mcpField
A
aliyun-liveportrait

aliyun-liveportrait

github.com/cinienceCreative & media39661 installsUpdated 11w ago
Repository

About aliyun-liveportrait

A skill for generating videos with Alibaba Cloud Model Studio LivePortrait, suited to turning a portrait image and speech audio into a talking-portrait clip. It supports image detection before generation and configurable templates and motion settings.

Key features

  1. 01Detect portrait input images
  2. 02Generate talking-portrait video from audio
  3. 03Choose normal, calm, or active templates
  4. 04Adjust eye, mouth, and head motion
  5. 05Poll tasks and retrieve video URLs

Use cases

  1. 01Create lightweight portrait animations
  2. 02Generate longer presenter-style clips

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/cinience/alicloud-skills --skill aliyun-liveportrait

After installing, type/aliyun-liveportraitin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

agents/
openai.yaml
references/
sources.md
scripts/
prepare_liveportrait_request.py

Details

From the project README

Category: provider

Model Studio LivePortrait

Validation

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

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

Output And Evidence

  • Save normalized request payloads, template choice, and task polling snapshots under output/aliyun-liveportrait/.
  • Record the exact portrait/audio URLs and motion-strength related parameters.

Use LivePortrait when the job is lightweight portrait animation with speech audio, especially for longer clips or simpler presenter-style motion.

Critical model names

Use these exact model strings:

  • liveportrait-detect
  • liveportrait

Selection guidance:

  • Run liveportrait-detect first to verify the portrait image.
  • Use liveportrait for the actual video generation task.

Prerequisites

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

Normalized interface (video.liveportrait)

Detect Request
  • model (string, optional): default liveportrait-detect
  • image_url (string, required)
Generate Request
  • model (string, optional): default liveportrait
  • image_url (string, required)
  • audio_url (string, required)
  • template_id (string, optional): normal, calm, or active
  • eye_move_freq (number, optional): 0 to 1
  • video_fps (int, optional): 15 to 30
  • mouth_move_strength (number, optional): 0 to 1.5
  • paste_back (bool, optional)
  • head_move_strength (number, optional): 0 to 1
Response
  • task_id (string)
  • task_status (string)
  • video_url (string, when finished)

Quick start

python skills/ai/video/aliyun-liveportrait/scripts/prepare_liveportrait_request.py \
  --image-url "https://example.com/portrait.png" \
  --audio-url "https://example.com/speech.mp3" \
  --template-id calm \
  --video-fps 24 \
  --paste-back

Operational guidance

  • Use a clear, front-facing portrait with low occlusion.
  • Keep the audio clean and voice-dominant.
  • paste_back=false outputs only the generated face region; keep it true for standard talking-head output.
  • LivePortrait is a better fit than EMO when you need longer, simpler presenter-style clips.

Output location

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

References

  • references/sources.md

Comments

Markdown supported