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douyin-video-transcribe抖音视频转录

Agent Skill

用于辅助视频生成、动画合成、脚本化剪辑或 Remotion 等视频项目开发。它适合让 Agent 组织镜头、生成素材说明、维护合成代码或排查渲染问题。使用时需要确认分辨率、时长、素材路径和导出格式;涉及外部素材、人物肖像或商业发布时,应先核对版权授权和内容审核要求。

总安装

13,030

周安装

554

GitHub Stars

公开资料未说明

下载量

4,565
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:douyin-video-transcribe(抖音视频转录)
来源仓库:https://github.com/don068589/douyin-video-transcribe
安装命令:
openclaw skills install douyin-video-transcribe
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install douyin-video-transcribe

简介

从抖音视频提取音频并使用 Whisper 进行转录。

  • 支持本地网络与云端两种音频处理模式。
  • 适用于内容转写与多语言字幕生成。
  • 安装命令:openclaw skills install douyin-video-transcribe,需安装 ffmpeg 与 Whisper 模型。
  • 大文件转录可能消耗较多计算资源与时间。

SKILL.md

name
douyin-transcribe
description
Douyin video transcription suite. Extract audio from Douyin/TikTok China videos, transcribe with Whisper, and analyze content. Supports video links, local files, and image notes. Trigger when user sends a Douyin link and asks for transcription, summary, or analysis.

Douyin Transcribe - Video Transcription Suite

A complete solution for transcribing Douyin (抖音/TikTok China) videos. Extracts audio, transcribes speech to text, and generates structured summaries.

Version History

VersionChanges
2.0.0Modular architecture, improved workflow, browser DOM extraction
1.0.0Initial release, basic transcription

Architecture

\\\ User Input (Douyin Link/File) │ ▼ ┌─────────────────────────────────────────┐ │ Workflow Orchestrator │ ├─────────────────────────────────────────┤ │ Step 1: Fetcher → Get video file │ │ Step 2: Transcriber → Extract & convert│ │ Step 3: Analyzer → Structure output │ │ Step 4: Output → Save results │ └─────────────────────────────────────────┘ \\\

Core Features

  • Video Fetching: Browser-based DOM extraction for CDN URLs
  • Audio Extraction: ffmpeg-powered audio conversion
  • Speech-to-Text: Whisper ASR with multiple model options
  • Content Analysis: Auto-structured transcripts with key points
  • Multi-format Support: Video links, local files, image notes

Prerequisites

ToolPurposeInstall
curlDownload filesBuilt-in (Windows: \curl.exe\)
ffmpegAudio extraction/merge\winget install Gyan.FFmpeg\
WhisperTranscription\pip install openai-whisper\ or Docker
BrowserVideo extractionOpenClaw profile required

Docker Whisper (Recommended): \\\\bash docker run -d -p 9000:9000 --name whisper-asr onerahmet/openai-whisper-asr-webservice:latest \\\

Workflow

Step 0: Input Classification

Input TypeDetectionAction
Video link (\/video/\)URL patternFull workflow
Image note (\/note/\)URL patternSnapshot only
Local video fileFile pathStart from Step 2
Text inputPlain textStart from Step 3

Step 1: Fetch Video

1.1 Resolve Short URL

\\\\bash

Windows PowerShell

curl.exe -sL -o NUL -w "%{url_effective}" "https://v.douyin.com/xxx/"

macOS/Linux

curl -sL -o /dev/null -w '%{url_effective}' "https://v.douyin.com/xxx/" \\\

Output: \https://www.douyin.com/video/7616020798351871284\

1.2 Open Video Page

\\\ browser(action='open', profile='openclaw', url='https://www.douyin.com/video/{VIDEO_ID}') \\\

Wait 10-15 seconds for page to load completely.

