TG Voice Whisper Transcriber

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name: tg-voice-whisper description: Auto-transcribe Telegram voice messages (.ogg Opus) to text using local OpenAI Whisper (tiny model). Reply with transcription + auto-delete file for privacy. No API keys, fully offline after install. emoji: 🎙️🔊

requires: bins: [whisper, ffmpeg]

install:

• kind: apt packages: [ffmpeg]
• kind: pip packages: [openai-whisper] flags: [--break-system-packages]

min-server: 4GB RAM recommended for fast/stable work (cached model <1s transcribe on 1vCPU).

Safe: Local-only, auto-rm files, no external APIs/credentials stored.

Usage (agent): When voice .ogg arrives in /root/.openclaw/media/inbound/:

exec 'whisper PATH --model tiny --language ru --output_format txt --output_dir /tmp/whisper; text=$(cat /tmp/whisper/*.txt); message action=send message="🔊 [text]" reply_to_current; rm PATH /tmp/whisper/*'

Auto-setup (non-block): Spawn sub-agent or cron every 5s:

sessions_spawn task="LOOP: find /root/.openclaw/media/inbound/*.ogg -mmin -1 → background whisper ru tiny → message reply text → rm" label="voice-auto" cleanup="keep"

Or cron:

cron add job={"name":"voice-auto","schedule":{"kind":"every","everyMs":5000},"payload":{"kind":"systemEvent","text":"🔊 VOICE_CHECK"},"sessionTarget":"main"}

Test: whisper /path.ogg --model tiny --language ru

Notes:

• First run: ~15s model download (72MB ~/.cache/whisper/tiny.bin).
• Cached: <1s on 1vCPU/4GB.
• Languages: ru/en best; --language detect auto.
• Accuracy: tiny 85-95% ru speech; upgrade to base/small for better.