/install alicloud-ai-video-wan-video
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-pluswan2.2-t2v-flashwan2.6-i2v-flashwan2.6-i2vwan2.6-i2v-uswan2.6-t2v-uswanx2.1-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_KEYin your environment, or adddashscope_api_keyto~/.alibabacloud/credentials(env takes precedence).
Normalized interface (video.generate)
Request
prompt(string, required)negative_prompt(string, optional)duration(number, required) secondsfps(number, required)size(string, required) e.g.1280*720seed(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_imagecan 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
WxHformat (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
- 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
-
See
references/api_reference.mdfor DashScope SDK mapping and async handling notes. -
Source list:
references/sources.md
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install alicloud-ai-video-wan-video - After installation, invoke the skill by name or use
/alicloud-ai-video-wan-video - Provide required inputs per the skill's parameter spec and get structured output
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.