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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 installations selon la source☆ 0 Étoiles du dépôtv1.0.0

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

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

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

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...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/cinience/alicloud-ai-image-qwen-image-edit
Version
1.0.0
Commit
1b558285e0dd6d25e1252e41c18326fe06ff4b78
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

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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