hyprwhspr-rs

Rust implementation of hyprwhspr | Blazing fast, native speech-to-text voice dictation for Hyprland and Omarchy | Waybar, Walker, and Elephant integrations (optional)

cargo install hyprwhspr-rs

---

hyprwhspr-rs-demo.mp4

Requirements

• whisper.cpp (GitHub, AUR)
  • Ensure whisper-cli is available on your PATH (or use the managed build locations).
• libudev + pkg-config (required for hotplug detection; libudev-dev on Debian/Ubuntu)
• GNU-only binaries (no musl releases)
• Groq or Gemini API key (optional)
  • Use GROQ_API_KEY for provider groq
  • Use GEMINI_API_KEY for provider gemini
  • Groq with whisper is cheap (~$0.10 USD/month) and fast as hell. [Data Controls]
  • Comparatively, Gemini is very slow but offers better output formatting.
• Parakeet TDT (optional) - NVIDIA's local ASR model via ONNX
  • Run ./scripts/download-parakeet-tdt.sh to download model files (~1.2GB)
  • Very fast, but not as accurate as whisper or Gemini

Features

• Fast speech-to-text
• Intuitive configuration
  • word overrides (many are already baked in)
  • multi provider support
  • hot reloading during runtime
• Optional fast VAD trims (fast_vad.enabled) audio files, reducing inferences costs while increasing output speed

Built for Hyprland

• Detects Hyprland via HYPRLAND_INSTANCE_SIGNATURE and opens the IPC socket at $XDG_RUNTIME_DIR/hypr/<signature>/.socket.sock.
• Execs dispatch sendshortcut commands against the active window to paste dictated text, inspecting activewindow to decide when Shift is required for a hardcoded list of programs.
• Falls back to a Wayland virtual keyboard client or a simulated keypress paste if IPC communication fails.
• See the example docs for additional integration paths outside of Waybar and Walker/Elephant.

Installation

From crates.io

1. Install the latest release from crates.io

   cargo install hyprwhspr-rs

   Omit parakeet backend:

   cargo install hyprwhspr-rs --no-default-features

2. Install systemd service and Waybar module (optionally, with a WIP elephant/walker menu using --with-elephant flag)

   # Interactive install
   hyprwhspr-rs install
   
   # Optionally, install specific components (systemd, waybar, elephant)
   hyprwhspr-rs install {--all| --service | --waybar | --elephant} {--force | -f}

Notes:

• The installer writes the systemd unit with an absolute ExecStart= pointing at the hyprwhspr-rs binary you ran hyprwhspr-rs install with. If you copy the unit template manually, ensure hyprwhspr-rs is resolvable by systemd (PATH / drop-in override).
• If audio start/stop sounds are missing in your packaging setup, you can point the app at an installed assets directory with HYPRWHSPR_ASSETS_DIR=/path/to/assets.

Using Nix

You can install the hyprwhspr-rs package from nixpkgs.

With NixOS:

{
  # required to listen for keyboard shortcuts
  users.users.<username>.extraGroups = [ "input" ];
  
  # have it auto start as a systemd unit with
  services.hyprwhspr-rs.enable = true; 
  # or just add it to your systemPackages
  environment.systemPackages = [ pkgs.hyprwhspr-rs ];
  
  # optional: to enable cuda (for AMD do `rocmSupport` instead of `cudaSupport`)
  # cuda is unfree so not in the default nixos build caches
  # I highly recommend adding the cuda build cache to your nixconfig https://discourse.nixos.org/t/cuda-cache-for-nix-community/56038
  services.hyprwhspr-rs = {
    enable = true;
    package = pkgs.hyprwhspr-rs.override {
      # to optimize build time you can skip enabling cudaSupport for one of these two
      # for whisper do whisper-cpp, for NVIDIA Parakeet do onnxruntime
      whispercpp = pkgs.whisper-cpp.override { cudaSupport = true; }; 
      onnxruntime = pkgs.onnxruntime.override { cudaSupport = true; };
    };
  };
  # you can also enable cuda/rocm globally, but this will increase the build time for your entire system if you dont add the cuda build cache
  nixpkgs.config.cudaSupport = true;
  
  # if you use groq or gemini for transcription, you can autoload their keys with
  services.hyprwhspr-rs = {
    enable = true;
    # put `GROQ_API_KEY=...` or `GEMINI_API_KEY=...` in the file you put at this path
    environmentFile = "/path/to/hyprwhspr_secret_file";
  };
}

From source

1. git clone https://github.com/better-slop/hyprwhispr-rs.git
2. cd hyprwhspr-rs
3. cargo build --release
4. sudo cp target/release/hyprwhspr-rs /usr/local/bin/

