSize === "1K" || args.imageSize === "2K" || args.imageSize === "4K") {
return args.imageSize;
}
const inferred = inferResolutionFromSize(args.size);
if (inferred) return inferred;
return args.quality === "normal" ? "1K" : "2K";
}
export function getOrientationFromAspectRatio(ar: string): "landscape" | "portrait" | null {
const parsed = parseAspectRatio(ar);
if (!parsed) return null;
const ratio = parsed.width / parsed.height;
if (Math.abs(ratio - 1) < 0.1) return null;
return ratio > 1 ? "landscape" : "portrait";
}
export function buildOpenAIGenerationsBody(
prompt: string,
model: string,
args: Pick<CliArgs, "aspectRatio" | "size" | "quality" | "imageSize" | "imageApiDialect">
): OpenAIGenerationsBody {
if (getOpenAIImageApiDialect(args) === "ratio-metadata") {
const aspectRatio = getOpenAIAspectRatio(args);
const metadata: Record<string, string> = {
resolution: getOpenAIResolution(args),
};
const orientation = getOrientationFromAspectRatio(aspectRatio);
if (orientation) metadata.orientation = orientation;
return {
model,
prompt,
size: aspectRatio,
metadata,
};
}
const body: OpenAIGenerationsBody = {
model,
prompt,
size: args.size || getOpenAISize(model, args.aspectRatio, args.quality),
};
if (model.includes("dall-e-3")) {
body.quality = args.quality === "2k" ? "hd" : "standard";
}
return body;
}
export async function generateImage(
prompt: string,
model: string,
@@ -78,18 +188,28 @@ export async function generateImage(
return generateWithChatCompletions(baseURL, apiKey, prompt, model);
}
const size = args.size || getOpenAISize(model, args.aspectRatio, args.quality);
const imageApiDialect = getOpenAIImageApiDialect(args);
if (args.referenceImages.length > 0) {
if (imageApiDialect !== "openai-native") {
throw new Error(
"Reference images are not supported with the ratio-metadata OpenAI dialect yet. Use openai-native, Google, Azure, OpenRouter, MiniMax, Seedream, or Replicate for image-edit workflows."
);
}
if (model.includes("dall-e-2") || model.includes("dall-e-3")) {
throw new Error(
"Reference images with OpenAI in this skill require GPT Image models. Use --model gpt-image-1.5 (or another gpt-image model)."
);
}
const size = args.size || getOpenAISize(model, args.aspectRatio, args.quality);
return generateWithOpenAIEdits(baseURL, apiKey, prompt, model, size, args.referenceImages, args.quality);
}
return generateWithOpenAIGenerations(baseURL, apiKey, prompt, model, size, args.quality);
return generateWithOpenAIGenerations(
baseURL,
apiKey,
buildOpenAIGenerationsBody(prompt, model, args)
);
}
async function generateWithChatCompletions(
@@ -129,17 +249,8 @@ async function generateWithChatCompletions(
async function generateWithOpenAIGenerations(
baseURL: string,
apiKey: string,
prompt: string,
model: string,
size: string,
quality: CliArgs["quality"]
body: OpenAIGenerationsBody
): Promise<Uint8Array> {
const body: Record<string, any> = { model, prompt, size };
if (model.includes("dall-e-3")) {
body.quality = quality === "2k" ? "hd" : "standard";
}
const res = await fetch(`${baseURL}/images/generations`, {
method: "POST",
headers: {
@@ -28,6 +28,7 @@ function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
size: null,
quality: null,
imageSize: null,
imageApiDialect: null,
referenceImages: [],
n: 1,
batchFile: null,
@@ -5,7 +5,10 @@ import type { CliArgs } from "../types.ts";
import {
buildInput,
extractOutputUrl,
getDefaultModel,
getModelFamily,
parseModelId,
validateArgs,
} from "./replicate.ts";
function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
@@ -16,9 +19,12 @@ function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
provider: null,
model: null,
aspectRatio: null,
aspectRatioSource: null,
size: null,
quality: null,
imageSize: null,
imageSizeSource: null,
imageApiDialect: null,
referenceImages: [],
n: 1,
batchFile: null,
@@ -29,10 +35,24 @@ function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
};
}
test("Replicate model parsing accepts official formats and rejects malformed ones", () => {
assert.deepEqual(parseModelId("google/nano-banana-pro"), {
test("Replicate default model now points at nano-banana-2", () => {
const previous = process.env.REPLICATE_IMAGE_MODEL;
delete process.env.REPLICATE_IMAGE_MODEL;
try {
assert.equal(getDefaultModel(), "google/nano-banana-2");
} finally {
if (previous == null) {
delete process.env.REPLICATE_IMAGE_MODEL;
} else {
process.env.REPLICATE_IMAGE_MODEL = previous;
}
}
});
test("Replicate model parsing and family detection accept supported official ids", () => {
assert.deepEqual(parseModelId("google/nano-banana-2"), {
owner: "google",
name: "nano-banana-pro",
name: "nano-banana-2",
version: null,
});
