OpenClaw

alicloud-ai-video-wan-r2v

Generate reference-based videos with Alibaba Cloud Model Studio Wan R2V models (wan2.6-r2v-flash, wan2.6-r2v). Use when creating multi-shot videos from reference video/image material, preserving character style, or documenting reference-to-video request/response flows.

cinience0 来源安装数☆ 0 仓库 Starsv1.0.0

查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install cinience/alicloud-ai-video-wan-r2v

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

Category: provider

Model Studio Wan R2V

Validation

mkdir -p output/alicloud-ai-video-wan-r2v
python -m py_compile skills/ai/video/alicloud-ai-video-wan-r2v/scripts/prepare_r2v_request.py && echo "py_compile_ok" > output/alicloud-ai-video-wan-r2v/validate.txt

Pass criteria: command exits 0 and output/alicloud-ai-video-wan-r2v/validate.txt is generated.

Output And Evidence

Save reference input metadata, request payloads, and task outputs in output/alicloud-ai-video-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-flash
wan2.6-r2v

Prerequisites

Install SDK in a virtual environment:

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 (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 SUCCEEDED or terminal failure status is returned.

Local helper script

Prepare a normalized request JSON and validate response schema:

.venv/bin/python skills/ai/video/alicloud-ai-video-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/alicloud-ai-video-wan-r2v/videos/
Overr...

来源信息

Source: github
Repository: openclaw/skills
Path: skills/cinience/alicloud-ai-video-wan-r2v
Version: 1.0.0
Commit: f068efa1862b0eb1caa90741e0045075632745a7
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

Category: provider

# Model Studio Wan R2V

## Validation

```bash
mkdir -p output/alicloud-ai-video-wan-r2v
python -m py_compile skills/ai/video/alicloud-ai-video-wan-r2v/scripts/prepare_r2v_request.py && echo "py_compile_ok" > output/alicloud-ai-video-wan-r2v/validate.txt
```

Pass criteria: command exits 0 and `output/alicloud-ai-video-wan-r2v/validate.txt` is generated.

## Output And Evidence

- Save reference input metadata, request payloads, and task outputs in `output/alicloud-ai-video-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-flash`
- `wan2.6-r2v`

## 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 (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 `SUCCEEDED` or terminal failure status is returned.

## Local helper script

Prepare a normalized request JSON and validate response schema:

```bash
.venv/bin/python skills/ai/video/alicloud-ai-video-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/alicloud-ai-video-wan-r2v/videos/`
- Overr...

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