Model Studio Qwen Image Edit

---

name: alicloud-ai-image-qwen-image-edit

description: 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.

version: 1.0.0

---

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

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:

Prerequisites

python3 -m venv .venv
. .venv/bin/activate
python -m pip install dashscope

Normalized interface (image.edit)

Request

Response

Operational guidance

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

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