assert.deepEqual(parseModelId("owner/model:abc123"), {
@@ -41,46 +61,224 @@ test("Replicate model parsing accepts official formats and rejects malformed one
version: "abc123",
});
assert.equal(getModelFamily("google/nano-banana-pro"), "nano-banana");
assert.equal(getModelFamily("bytedance/seedream-4.5"), "seedream45");
assert.equal(getModelFamily("bytedance/seedream-5-lite"), "seedream5lite");
assert.equal(getModelFamily("wan-video/wan-2.7-image"), "wan27image");
assert.equal(getModelFamily("wan-video/wan-2.7-image-pro"), "wan27imagepro");
assert.equal(getModelFamily("stability-ai/sdxl"), "unknown");
assert.throws(
() => parseModelId("just-a-model-name"),
/Invalid Replicate model format/,
);
});
test("Replicate input builder maps aspect ratio, image count, quality, and refs", () => {
test("Replicate nano-banana input builder maps refs, aspect ratio, and quality presets", () => {
assert.deepEqual(
buildInput(
"google/nano-banana-2",
"A robot painter",
makeArgs({
aspectRatio: "16:9",
quality: "2k",
n: 3,
}),
["data:image/png;base64,AAAA"],
),
{
prompt: "A robot painter",
aspect_ratio: "16:9",
number_of_images: 3,
resolution: "2K",
output_format: "png",
aspect_ratio: "16:9",
image_input: ["data:image/png;base64,AAAA"],
},
);
assert.deepEqual(
buildInput("A robot painter", makeArgs({ quality: "normal" }), ["ref"]),
buildInput(
"google/nano-banana-2",
"A robot painter",
makeArgs({ size: "1024x1024", quality: "normal" }),
[],
),
{
prompt: "A robot painter",
aspect_ratio: "match_input_image",
resolution: "1K",
output_format: "png",
image_input: ["ref"],
aspect_ratio: "1:1",
},
);
});
test("Replicate output extraction supports string, array, and object URLs", () => {
test("Replicate Seedream and Wan inputs use family-specific request fields", () => {
assert.deepEqual(
buildInput(
"bytedance/seedream-4.5",
"A cinematic portrait",
makeArgs({ quality: "2k", referenceImages: ["local.png"] }),
["data:image/png;base64,AAAA"],
),
{
prompt: "A cinematic portrait",
size: "4K",
image_input: ["data:image/png;base64,AAAA"],
aspect_ratio: "match_input_image",
},
);
assert.deepEqual(
buildInput(
"bytedance/seedream-4.5",
"A cinematic portrait",
makeArgs({ size: "1536x1024" }),
[],
),
{
prompt: "A cinematic portrait",
size: "custom",
width: 1536,
height: 1024,
},
);
assert.deepEqual(
buildInput(
"bytedance/seedream-5-lite",
"A poster",
makeArgs({ aspectRatio: "21:9", quality: "2k" }),
[],
),
{
prompt: "A poster",
size: "3K",
aspect_ratio: "21:9",
},
);
assert.deepEqual(
buildInput(
"wan-video/wan-2.7-image",
"A storyboard frame",
makeArgs({ aspectRatio: "16:9", quality: "2k" }),
[],
),
{
prompt: "A storyboard frame",
size: "2048*1152",
},
);
assert.deepEqual(
buildInput(
"wan-video/wan-2.7-image-pro",
"Blend these references",
makeArgs({ size: "2K", referenceImages: ["a.png", "b.png"] }),
["ref-a", "ref-b"],
),
{
prompt: "Blend these references",
size: "2K",
images: ["ref-a", "ref-b"],
},
);
});
test("Replicate validateArgs blocks misleading multi-output and unsupported family options locally", () => {
assert.throws(
() =>
validateArgs(
"google/nano-banana-2",
makeArgs({ n: 2 }),
),
/exactly one output image/,
);
assert.throws(
() =>
validateArgs(
"bytedance/seedream-4.5",
makeArgs({ size: "1K" }),
),
/2K, 4K, or an explicit WxH size/,
);
assert.throws(
() =>
validateArgs(
"bytedance/seedream-5-lite",
makeArgs({ size: "4K" }),
),
/supports 2K or 3K output/,
);
assert.throws(
() =>
validateArgs(
"wan-video/wan-2.7-image",
makeArgs({ referenceImages: new Array(10).fill("ref.png") }),
),
/at most 9 reference images/,
);
assert.throws(
() =>
validateArgs(
"wan-video/wan-2.7-image-pro",
makeArgs({ referenceImages: ["ref.png"], size: "4K" }),
),
/only supports 4K text-to-image/,
);
assert.throws(
() =>
validateArgs(
"stability-ai/sdxl",
makeArgs({ aspectRatio: "16:9" }),
),
/compatibility list/,
);
assert.doesNotThrow(() =>
validateArgs(
"google/nano-banana-2",
makeArgs({ imageSize: "2K", imageSizeSource: "config" }),
),
);
assert.throws(
() =>
validateArgs(
"google/nano-banana-2",
makeArgs({ imageSize: "2K", imageSizeSource: "cli" }),
),
/do not use --imageSize/,
);
assert.doesNotThrow(() =>
validateArgs(
"stability-ai/sdxl",
makeArgs({ aspectRatio: "16:9", aspectRatioSource: "config" }),
),
);
assert.throws(
() =>
validateArgs(
"stability-ai/sdxl",
makeArgs({ aspectRatio: "16:9", aspectRatioSource: "cli" }),
),
/compatibility list/,
);
assert.doesNotThrow(() =>
validateArgs(
"stability-ai/sdxl",
makeArgs(),
),
);
});
test("Replicate output extraction supports single outputs and rejects silent multi-image drops", () => {
assert.equal(
extractOutputUrl({ output: "https://example.com/a.png" } as never),
"https://example.com/a.png",
