blitztext-app-linux/linux
mARTin-B78 15f8c1d9f7 install: auto-install python3-gi and other missing apt deps
Check for python3-gi (PyGObject), xdotool, libnotify-bin, and pipewire-bin
before creating the venv; if any are missing, run sudo apt-get install
automatically so the install works out of the box on a fresh system.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-08 20:24:41 +02:00
..
blitztext gtksettings: align Input tab labels to uniform 175px width; autostart: add 12s delay 2026-06-08 20:00:33 +02:00
packaging overlay: drive waveform + silence countdown via pw-record (fix PipeWire); app reports as "Blitztext" not __main__.py; Release 1.7.1 2026-06-08 08:39:37 +02:00
tests routing: send-by-voice keyword (types + presses Enter); wakeword benchmark via TTS; Release 1.8.0 2026-06-08 13:17:33 +02:00
.gitignore Add Debian (.deb) installer (v1.1.0) 2026-06-04 09:25:32 +02:00
blitztext.service Add Blitztext for Linux v1.0.0 — native dictation tool 2026-06-03 22:44:28 +02:00
CHANGELOG.md settings: lazy-build tabs (instant open); move connection dots beside the field; single-instance Settings dialog; Release 1.9.1 2026-06-08 19:30:08 +02:00
install.sh install: auto-install python3-gi and other missing apt deps 2026-06-08 20:24:41 +02:00
README.md routing: send-by-voice keyword (types + presses Enter); wakeword benchmark via TTS; Release 1.8.0 2026-06-08 13:17:33 +02:00
requirements.txt Add realtime streaming and Linux app docs 2026-06-05 15:06:17 +02:00

Blitztext for Linux (native dictation)

A native Linux port of the Blitztext workflow: focus any text field → press a hotkey → speak → the text is typed into that field, optionally rewritten by an LLM first (e.g. turn rough speech into a nicer, more detailed email).

This runs on the host (not in a container), so it can type into any application — the Linux equivalent of the macOS app's Accessibility-based auto-paste. (A sandboxed Docker/browser version can't do that; an earlier experiment along those lines was moved out to ~/Docker/correspondence/blitztext.) Batch transcription is local via faster-whisper; live streaming can use a local Riva/NIM realtime server. Only the optional rewrite step calls out to an LLM.

Blitztext control panel    Blitztext system-tray menu

Inspiration

Blitztext App Linux is inspired by cmagnussen/blitztext-app, the original macOS menu-bar workflow for turning speech into text and cleaner writing. This Linux version keeps the workflow but uses Linux-native pieces: GTK, AppIndicator, global hotkeys, faster-whisper, optional Riva/NIM realtime STT, and xdotool.

How it works

hotkey ──▶ record mic (pw-record/arecord) ──▶ faster-whisper (local)
                                                    │
                          ┌── mode "transcribe" ────┤
                          │                          └── mode "rewrite": LLM (OpenAI-compatible)
                          ▼
                 xdotool types it into the focused window

mode "stream" ──▶ mic PCM chunks ──▶ Riva/NIM realtime WebSocket ──▶ live xdotool typing

Each normal hotkey toggles: press to start recording, press again to stop — then it transcribes, optionally rewrites, and types the result where your cursor is. Streaming workflows type stable words live while you speak.

Cancel by voice: say "abbrechen" (or "cancel") at the start or end of a clip and the whole dictation is discarded — never routed, rewritten, or typed. It's the rescue for an accidentally triggered (e.g. wakeword) recording. Set the words under [routing] cancel_keywords (default ["abbrechen", "cancel"]; an empty list turns it off).

Send by voice: say a distinctive phrase like "computer send" at the start or end of a clip and the word is stripped, then the rest is typed and submitted with Enter — the spoken equivalent of "stop + paste + Enter", ideal hands-free. Off by default; set the phrases under [routing] send_keywords (use a multi-word phrase so a sentence merely ending in "send" doesn't submit by accident).

