OpenAI Whisper — Speech-to-Text

SkillMedia

Local speech-to-text with the Whisper CLI (no API key).

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the OpenAI Whisper — Speech-to-Text skill

What this skill tells your AI

The instructions your AI receives, as published by argentaios/argentos-core in skills/openai-whisper/SKILL.md and read by ahel’s review.

Transcribe audio files using OpenAI's Whisper model. Two modes available depending on your needs:

ModeLatencyCostPrivacySetup
Local CLISlower (on-device GPU/CPU)FreeAudio never leaves machineInstall whisper binary
Cloud APIFastPer-minute pricingAudio sent to OpenAIOPENAI_API_KEY required

Mode 1: Local CLI

Run Whisper locally with no API key required. Models download to ~/.cache/whisper on first run.

Quick Start

whisper /path/audio.mp3 --model medium --output_format txt --output_dir .

Common Commands

# Transcribe to text file
whisper /path/audio.mp3 --model medium --output_format txt --output_dir .

# Transcribe with translation to English
whisper /path/audio.m4a --task translate --output_format srt

# Transcribe with specific language
whisper /path/audio.wav --model large --language en --output_format json

Model Selection

ModelSpeedAccuracyVRAM
tinyFastestLowest~1 GB
baseFastLow~1 GB
smallMediumGood~2 GB
mediumSlowBetter~5 GB
largeSlowestBest~10 GB
turboFastGood (default)~6 GB

Output Formats

  • txt — Plain text transcript
  • srt — SubRip subtitle format with timestamps
  • vtt — WebVTT subtitle format
  • json — Detailed JSON with word-level timestamps
  • tsv — Tab-separated values

Notes

  • --model defaults to turbo on most installs
  • Use smaller models for speed, larger for accuracy
  • GPU acceleration used automatically when available

Mode 2: Cloud API

Transcribe via OpenAI's /v1/audio/transcriptions endpoint. Faster for large batches, no local GPU needed.

Quick Start

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

Defaults:

  • Model: whisper-1
  • Output: <input>.txt

Common Commands

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

# Specify model and output
{baseDir}/scripts/transcribe.sh /path/to/audio.ogg --model whisper-1 --out /tmp/transcript.txt

# With language hint
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --language en

# With speaker name hints (improves accuracy)
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --prompt "Speaker names: Peter, Daniel"

# JSON output with timestamps
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --json --out /tmp/transcript.json

Raw curl Example

curl https://api.openai.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F file="@/path/to/audio.m4a" \
  -F model="whisper-1" \
  -F response_format="text"

API Key Setup

Set OPENAI_API_KEY environment variable, or configure in ~/.clawdbot/clawdbot.json:

{
  skills: {
    "openai-whisper-api": {
      apiKey: "OPENAI_KEY_HERE"
    }
  }
}

Choosing Between Modes

ConsiderationLocal CLICloud API
Privacy-sensitive audioBestAudio sent to OpenAI
Large batch processingSlow without GPUFast and parallel
Offline usageWorks offlineRequires internet
CostFree (hardware cost)Per-minute pricing
Setup complexityInstall binary + modelsAPI key only
Audio format supportMost formatsMost formats

Signals

GitHub stars
126
Forks
22
Last commit
Jul 2026

ahel review

  • S4info
    community integration — published by argentaios, not openai

Automated review, not a security audit. Ruleset v1.

Others that do the same job

Advanced
Catalog kind
skill
Gateway key
openai-whisper
Source
github.com/argentaios/argentos-core