@@ -94,6 +292,17 @@ test("Replicate output extraction supports string, array, and object URLs", () =
"https://example.com/c.png",
);
assert.throws(
() =>
extractOutputUrl({
output: [
"https://example.com/one.png",
"https://example.com/two.png",
],
} as never),
/supports saving exactly one image/,
);
assert.throws(
() => extractOutputUrl({ output: { invalid: true } } as never),
/Unexpected Replicate output format/,
@@ -2,10 +2,37 @@ import path from "node:path";
import { readFile } from "node:fs/promises";
import type { CliArgs } from "../types";
const DEFAULT_MODEL = "google/nano-banana-pro";
const DEFAULT_MODEL = "google/nano-banana-2";
const SYNC_WAIT_SECONDS = 60;
const POLL_INTERVAL_MS = 2000;
const MAX_POLL_MS = 300_000;
const DOCUMENTED_REPLICATE_ASPECT_RATIOS = new Set([
"1:1",
"2:3",
"3:2",
"3:4",
"4:3",
"5:4",
"4:5",
"9:16",
"16:9",
"21:9",
]);
export type ReplicateModelFamily =
| "nano-banana"
| "seedream45"
| "seedream5lite"
| "wan27image"
| "wan27imagepro"
| "unknown";
type PixelSize = {
width: number;
height: number;
};
type Seedream45Size = "2K" | "4K" | { width: number; height: number };
export function getDefaultModel(): string {
return process.env.REPLICATE_IMAGE_MODEL || DEFAULT_MODEL;
@@ -20,6 +47,40 @@ function getBaseUrl(): string {
return base.replace(/\/+$/g, "");
}
function normalizeModelId(model: string): string {
return model.trim().toLowerCase().split(":")[0]!;
}
export function getModelFamily(model: string): ReplicateModelFamily {
const normalized = normalizeModelId(model);
if (
normalized === "google/nano-banana" ||
normalized === "google/nano-banana-pro" ||
normalized === "google/nano-banana-2"
) {
return "nano-banana";
}
if (normalized === "bytedance/seedream-4.5") {
return "seedream45";
}
if (normalized === "bytedance/seedream-5-lite") {
return "seedream5lite";
}
if (normalized === "wan-video/wan-2.7-image") {
return "wan27image";
}
if (normalized === "wan-video/wan-2.7-image-pro") {
return "wan27imagepro";
}
return "unknown";
}
export function parseModelId(model: string): { owner: string; name: string; version: string | null } {
const [ownerName, version] = model.split(":");
const parts = ownerName!.split("/");
@@ -31,27 +92,219 @@ export function parseModelId(model: string): { owner: string; name: string; vers
return { owner: parts[0], name: parts[1], version: version || null };
}
export function buildInput(prompt: string, args: CliArgs, referenceImages: string[]): Record<string, unknown> {
const input: Record<string, unknown> = { prompt };
function parsePixelSize(value: string): PixelSize | null {
const match = value.trim().match(/^(\d+)\s*[xX*]\s*(\d+)$/);
if (!match) return null;
const width = parseInt(match[1]!, 10);
const height = parseInt(match[2]!, 10);
if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
return null;
}
return { width, height };
}
function parseAspectRatio(value: string): PixelSize | null {
const match = value.trim().match(/^(\d+)\s*:\s*(\d+)$/);
if (!match) return null;
const width = parseInt(match[1]!, 10);
const height = parseInt(match[2]!, 10);
if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
return null;
}
return { width, height };
}
function gcd(a: number, b: number): number {
let x = Math.abs(a);
let y = Math.abs(b);
while (y !== 0) {
const next = x % y;
x = y;
y = next;
}
return x || 1;
}
function inferAspectRatioFromSize(size: string): string | null {
const parsed = parsePixelSize(size);
if (!parsed) return null;
const divisor = gcd(parsed.width, parsed.height);
const normalized = `${parsed.width / divisor}:${parsed.height / divisor}`;
if (!DOCUMENTED_REPLICATE_ASPECT_RATIOS.has(normalized)) {
return null;
}
return normalized;
}
function getQualityPreset(args: CliArgs): "normal" | "2k" {
return args.quality === "normal" ? "normal" : "2k";
}
function validateDocumentedAspectRatio(model: string, aspectRatio: string): void {
if (aspectRatio === "match_input_image") {
return;
}
if (DOCUMENTED_REPLICATE_ASPECT_RATIOS.has(aspectRatio)) {
return;
}
throw new Error(
`Replicate model ${model} does not support aspect ratio ${aspectRatio}. Supported values: ${Array.from(DOCUMENTED_REPLICATE_ASPECT_RATIOS).join(", ")}`
);
}
function getRequestedAspectRatio(model: string, args: CliArgs): string | null {
if (args.aspectRatio) {
validateDocumentedAspectRatio(model, args.aspectRatio);
return args.aspectRatio;
}
if (!args.size) return null;
const inferred = inferAspectRatioFromSize(args.size);
if (!inferred) {
throw new Error(
`Replicate model ${model} cannot derive a supported aspect ratio from --size ${args.size}. Use one of: ${Array.from(DOCUMENTED_REPLICATE_ASPECT_RATIOS).join(", ")}`
);
}
return inferred;
}
