/install aliyun-wan-r2v
Category: provider
Model Studio Wan R2V
Validation
mkdir -p output/aliyun-wan-r2v
python -m py_compile skills/ai/video/aliyun-wan-r2v/scripts/prepare_r2v_request.py && echo "py_compile_ok" > output/aliyun-wan-r2v/validate.txt
Pass criteria: command exits 0 and output/aliyun-wan-r2v/validate.txt is generated.
Output And Evidence
- Save reference input metadata, request payloads, and task outputs in
output/aliyun-wan-r2v/. - Keep at least one polling result snapshot.
Use Wan R2V for reference-to-video generation. This is different from i2v (single image to video).
Critical model names
Use one of these exact model strings:
wan2.6-r2v-flashwan2.6-r2v
Newer official releases may prefer the flash variant for lower latency and lower cost.
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 (video.generate_reference)
Request
prompt(string, required)reference_video(string | bytes, required)reference_image(string | bytes, optional)duration(number, optional)fps(number, optional)size(string, optional)seed(int, optional)
Response
video_url(string)task_id(string, when async)request_id(string)
Async handling
- Prefer async submission for production traffic.
- Poll task result with 15-20s intervals.
- Stop polling when
SUCCEEDEDor terminal failure status is returned.
Local helper script
Prepare a normalized request JSON and validate response schema:
.venv/bin/python skills/ai/video/aliyun-wan-r2v/scripts/prepare_r2v_request.py \
--prompt "Generate a short montage with consistent character style" \
--reference-video "https://example.com/reference.mp4"
Output location
- Default output:
output/aliyun-wan-r2v/videos/ - Override base dir with
OUTPUT_DIR.
Workflow
- Confirm user intent, region, identifiers, and whether the operation is read-only or mutating.
- Run one minimal read-only query first to verify connectivity and permissions.
- Execute the target operation with explicit parameters and bounded scope.
- Verify results and save output/evidence files.
References
references/sources.md
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install aliyun-wan-r2v - 安装完成后,直接呼叫该 Skill 的名称或使用
/aliyun-wan-r2v触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Aliyun Wan R2v 是什么?
Use when generating reference-based videos with Alibaba Cloud Model Studio Wan R2V models (wan2.6-r2v-flash, wan2.6-r2v). Use when creating multi-shot videos... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 88 次。
如何安装 Aliyun Wan R2v?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install aliyun-wan-r2v」即可一键安装,无需额外配置。
Aliyun Wan R2v 是免费的吗?
是的,Aliyun Wan R2v 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Aliyun Wan R2v 支持哪些平台?
Aliyun Wan R2v 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Aliyun Wan R2v?
由 cinience(@cinience)开发并维护,当前版本 v1.0.0。