Install
openclaw skills install aliyun-emoUse when generating expressive portrait videos from a person image and speech audio with Alibaba Cloud Model Studio EMO (`emo-v1`). Use when creating non-Wan avatar clips with stronger expression style control from a detected portrait image.
openclaw skills install aliyun-emoCategory: provider
mkdir -p output/aliyun-emo
python -m py_compile skills/ai/video/aliyun-emo/scripts/prepare_emo_request.py && echo "py_compile_ok" > output/aliyun-emo/validate.txt
Pass criteria: command exits 0 and output/aliyun-emo/validate.txt is generated.
output/aliyun-emo/.style_level and the exact face_bbox / ext_bbox.Use EMO when the input is a portrait image and speech audio, and you need a non-Wan expressive talking-head result.
Use these exact model strings:
emo-v1-detectemo-v1Selection guidance:
face_bbox and ext_bbox.emo-v1 only after detection succeeds.DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials.model (string, optional): default emo-v1-detectimage_url (string, required)model (string, optional): default emo-v1image_url (string, required)audio_url (string, required)face_bbox (array<int>, required)ext_bbox (array<int>, required)style_level (string, optional): normal, calm, or activetask_id (string)task_status (string)video_url (string, when finished)python skills/ai/video/aliyun-emo/scripts/prepare_emo_request.py \
--image-url "https://example.com/portrait.png" \
--audio-url "https://example.com/speech.mp3" \
--face-bbox 302,286,610,593 \
--ext-bbox 71,9,840,778 \
--style-level active
face_bbox or ext_bbox; use the detection API output.ext_bbox ratio determines output format: 1:1 yields 512x512, 3:4 yields 512x704.output/aliyun-emo/request.jsonOUTPUT_DIR.references/sources.md