Waybar Integration

./scripts/install-waybar.sh

Configuration

Example config

Configure in ~/.config/hyprwhspr-rs/config.jsonc

{
  "shortcuts": {
    "press": "SUPER+ALT+D",
    "hold": "SUPER+ALT+CTRL",
  },
  "word_overrides": {
    "under score": "_",
    "em dash": "—",
    "equal": "=",
    "at sign": "@",
    "pound": "#",
    "hashtag": "#",
    "hash tag": "#",
    "newline": "\n",
    "Omarkey": "Omarchy",
    "dot": ".",
    "Hyperland": "hyprland",
    "hyperland": "hyprland",
  },
  "audio_feedback": true, // Play start/stop sounds while recording
  "start_sound_volume": 0.1, // 0.1 - 1.0
  "stop_sound_volume": 0.1, // 0.1 - 1.0
  "start_sound_path": null, // Optional custom audio asset overrides
  "stop_sound_path": null, // Optional custom audio asset overrides
  "auto_copy_clipboard": true, // Automatically copy the final transcription to the clipboard
  "shift_paste": false, // Whether to force shift paste
  "global_paste_shortcut": false, // Enable compositor-level paste; uses Hyprland sendshortcut with Shift+Insert for all pastes
  "paste_hints": {
    "shift": [
      // List of window classes that will always paste with Ctrl+Shift+V
    ],
    "shift_insert": [
      // List of window classes that will always paste with Shift+Insert
    ],
  },
  "audio_device": null, // Force a specific input device index (null uses system default)
  "fast_vad": {
    "enabled": false, // Enable Earshot fast VAD trimming
    "profile": "aggressive", // quality | low_bitrate | aggressive | very_aggressive (lowercase only, serde-enforced; default aggressive)
    "min_speech_ms": 120, // Minimum detected speech before keeping a segment
    "silence_timeout_ms": 500, // Drop silence longer than this (ms)
    "pre_roll_ms": 120, // Audio to keep before speech to avoid clipping words
    "post_roll_ms": 150, // Audio to keep after speech before trimming
    "volatility_window": 24, // Frames observed for adaptive aggressiveness (30 ms per frame, matches FRAME_MS in src/audio/vad.rs)
    "volatility_increase_threshold": 0.35, // Bump profile when toggles exceed this ratio
    "volatility_decrease_threshold": 0.12, // Relax profile when toggles stay below this ratio
  },
  "transcription": {
    "provider": "whisper_cpp", // whisper_cpp | groq | gemini | parakeet
    "request_timeout_secs": 45,
    "max_retries": 2,
    "whisper_cpp": {
      "prompt": "Transcribe as technical documentation with proper capitalization, acronyms, and technical terminology. Do not add punctuation.",
      "model": "large-v3-turbo-q8_0", // Whisper model to use (must exist in specified directories)
      "threads": 4, // CPU threads dedicated to whisper.cpp
      "gpu_layers": 999, // Number of layers to keep on GPU (999 = auto/GPU preferred)
      "fallback_cli": false, // Fallback to whisper-cli (uses CPU)
      "no_speech_threshold": 0.6, // Whisper's "no speech" confidence gate
      "models_dirs": ["~/.local/share/hyprwhspr-rs/models"], // Directories to search for models
      "vad": {
        "enabled": false, // Toggle whisper-cli's native Silero VAD
        "model": "ggml-silero-v5.1.2.bin", // Path or filename for the ggml Silero VAD model
        // Probability threshold for deciding a frame is speech. Higher = fewer false positives, but may miss quiet speech.
        "threshold": 0.5,
        // Minimum contiguous speech duration (ms) to accept. Increase to ignore quick clicks/taps.
        "min_speech_ms": 250,
        // Minimum silence gap (ms) required to end a speech segment. Raise if mid-sentence pauses are being split.
        "min_silence_ms": 120,
        // Maximum speech duration (seconds) before forcing a cut. Use null (or omit) to leave unlimited.
        "max_speech_s": 15.0,
        // Extra padding (ms) added before/after detected speech so words aren't clipped.
        "speech_pad_ms": 80,
        // Overlap ratio between segments. Higher overlap helps smooth transitions at the cost of a little extra decode time.
        "samples_overlap": 0.1,
      },
    },
    "groq": {
      "model": "whisper-large-v3-turbo",
      "endpoint": "https://api.groq.com/openai/v1/audio/transcriptions",
      "prompt": "Transcribe as technical documentation with proper capitalization, acronyms, and technical terminology. Do not add punctuation.",
    },
    "gemini": {
      "model": "gemini-2.5-flash-preview-09-2025",
      "endpoint": "https://generativelanguage.googleapis.com/v1beta/models",
      "temperature": 0.0,
      "max_output_tokens": 1024,
      "prompt": "Transcribe as technical documentation with proper capitalization, acronyms, and technical terminology. Do not add punctuation.",
    },
    "parakeet": {
      "model_dir": "models/parakeet/parakeet-tdt-0.6b-v3-onnx", // Relative to $XDG_DATA_HOME/hyprwhspr-rs (or ~/.local/share/hyprwhspr-rs)
      "prompt": "Transcribe as technical documentation with proper capitalization, acronyms, and technical terminology. Do not add punctuation.",
    },
  },
}