function getNanoBananaResolution(args: CliArgs): "1K" | "2K" {
if (args.size) {
const parsed = parsePixelSize(args.size);
if (!parsed) {
throw new Error("Replicate nano-banana --size must be in WxH format, for example 1536x1024.");
}
const longestEdge = Math.max(parsed.width, parsed.height);
if (longestEdge <= 1024) return "1K";
if (longestEdge <= 2048) return "2K";
throw new Error("Replicate nano-banana only supports sizes that map to 1K or 2K output.");
}
return getQualityPreset(args) === "normal" ? "1K" : "2K";
}
function resolveSeedream45Size(args: CliArgs): Seedream45Size {
if (args.size) {
const upper = args.size.trim().toUpperCase();
if (upper === "2K" || upper === "4K") {
return upper;
}
const parsed = parsePixelSize(args.size);
if (!parsed) {
throw new Error("Replicate Seedream 4.5 --size must be 2K, 4K, or an explicit WxH size.");
}
if (parsed.width < 1024 || parsed.width > 4096 || parsed.height < 1024 || parsed.height > 4096) {
throw new Error("Replicate Seedream 4.5 custom --size must keep width and height between 1024 and 4096.");
}
return parsed;
}
return getQualityPreset(args) === "normal" ? "2K" : "4K";
}
function resolveSeedream5LiteSize(args: CliArgs): "2K" | "3K" {
if (args.size) {
const upper = args.size.trim().toUpperCase();
if (upper === "2K" || upper === "3K") {
return upper;
}
throw new Error("Replicate Seedream 5 Lite currently supports 2K or 3K output in this tool.");
}
return getQualityPreset(args) === "normal" ? "2K" : "3K";
}
function formatCustomWanSize(size: PixelSize): string {
return `${size.width}*${size.height}`;
}
function resolveWanSizeFromAspectRatio(
aspectRatio: string,
maxDimension: number,
): string {
const parsedRatio = parseAspectRatio(aspectRatio);
if (!parsedRatio) {
throw new Error(`Replicate Wan aspect ratio must be in W:H format, got ${aspectRatio}.`);
}
const scale = Math.min(maxDimension / parsedRatio.width, maxDimension / parsedRatio.height);
const width = Math.max(1, Math.floor(parsedRatio.width * scale));
const height = Math.max(1, Math.floor(parsedRatio.height * scale));
return formatCustomWanSize({ width, height });
}
function resolveWanSize(family: "wan27image" | "wan27imagepro", args: CliArgs): "1K" | "2K" | "4K" | string {
const referenceMode = args.referenceImages.length > 0;
const maxDimension = family === "wan27imagepro" && !referenceMode ? 4096 : 2048;
if (args.size) {
const upper = args.size.trim().toUpperCase();
if (upper === "1K" || upper === "2K" || upper === "4K") {
if (upper === "4K" && family !== "wan27imagepro") {
throw new Error("Replicate Wan 2.7 Image only supports 1K, 2K, or custom sizes up to 2048px.");
}
if (upper === "4K" && referenceMode) {
throw new Error("Replicate Wan 2.7 Image Pro only supports 4K text-to-image. Remove --ref or lower the size.");
}
return upper;
}
const parsed = parsePixelSize(args.size);
if (!parsed) {
throw new Error("Replicate Wan --size must be 1K, 2K, 4K, or an explicit WxH size.");
}
if (parsed.width > maxDimension || parsed.height > maxDimension) {
throw new Error(
`Replicate ${family === "wan27imagepro" ? "Wan 2.7 Image Pro" : "Wan 2.7 Image"} custom --size must keep width and height at or below ${maxDimension}px in the current mode.`
);
}
return formatCustomWanSize(parsed);
}
if (args.aspectRatio) {
input.aspect_ratio = args.aspectRatio;
return resolveWanSizeFromAspectRatio(
args.aspectRatio,
getQualityPreset(args) === "normal" ? 1024 : 2048,
);
}
return getQualityPreset(args) === "normal" ? "1K" : "2K";
}
function buildNanoBananaInput(
prompt: string,
model: string,
args: CliArgs,
referenceImages: string[],
): Record<string, unknown> {
const input: Record<string, unknown> = {
prompt,
resolution: getNanoBananaResolution(args),
output_format: "png",
};
const aspectRatio = getRequestedAspectRatio(model, args);
if (aspectRatio) {
input.aspect_ratio = aspectRatio;
} else if (referenceImages.length > 0) {
input.aspect_ratio = "match_input_image";
}
if (args.n > 1) {
input.number_of_images = args.n;
}
if (args.quality === "normal") {
input.resolution = "1K";
} else if (args.quality === "2k") {
input.resolution = "2K";
}
input.output_format = "png";
if (referenceImages.length > 0) {
input.image_input = referenceImages;
}
@@ -59,6 +312,158 @@ export function buildInput(prompt: string, args: CliArgs, referenceImages: strin
return input;
}
function buildSeedreamInput(
family: "seedream45" | "seedream5lite",
prompt: string,
model: string,
args: CliArgs,
referenceImages: string[],
): Record<string, unknown> {
const size = family === "seedream45" ? resolveSeedream45Size(args) : resolveSeedream5LiteSize(args);
const input: Record<string, unknown> = {
prompt,
};
