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dsewell-583h0

Liveportrait

作者 dsewell-583h0 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install liveportrait
功能描述
Get animated portrait video ready to post, without touching a single slider. Upload your portrait images (JPG, PNG, WEBP, MP4, up to 200MB), say something li...
使用说明 (SKILL.md)

Getting Started

Got portrait images to work with? Send it over and tell me what you need — I'll take care of the AI portrait animation.

Try saying:

  • "animate a single front-facing photo of a person into a 1080p MP4"
  • "animate my portrait photo to talk and move naturally"
  • "animating still portrait photos into realistic talking videos for content creators, marketers, social media users"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: \x3Cuuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Live Portrait — Animate portraits into videos

This tool takes your portrait images and runs AI portrait animation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a single front-facing photo of a person and want to animate my portrait photo to talk and move naturally — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: front-facing, well-lit photos with a clear face produce the most realistic animations.

Matching Input to Actions

User prompts referencing liveportrait, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says... Action Skip SSE?
"export" / "导出" / "download" / "send me the video" → §3.5 Export
"credits" / "积分" / "balance" / "余额" → §3.3 Credits
"status" / "状态" / "show tracks" → §3.4 State
"upload" / "上传" / user sends file → §3.2 Upload
Everything else (generate, edit, add BGM…) → §3.1 SSE

Cloud Render Pipeline Details

Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint Method Purpose
/api/tasks/me/with-session/nemo_agent POST Start a new editing session. Body: {"task_name":"project","language":"\x3Clang>"}. Returns session_id.
/run_sse POST Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/\x3Csid> POST Upload a file (multipart) or URL.
/api/credits/balance/simple GET Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/\x3Csid>/latest GET Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda POST Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source: liveportrait
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

Error Handling

Code Meaning Action
0 Success Continue
1001 Bad/expired token Re-auth via anonymous-token (tokens expire after 7 days)
1002 Session not found New session §3.0
2001 No credits Anonymous: show registration URL with ?bind=\x3Cid> (get \x3Cid> from create-session or state response when needed). Registered: "Top up credits in your account"
4001 Unsupported file Show supported formats
4002 File too large Suggest compress/trim
400 Missing X-Client-Id Generate Client-Id and retry (see §1)
402 Free plan export blocked Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429 Rate limit (1 token/client/7 days) Retry in 30s once

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend says You do
"click [button]" / "点击" Execute via API
"open [panel]" / "打开" Query session state
"drag/drop" / "拖拽" Send edit via SSE
"preview in timeline" Show track summary
"Export button" / "导出" Execute export workflow

Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

Common Workflows

Quick edit: Upload → "animate my portrait photo to talk and move naturally" → Download MP4. Takes 30-60 seconds for a 30-second clip.

Batch style: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.

Iterative: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "animate my portrait photo to talk and move naturally" — concrete instructions get better results.

Max file size is 200MB. Stick to JPG, PNG, WEBP, MP4 for the smoothest experience.

Export as MP4 for widest compatibility across social platforms.

安全使用建议
This skill appears to do what it claims (animate portraits by sending your images to nemovideo's API) and only requests a single token (NEMO_TOKEN). Before installing: (1) be aware that your images/audio will be uploaded to an external service — do not upload sensitive or private images unless you trust the provider; (2) provenance is weak (no homepage, unknown owner); consider whether you trust the endpoint mega-api-prod.nemovideo.ai and search for the service and privacy policy; (3) note the metadata mismatch: SKILL.md mentions a config path (~/.config/nemovideo/) and asks the agent to read this SKILL.md frontmatter and detect install paths — that suggests filesystem reads that were not declared in the registry metadata; if you need stricter guarantees, ask the skill author to clarify why the configPath is required and to publish a homepage/privacy policy and source. If you proceed, avoid using highly sensitive images and rotate any tokens or credentials if you stop using the skill.
功能分析
Type: OpenClaw Skill Name: liveportrait Version: 1.0.0 The skill is a functional integration for a cloud-based AI video animation service (LivePortrait) hosted at nemovideo.ai. It provides clear instructions for the agent to manage authentication tokens, handle file uploads, and interact with a rendering pipeline. The requested permissions (environment variables and a specific config path) and network activities are consistent with the stated purpose of processing media files via a third-party API, and the instructions include security-conscious directives such as not printing raw tokens.
能力评估
Purpose & Capability
Name/description (animate portrait images) align with the runtime instructions: the SKILL.md describes uploading images, creating sessions, streaming edits, and exporting MP4 via the nemovideo API. Requesting a single service token (NEMO_TOKEN) is proportional to this purpose. However, the skill has no published homepage or known source, which reduces provenance and increases risk.
Instruction Scope
Instructions explicitly tell the agent to obtain/use NEMO_TOKEN, generate an anonymous token when missing, POST files and messages to mega-api-prod.nemovideo.ai, and stream SSE results. Those are all consistent with the stated function. Concern: the SKILL.md metadata asks the agent to read this file's YAML frontmatter at runtime and to detect install paths (e.g. ~/.clawhub/, ~/.cursor/). The registry metadata shown to you earlier claims no required config paths while the SKILL.md includes a configPaths entry (~/.config/nemovideo/). That mismatch implies either the published registry info is incomplete or the runtime instructions expect filesystem access that wasn't declared.
Install Mechanism
Instruction-only skill with no install spec and no code files — lowest install risk. The skill issues network requests to a third-party API, but it does not download or install code.
Credentials
Only NEMO_TOKEN (primary credential) is required and the SKILL.md includes a path to acquire an anonymous token if none is set. This is proportional to a cloud rendering service. Note: the skill will upload user media to an external service (expected for the purpose); users should be aware this transmits potentially sensitive image/audio data off-device.
Persistence & Privilege
always:false and no install hooks are present. The skill does not request persistent platform privileges and does not attempt to modify other skills or system-wide config. It asks the agent to store session_id and use tokens for the session (normal for a remote API).
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install liveportrait
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /liveportrait 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release of Live Portrait — instantly animate portrait images into ready-to-post talking videos. - Upload a portrait image (JPG, PNG, WEBP, MP4 up to 200MB) and describe your desired animation in plain language. - AI animates still portrait photos into lifelike 1080p MP4 videos, typically in 30–60 seconds. - Seamless onboarding with auto token/session setup — no manual config required. - Supports file uploads, export/download, status tracking, and credit checks. - Clear user flows for uploading, editing, exporting, and handling errors or session issues.
元数据
Slug liveportrait
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Liveportrait 是什么?

Get animated portrait video ready to post, without touching a single slider. Upload your portrait images (JPG, PNG, WEBP, MP4, up to 200MB), say something li... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 93 次。

如何安装 Liveportrait?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install liveportrait」即可一键安装,无需额外配置。

Liveportrait 是免费的吗?

是的,Liveportrait 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Liveportrait 支持哪些平台?

Liveportrait 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Liveportrait?

由 dsewell-583h0(@dsewell-583h0)开发并维护,当前版本 v1.0.0。

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