modbender Faster Whisper Local Service
Provision a local STT backend used by voice skills.
What this sets up
- Python venv for faster-whisper
transcribe-server.pyHTTP endpoint athttp://127.0.0.1:18790/transcribe- systemd user service:
openclaw-transcribe.service
Important: Model download on first run
On first startup, faster-whisper downloads model weights from Hugging Face (~1.5 GB for medium). This requires internet access and disk space. After the initial download, models are cached locally and the service runs fully offline.
| Model | Download size | RAM usage |
|---|---|---|
| tiny | ~75 MB | ~400 MB |
| base | ~150 MB | ~500 MB |
| small | ~500 MB | ~800 MB |
| medium | ~1.5 GB | ~1.4 GB |
| large-v3 | ~3.0 GB | ~3.5 GB |
To pre-download models in an air-gapped environment, see faster-whisper docs.
Security notes
- gst-launch-1.0: The service uses GStreamer's
decodebinto convert incoming audio to WAV. While arguments are passed as a list (no shell injection), processing untrusted/malformed audio files carries inherent risk through GStreamer's media parsers. Ensuregst-launch-1.0is installed from your OS vendor's trusted packages. - Bind address: The service binds to
127.0.0.1only (not exposed externally). - CORS: Restricted to a single origin by default (
https://127.0.0.1:8443). - No credentials: The skill does not request any API keys or secrets.
Security and reproducibility defaults
- pinned package install:
faster-whisper==1.1.1(override via env) - explicit dependency check for
gst-launch-1.0 - CORS is restricted to one origin by default:
https://127.0.0.1:8443(override via env) - configurable workspace/service paths (no hardcoded user path required)
Deploy
bash scripts/deploy.sh
With custom settings:
WORKSPACE=~/.openclaw/workspace \
TRANSCRIBE_PORT=18790 \
WHISPER_MODEL_SIZE=medium \
WHISPER_LANGUAGE=auto \
TRANSCRIBE_ALLOWED_ORIGIN=https://10.0.0.42:8443 \
bash scripts/deploy.sh
Language setting
Default: auto (auto-detect language). Set WHISPER_LANGUAGE=de for German-only, en for English-only, etc. Fixed language is faster and more accurate if you only use one language.
Idempotent: safe to run repeatedly.
What this skill modifies
| What | Path | Action |
|---|---|---|
| Python venv | $WORKSPACE/.venv-faster-whisper/ |
Creates venv, installs faster-whisper via pip |
| Transcribe server | $WORKSPACE/voice-input/transcribe-server.py |
Writes server script |
| Systemd service | ~/.config/systemd/user/openclaw-transcribe.service |
Creates + enables persistent service |
| Model cache | ~/.cache/huggingface/ |
Downloads model weights on first run |
Uninstall
systemctl --user stop openclaw-transcribe.service
systemctl --user disable openclaw-transcribe.service
rm -f ~/.config/systemd/user/openclaw-transcribe.service
systemctl --user daemon-reload
Optional full cleanup:
rm -rf ~/.openclaw/workspace/.venv-faster-whisper
rm -f ~/.openclaw/workspace/voice-input/transcribe-server.py
Verify
bash scripts/status.sh
Expected:
- service
active - endpoint responds (HTTP 200/500 acceptable for invalid sample payload)
Notes
- This skill provides backend transcription only.
- Pair with
webchat-voice-proxyfor browser mic + HTTPS/WSS integration. - For one-step install, use
webchat-voice-full-stack(deploys backend + proxy in order).