if (family === "seedream45" && typeof size === "object") {
input.size = "custom";
input.width = size.width;
input.height = size.height;
} else {
input.size = size;
}
if (referenceImages.length > 0) {
input.image_input = referenceImages;
}
if (args.aspectRatio) {
validateDocumentedAspectRatio(model, args.aspectRatio);
input.aspect_ratio = args.aspectRatio;
} else if (referenceImages.length > 0 && family === "seedream45") {
input.aspect_ratio = "match_input_image";
}
return input;
}
function buildWanInput(
family: "wan27image" | "wan27imagepro",
prompt: string,
args: CliArgs,
referenceImages: string[],
): Record<string, unknown> {
const input: Record<string, unknown> = {
prompt,
size: resolveWanSize(family, args),
};
if (referenceImages.length > 0) {
input.images = referenceImages;
}
return input;
}
export function validateArgs(model: string, args: CliArgs): void {
parseModelId(model);
if (args.n !== 1) {
throw new Error("Replicate integration currently supports exactly one output image per request. Remove --n or use --n 1.");
}
if (args.imageSize && args.imageSizeSource !== "config") {
throw new Error("Replicate models in baoyu-imagine do not use --imageSize. Use --quality, --ar, or --size instead.");
}
const family = getModelFamily(model);
if (family === "nano-banana") {
if (args.referenceImages.length > 14) {
throw new Error("Replicate nano-banana supports at most 14 reference images.");
}
if (args.aspectRatio) {
validateDocumentedAspectRatio(model, args.aspectRatio);
}
if (args.size) {
getRequestedAspectRatio(model, args);
getNanoBananaResolution(args);
}
return;
}
if (family === "seedream45") {
if (args.referenceImages.length > 14) {
throw new Error("Replicate Seedream 4.5 supports at most 14 reference images.");
}
if (args.aspectRatio) {
validateDocumentedAspectRatio(model, args.aspectRatio);
}
resolveSeedream45Size(args);
return;
}
if (family === "seedream5lite") {
if (args.referenceImages.length > 14) {
throw new Error("Replicate Seedream 5 Lite supports at most 14 reference images.");
}
if (args.aspectRatio) {
validateDocumentedAspectRatio(model, args.aspectRatio);
}
resolveSeedream5LiteSize(args);
return;
}
if (family === "wan27image" || family === "wan27imagepro") {
if (args.referenceImages.length > 9) {
throw new Error("Replicate Wan 2.7 image models support at most 9 reference images.");
}
if (args.aspectRatio) {
const parsed = parseAspectRatio(args.aspectRatio);
if (!parsed) {
throw new Error(`Replicate Wan aspect ratio must be in W:H format, got ${args.aspectRatio}.`);
}
}
resolveWanSize(family, args);
return;
}
const hasExplicitAspectRatio = !!args.aspectRatio && args.aspectRatioSource !== "config";
if (args.referenceImages.length > 0 || hasExplicitAspectRatio || args.size) {
throw new Error(
`Replicate model ${model} is not in the baoyu-imagine compatibility list. Supported families: google/nano-banana*, bytedance/seedream-4.5, bytedance/seedream-5-lite, wan-video/wan-2.7-image, wan-video/wan-2.7-image-pro.`
);
}
}
export function getDefaultOutputExtension(model: string): ".png" {
const _family = getModelFamily(model);
return ".png";
}
export function buildInput(
model: string,
prompt: string,
args: CliArgs,
referenceImages: string[],
): Record<string, unknown> {
const family = getModelFamily(model);
if (family === "nano-banana") {
return buildNanoBananaInput(prompt, model, args, referenceImages);
}
if (family === "seedream45" || family === "seedream5lite") {
return buildSeedreamInput(family, prompt, model, args, referenceImages);
}
if (family === "wan27image" || family === "wan27imagepro") {
return buildWanInput(family, prompt, args, referenceImages);
}
return { prompt };
}
async function readImageAsDataUrl(p: string): Promise<string> {
const buf = await readFile(p);
const ext = path.extname(p).toLowerCase();
@@ -150,6 +555,11 @@ export function extractOutputUrl(prediction: PredictionResponse): string {
if (typeof output === "string") return output;
if (Array.isArray(output)) {
if (output.length !== 1) {
throw new Error(
`Replicate returned ${output.length} outputs, but baoyu-imagine currently supports saving exactly one image per request.`
);
}
const first = output[0];
if (typeof first === "string") return first;
}
@@ -178,13 +588,14 @@ export async function generateImage(
if (!apiToken) throw new Error("REPLICATE_API_TOKEN is required. Get one at https://replicate.com/account/api-tokens");
const parsedModel = parseModelId(model);
validateArgs(model, args);
const refDataUrls: string[] = [];
for (const refPath of args.referenceImages) {
refDataUrls.push(await readImageAsDataUrl(refPath));
}
const input = buildInput(prompt, args, refDataUrls);
const input = buildInput(model, prompt, args, refDataUrls);