1.3 Extract Video URL (Browser DOM Method)

\\\javascript browser(action='act', targetId='PAGE_ID', request={ "kind": "evaluate", "fn": "(() => { const entries = performance.getEntriesByType('resource'); const videoEntries = entries.filter(e => { const name = e.name.toLowerCase(); return name.includes('douyinvod') && (name.includes('.mp4') || name.includes('video')); }); if (videoEntries.length > 0) { const video = videoEntries[videoEntries.length - 1]; return { url: video.name, type: video.name.includes('.mp4') ? 'mp4' : 'dash' }; } return null; })()" }) \\\

Important Notes:

  • \ct\ action requires nested \ equest\ object with \kind\ and \\fn\
  • Wrong: \\browser(action='act', fn='...')\
  • Correct: \\browser(action='act', request={"kind": "evaluate", "fn": "..."})\

1.4 Download Video

\\\\bash curl.exe -L -H "Referer: https://www.douyin.com/" -o video.mp4 "<CDN_URL>" \\\

Referer header is required, otherwise 403.

Step 2: Transcribe Audio

2.1 Extract Audio

\\\\bash

For MP4 videos

ffmpeg -i video.mp4 -ar 16000 -ac 1 -c:a pcm_s16le audio.wav -y

For DASH videos (need merge)

ffmpeg -i video.mp4 -i audio.mp4 -c copy merged.mp4 -y ffmpeg -i merged.mp4 -ar 16000 -ac 1 -c:a pcm_s16le audio.wav -y \\\

Parameters:

  • \-ar 16000\: 16kHz sample rate (Whisper requirement)
  • \-ac 1\: Mono channel
  • \-c:a pcm_s16le\: 16-bit PCM

2.2 Transcribe with Docker Whisper

\\\\bash curl.exe -X POST "http://localhost:PORT/asr" -F "audio_file=@audio.wav" \\\

2.3 Alternative: Local Whisper

\\\\bash python -m whisper audio.wav --model small --language zh \\\

Model Selection:

ModelSize5-min Video (CPU)AccuracyUse Case
tiny75MB~30sFairQuick preview
base142MB~1minGoodDaily use
small466MB~3minBetterRecommended
medium1.5GB~8minBestHigh accuracy

Step 3: Analyze Content

Agent processes transcript and generates:

  1. Fix transcription errors

- Correct homophones - Fix speaker names - Remove filler words

  1. Structure content

- Add paragraph breaks - Create sections

  1. Extract key points

- Main ideas - Important quotes

  1. Generate tags

- 3-5 topic tags

Step 4: Save Output

Transcript Format

\\\markdown

{Title}

作者: {Author} 来源: 抖音 日期: {Date} 转录时间: {Transcription Date}


摘要

{Summary}


正文

{Transcript content with paragraphs}


要点

  • {Key point 1}
  • {Key point 2}
  • {Key point 3}

标签

#{tag1} #{tag2} #{tag3} \\\

File Naming Convention

\\\ {VIDEO_ID}-抖音转录.md \\\

Troubleshooting

StageIssueSolution
Step 1Short URL failsCheck link completeness, remove share text
Step 1JS returns nullWait 15-20s and retry, increase timeout
Step 1Download 403URL expired, re-fetch from browser
Step 1DASH no audioMerge with \\ffmpeg -i video -i audio -c copy\
Step 2ffmpeg not installed\winget install Gyan.FFmpeg\
Step 2Whisper service down\docker start whisper-asr\
Step 2Transcription slow10-min video takes 15-20 min on CPU
Step 2Poor qualityUse larger model (medium)

Image Note Handling

Image notes (\/note/\) don't need transcription:

\\\

  1. browser(action='open', profile='openclaw', url='IMAGE_NOTE_URL')
  2. browser(action='snapshot')
  3. Extract content from snapshot
  4. Save to output directory

\\\

Edge Cases

  • Article links (\/article/\): Use browser snapshot, no transcription
  • Douyin AI summary: Extract from page as supplement
  • Other platforms: Use yt-dlp for YouTube/Bilibili
  • Live streams: Not supported

Related Modules

This skill can be extended with standalone modules:

ModulePurpose
douyin-fetcherVideo fetching only
douyin-transcriberAudio transcription only
douyin-analyzerContent analysis only
douyin-orchestratorWorkflow coordination

License

MIT-0 License - Free to use, modify, and redistribute.

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