Local Whisper

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

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.

• ✅ Free forever
• ✅ Private (audio never leaves your Mac)
• ✅ Fast (~1 second per message)
• ✅ Works offline

⚠️ Important Notes

• First run downloads ~1.5GB model — be patient, this only happens once
• First transcription is slow — 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 → English:

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

Requirements

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

License

MIT