aliyun-wan-video

Use when generating videos with Model Studio DashScope SDK using Wan video generation models (wan2.6-t2v, wan2.6-i2v-flash, wan2.6-i2v and regional variants). Use when implementing or documenting video.generate requests/responses, mapping prompt/negative_prompt/duration/fps/size/seed/reference_image/motion_strength, or integrating video generation into the video-agent pipeline.

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "aliyun-wan-video" with this command: npx skills add cinience/aliyun-wan-video

Category: provider

Model Studio Wan Video

Validation

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

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

Output And Evidence

  • Save task IDs, polling responses, and final video URLs to output/aliyun-wan-video/.
  • Keep one end-to-end run log for troubleshooting.

Provide consistent video generation behavior for the video-agent pipeline by standardizing video.generate inputs/outputs and using DashScope SDK (Python) with the exact model name.

Critical model names

Use one of these exact model strings:

  • wan2.6-t2v
  • wan2.6-t2v-us
  • wan2.2-t2v-plus
  • wan2.2-t2v-flash
  • wan2.6-i2v-flash
  • wan2.6-i2v
  • wan2.6-i2v-us
  • wanx2.1-t2v-turbo

Prerequisites

  • Install SDK (recommended in a venv to avoid PEP 668 limits):
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 (env takes precedence).

Normalized interface (video.generate)

Request

  • prompt (string, required)
  • negative_prompt (string, optional)
  • duration (number, required) seconds
  • fps (number, required)
  • size (string, required) e.g. 1280*720
  • seed (int, optional)
  • reference_image (string | bytes, optional for t2v, required for i2v family models)
  • motion_strength (number, optional)

Response

  • video_url (string)
  • duration (number)
  • fps (number)
  • seed (int)

Quick start (Python + DashScope SDK)

Video generation is usually asynchronous. Expect a task ID and poll until completion. Note: Wan i2v models require an input image; pure t2v models such as wan2.6-t2v can omit reference_image.

import os
from dashscope import VideoSynthesis

# Prefer env var for auth: export DASHSCOPE_API_KEY=...
# Or use ~/.alibabacloud/credentials with dashscope_api_key under [default].

def generate_video(req: dict) -> dict:
    payload = {
        "model": req.get("model", "wan2.6-i2v-flash"),
        "prompt": req["prompt"],
        "negative_prompt": req.get("negative_prompt"),
        "duration": req.get("duration", 4),
        "fps": req.get("fps", 24),
        "size": req.get("size", "1280*720"),
        "seed": req.get("seed"),
        "motion_strength": req.get("motion_strength"),
        "api_key": os.getenv("DASHSCOPE_API_KEY"),
    }

    if req.get("reference_image"):
        # DashScope expects img_url for i2v models; local files are auto-uploaded.
        payload["img_url"] = req["reference_image"]

    response = VideoSynthesis.call(**payload)

    # Some SDK versions require polling for the final result.
    # If a task_id is returned, poll until status is SUCCEEDED.
    result = response.output.get("results", [None])[0]

    return {
        "video_url": None if not result else result.get("url"),
        "duration": response.output.get("duration"),
        "fps": response.output.get("fps"),
        "seed": response.output.get("seed"),
    }

Async handling (polling)

import os
from dashscope import VideoSynthesis

task = VideoSynthesis.async_call(
    model=req.get("model", "wan2.6-i2v-flash"),
    prompt=req["prompt"],
    img_url=req["reference_image"],
    duration=req.get("duration", 4),
    fps=req.get("fps", 24),
    size=req.get("size", "1280*720"),
    api_key=os.getenv("DASHSCOPE_API_KEY"),
)

final = VideoSynthesis.wait(task)
video_url = final.output.get("video_url")

Operational guidance

  • Video generation can take minutes; expose progress and allow cancel/retry.
  • Cache by (prompt, negative_prompt, duration, fps, size, seed, reference_image hash, motion_strength).
  • Store video assets in object storage and persist only URLs in metadata.
  • reference_image can be a URL or local path; the SDK auto-uploads local files.
  • If you get Field required: input.img_url, the reference image is missing or not mapped.
  • wan2.6-t2v and wan2.6-t2v-us add multi-shot narrative support and optional audio input according to the official docs.

Size notes

  • Use WxH format (e.g. 1280*720).
  • Prefer common sizes; unsupported sizes can return 400.

Output location

  • Default output: output/aliyun-wan-video/videos/
  • Override base dir with OUTPUT_DIR.

Anti-patterns

  • Do not invent model names or aliases; use official Wan i2v model IDs only.
  • Do not block the UI without progress updates.
  • Do not retry blindly on 4xx; handle validation failures explicitly.

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

  • See references/api_reference.md for DashScope SDK mapping and async handling notes.

  • Source list: references/sources.md

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

General

Huo15 Openclaw Enhance

火一五·克劳德·龙虾增强插件 v5.7.8 — 全面适配 openclaw 2026.4.24:peerDep ^4.24 + build/compat 同步到 4.24 + 14 处 api.on 全部去掉 as any 改成 typed hook(hookName 联合类型 + handler 自动推断 Pl...

Registry SourceRecently Updated
General

Content Trend Analyzer

Aggregates and analyzes content trends across platforms to identify hot topics, user intent, content gaps, and generates data-driven article outlines.

Registry SourceRecently Updated
General

Prompt Debugger

Debug prompts that produce unexpected AI outputs — diagnose failure modes, identify ambiguity and conflicting instructions, test variations, compare model re...

Registry SourceRecently Updated
General

Indie Maker News

独行者 Daily - 变现雷达。读对一条新闻,少走一年弯路。每天5分钟,给创业者装上商业雷达。聚焦一人公司、副业、创业变现资讯,智能分类,行动导向。用户下载即能用,无需本地部署!

Registry SourceRecently Updated