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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 source installs☆ 0 Repository starsv1.0.0

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

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

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

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...

Source information

Source
github
Repository
openclaw/skills
Path
skills/cinience/alicloud-ai-image-qwen-image-edit
Version
1.0.0
Commit
1b558285e0dd6d25e1252e41c18326fe06ff4b78
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

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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