AgentSkillsCN

whisper-transcribe-docker

在Docker中使用faster-whisper（本地运行，无需API密钥）进行语音转文字（逐字稿/转写）。当您已拥有音频文件（例如来自`media-audio-download`），并需要一份带有可选时间戳的转录文本，以供摘要使用时，可使用此技能。

SKILL.md
--- frontmatter
name: whisper-transcribe-docker
description: Speech-to-text (逐字稿/转写) in Docker using faster-whisper (local, no API key). Use when you already have an audio file (e.g. from `media-audio-download`) and need a transcript with optional timestamps for summarization.

Whisper Transcribe (Docker, faster-whisper)

This skill turns an audio file into a transcript locally (no OpenAI key).

Use with media-audio-download:

  1. •Download audio -> out/*.m4a
  2. •Transcribe -> out/*.txt (or JSON)

Quick Start

Build image:

bash
docker build -t moltbot-whisper-transcribe {baseDir}

Transcribe an audio file (writes plain text to stdout by default):

bash
docker run --rm -v "$PWD:/work" -v whisper-models:/models \
  moltbot-whisper-transcribe /work/out/audio.m4a --model small

If huggingface.co is blocked/unreachable in your network, set a mirror endpoint:

bash
docker run --rm -e HF_ENDPOINT='https://hf-mirror.com' -v "$PWD:/work" -v whisper-models:/models \
  moltbot-whisper-transcribe /work/out/audio.m4a --model small

Write transcript to a file:

bash
docker run --rm -v "$PWD:/work" -v whisper-models:/models \
  moltbot-whisper-transcribe /work/out/audio.m4a --model small --out /work/out/audio.txt

With timestamps:

bash
docker run --rm -v "$PWD:/work" -v whisper-models:/models \
  moltbot-whisper-transcribe /work/out/audio.m4a --model small --timestamps --out /work/out/audio.txt

Notes:

  • •First run downloads model weights (cached in the whisper-models Docker volume).
  • •For speed, start with --model tiny / --model base.
  • •For quality, use --model medium (CPU will be slower).