skills/cinience/alicloud-skills/aliyun-video-style-repaint

aliyun-video-style-repaint

Installation
SKILL.md

Video Style Repaint

Validation

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

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

Output And Evidence

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

Prerequisites

  • Install SDK (recommended in a venv):
python3 -m venv .venv
. .venv/bin/activate
python -m pip install requests
  • Set DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials.
  • This API is only available in the Beijing region. You must use a Beijing-region API Key.

Critical model names

  • video-style-transform -- supports 8 preset artistic styles

Supported styles

Style ID Name (EN) Name (CN)
0 Japanese Manga 日式漫画
1 American Comics 美式漫画
2 Fresh Comics 清新漫画
3 3D Cartoon 3D 卡通
4 Chinese Cartoon 国风卡通
5 Paper Art 纸艺风格
6 Simple Illustration 简易插画
7 Chinese Ink Painting 国风水墨

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

  • video_url (string, required) -- public HTTP/HTTPS URL of the input video
  • style (integer, optional) -- style ID 0-7 (default: 0, Japanese Manga)
  • video_fps (integer, optional) -- output frame rate, range [15, 25] (default: 15)
  • animate_emotion (boolean, optional) -- facial expression optimization (default: true)
  • min_len (integer, optional) -- output short-side pixels, 720 or 540 (default: 720)
  • use_SR (boolean, optional) -- super-resolution enhancement (default: false)

Video input limits

  • Formats: MP4, AVI, MKV, MOV, FLV, TS, MPG, MXF
  • Resolution: [256, 4096] pixels per side, aspect ratio max 1.8:1
  • Duration: up to 30 seconds
  • Max size: 100MB
  • URL: must be URL-encoded if contains non-ASCII characters

Response (task creation)

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

Response (task result)

  • output.output_video_url (string) -- result video URL
  • output.task_status (string) -- final status
  • output.submit_time (string) -- task submission time
  • output.scheduled_time (string) -- task execution start time
  • output.end_time (string) -- task completion time
  • usage.duration (integer) -- video duration in seconds
  • usage.SR (integer) -- resolution used

Quick start (Python + HTTP)

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_style_repaint_task(video_url: str, style: int = 0) -> str:
    """Create a video style repaint task and return task_id."""
    payload = {
        "model": "video-style-transform",
        "input": {
            "video_url": video_url,
        },
        "parameters": {
            "style": style,
            "video_fps": 15,
        },
    }
    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", "SUSPENDED"):
            return data
        time.sleep(interval)

Error handling

Error Likely cause Action
401/403 Missing or invalid DASHSCOPE_API_KEY Check env var or credentials file
400 InvalidParameter Unsupported video format, bad dimensions, invalid style Validate parameters
"does not support synchronous calls" Missing X-DashScope-Async: enable header Add required header
429 Rate limit or quota Retry with backoff

Output location

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

Anti-patterns

  • Do not use model names other than video-style-transform.
  • Do not call this API synchronously -- async header is required.
  • Do not use style IDs outside 0-7 range.
  • Video URLs expire after 24 hours; download and persist immediately.
  • Do not use Singapore endpoint -- this API is Beijing-region only.

Workflow

  1. Confirm user intent: select desired artistic style from the 8 presets.
  2. Prepare video URL with valid format and dimensions.
  3. Configure parameters (style, fps, resolution, super-resolution).
  4. Create async task and poll for results.
  5. Download and save transformed video before URL expiration.

References

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