While you dictate, an optional on-screen overlay (Settings → General → "Visual overlay", default on) shows a translucent bubble at the cursor with a pulsing microphone, a live waveform of your mic level, and the recognised text — word-by-word in streaming mode, or the final result as a brief confirmation. Its tail points at the text caret (via AT-SPI accessibility) or the mouse pointer; it is click-through, never steals focus, and also gives hands-free wakeword sessions visible feedback. Tune the anchor with [general] overlay_anchor. X11 only.

Screenshots

Everything is configured in the Settings window — every tab has tooltips and screen-reader (ATK) support. Click any image to open it full size.

Presets settings tab
Presets — your dictation actions. Each preset is either a plain transcription or an LLM rewrite, and carries its own spoken keyword(s) for voice routing, an optional global hotkey, and a custom rewrite prompt.

Engines settings tab
Engines — your speech-to-text and language-model back-ends, local or remote. Add and rename engines, watch live online/offline status, and pick models from a searchable list fetched straight from the endpoint.

Input settings tab
Input — how you start and stop dictation: the modifier-key scheme (Ctrl+Win / Ctrl / Alt / Esc) or custom hotkeys, plus the silence-based auto-stop (VAD), the quality gate, and audio cues.

Wakeword (hands-free) settings
Wakeword (hands-free) — point Blitztext at a Wyoming/openWakeWord server, choose a wake model, and test the connection live so a spoken keyword starts dictation with no keys at all.

General settings tab
General — core preferences: microphone with a live level meter, output mode (type vs. paste), language hint, type delay, the on-screen dictation overlay, and autostart on login.

Benchmark settings tab
Benchmark — compare every configured STT engine against a reference WAV + transcript to find the fastest and most accurate, with a Device column (CPU / GPU / remote). Also includes a wakeword benchmark: point it at any OpenAI-compatible TTS server (Kokoro, XTTS, …), and it synthesizes your wake phrase in random voices, streams it to your wyoming-openwakeword server, and reports recall + false-fires per voice.

Log settings tab
Log — the in-app log buffer: a live view of recording, transcription, routing, and wakeword events for quick troubleshooting.

About settings tab
About — version, source link, changelog, and licence.

Requirements

  • X11 session (this uses xdotool; Wayland would need ydotool/wtype).
  • Host tools: xdotool, notify-send (libnotify-bin), and a recorder (pw-record from pipewire, or arecord/parecord).
    sudo apt install xdotool libnotify-bin pipewire-bin
    
  • Python 3.11+.
  • Optional realtime STT streaming: a Riva/NIM realtime server such as Nemotron ASR Streaming, reachable through /v1/realtime.

Install

Build a .deb and install it with the Software app or apt:

cd linux
bash packaging/build-deb.sh            # -> dist/blitztext_<ver>_arm64.deb
sudo apt install ./dist/blitztext_*.deb   # or double-click the .deb in Files

This installs blitztext to /opt/blitztext (a self-contained bundle — no pip step), adds a Blitztext entry to your app grid, and pulls in the system deps (python3-gi, xdotool, libnotify-bin, a recorder). Launch it from the app grid, or run blitztext / blitztext gui from a terminal. Remove with sudo apt remove blitztext.

Option B — run from source (venv)

cd linux
./install.sh

This creates .venv, installs the Python dependencies from requirements.txt, and writes the default config to ~/.config/blitztext/config.toml.

For the tray from source, the venv must be built on a Python that can see the system python3-giinstall.sh uses python3 -m venv --system-site-packages, so use the system /usr/bin/python3 (a conda/miniforge Python won't see the apt-installed gi). The .deb handles this for you.

