aliyun-wan-videoedit

v2026.09.25

Use when editing videos with DashScope Wan 2.7 video editing model (wan2.7-videoedit). Use when implementing video style transfer, instruction-based video editing with optional reference images, or video content modification via the video-synthesis async API.

GitHub
Install command
npx skhub add cinience/aliyun-wan-videoedit
Markdown
SKILL.md

Wan 2.7 Video Editing

Validation

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

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

Output And Evidence

  • Save task IDs, polling responses, and final video URLs to output/aliyun-wan-videoedit/.
  • 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 dashscope
  • Set DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials.

Critical model names

  • wan2.7-videoedit — supports style transfer and instruction-based video editing

Capabilities

CapabilityDescriptionRequired media
Style transferConvert video to a different visual style (clay, anime, etc.)video only
Instruction editingEdit video content with text instructions and optional reference imagesvideo + optional reference_image (up to 3)

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

Singapore endpoint: replace dashscope.aliyuncs.com with dashscope-intl.aliyuncs.com.

Normalized interface

Request

  • prompt (string, optional) — up to 5000 characters, describes desired editing
  • negative_prompt (string, optional) — up to 500 characters
  • media (array, required) — media objects with type and url fields:
    • type: video (required, exactly 1) | reference_image (optional, up to 3)
    • url: public URL (HTTP/HTTPS) or OSS temporary URL
  • resolution (string, optional) — 720P or 1080P (default: 1080P)
  • ratio (string, optional) — output aspect ratio: 16:9, 9:16, 1:1, 4:3, 3:4. If omitted, follows input video ratio.
  • duration (integer, optional) — truncate input video to this length in seconds, range [2, 10]. Default 0 (use input video duration).
  • audio_setting (string, optional) — auto (default, AI decides) or origin (keep original audio)
  • prompt_extend (boolean, optional) — AI prompt rewriting (default: true)
  • watermark (boolean, optional) — add "AI generated" watermark (default: false)
  • seed (integer, optional) — range [0, 2147483647]

Media input limits

Video (type=video):

  • Formats: mp4, mov
  • Duration: 2-10s
  • Resolution: [240, 4096] pixels per side
  • Aspect ratio: 1:8 to 8:1
  • Max size: 100MB

Reference images (type=reference_image):

  • Formats: JPEG, JPG, PNG (no transparency), BMP, WEBP
  • Resolution: [240, 8000] pixels per side
  • Aspect ratio: 1:8 to 8:1
  • Max size: 20MB
  • Maximum 3 reference images

Resolution output table

ResolutionRatioOutput (W*H)
720P16:91280*720
720P9:16720*1280
720P1:1960*960
720P4:31104*832
720P3:4832*1104
1080P16:91920*1080
1080P9:161080*1920
1080P1:11440*1440
1080P4:31648*1248
1080P3:41248*1648

Response (task creation)

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

Response (task result)

  • output.video_url (string) — edited video URL
  • usage.video_count (integer)
  • usage.video_duration (integer) — duration in seconds

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_videoedit_task(req: dict) -> str:
    """Create a video editing task and return task_id."""
    payload = {
        "model": "wan2.7-videoedit",
        "input": {
            "prompt": req.get("prompt", ""),
            "media": req["media"],
        },
        "parameters": {
            "resolution": req.get("resolution", "1080P"),
            "prompt_extend": req.get("prompt_extend", True),
            "watermark": req.get("watermark", False),
        },
    }
    if req.get("negative_prompt"):
        payload["input"]["negative_prompt"] = req["negative_prompt"]
    if req.get("ratio"):
        payload["parameters"]["ratio"] = req["ratio"]
    if req.get("duration"):
        payload["parameters"]["duration"] = req["duration"]
    if req.get("audio_setting"):
        payload["parameters"]["audio_setting"] = req["audio_setting"]
    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)

Usage examples

# Style transfer — convert to clay style
media = [{"type": "video", "url": "https://example.com/input.mp4"}]
task_id = create_videoedit_task({
    "prompt": "将整个画面转换为黏土风格",
    "media": media,
    "resolution": "720P",
})

# Instruction editing with reference image
media = [
    {"type": "video", "url": "https://example.com/input.mp4"},
    {"type": "reference_image", "url": "https://example.com/hat.jpg"},
]
task_id = create_videoedit_task({
    "prompt": "为人物换上酷闪的衣服,再戴参考图里的帽子",
    "media": media,
    "audio_setting": "origin",
})

Error handling

ErrorLikely causeAction
401/403Missing or invalid DASHSCOPE_API_KEYCheck env var or credentials file
400 InvalidParameterBad resolution, missing video, too many reference imagesValidate parameters
"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-wan-videoedit/videos/
  • Override base dir with OUTPUT_DIR.

Anti-patterns

  • Do not use model names other than wan2.7-videoedit.
  • Do not call this API synchronously — async header is required.
  • Do not pass more than 1 video or more than 3 reference images.
  • Video URLs expire after 24 hours; download and persist immediately.
  • Do not use this API for video generation — use aliyun-wan-i2v instead.

Workflow

  1. Confirm user intent: style transfer or instruction-based editing.
  2. Prepare media array with video (required) and optional reference images.
  3. Create async task and poll for results.
  4. Download and save edited 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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Version
Latest version metadata

Version

v2026.09.25

Published

Sep 25, 2026

Category

Uncategorized

License

MIT

Source path

skills/ai/video/aliyun-wan-videoedit

Default branch

main

Latest commit

1818263

Tree SHA

1da6a31