OpenClaw

alicloud-ai-image-qwen-image

Generate images with Model Studio DashScope SDK using Qwen Image generation models (qwen-image, qwen-image-plus, qwen-image-max and snapshots). Use when implementing or documenting image.generate requests/responses, mapping prompt/negative_prompt/size/seed/reference_image, or integrating image generation into the video-agent pipeline.

cinience0 来源安装数☆ 0 仓库 Starsv1.0.0

查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install cinience/alicloud-ai-image-qwen-image

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

Category: provider

Model Studio Qwen Image

Validation

mkdir -p output/alicloud-ai-image-qwen-image
python -m py_compile skills/ai/image/alicloud-ai-image-qwen-image/scripts/generate_image.py && echo "py_compile_ok" > output/alicloud-ai-image-qwen-image/validate.txt

Pass criteria: command exits 0 and output/alicloud-ai-image-qwen-image/validate.txt is generated.

Output And Evidence

Write generated image URLs, prompts, and metadata to output/alicloud-ai-image-qwen-image/.
Keep at least one sample JSON response per run.

Build consistent image generation behavior for the video-agent pipeline by standardizing image.generate inputs/outputs and using DashScope SDK (Python) with the exact model name.

Prerequisites

Install SDK (recommended in a venv to avoid PEP 668 limits):

python3 -m venv .venv
. .venv/bin/activate
python -m pip install dashscope

Set DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials (env takes precedence).

Critical model names

Use one of these exact model strings:

qwen-image
qwen-image-plus
qwen-image-max
qwen-image-2.0
qwen-image-2.0-pro
qwen-image-max-2025-12-30
qwen-image-plus-2026-01-09

Normalized interface (image.generate)

Request

prompt (string, required)
negative_prompt (string, optional)
size (string, required) e.g. 1024*1024, 768*1024
style (string, optional)
seed (int, optional)
reference_image (string | bytes, optional)

Response

image_url (string)
width (int)
height (int)
seed (int)

Quickstart (normalized request + preview)

Minimal normalized request body:

{
  "prompt": "a cinematic portrait of a cyclist at dusk, soft rim light, shallow depth of field",
  "negative_prompt": "blurry, low quality, watermark",
  "size": "1024*1024",
  "seed": 1234
}

Preview workflow (download then open):

curl -L -o output/alicloud-ai-image-...

来源信息

Source: github
Repository: openclaw/skills
Path: skills/cinience/alicloud-ai-image-qwen-image
Version: 1.0.0
Commit: 352a2c1ee8d5b01423291dd595142691a903ecfc
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

Category: provider

# Model Studio Qwen Image

## Validation

```bash
mkdir -p output/alicloud-ai-image-qwen-image
python -m py_compile skills/ai/image/alicloud-ai-image-qwen-image/scripts/generate_image.py && echo "py_compile_ok" > output/alicloud-ai-image-qwen-image/validate.txt
```

Pass criteria: command exits 0 and `output/alicloud-ai-image-qwen-image/validate.txt` is generated.

## Output And Evidence

- Write generated image URLs, prompts, and metadata to `output/alicloud-ai-image-qwen-image/`.
- Keep at least one sample JSON response per run.

Build consistent image generation behavior for the video-agent pipeline by standardizing `image.generate` inputs/outputs and using DashScope SDK (Python) with the exact model name.

## Prerequisites

- Install SDK (recommended in a venv to avoid PEP 668 limits):

```bash
python3 -m venv .venv
. .venv/bin/activate
python -m pip install dashscope
```
- Set `DASHSCOPE_API_KEY` in your environment, or add `dashscope_api_key` to `~/.alibabacloud/credentials` (env takes precedence).

## Critical model names

Use one of these exact model strings:
- `qwen-image`
- `qwen-image-plus`
- `qwen-image-max`
- `qwen-image-2.0`
- `qwen-image-2.0-pro`
- `qwen-image-max-2025-12-30`
- `qwen-image-plus-2026-01-09`

## Normalized interface (image.generate)

### Request
- `prompt` (string, required)
- `negative_prompt` (string, optional)
- `size` (string, required) e.g. `1024*1024`, `768*1024`
- `style` (string, optional)
- `seed` (int, optional)
- `reference_image` (string | bytes, optional)

### Response
- `image_url` (string)
- `width` (int)
- `height` (int)
- `seed` (int)

## Quickstart (normalized request + preview)

Minimal normalized request body:

```json
{
  "prompt": "a cinematic portrait of a cyclist at dusk, soft rim light, shallow depth of field",
  "negative_prompt": "blurry, low quality, watermark",
  "size": "1024*1024",
  "seed": 1234
}
```

Preview workflow (download then open):

```bash
curl -L -o output/alicloud-ai-image-...

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