Aliyun Kling Video logo

Aliyun Kling Video

Community
cinience
aliyun-kling-video

Use when generating videos with Kling v3 models on DashScope (kling/kling-v3-video-generation, kling/kling-v3-omni-video-generation). Use when implementing text-to-video, image-to-video, reference-to-video, smart storyboard, or video editing via the video-synthesis async API.

Overview

Publishercinience
Repositoryalicloud-skills
Skill namealiyun-kling-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 Kling 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-kling-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-kling-video .claude/skills/aliyun-kling-video
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aliyun Kling 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 Kling 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 Kling 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.

Kling V3 Video Generation

Validation

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

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

Output And Evidence

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

Prerequisites

  • Install dependencies (recommended in a venv):
bash
python3 -m venv .venv
. .venv/bin/activate
python -m pip install requests
  • Set DASHSCOPE_API_KEY in your environment (must be Beijing region API Key).
  • Enable Kling in 百炼控制台 — search "kling" and activate.

Critical model names

  • kling/kling-v3-video-generation — standard model: t2v, i2v (first frame, first+last frame)
  • kling/kling-v3-omni-video-generation — omni model: adds reference-to-video, video editing, multi-subject references

Capabilities

CapabilityModelRequired media
Text-to-videobothnone
Smart storyboard (multi-shot)bothnone (use multi_prompt)
Image-to-video (first frame)bothfirst_frame
Image-to-video (first+last frame)bothfirst_frame + last_frame
Reference-to-videoomni onlyrefer and/or feature
Video editingomni onlybase + optional refer

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

Region: Beijing only. No Singapore endpoint.

Normalized interface

Request (input)

  • prompt (string, conditional) — up to 2500 characters. Required for shot_type=intelligence. For omni reference-to-video, use <<<element_1>>>, <<<image_1>>>, <<<video_1>>> to reference media.
  • negative_prompt (string, optional) — content to exclude
  • media (array, optional) — media objects with type and url:
    • Standard model types: first_frame, last_frame
    • Omni model types: first_frame, last_frame, refer, base, feature
  • multi_shot (boolean, optional) — enable multi-shot generation (default: false)
  • shot_type (string, conditional) — intelligence (AI auto-split) or customize (manual). Required when multi_shot=true.
  • multi_prompt (array, optional) — per-shot prompts when shot_type=customize
  • element_list (array, optional) — multi-subject element images (omni model only)
  • keep_original_sound (string, optional) — no (default) or yes, for videos (omni model only)

Request (parameters)

  • mode (string, optional) — pro (default, 1080P) or std (720P)
  • aspect_ratio (string, conditional) — 16:9 (default), 9:16, 1:1. Required for t2v and reference-to-video.
  • duration (integer, optional) — video length [3, 15] seconds (default: 5). When using reference video, [3, 10].
  • audio (boolean, optional) — generate audio (default: false). Affects pricing.
  • watermark (boolean, optional) — add "可灵 AI" watermark (default: false)

Media input limits

Images (first_frame, last_frame, refer):

  • Formats: JPEG, JPG, PNG (no transparency)
  • Resolution: [300, 8000] pixels per side
  • Max size: 10MB

Videos (base, feature):

  • Formats: mp4, mov
  • Duration: 3-10s
  • Resolution: [720, 2160] pixels per side
  • Frame rate: 24-60 fps
  • Max size: 200MB

Media combination rules

kling/kling-v3-video-generation:

  • i2v first frame: first_frame (1 image)
  • i2v first+last: first_frame + last_frame (1 each)

kling/kling-v3-omni-video-generation (all above plus):

  • Reference: feature only (1 video), or refer only (up to 7 with elements), or feature+refer (1 video + up to 4 with elements), or feature+first_frame (1 video + 1 image)
  • Video editing: base only (1 video), or base+refer (1 video + up to 4 with elements)

Response (task creation)

  • output.task_id (string) — valid 24 hours
  • output.task_status (string) — PENDING | RUNNING | SUCCEEDED | FAILED | CANCELED
  • request_id (string)

Response (task result)

  • output.video_url (string) — generated video URL
  • output.watermark_video_url (string) — watermarked video URL
  • usage.duration (integer), usage.size (string), usage.fps (integer), usage.audio (boolean)

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_kling_task(req: dict) -> str:
    """Create a Kling video generation task and return task_id."""
    payload = {
        "model": req.get("model", "kling/kling-v3-video-generation"),
        "input": {"prompt": req.get("prompt", "")},
        "parameters": {
            "mode": req.get("mode", "pro"),
            "duration": req.get("duration", 5),
            "audio": req.get("audio", False),
            "watermark": req.get("watermark", False),
        },
    }
    if req.get("aspect_ratio"):
        payload["parameters"]["aspect_ratio"] = req["aspect_ratio"]
    if req.get("negative_prompt"):
        payload["input"]["negative_prompt"] = req["negative_prompt"]
    if req.get("media"):
        payload["input"]["media"] = req["media"]

    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)

Usage examples

python
# Text-to-video
task_id = create_kling_task({
    "prompt": "一只小猫在月光下奔跑",
    "aspect_ratio": "16:9",
    "duration": 5,
    "mode": "std",
})

# Image-to-video (first frame)
task_id = create_kling_task({
    "prompt": "花朵绽放的延时摄影",
    "media": [{"type": "first_frame", "url": "https://example.com/flower.jpg"}],
    "duration": 5,
})

# Reference-to-video with omni model
task_id = create_kling_task({
    "model": "kling/kling-v3-omni-video-generation",
    "prompt": "一只<<<element_1>>>在月光下奔跑",
    "media": [{"type": "refer", "url": "https://example.com/cat.jpg"}],
    "aspect_ratio": "16:9",
})

Error handling

ErrorLikely causeAction
401/403Missing or invalid API KeyCheck env var, must be Beijing region
400 InvalidParameterBad media combination or missing required paramsValidate against model's media rules
"does not support synchronous calls"Missing X-DashScope-Async: enable headerAdd required header
429Rate limit or quotaRetry with backoff

Output location

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

Anti-patterns

  • Do not use model names other than kling/kling-v3-video-generation or kling/kling-v3-omni-video-generation.
  • Do not call this API synchronously — async header is required.
  • Do not use refer, base, or feature media types with the standard model — use omni only.
  • Do not mix incompatible media combinations.
  • Video URLs expire; download and persist immediately.
  • Beijing region only — do not use Singapore endpoint.

Workflow

  1. Confirm user intent: t2v, i2v, reference-to-video, editing, or storyboard.
  2. Select appropriate model (standard for basic t2v/i2v, omni for reference/editing).
  3. Prepare media array with correct types and valid URLs.
  4. Create async task and poll for results.
  5. Download and save generated video before URL expiration.

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 Kling Video AI skill do?

Use when generating videos with Kling v3 models on DashScope (kling/kling-v3-video-generation, kling/kling-v3-omni-video-generation). Use when implementing text-to-video, image-to-video, reference-to-video, smart storyboard, or video editing via the video-synthesis async API.

Why use Aliyun Kling Video on TypingMind?

Because you install it once and use it with any model. Aliyun Kling 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 Kling 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-kling-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 Kling 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 Kling Video?

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

Is the Aliyun Kling 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