OpenClaw

alicloud-ai-image-qwen-image-edit

Edit images with Alibaba Cloud Model Studio Qwen Image Edit models (qwen-image-edit, qwen-image-edit-plus, qwen-image-edit-max and snapshots). Use when modifying existing images (inpaint, replace, style transfer, local edits), preserving subject consistency, or documenting image edit request/response mappings.

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-edit

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 Edit

Validation

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

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

Output And Evidence

Save edit request payloads, result URLs, and model parameters under output/alicloud-ai-image-qwen-image-edit/.
Keep one sample request/response pair for reproducibility.

Use Qwen Image Edit models for instruction-based image editing instead of text-to-image generation.

Critical model names

Use one of these exact model strings:

qwen-image-edit
qwen-image-edit-plus
qwen-image-edit-max
qwen-image-2.0
qwen-image-2.0-pro
qwen-image-edit-plus-2025-12-15
qwen-image-edit-max-2026-01-16

Prerequisites

Install SDK in a virtual environment:

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.

Normalized interface (image.edit)

Request

prompt (string, required)
image (string | bytes, required) source image URL/path/bytes
mask (string | bytes, optional) inpaint region mask
size (string, optional) e.g. 1024*1024
seed (int, optional)

Response

image_url (string)
seed (int)
request_id (string)

Operational guidance

Keep prompts task-oriented: describe what to change and what to preserve.
Use masks for deterministic local edits.
Save output assets to object storage and persist only URLs.
For subject consistency, provide explicit constraints in prompt.

Local helper script

Prepare a normalized request JSON and validate response schema:

.venv/bin/python skills/ai/image/alicloud-ai-image-qwen-ima...

来源信息

Source: github
Repository: openclaw/skills
Path: skills/cinience/alicloud-ai-image-qwen-image-edit
Version: 1.0.0
Commit: 1b558285e0dd6d25e1252e41c18326fe06ff4b78
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 Edit

## Validation

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

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

## Output And Evidence

- Save edit request payloads, result URLs, and model parameters under `output/alicloud-ai-image-qwen-image-edit/`.
- Keep one sample request/response pair for reproducibility.

Use Qwen Image Edit models for instruction-based image editing instead of text-to-image generation.

## Critical model names

Use one of these exact model strings:
- `qwen-image-edit`
- `qwen-image-edit-plus`
- `qwen-image-edit-max`
- `qwen-image-2.0`
- `qwen-image-2.0-pro`
- `qwen-image-edit-plus-2025-12-15`
- `qwen-image-edit-max-2026-01-16`

## Prerequisites

- Install SDK in a virtual environment:

```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`.

## Normalized interface (image.edit)

### Request
- `prompt` (string, required)
- `image` (string | bytes, required) source image URL/path/bytes
- `mask` (string | bytes, optional) inpaint region mask
- `size` (string, optional) e.g. `1024*1024`
- `seed` (int, optional)

### Response
- `image_url` (string)
- `seed` (int)
- `request_id` (string)

## Operational guidance

- Keep prompts task-oriented: describe what to change and what to preserve.
- Use masks for deterministic local edits.
- Save output assets to object storage and persist only URLs.
- For subject consistency, provide explicit constraints in prompt.

## Local helper script

Prepare a normalized request JSON and validate response schema:

```bash
.venv/bin/python skills/ai/image/alicloud-ai-image-qwen-ima...

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