aliyun-qwen-image-edit

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Use when editing images with Alibaba Cloud Model Studio Qwen Image Edit models (qwen-image-edit, qwen-image-edit-plus, qwen-image-edit-max, qwen-image-2.0 series 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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NPX Install

npx skill4agent add cinience/alicloud-skills aliyun-qwen-image-edit

Tags

Translated version includes tags in frontmatter
qwen-image-editalibaba-cloud-aiimage-editingdashscopeai-model

SKILL.md Content

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Category: provider

Model Studio Qwen Image Edit

Validation

bash
mkdir -p output/aliyun-qwen-image-edit
python -m py_compile skills/ai/image/aliyun-qwen-image-edit/scripts/prepare_edit_request.py && echo "py_compile_ok" > output/aliyun-qwen-image-edit/validate.txt
Pass criteria: command exits 0 and 
output/aliyun-qwen-image-edit/validate.txt
is generated.

Output And Evidence

  • Save edit request payloads, result URLs, and model parameters under 
    output/aliyun-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-2.0-2026-03-03
  • qwen-image-2.0-pro-2026-03-03
  • 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/aliyun-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/aliyun-qwen-image-edit/images/
  • Override base dir with 
    OUTPUT_DIR
    .

Workflow

  1. Confirm user intent, region, identifiers, and whether the operation is read-only or mutating.
  2. Run one minimal read-only query first to verify connectivity and permissions.
  3. Execute the target operation with explicit parameters and bounded scope.
  4. Verify results and save output/evidence files.

References

  • references/sources.md