aliyun-emo

name	aliyun-emo
description	Use 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.
version	1.0.0

Category: provider

Model Studio EMO

Validation

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 And Evidence

• Save normalized request payloads, detection boxes, and task polling snapshots under output/aliyun-emo/.
• Record the chosen 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.

Critical model names

Use these exact model strings:

• emo-v1-detect
• emo-v1

Selection guidance:

• Run image detection first to obtain face_bbox and ext_bbox.
• Use emo-v1 only after detection succeeds.

Prerequisites

• China mainland (Beijing) only.
• Set DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials.
• Input files must be public HTTP/HTTPS URLs.

Normalized interface (video.emo)

Detect Request

• model (string, optional): default emo-v1-detect
• image_url (string, required)

Generate Request

• model (string, optional): default emo-v1
• image_url (string, required)
• audio_url (string, required)
• face_bbox (array, required)
• ext_bbox (array, required)
• style_level (string, optional): normal, calm, or active

Response

• task_id (string)
• task_status (string)
• video_url (string, when finished)

Quick start

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

Operational guidance

• Do not invent face_bbox or ext_bbox; use the detection API output.
• ext_bbox ratio determines output format: 1:1 yields 512x512, 3:4 yields 512x704.
• Keep the input portrait clear and front-facing for better expression quality.
• EMO is portrait-focused; for full-scene human videos use other skills instead.

Output location

• Default output: output/aliyun-emo/request.json
• Override base dir with OUTPUT_DIR.

References

• references/sources.md