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Aliyun Vidu Video

Community
cinience
aliyun-vidu-video

Use when generating videos with DashScope Vidu models. Use when implementing text-to-video, image-to-video (first frame), keyframe-to-video (first+last frame), or reference-to-video generation via the video-synthesis async API.

Overview

Publishercinience
Repositoryalicloud-skills
Skill namealiyun-vidu-video
Stars
397
Forks
34
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by cinience on GitHub. Read the source before you install it.

Installation

Install the Aliyun Vidu Video AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-vidu-video
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/cinience/alicloud-skills.git /tmp/alicloud-skills
mkdir -p .claude/skills
cp -r /tmp/alicloud-skills/skills/ai/video/aliyun-vidu-video .claude/skills/aliyun-vidu-video
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aliyun Vidu Video in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Aliyun Vidu Video on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Aliyun Vidu Video is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Vidu Video Generation

Validation

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

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

Output And Evidence

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

Prerequisites

  • Set DASHSCOPE_API_KEY in your environment (Beijing region key required).
  • Region: China Mainland (Beijing) only. Model, Endpoint URL, and API Key must belong to the same region.
  • Enable Vidu models in the Alibaba Cloud Model Studio console before first use.

Critical model names

Text-to-video

  • vidu/viduq3-pro_text2video
  • vidu/viduq3-turbo_text2video
  • vidu/viduq2_text2video

Image-to-video (first frame)

  • vidu/viduq3-pro_img2video
  • vidu/viduq3-turbo_img2video
  • vidu/viduq2-pro_img2video
  • vidu/viduq2-turbo_img2video

Keyframe-to-video (first+last frame)

  • vidu/viduq3-pro_start-end2video
  • vidu/viduq3-turbo_start-end2video
  • vidu/viduq2-pro_start-end2video
  • vidu/viduq2-turbo_start-end2video

Reference-to-video

  • vidu/viduq2_reference2video
  • vidu/viduq2-pro_reference2video

Capabilities

CapabilityDescriptionModel suffixRequired input
Text-to-videoGenerate video from text prompt only_text2videoprompt
Image-to-videoGenerate video from a single image + optional prompt_img2videomedia[image]
Keyframe-to-videoInterpolate video between first and last frame images_start-end2videomedia[image x2] + prompt
Reference-to-videoEmbed reference subject(s) into prompted scene_reference2videomedia[image 1-7] + prompt

API endpoint (async only)

POST https://dashscope.aliyuncs.com/api/v1/services/aigc/video-generation/video-synthesis

Required headers:

  • Authorization: Bearer $DASHSCOPE_API_KEY
  • Content-Type: application/json
  • X-DashScope-Async: enable

Normalized interface

Request

  • model (string, required) -- one of the model names listed above
  • input.prompt (string) -- up to 5000 characters, describes desired video content
    • Required for text-to-video, keyframe, and reference modes
    • Optional for image-to-video
  • input.media (array) -- media objects with type and url fields (not used for text-to-video)
    • type: image or video
    • url: public URL (HTTP/HTTPS)
  • parameters.resolution (string, optional) -- 540P, 720P (default), or 1080P
  • parameters.size (string, optional) -- pixel dimensions width*height (e.g., 1280*720). Values depend on resolution tier. For text-to-video and reference-to-video, explicit size values are supported.
  • parameters.duration (integer, optional) -- video length in seconds
    • Q3 models: [1, 16], default 5
    • Q2 models: [1, 10], default 5
  • parameters.audio (boolean, optional) -- generate audio track (Q3 models only, default false)
  • parameters.watermark (boolean, optional) -- add "AI generated" watermark (default false)
  • parameters.seed (integer, optional) -- range [0, 2147483647]

Size values by resolution tier (text-to-video)

ResolutionAspect ratioSize (width*height)
540P16:9960*528
540P9:16528*960
540P1:1720*720
540P4:3816*608
540P3:4608*816
720P16:91280*720
720P9:16720*1280
720P1:1960*960
720P4:31104*816
720P3:4816*1104
1080P16:91920*1080
1080P9:161080*1920
1080P1:11440*1440
1080P4:31674*1238
1080P3:41238*1674

Size values by resolution tier (reference-to-video)

ResolutionAspect ratioSize (width*height)
540P16:9960*540
540P9:16540*960
540P1:1540*540
540P4:3720*540
540P3:4540*720
720P16:91280*720
720P9:16720*1280
720P1:1720*720
720P4:3960*720
720P3:4720*960
1080P16:91920*1080
1080P9:161080*1920
1080P1:11080*1080
1080P4:31440*1080
1080P3:41080*1440

Media input limits

Images (type=image):

  • Formats: JPG, PNG, WEBP
  • Aspect ratio: 1:4 to 4:1
  • Max size: 50MB

Videos (type=video, reference-to-video only):

  • Formats: mp4, avi, mov
  • Resolution: min 128x128 pixels
  • Aspect ratio: 1:4 to 4:1
  • Duration: 1-5s
  • Max size: 50MB

Response (task creation)

  • output.task_id (string) -- use for polling, valid 24 hours
  • output.task_status (string) -- PENDING | RUNNING | SUCCEEDED | FAILED | CANCELED | UNKNOWN
  • request_id (string)

Response (task result)

  • output.video_url (string) -- generated video URL (MP4, H.264), valid 24 hours
  • output.orig_prompt (string) -- original prompt
  • usage.duration (integer) -- billable video duration in seconds
  • usage.output_video_duration (integer) -- actual output duration
  • usage.size (string) -- output resolution
  • usage.fps (integer) -- frame rate (24)
  • usage.audio (boolean) -- whether audio was generated
  • usage.SR (string) -- resolution tier