Run

Three front-ends, same engine layer (STT engines + global hotkeys + xdotool typing):

# optional: only needed for the "rewrite" workflows
export OPENAI_API_KEY=sk-...

.venv/bin/python -m blitztext tray   # system-tray menu (macOS-menu-bar-like, default)
.venv/bin/python -m blitztext gui    # control-panel window
.venv/bin/python -m blitztext run    # headless, hotkeys only

Realtime STT streaming

For Nemotron ASR Streaming, add a realtime engine in Settings > Engines with + Stream, save/restart, then create or edit a workflow with mode = "stream". The default realtime URL is:

[[stt_engine]]
name = "Nemotron ASR Streaming"
type = "riva_realtime"
url = "http://127.0.0.1:8006/v1"
model = ""

[[workflow]]
name = "STT Streaming"
hotkey = "<ctrl>+<alt>+s"
mode = "stream"

The current Nemotron ASR Streaming model exposed by the tested NIM is English en-US, so use language = "en" or language = "en-US" in [general] for that engine.

The tray is the closest match to the macOS menu-bar app: a status icon with a menu listing every workflow (click to record), plus Show panel, Settings…, and Quit. It needs PyGObject (python3-gi) and the GTK/AppIndicator typelibs — already present on a standard Ubuntu GNOME install (the .deb declares them as dependencies):

sudo apt install python3-gi      # usually already installed
.venv/bin/python -m blitztext tray

If PyGObject isn't visible, tray prints this hint and falls back to the window. The venv is created with --system-site-packages so it can see the system gi — build it from /usr/bin/python3, not a conda/miniforge Python.

Either way, focus any text field and trigger a workflow — by tray menu, panel button, or hotkey (defaults):

Hotkey Workflow What it does
Ctrl+Alt+Space Transcribe Types the raw transcript
Ctrl+Alt+E Nicer email Rewrites speech into a polished email
Ctrl+Alt+I Improve text Proofreads / improves wording
Ctrl+Alt+C Calm down Rewrites an angry message into a calm one
Ctrl+Alt+J Add emojis Adds fitting emojis

Configuration

Everything lives in ~/.config/blitztext/config.toml (python -m blitztext config-path prints the location). You can change hotkeys, the Whisper model, and the rewrite endpoint, and add/edit [[workflow]] blocks with your own prompts.

Local Whisper

[whisper]
model = "small"      # tiny|base|small|medium|large-v3, or a local model path
device = "auto"      # auto tries cuda, falls back to cpu
compute_type = "auto"

On this arm64 host the pip ctranslate2 wheel is CPU-only, so it runs on the Grace CPU with int8. That's fast for dictation (≈2s for a 10s clip with small). device = "auto" attempts CUDA and falls back automatically — to get GPU you'd need a CUDA-enabled CTranslate2 build for aarch64/sm_121.

Rewrite endpoint (OpenAI or your local LLM)

[rewrite]
base_url = "https://api.openai.com/v1"   # or e.g. http://localhost:8000/v1 for vLLM/llama-swap
api_key_env = "OPENAI_API_KEY"
model = "gpt-4o-mini"

Point base_url at a local OpenAI-compatible server (vLLM, llama-swap) to keep rewriting fully on-box too.

Run on login

See blitztext.service for a systemd user unit.

Verified

On this machine (Ubuntu/GNOME, X11, GB10): recorder → valid 16 kHz WAV; faster-whisper CPU transcription accurate; config + all hotkeys parse; and xdotool typing of German text into a focused GTK field. The live global-hotkey loop and the LLM rewrite HTTP call were not auto-tested here (the former hijacks the keyboard during a session; the latter needs your key) — try them with the run command above.

CLI

python -m blitztext tray               # tray menu (default)
python -m blitztext gui                # control-panel window
python -m blitztext run                # headless daemon, hotkeys only
python -m blitztext transcribe f.wav   # one-shot, prints text (no hotkeys)
python -m blitztext config-path        # print config location

License

Code is released under the MIT License. See ../LICENSE.

Project names, logos, and app icons are not automatically granted as trademarks or brand assets. See ../TRADEMARKS.md.

This is an experimental, non-commercial open-source project, provided as-is under the MIT License without warranty or support. Nothing is sold here and no installation or operation is performed on your behalf.

The companion website (blitztext.de) is operated by Blackboat Internet GmbH: