Overview
- Skill Key
- cinience/alicloud-ai-image-qwen-image-edit
- Author
- cinience
- Source Repo
- openclaw/skills
- Version
- 1.0.0
- Source Path
- skills/cinience/alicloud-ai-image-qwen-image-edit
- Latest Commit SHA
- 1b558285e0dd6d25e1252e41c18326fe06ff4b78
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.
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Status
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Visibility
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直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 alicloud-ai-image-qwen-image-edit 技能。 若已安装,则直接安装 alicloud-ai-image-qwen-image-edit 技能。
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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