console.log(`Generating image with Replicate (${model})...`);
@@ -25,6 +25,7 @@ function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
size: null,
quality: null,
imageSize: null,
imageApiDialect: null,
referenceImages: [],
n: 1,
batchFile: null,
@@ -0,0 +1,181 @@
import assert from "node:assert/strict";
import test, { type TestContext } from "node:test";
import type { CliArgs } from "../types.ts";
import {
buildRequestBody,
buildZaiUrl,
extractImageFromResponse,
getDefaultModel,
getModelFamily,
parseAspectRatio,
parseSize,
resolveSizeForModel,
validateArgs,
} from "./zai.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,
imageApiDialect: 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("Z.AI default model prefers env override and otherwise uses glm-image", (t) => {
useEnv(t, {
ZAI_IMAGE_MODEL: null,
BIGMODEL_IMAGE_MODEL: null,
});
assert.equal(getDefaultModel(), "glm-image");
process.env.BIGMODEL_IMAGE_MODEL = "cogview-4-250304";
assert.equal(getDefaultModel(), "cogview-4-250304");
});
test("Z.AI URL builder normalizes host, v4 base, and full endpoint inputs", (t) => {
useEnv(t, { ZAI_BASE_URL: "https://api.z.ai" });
assert.equal(buildZaiUrl(), "https://api.z.ai/api/paas/v4/images/generations");
process.env.ZAI_BASE_URL = "https://proxy.example.com/api/paas/v4/";
assert.equal(buildZaiUrl(), "https://proxy.example.com/api/paas/v4/images/generations");
process.env.ZAI_BASE_URL = "https://proxy.example.com/custom/images/generations";
assert.equal(buildZaiUrl(), "https://proxy.example.com/custom/images/generations");
});
test("Z.AI model family and parsing helpers recognize documented formats", () => {
assert.equal(getModelFamily("glm-image"), "glm");
assert.equal(getModelFamily("cogview-4-250304"), "legacy");
assert.deepEqual(parseAspectRatio("16:9"), { width: 16, height: 9 });
assert.equal(parseAspectRatio("wide"), null);
assert.deepEqual(parseSize("1280x1280"), { width: 1280, height: 1280 });
assert.deepEqual(parseSize("1472*1088"), { width: 1472, height: 1088 });
assert.equal(parseSize("big"), null);
});
test("Z.AI size resolution follows documented recommended ratios and validates custom sizes", () => {
assert.equal(
resolveSizeForModel("glm-image", makeArgs({ aspectRatio: "16:9", quality: "2k" })),
"1728x960",
);
assert.equal(
resolveSizeForModel("cogview-4-250304", makeArgs({ aspectRatio: "4:3", quality: "normal" })),
"1152x864",
);
assert.equal(
resolveSizeForModel("glm-image", makeArgs({ size: "1568x1056", quality: "2k" })),
"1568x1056",
);
const uncommon = resolveSizeForModel(
"glm-image",
makeArgs({ aspectRatio: "5:2", quality: "normal" }),
);
const parsed = parseSize(uncommon);
assert.ok(parsed);
assert.ok(parsed.width % 32 === 0);
assert.ok(parsed.height % 32 === 0);
assert.ok(parsed.width * parsed.height <= 2 ** 22);
assert.throws(
() => resolveSizeForModel("glm-image", makeArgs({ size: "1000x1000", quality: "2k" })),
/between 1024 and 2048/,
);
assert.throws(
() => resolveSizeForModel("glm-image", makeArgs({ size: "1280x1260", quality: "2k" })),
/divisible by 32/,
);
assert.throws(
() => resolveSizeForModel("cogview-4-250304", makeArgs({ size: "2048x2048", quality: "2k" })),
/must not exceed 2\^21 total pixels/,
);
});
test("Z.AI validation rejects unsupported refs and multi-image requests", () => {
assert.throws(
() => validateArgs("glm-image", makeArgs({ referenceImages: ["ref.png"] })),
/text-to-image only/,
);
assert.throws(
() => validateArgs("glm-image", makeArgs({ n: 2 })),
/single image per request/,
);
});
test("Z.AI request body maps skill quality and resolved size into provider fields", () => {
const body = buildRequestBody(
"A cinematic science poster",
"glm-image",
makeArgs({ aspectRatio: "4:3", quality: "normal" }),
);
assert.deepEqual(body, {
model: "glm-image",
prompt: "A cinematic science poster",
quality: "standard",
size: "1472x1088",
});
});
test("Z.AI response extraction downloads the returned image URL", async (t) => {
const originalFetch = globalThis.fetch;
t.after(() => {
globalThis.fetch = originalFetch;
});
globalThis.fetch = async () =>
new Response(Uint8Array.from([1, 2, 3]), {
status: 200,
headers: { "Content-Type": "image/png" },
});
const image = await extractImageFromResponse({
data: [{ url: "https://cdn.example.com/glm-image.png" }],
});
assert.deepEqual([...image], [1, 2, 3]);
await assert.rejects(
() => extractImageFromResponse({ data: [{}] }),
/No image URL/,
);
});
@@ -0,0 +1,306 @@
import type { CliArgs, Quality } from "../types";
type ZaiModelFamily = "glm" | "legacy";
type ZaiRequestBody = {
model: string;
prompt: string;
quality: "hd" | "standard";
size: string;
};
type ZaiResponse = {
data?: Array<{ url?: string }>;
