Ratatoskr: Voice to Clipboard, No Cloud Required

· 3 min
pythonwhisperaudiodesktop-appprivacyvibe-coding

A local speech-to-text tool: press a hotkey, speak, and paste the transcription. No cloud, no accounts.

Every dictation tool I tried wanted me to sign up, open a browser, or send my audio to someone’s server. I just wanted to press a key, talk, and paste. So I built one that does exactly that.

The idea

Ratatoskr sits in your system tray and does one thing: press a hotkey, speak, get text in your clipboard. Everything runs locally through faster-whisper, the same Whisper model OpenAI released but optimized with CTranslate2. No audio ever leaves your machine. The only network call is a one-time model download from Hugging Face on first run.

That last part mattered to me. I dictate notes, draft messages, and dump half-formed thoughts into it, and none of that should end up on someone else’s server.

How it works

You press Ctrl+Alt+R (or whatever you configure). A small overlay pops up in the bottom-right corner showing that you’re recording, with a timer and pause/stop buttons.

Ratatoskr's recording overlay: a minimal dark bar showing recording status, elapsed time, and pause/stop buttons.

When you stop, the audio goes straight to Whisper. A few seconds later the transcription lands in your clipboard. Paste it wherever you want: email, Slack, your editor, a terminal. If you also want a .txt file saved, there’s a toggle for that.

That’s the whole workflow. There’s nothing to manage and no UI to navigate; the app stays invisible until you need it.

Under the hood

The stack is intentionally small:

The model preloads in a background thread at startup so the first transcription doesn’t stall. Audio is kept in memory as a float32 numpy array and passed straight to Whisper, with no temp files in the happy path.

There is one file written to disk: a recovery WAV saved right before transcription starts. If the app crashes mid-transcribe, the next launch picks it up and finishes the job. On success or failure, the file is deleted.

Settings

Right-click the tray icon to open settings. You can change the Whisper model size (from tiny for speed to large-v3 for accuracy), pick a source language or leave it on auto-detect, remap the hotkey, and toggle clipboard/file output.

The small model is the default. It strikes a good balance: fast enough for real-time use and accurate enough for most languages. If you have a GPU, the bigger models become practical too.

Vibe-coded, then audited

Like Mamrot, this started as a vibe-coding project: I described what I wanted and let Claude build the first version. Before making it public, I had Claude and GPT audit the code against each other for thread safety, license compliance, privacy (making sure no audio lingers on disk after an error), TOML structure, and font-rendering bugs. Having two models pick holes in each other’s work caught more than either did alone. Vibe-coding gets you to a working prototype fast; the cross-audit is what makes it something you can actually release.

Lessons learned

RegisterHotKey over keyboard libraries. I started with the keyboard Python package for global hotkeys. It worked fine, right up until it didn’t. Some antivirus tools flag low-level keyboard hooks, and in certain setups the library needed admin privileges. Switching to the native Win32 RegisterHotKey API fixed all of it. It’s a few more lines of ctypes, but it just works.

Keep audio in memory. Early versions wrote a WAV to disk, passed the path to Whisper, then deleted it. Cutting out the disk round-trip by passing the numpy array directly made the whole flow noticeably snappier, with one less file to worry about cleaning up.

Font sizes in Qt stylesheets: use pt, not px. If you set font-size: 13px in a Qt stylesheet, some widgets internally try to read the point size, get -1, and Qt prints a warning. Switching to pt units fixed it silently.

Try it

git clone https://github.com/konradozog/Ratatoskr.git
cd Ratatoskr
python -m venv .venv
.venv\Scripts\activate
pip install .
ratatoskr

Windows 10/11, Python 3.10+. That’s all you need.

GitHub →