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πŸ¦€ ClawHub

Local Whisper

by @impkind

Free local speech-to-text for Telegram and WhatsApp using MLX Whisper on Apple Silicon. Private, no API costs.

Versionv1.5.0
Downloads3,785
Stars⭐ 9
TERMINAL
clawhub install whisper-mlx-local

πŸ“– About This Skill


name: whisper-mlx-local description: "Free local speech-to-text for Telegram and WhatsApp using MLX Whisper on Apple Silicon. Private, no API costs." metadata: openclaw: emoji: "🎀" version: "1.5.0" author: "Community" repo: "https://github.com/ImpKind/local-whisper" requires: os: ["darwin"] arch: ["arm64"] bins: ["python3"] install: - id: "deps" kind: "manual" label: "Install dependencies" instructions: "pip3 install -r requirements.txt"

Local Whisper

Transcribe voice messages for free on Telegram and WhatsApp. No API keys. No costs. Runs on your Mac.

The Problem

Voice transcription APIs cost money:

  • OpenAI Whisper: $0.006/minute
  • Groq: $0.001/minute
  • AssemblyAI: $0.01/minute
  • If you transcribe a lot of Telegram voice messages, it adds up.

    The Solution

    This skill runs Whisper locally on your Mac. Same quality, zero cost.

  • βœ… Free forever
  • βœ… Private (audio never leaves your Mac)
  • βœ… Fast (~1 second per message)
  • βœ… Works offline
  • ⚠️ Important Notes

  • First run downloads ~1.5GB model β€” be patient, this only happens once
  • First transcription is slow β€” model loads into memory (~10-30 seconds), then it's instant
  • Already using OpenAI API for transcription? Replace your existing tools.media.audio config with the one below
  • Quick Start

    1. Install dependencies

    pip3 install -r requirements.txt
    

    2. Start the daemon

    python3 scripts/daemon.py
    
    First run will download the Whisper model (~1.5GB). Wait for "Ready" message.

    3. Add to OpenClaw config

    Add this to your ~/.openclaw/openclaw.json:

    {
      "tools": {
        "media": {
          "audio": {
            "enabled": true,
            "models": [
              {
                "type": "cli",
                "command": "~/.openclaw/workspace/skills/local-whisper/scripts/transcribe.sh",
                "args": ["{{MediaPath}}"],
                "timeoutSeconds": 60
              }
            ]
          }
        }
      }
    }
    

    4. Restart gateway

    openclaw gateway restart
    

    Now voice messages from Telegram, WhatsApp, etc. will be transcribed locally for free!

    Manual test

    ./scripts/transcribe.sh voice_message.ogg
    

    Use Case: Telegram Voice Messages

    Instead of paying for OpenAI API to transcribe incoming voice messages, point OpenClaw to this local daemon. Free transcription forever.

    Auto-Start on Login

    cp com.local-whisper.plist ~/Library/LaunchAgents/
    launchctl load ~/Library/LaunchAgents/com.local-whisper.plist
    

    API

    Daemon runs at localhost:8787:

    curl -X POST http://localhost:8787/transcribe -F "file=@audio.ogg"
    

    {"text": "Hello world", "language": "en"}

    Translation

    Any language β†’ English:

    ./scripts/transcribe.sh spanish_audio.ogg --translate
    

    Requirements

  • macOS with Apple Silicon (M1/M2/M3/M4)
  • Python 3.9+
  • License

    MIT

    πŸ’‘ Examples

    1. Install dependencies

    pip3 install -r requirements.txt
    

    2. Start the daemon

    python3 scripts/daemon.py
    
    First run will download the Whisper model (~1.5GB). Wait for "Ready" message.

    3. Add to OpenClaw config

    Add this to your ~/.openclaw/openclaw.json:

    {
      "tools": {
        "media": {
          "audio": {
            "enabled": true,
            "models": [
              {
                "type": "cli",
                "command": "~/.openclaw/workspace/skills/local-whisper/scripts/transcribe.sh",
                "args": ["{{MediaPath}}"],
                "timeoutSeconds": 60
              }
            ]
          }
        }
      }
    }
    

    4. Restart gateway

    openclaw gateway restart
    

    Now voice messages from Telegram, WhatsApp, etc. will be transcribed locally for free!

    Manual test

    ./scripts/transcribe.sh voice_message.ogg