};
const DEFAULT_MODEL = "glm-image";
const GLM_MAX_PIXELS = 2 ** 22;
const LEGACY_MAX_PIXELS = 2 ** 21;
const GLM_SIZE_STEP = 32;
const LEGACY_SIZE_STEP = 16;
const GLM_RECOMMENDED_SIZES: Record<string, string> = {
"1:1": "1280x1280",
"3:2": "1568x1056",
"2:3": "1056x1568",
"4:3": "1472x1088",
"3:4": "1088x1472",
"16:9": "1728x960",
"9:16": "960x1728",
};
const LEGACY_RECOMMENDED_SIZES: Record<string, string> = {
"1:1": "1024x1024",
"9:16": "768x1344",
"3:4": "864x1152",
"16:9": "1344x768",
"4:3": "1152x864",
"2:1": "1440x720",
"1:2": "720x1440",
};
export function getDefaultModel(): string {
return process.env.ZAI_IMAGE_MODEL || process.env.BIGMODEL_IMAGE_MODEL || DEFAULT_MODEL;
}
function getApiKey(): string | null {
return process.env.ZAI_API_KEY || process.env.BIGMODEL_API_KEY || null;
}
export function buildZaiUrl(): string {
const base = (process.env.ZAI_BASE_URL || process.env.BIGMODEL_BASE_URL || "https://api.z.ai/api/paas/v4")
.replace(/\/+$/g, "");
if (base.endsWith("/images/generations")) return base;
if (base.endsWith("/api/paas/v4")) return `${base}/images/generations`;
if (base.endsWith("/v4")) return `${base}/images/generations`;
return `${base}/api/paas/v4/images/generations`;
}
export function getModelFamily(model: string): ZaiModelFamily {
return model.trim().toLowerCase() === "glm-image" ? "glm" : "legacy";
}
export function parseAspectRatio(ar: string): { width: number; height: number } | null {
const match = ar.match(/^(\d+(?:\.\d+)?):(\d+(?:\.\d+)?)$/);
if (!match) return null;
const width = Number(match[1]);
const height = Number(match[2]);
if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
return null;
}
return { width, height };
}
export function parseSize(size: string): { width: number; height: number } | null {
const match = size.trim().match(/^(\d+)\s*[xX*]\s*(\d+)$/);
if (!match) return null;
const width = parseInt(match[1]!, 10);
const height = parseInt(match[2]!, 10);
if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
return null;
}
return { width, height };
}
function formatSize(width: number, height: number): string {
return `${width}x${height}`;
}
function roundToStep(value: number, step: number): number {
return Math.max(step, Math.round(value / step) * step);
}
function getRatioValue(ar: string): number | null {
const parsed = parseAspectRatio(ar);
if (!parsed) return null;
return parsed.width / parsed.height;
}
function findClosestRatioKey(ar: string, candidates: string[]): string | null {
const targetRatio = getRatioValue(ar);
if (targetRatio == null) return null;
let bestKey: string | null = null;
let bestDiff = Infinity;
for (const candidate of candidates) {
const candidateRatio = getRatioValue(candidate);
if (candidateRatio == null) continue;
const diff = Math.abs(candidateRatio - targetRatio);
if (diff < bestDiff) {
bestDiff = diff;
bestKey = candidate;
}
}
return bestDiff <= 0.05 ? bestKey : null;
}
function getTargetPixels(quality: Quality): number {
return quality === "normal" ? 1024 * 1024 : 1536 * 1536;
}
function fitToPixelBudget(
width: number,
height: number,
targetPixels: number,
maxPixels: number,
step: number,
): { width: number; height: number } {
let nextWidth = width;
let nextHeight = height;
const pixels = nextWidth * nextHeight;
if (pixels > maxPixels) {
const scale = Math.sqrt(maxPixels / pixels);
nextWidth *= scale;
nextHeight *= scale;
} else {
const scale = Math.sqrt(targetPixels / pixels);
nextWidth *= scale;
nextHeight *= scale;
}
let roundedWidth = roundToStep(nextWidth, step);
let roundedHeight = roundToStep(nextHeight, step);
let roundedPixels = roundedWidth * roundedHeight;
while (roundedPixels > maxPixels && (roundedWidth > step || roundedHeight > step)) {
if (roundedWidth >= roundedHeight && roundedWidth > step) {
roundedWidth -= step;
} else if (roundedHeight > step) {
roundedHeight -= step;
} else {
break;
}
roundedPixels = roundedWidth * roundedHeight;
}
return { width: roundedWidth, height: roundedHeight };
}
function validateCustomSize(
size: string,
family: ZaiModelFamily,
): string {
const parsed = parseSize(size);
if (!parsed) {
throw new Error("Z.AI --size must be in WxH format, for example 1280x1280.");
}
const widthStep = family === "glm" ? GLM_SIZE_STEP : LEGACY_SIZE_STEP;
const minEdge = family === "glm" ? 1024 : 512;
const maxPixels = family === "glm" ? GLM_MAX_PIXELS : LEGACY_MAX_PIXELS;
if (parsed.width < minEdge || parsed.width > 2048 || parsed.height < minEdge || parsed.height > 2048) {
throw new Error(
family === "glm"
? "GLM-image custom size requires width and height between 1024 and 2048."
: "Z.AI legacy image models require width and height between 512 and 2048."
