aliyun-cosyvoice-voice…
Use when creating cloned voices with Alibaba Cloud Model Studio CosyVoice customization models, especially cosyvoice-v3.5-plus or…
Use when editing videos with DashScope HappyHorse 1.0 video editing model (happyhorse-1.0-video-edit). Use when implementing instruction-based video editing such as style transfer or local replacement, optionally guided by 0-5 reference images, via the video-synthesis async API
$ npx -y skills add cinience/alicloud-skills --skill aliyun-happyhorse-videoedit --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/aliyun-happyhorse-videoeditContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when editing videos with DashScope HappyHorse 1.0 video editing model (happyhorse-1.0-video-edit). Use when implementing instruction-based video editing such as style transfer or local replacement, optionally guided by 0-5 reference images, via the video-synthesis async API
name: aliyun-happyhorse-videoedit description: Use when editing videos with DashScope HappyHorse 1.0 video editing model (happyhorse-1.0-video-edit). Use when implementing instruction-based video editing such as style transfer or local replacement, optionally guided by 0-5 reference images, via the video-synthesis async API on Alibaba Cloud Model Studio.
mkdir -p output/aliyun-happyhorse-videoedit python -m py_compile skills/ai/video/aliyun-happyhorse-videoedit/scripts/edit_happyhorse.py && echo "py_compile_ok" > output/aliyun-happyhorse-videoedit/validate.txt
Pass criteria: command exits 0 and `output/aliyun-happyhorse-videoedit/validate.txt` is generated.
python3 -m venv .venv . .venv/bin/activate python -m pip install requests
| Capability | Description | Required media | |---|---|---| | Style transfer | Convert the input video to a different visual style via a text instruction | exactly 1 `video` | | Local replacement / instruction edit | Replace or modify subjects guided by a prompt and optional reference images | 1 `video` + 0-5 `reference_image` |
POST https://dashscope.aliyuncs.com/api/v1/services/aigc/video-generation/video-synthesis
Required headers:
Singapore endpoint: replace `dashscope.aliyuncs.com` with `dashscope-intl.aliyuncs.com`.
Polling endpoint: `GET https://dashscope.aliyuncs.com/api/v1/tasks/{task_id}` — recommended interval 15s.
**Input video** (`type=video`):
**Reference image** (`type=reference_image`):
import os
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-edit task and return task_id."""
media = [{"type": "video", "url": req["video_url"]}]
for url in req.get("reference_images", []):
media.append({"type": "reference_image", "url": url})
if len(media) - 1 > 5:
raise ValueError("At most 5 reference images")
payload = {
"model": "happyhorse-1.0-video-edit",
"input": {"prompt": req["prompt"], "media": media},
"parameters": {
"resolution": req.get("resolution", "1080P"),
"watermark": req.get("watermark", True),
},
}
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()
return resp.json()["output"]["task_id"]
def poll_task(task_id: str, interval: int = 15) -> dict:
while True:
resp = requests.get(
f"{BASE_URL}/tasks/{task_id}",
headers={"Authorization": f"Bearer {API_KEY}"},
)
resp.raise_for_status()
data = resp.json()
if data["output"]["task_status"] in ("SUCCEEDED", "FAILED", "CANCELED"):
return data
time.sleep(interval)`
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