Quick start (Python + HTTP)

python
import os
import json
import time
import requests

API_KEY = os.getenv("DASHSCOPE_API_KEY")
BASE_URL = "https://dashscope.aliyuncs.com/api/v1"

def create_vidu_task(req: dict) -> str:
    """Create a Vidu video generation task and return task_id."""
    payload = {
        "model": req["model"],
        "input": {},
        "parameters": {
            "resolution": req.get("resolution", "720P"),
            "duration": req.get("duration", 5),
        },
    }
    if req.get("prompt"):
        payload["input"]["prompt"] = req["prompt"]
    if req.get("media"):
        payload["input"]["media"] = req["media"]
    if req.get("size"):
        payload["parameters"]["size"] = req["size"]
    if req.get("audio") is not None:
        payload["parameters"]["audio"] = req["audio"]
    if req.get("watermark") is not None:
        payload["parameters"]["watermark"] = req["watermark"]
    if req.get("seed") is not None:
        payload["parameters"]["seed"] = req["seed"]

    resp = requests.post(
        f"{BASE_URL}/services/aigc/video-generation/video-synthesis",
        headers={
            "Authorization": f"Bearer {API_KEY}",
            "Content-Type": "application/json",
            "X-DashScope-Async": "enable",
        },
        json=payload,
    )
    resp.raise_for_status()
    data = resp.json()
    return data["output"]["task_id"]


def poll_task(task_id: str, interval: int = 15) -> dict:
    """Poll until task completes. Returns final response."""
    while True:
        resp = requests.get(
            f"{BASE_URL}/tasks/{task_id}",
            headers={"Authorization": f"Bearer {API_KEY}"},
        )
        resp.raise_for_status()
        data = resp.json()
        status = data["output"]["task_status"]
        if status in ("SUCCEEDED", "FAILED", "CANCELED"):
            return data
        time.sleep(interval)

Mode-specific examples

python
# Text-to-video
task_id = create_vidu_task({
    "model": "vidu/viduq3-turbo_text2video",
    "prompt": "A cat running under moonlight",
    "resolution": "540P",
    "size": "960*528",
    "duration": 5,
})

# Image-to-video (first frame)
task_id = create_vidu_task({
    "model": "vidu/viduq3-pro_img2video",
    "prompt": "Camera slowly pans upward",
    "media": [{"type": "image", "url": "https://example.com/image.jpg"}],
    "resolution": "720P",
    "duration": 5,
})

# Keyframe-to-video (first + last frame)
task_id = create_vidu_task({
    "model": "vidu/viduq3-turbo_start-end2video",
    "prompt": "A cat jumps from windowsill to sofa",
    "media": [
        {"type": "image", "url": "https://example.com/first.png"},
        {"type": "image", "url": "https://example.com/last.png"},
    ],
    "resolution": "540P",
    "duration": 5,
})

# Reference-to-video
task_id = create_vidu_task({
    "model": "vidu/viduq2_reference2video",
    "prompt": "Man playing guitar in a cafe",
    "media": [
        {"type": "image", "url": "https://example.com/ref1.jpg"},
        {"type": "image", "url": "https://example.com/ref2.jpg"},
    ],
    "resolution": "720P",
    "size": "1280*720",
    "duration": 5,
})

Error handling

ErrorLikely causeAction
401/403Missing or invalid DASHSCOPE_API_KEYCheck env var; ensure Beijing region key
400 InvalidParameterUnsupported resolution/size combo, bad duration, missing mediaValidate parameters against size tables
"does not support synchronous calls"Missing X-DashScope-Async: enable headerAdd required header
429Rate limit or quotaRetry with backoff
Cross-region errorModel and API Key from different regionsEnsure all are Beijing region

Output location

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

Anti-patterns

  • Do not use model names not listed in "Critical model names" above.
  • Do not call this API synchronously -- async header is required.
  • Do not omit size when using reference-to-video -- it is required for that mode.
  • Do not pass audio=true with Q2 models -- only Q3 models support audio generation.
  • Video URLs expire after 24 hours; download and persist immediately.
  • For image-to-video, supply exactly 1 image. For keyframe, supply exactly 2 images (first, then last).
  • For reference-to-video with viduq2_reference2video, only images are accepted (1-7). For viduq2-pro_reference2video, images (1-4) plus optional videos (1-2) are accepted.
  • Keyframe mode: first and last frame pixel count ratio must be between 0.8 and 1.25.

Workflow

  1. Confirm user intent: text-to-video, image-to-video, keyframe, or reference-to-video.
  2. Select the appropriate model name based on capability and quality tier (Q3 pro/turbo or Q2).
  3. Prepare input: prompt and/or media array with correct types and valid public URLs.
  4. Set resolution, size, and duration parameters.
  5. Create async task and poll for results (15s interval recommended).
  6. Download and save generated video before URL expiration (24 hours).

References

  • See references/api_reference.md for full HTTP API details.
  • See references/sources.md for source links.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Aliyun Vidu Video AI skill do?

Use when generating videos with DashScope Vidu models. Use when implementing text-to-video, image-to-video (first frame), keyframe-to-video (first+last frame), or reference-to-video generation via the video-synthesis async API.

Why use Aliyun Vidu Video on TypingMind?

Because you install it once and use it with any model. Aliyun Vidu Video is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Aliyun Vidu Video in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-vidu-video. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Aliyun Vidu Video?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Aliyun Vidu Video?

As many as you like. As long as a model supports skills, you can use Aliyun Vidu Video with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Aliyun Vidu Video AI skill free?

Yes. It is published on GitHub by cinience under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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