360 Secure SkillHub
360 安全技能中心

K8s Self Hosted Whisper Api

该 Skill 提供 shell 脚本，调用自托管的 Whisper ASR webservice，将音频转写为 txt、json、srt、vtt 或 tsv，可启用英文翻译、VAD 过滤和词级时间戳；需要 curl、网络访问及可用的 ASR 服务。

xavjer
xavjer
热度 85.74
最近更新 2026-05-18 12:11:09
分类：效率依赖：代码执行 / 读写文件 / 第三方 API应用场景：文件转换 / 翻译 / 自动化脚本

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add openclaw-self-hosted-whisper
Metadata
name
self-hosted-whisper-api
description
Transcribe audio via the self-hosted Whisper ASR instance running on Kubernetes. Use this skill whenever the user wants to transcribe audio files, convert speech to text, generate subtitles, or translate audio. Triggers on audio transcription, speech-to-text, whisper, voice-to-text, subtitle generation, or audio translation requests.
version
1.0.0
user-invocable
true
metadata
{"openclaw":{"emoji":"🎙️","requires":{"bins":["curl"]}}}

Self-Hosted Whisper API (curl)

Transcribe an audio file via the Whisper ASR webservice at http://whisper-asr.whisper-asr.svc.cluster.local:9000.

Uses the onerahmet/openai-whisper-asr-webservice API (/asr endpoint).

Quick start

{baseDir}/scripts/transcribe.sh /path/to/audio.m4a

Defaults:

  • Endpoint: http://whisper-asr.whisper-asr.svc.cluster.local:9000/asr
  • Task: transcribe
  • Output: txt

Useful flags

{baseDir}/scripts/transcribe.sh /path/to/audio.ogg --language en --out /tmp/transcript.txt
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --language de
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --json --out /tmp/transcript.json
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --output srt --out /tmp/subtitles.srt
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --output vtt
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --translate
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --vad-filter --json
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --word-timestamps --json

Notes

  • Supported --output formats: txt, json, vtt, srt, tsv
  • --translate produces an English transcript regardless of source language
  • --vad-filter enables voice activity detection to skip silent sections
  • --word-timestamps adds word-level timing (use with --json)
  • The model is configured on the server side (ASR_MODEL env var), not per request
  • Swagger docs available at http://whisper-asr.whisper-asr.svc.cluster.local:9000/docs
  • No authentication required