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Alicloud Ai Video Wan Video

by cinience · GitHub ↗ · v1.0.2 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install alicloud-ai-video-wan-video
Description
Generate videos with Model Studio DashScope SDK using Wan i2v models (wan2.6-i2v-flash, wan2.6-i2v, wan2.6-i2v-us). Use when implementing or documenting vide...
README (SKILL.md)

Category: provider

Model Studio Wan Video

Validation

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

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

Output And Evidence

  • Save task IDs, polling responses, and final video URLs to output/alicloud-ai-video-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:

  • wan2.2-t2v-plus
  • wan2.2-t2v-flash
  • wan2.6-i2v-flash
  • wan2.6-i2v
  • wan2.6-i2v-us
  • wan2.6-t2v-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 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.

Size notes

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

Output location

  • Default output: output/alicloud-ai-video-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

Usage Guidance
This skill appears to do what it says (generate videos via DashScope), but note two important points before installing: 1) The package metadata does not declare required credentials, yet the code and SKILL.md require DASHSCOPE_API_KEY (via env or ~/.alibabacloud/credentials). Expect to provide that API key and verify it is scoped appropriately. 2) The scripts automatically read .env files, ~/.alibabacloud/credentials, and may upload local reference_image files; avoid running these scripts in directories containing unrelated secrets or private files. Use a dedicated virtualenv, install dashscope from PyPI, inspect the dashscope package you install, and consider running the scripts on a machine/account that holds only the minimum privileges and keys needed for video generation.
Capability Analysis
Type: OpenClaw Skill Name: alicloud-ai-video-wan-video Version: 1.0.2 The skill bundle facilitates AI video generation using the Alibaba Cloud DashScope SDK. It includes scripts (generate_video.py, generate_dancing_video.py) that perform high-risk operations, specifically reading sensitive credential files (~/.alibabacloud/credentials) and downloading content from remote URLs via urllib.request.urlopen. While these actions are plausibly necessary for authenticating with the cloud provider and retrieving generated video assets, they constitute meaningful high-risk behaviors under the analysis criteria.
Capability Assessment
Purpose & Capability
The name, description, SKILL.md, and included scripts consistently implement video generation via the DashScope SDK and the listed Wan model names. The code uses the expected DashScope classes and model IDs, so the capability matches the stated purpose.
Instruction Scope
Runtime instructions and the scripts explicitly read .env files, attempt to load credentials from ~/.alibabacloud/credentials, and auto-upload local reference images via the SDK. These behaviors are reasonable for a video-generation skill but broaden the data the skill will read (local .env, profile-based credentials, and any local reference_image paths). The SKILL.md also directs saving task IDs, logs, and output files under an output directory. None of these steps appear malicious, but they do access local secrets/config and will cause network uploads of local files if those are supplied as reference images.
Install Mechanism
There is no install spec (instruction-only), and the SKILL.md recommends installing the dashscope Python package in a virtualenv. This is a low-risk, common pattern; no remote arbitrary archive downloads or unusual install steps are present.
Credentials
The registry metadata lists no required environment variables or primary credential, but the SKILL.md and scripts require DASHSCOPE_API_KEY (env or ~/.alibabacloud/credentials) and may honor ALIBABA_CLOUD_PROFILE/ALICLOUD_PROFILE. That mismatch (declared none vs runtime expectation) is a coherence issue: users must provide an API key for the service, and the skill will look in local credential files which can contain other secrets/profiles.
Persistence & Privilege
The skill is not always-enabled and does not request elevated platform privileges. It only writes outputs and logs under project output directories it documents; it does not modify other skills or request permanent platform presence.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install alicloud-ai-video-wan-video
  3. After installation, invoke the skill by name or use /alicloud-ai-video-wan-video
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.2
batch publish from alicloud-skills on 2026-03-11
v1.0.1
Initial ClawHub publish for Alibaba Cloud skills with agents metadata.
v1.0.0
Initial ClawHub publish for Alibaba Cloud skills with agents metadata.
Metadata
Slug alicloud-ai-video-wan-video
Version 1.0.2
License MIT-0
All-time Installs 2
Active Installs 2
Total Versions 3
Frequently Asked Questions

What is Alicloud Ai Video Wan Video?

Generate videos with Model Studio DashScope SDK using Wan i2v models (wan2.6-i2v-flash, wan2.6-i2v, wan2.6-i2v-us). Use when implementing or documenting vide... It is an AI Agent Skill for Claude Code / OpenClaw, with 1169 downloads so far.

How do I install Alicloud Ai Video Wan Video?

Run "/install alicloud-ai-video-wan-video" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Alicloud Ai Video Wan Video free?

Yes, Alicloud Ai Video Wan Video is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Alicloud Ai Video Wan Video support?

Alicloud Ai Video Wan Video is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Alicloud Ai Video Wan Video?

It is built and maintained by cinience (@cinience); the current version is v1.0.2.

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