lel

Python X11 STT daemon that records audio, runs Whisper, logs the transcript, and can optionally run AI post-processing before injecting text.

Requirements

• X11 (not Wayland)
• sounddevice (PortAudio)
• faster-whisper
• llama-cpp-python
• Tray icon deps: gtk3, libayatana-appindicator3
• Python deps: pillow, python-xlib, faster-whisper, llama-cpp-python, PyGObject, sounddevice

System packages (example names): portaudio/libportaudio2.

Python Daemon

Install Python deps:

uv sync

Run:

uv run python3 src/leld.py --config ~/.config/lel/config.json

Config

Create ~/.config/lel/config.json:

{
  "daemon": { "hotkey": "Cmd+m" },
  "recording": { "input": "0" },
  "stt": { "model": "base", "device": "cpu" },
  "injection": { "backend": "clipboard" }
}

Recording input can be a device index (preferred) or a substring of the device name.

The LLM model is downloaded on first startup to ~/.cache/lel/models/ and uses the locked Llama-3.2-3B GGUF model. Pass -v/--verbose to see verbose logs, including llama.cpp loader logs; these messages are prefixed with llama::.

systemd user service

mkdir -p ~/.local/bin
cp src/leld.py ~/.local/bin/leld.py
cp systemd/lel.service ~/.config/systemd/user/lel.service
systemctl --user daemon-reload
systemctl --user enable --now lel

Usage

• Press the hotkey once to start recording.
• Press it again to stop and run STT.
• The transcript is logged to stderr.

Injection backends:

• clipboard: copy to clipboard and inject via Ctrl+Shift+V (GTK clipboard + XTest)
• injection: type the text with simulated keypresses (XTest)

AI provider:

• Generic OpenAI-compatible chat API at ai_base_url (base URL only; the app uses /v1/chat/completions)

Control:

make run