);
}
if (parsed.width % widthStep !== 0 || parsed.height % widthStep !== 0) {
throw new Error(
family === "glm"
? "GLM-image custom size requires width and height divisible by 32."
: "Z.AI legacy image models require width and height divisible by 16."
);
}
if (parsed.width * parsed.height > maxPixels) {
throw new Error(
family === "glm"
? "GLM-image custom size must not exceed 2^22 total pixels."
: "Z.AI legacy image size must not exceed 2^21 total pixels."
);
}
return formatSize(parsed.width, parsed.height);
}
export function resolveSizeForModel(
model: string,
args: Pick<CliArgs, "size" | "aspectRatio" | "quality">,
): string {
const family = getModelFamily(model);
const quality = args.quality === "normal" ? "normal" : "2k";
if (args.size) {
return validateCustomSize(args.size, family);
}
const recommended = family === "glm" ? GLM_RECOMMENDED_SIZES : LEGACY_RECOMMENDED_SIZES;
const defaultSize = family === "glm" ? "1280x1280" : "1024x1024";
if (!args.aspectRatio) return defaultSize;
const recommendedRatio = findClosestRatioKey(args.aspectRatio, Object.keys(recommended));
if (recommendedRatio) {
return recommended[recommendedRatio]!;
}
const parsedRatio = parseAspectRatio(args.aspectRatio);
if (!parsedRatio) return defaultSize;
const targetPixels = getTargetPixels(quality);
const maxPixels = family === "glm" ? GLM_MAX_PIXELS : LEGACY_MAX_PIXELS;
const step = family === "glm" ? GLM_SIZE_STEP : LEGACY_SIZE_STEP;
const fit = fitToPixelBudget(
parsedRatio.width,
parsedRatio.height,
targetPixels,
maxPixels,
step,
);
return formatSize(fit.width, fit.height);
}
function getZaiQuality(quality: CliArgs["quality"]): "hd" | "standard" {
return quality === "normal" ? "standard" : "hd";
}
export function validateArgs(_model: string, args: CliArgs): void {
if (args.referenceImages.length > 0) {
throw new Error("Z.AI GLM-image currently supports text-to-image only in baoyu-imagine. Remove --ref or choose another provider.");
}
if (args.n > 1) {
throw new Error("Z.AI image generation currently returns a single image per request in baoyu-imagine.");
}
}
export function buildRequestBody(
prompt: string,
model: string,
args: CliArgs,
): ZaiRequestBody {
validateArgs(model, args);
return {
model,
prompt,
quality: getZaiQuality(args.quality),
size: resolveSizeForModel(model, args),
};
}
export async function extractImageFromResponse(result: ZaiResponse): Promise<Uint8Array> {
const url = result.data?.[0]?.url;
if (!url) {
throw new Error("No image URL in Z.AI response");
}
const imageResponse = await fetch(url);
if (!imageResponse.ok) {
throw new Error(`Failed to download image from Z.AI: ${imageResponse.status}`);
}
return new Uint8Array(await imageResponse.arrayBuffer());
}
export async function generateImage(
prompt: string,
model: string,
args: CliArgs,
): Promise<Uint8Array> {
const apiKey = getApiKey();
if (!apiKey) {
throw new Error("ZAI_API_KEY is required. Get one from https://docs.z.ai/.");
}
const response = await fetch(buildZaiUrl(), {
method: "POST",
headers: {
"Content-Type": "application/json",
Authorization: `Bearer ${apiKey}`,
},
body: JSON.stringify(buildRequestBody(prompt, model, args)),
});
if (!response.ok) {
const err = await response.text();
throw new Error(`Z.AI API error (${response.status}): ${err}`);
}
const result = (await response.json()) as ZaiResponse;
return extractImageFromResponse(result);
}
+8
View File
@@ -3,12 +3,14 @@ export type Provider =
| "openai"
| "openrouter"
| "dashscope"
| "zai"
| "minimax"
| "replicate"
| "jimeng"
| "seedream"
| "azure";
export type Quality = "normal" | "2k";
export type OpenAIImageApiDialect = "openai-native" | "ratio-metadata";
export type CliArgs = {
prompt: string | null;
@@ -17,9 +19,12 @@ export type CliArgs = {
provider: Provider | null;
model: string | null;
aspectRatio: string | null;
aspectRatioSource?: "cli" | "task" | "config" | null;
size: string | null;
quality: Quality | null;
imageSize: string | null;
imageSizeSource?: "cli" | "task" | "config" | null;
imageApiDialect: OpenAIImageApiDialect | null;
referenceImages: string[];
n: number;
batchFile: string | null;
@@ -39,6 +44,7 @@ export type BatchTaskInput = {
size?: string | null;
quality?: Quality | null;
imageSize?: "1K" | "2K" | "4K" | null;
imageApiDialect?: OpenAIImageApiDialect | null;
ref?: string[];
n?: number;
};
@@ -56,11 +62,13 @@ export type ExtendConfig = {
default_quality: Quality | null;
default_aspect_ratio: string | null;
default_image_size: "1K" | "2K" | "4K" | null;
default_image_api_dialect: OpenAIImageApiDialect | null;
default_model: {
google: string | null;
openai: string | null;
openrouter: string | null;
dashscope: string | null;
zai: string | null;
minimax: string | null;
replicate: string | null;
jimeng: string | null;