Category: provider
Model Studio Qwen Image Edit
Validation
CODEBLOCK0
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:
- - INLINECODE2
- INLINECODE3
- INLINECODE4
- INLINECODE5
- INLINECODE6
- INLINECODE7
- INLINECODE8
- INLINECODE9
- INLINECODE10
Prerequisites
- - Install SDK in a virtual environment:
CODEBLOCK1
- - Set
DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials.
Normalized interface (image.edit)
Request
- -
prompt (string, required) - INLINECODE15 (string | bytes, required) source image URL/path/bytes
- INLINECODE16 (string | bytes, optional) inpaint region mask
- INLINECODE17 (string, optional) e.g. INLINECODE18
- INLINECODE19 (int, optional)
Response
- -
image_url (string) - INLINECODE21 (int)
- INLINECODE22 (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:
CODEBLOCK2
Output location
- - Default output: INLINECODE23
- 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
技能名称: aliyun-qwen-image-edit
详细描述:
分类: 提供商
Model Studio Qwen 图像编辑
验证
bash
mkdir -p output/aliyun-qwen-image-edit
python -m pycompile skills/ai/image/aliyun-qwen-image-edit/scripts/prepareeditrequest.py && echo pycompile_ok > output/aliyun-qwen-image-edit/validate.txt
通过标准:命令退出码为0,且已生成 output/aliyun-qwen-image-edit/validate.txt 文件。
输出与证据
- - 将编辑请求负载、结果URL和模型参数保存到 output/aliyun-qwen-image-edit/ 目录下。
- 保留一份示例请求/响应对,以确保可复现性。
使用Qwen图像编辑模型进行基于指令的图像编辑,而非文本到图像的生成。
关键模型名称
请使用以下精确的模型字符串之一:
- - 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
前提条件
bash
python3 -m venv .venv
. .venv/bin/activate
python -m pip install dashscope
- - 在环境中设置 DASHSCOPEAPIKEY,或将 dashscopeapikey 添加到 ~/.alibabacloud/credentials 文件中。
标准化接口 (image.edit)
请求
- - prompt (字符串,必填)
- image (字符串 | 字节,必填) 源图像的URL/路径/字节数据
- mask (字符串 | 字节,可选) 修复区域的遮罩
- size (字符串,可选) 例如 1024*1024
- seed (整数,可选)
响应
- - imageurl (字符串)
- seed (整数)
- requestid (字符串)
操作指南
- - 保持提示词以任务为导向:描述要更改的内容和要保留的内容。
- 使用遮罩进行确定性的局部编辑。
- 将输出资源保存到对象存储中,仅保留URL。
- 为保持主体一致性,在提示词中提供明确的约束条件。
本地辅助脚本
准备标准化的请求JSON并验证响应模式:
bash
.venv/bin/python skills/ai/image/aliyun-qwen-image-edit/scripts/prepareeditrequest.py \
--prompt 将天空替换为日落,保持建筑物不变 \
--image https://example.com/input.png
输出位置
- - 默认输出:output/aliyun-qwen-image-edit/images/
- 可通过 OUTPUT_DIR 覆盖基础目录。
工作流程
1) 确认用户意图、区域、标识符,以及操作是只读还是修改型。
2) 首先执行一次最小的只读查询,以验证连接和权限。
3) 使用明确的参数和有限的范围执行目标操作。
4) 验证结果并保存输出/证据文件。
参考资料