Environment Variables

Configuring providers and other overrides.

Use transcription.provider in ~/.config/hyprwhspr-rs/config.jsonc to pick the backend.

Provider API key environment variables

• groq provider requires: GROQ_API_KEY
• gemini provider requires: GEMINI_API_KEY
• whisper_cpp (whisper-cli) does not require an API key; the binary is discovered via PATH and managed locations under $XDG_DATA_HOME / $HOME

Recommended setup (systemd user service)

hyprwhspr-rs install installs a user unit with:

• EnvironmentFile=-%h/.config/hyprwhspr-rs/env

Otherwise, set the env vars in your shell.

Extra env vars that affect provider behavior

• For whisper_cpp / whisper-cli discovery, the app also consults:
  • PATH (searches for whisper-cli, optional fallback names)
  • XDG_DATA_HOME / HOME (managed whisper.cpp locations)
• For asset overrides (start/stop sounds): HYPRWHSPR_ASSETS_DIR
• Resolution logic lives in:
  • src/config.rs (discover_whisper_binary_candidates, find_binaries_on_path, discover_assets_dir)

Earshot VAD trimming (recommended)

The default build ships with the impressive and lightweight earshot VoiceActivityDetector baked in. Toggle fast_vad.enabled in your config to trim silence before any provider (whisper.cpp, Groq, Gemini) sees the audio. Extremely useful for lowering costs and increasing speed.

Configuring fast_vad

"fast_vad": {
  "enabled": false,
  "profile": "aggressive", // quality | low_bitrate | aggressive | very_aggressive
  "min_speech_ms": 120, // minimum speech chunk to keep
  "silence_timeout_ms": 500, // silence length that ends a segment
  "pre_roll_ms": 120, // speech-leading padding
  "post_roll_ms": 150, // speech-trailing padding
  "volatility_window": 24, // decision history window
  "volatility_increase_threshold": 0.35, // become more aggressive above this
  "volatility_decrease_threshold": 0.12 // relax aggressiveness below this
}

About earshot

• Works well for silence, not as accurate at speech compared to other models.
• Operates on the 16 kHz PCM emitted by the capture layer and shares the trimmed buffer across all providers.
• Drops silent stretches longer than the configured timeout while keeping configurable pre-roll and post-roll padding so word edges remain intact.
• Adapts Earshot’s aggressiveness based on recent speech/silence volatility—fewer uploads when the room is noisy.
• If an entire recording is silent, the app attempts to short-circuit the upload path instead of dispatching an empty request.

All other fields in the fast_vad block map directly to the trimmer’s behaviour, so you can tune aggressiveness without recompiling.

Development

1. git clone https://github.com/better-slop/hyprwhispr-rs.git
2. cd hyprwhspr-rs
3. cargo build --release
   • Faster build (skips Parakeet backend): cargo build --release --no-default-features
4. Run using:
   • pretty logs: RUST_LOG=debug ./target/release/hyprwhspr-rs
   • production release: ./target/release/hyprwhspr-rs

Release process

Runtime builds rely on a local whisper.cpp installation, so validate that dependency before shipping a tagged version.

1. Use Conventional Commits – fix: bumps patch, feat: bumps minor, and type!: indicates a breaking change (major bump).
2. On every push to main, the release-plz workflow runs release-pr to open or refresh a release-plz-* pull request. Review the proposed version and changelog there.
3. When the release PR looks good, merge it. The same workflow runs release-plz release, tagging (vX.Y.Z) and publishing the crate to crates.io if it’s a stable tag.
4. The tag triggers the release workflow, which builds the Linux GNU binary, uploads the tarball + checksum, and publishes the GitHub release with the full commit list (plus PR links when available).

Define CARGO_REGISTRY_TOKEN in the repository secrets with publish-only permissions so the workflow can push stable releases to crates.io.

To Do

• Slop review/clean up
• Ship waybar integration
• Release on Cargo
• Release on AUR
• Add support for other operating systems/setups
• Refine paste layer
• Investigate formatting model