Category: provider
Model Studio Qwen Image Edit
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-maxqwen-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_KEYin your environment, or adddashscope_api_keyto~/.alibabacloud/credentials.
Normalized interface (image.edit)
Request
prompt(string, required)image(string | bytes, required) source image URL/path/bytesmask(string | bytes, optional) inpaint region masksize(string, optional) e.g.1024*1024seed(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-image-edit/scripts/prepare_edit_request.py \
--prompt "Replace the sky with sunset, keep buildings unchanged" \
--image "https://example.com/input.png"
Output location
- Default output:
output/ai-image-qwen-image-edit/images/ - Override base dir with
OUTPUT_DIR.
References
references/sources.md