cinience/alicloud-skills/aliyun-happyhorse-test

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Minimal smoke test matrix for the four Model Studio HappyHorse 1.0 video skills (t2v, i2v, r2v, video-edit).

Install

npx vskill@latest install cinience/alicloud-skills/aliyun-happyhorse-test

SKILL.md

Category: test

Minimal Viable Test (HappyHorse 1.0 Family)

Goals

  • Validate the smallest viable request payload for each of the four HappyHorse skills (t2v, i2v, r2v, video-edit).
  • If execution fails, record exact error details (HTTP status, code, message, request_id) without guessing parameters.

Prerequisites

  • Authentication: DASHSCOPE_API_KEY exported, or dashscope_api_key configured in ~/.alibabacloud/credentials.
  • Region: Beijing endpoint by default (override with DASHSCOPE_BASE_URL if testing Singapore).
  • Target skills under test:
  • skills/ai/video/aliyun-happyhorse-t2v
  • skills/ai/video/aliyun-happyhorse-i2v
  • skills/ai/video/aliyun-happyhorse-r2v
  • skills/ai/video/aliyun-happyhorse-videoedit

Test Steps (Minimal)

For each model, send the smallest valid request and poll until terminal status. Save the full response JSON to output/aliyun-happyhorse-test/<model>.json.

1. t2v — happyhorse-1.0-t2v
bash
.venv/bin/python skills/ai/video/aliyun-happyhorse-t2v/scripts/t2v_happyhorse.py \
--prompt "A red kite flying over a green hill at sunset." \
--resolution 720P \
--duration 3 \
--output output/aliyun-happyhorse-test/t2v
2. i2v — happyhorse-1.0-i2v
bash
.venv/bin/python skills/ai/video/aliyun-happyhorse-i2v/scripts/i2v_happyhorse.py \
--first-frame https://cdn.translate.alibaba.com/r/wanx-demo-1.png \
--prompt "A cat running on grass." \
--resolution 720P \
--duration 3 \
--output output/aliyun-happyhorse-test/i2v
3. r2v — happyhorse-1.0-r2v
bash
.venv/bin/python skills/ai/video/aliyun-happyhorse-r2v/scripts/r2v_happyhorse.py \
--reference-image https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20260424/mvzfud/hh-v2v-girl.jpg \
--prompt "character1 turns slowly to face the camera." \
--resolution 720P \
--ratio 16:9 \
--duration 3 \
--output output/aliyun-happyhorse-test/r2v
4. video-edit — happyhorse-1.0-video-edit
bash
.venv/bin/python skills/ai/video/aliyun-happyhorse-videoedit/scripts/edit_happyhorse.py \
--video https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20260409/dozxak/Wan_Video_Edit_33_1.mp4 \
--prompt "Convert the scene to a watercolor painting style." \
--resolution 720P \
--audio-setting origin \
--output output/aliyun-happyhorse-test/videoedit

Offline-only fallback (no API key)

If DASHSCOPE_API_KEY is unavailable, run only the static syntax checks and record results:

bash
mkdir -p output/aliyun-happyhorse-test
for s in t2v i2v r2v videoedit; do
case "$s" in
videoedit) script="edit_happyhorse.py" ;;
*) script="${s}_happyhorse.py" ;;
esac
python -m py_compile "skills/ai/video/aliyun-happyhorse-$s/scripts/$script" \
&& echo "py_compile_ok $s" >> output/aliyun-happyhorse-test/offline.txt
done

Pass criteria

  • Each of the four executable examples exits 0 with task_status: SUCCEEDED and a downloadable video_url, OR — in offline-only mode — output/aliyun-happyhorse-test/offline.txt contains four py_compile_ok lines (one per model).
  • For any FAILED task, code and message are recorded verbatim under output/aliyun-happyhorse-test/<model>.json.

Result Template

  • Date: YYYY-MM-DD
  • Skills under test:
  • skills/ai/video/aliyun-happyhorse-t2v
  • skills/ai/video/aliyun-happyhorse-i2v
  • skills/ai/video/aliyun-happyhorse-r2v
  • skills/ai/video/aliyun-happyhorse-videoedit
  • Mode: live / offline-only
  • Conclusion per model: t2v=pass|fail, i2v=pass|fail, r2v=pass|fail, videoedit=pass|fail
  • Notes:

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
396
Repository forks
35
7-day trend score
30

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 1 Sep 2026, a month ago.

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