jerlendds · March 4, 2026 08:56 · jerlendds · Mar 4, 2026 · jerlendds · Mar 4, 2026
diff --git a/voxtype.toml b/voxtype.toml
 # Voxtype Configuration
 #
 # Location: ~/.config/voxtype/config.toml
 # All settings can be overridden via CLI flags

 # State file for external integrations (Waybar, polybar, etc.)
 # Use "auto" for default location ($XDG_RUNTIME_DIR/voxtype/state),
 # a custom path, or "disabled" to turn off. The daemon writes state
 # ("idle", "recording", "transcribing") to this file whenever it changes.
 # Required for `voxtype record toggle` and `voxtype status` commands.
 state_file = "auto"

 [hotkey]
 # Key to hold for push-to-talk
 # Common choices: SCROLLLOCK, PAUSE, RIGHTALT, F13-F24
 # Use `evtest` to find key names for your keyboard
 key = "KEY_F9"

 # Optional modifier keys that must also be held
 # Example: modifiers = ["LEFTCTRL", "LEFTALT"]
 modifiers = []

 # Activation mode: "push_to_talk" or "toggle"
 # - push_to_talk: Hold hotkey to record, release to transcribe (default)
 # - toggle: Press hotkey once to start recording, press again to stop
 # mode = "push_to_talk"

 # Enable built-in hotkey detection (default: true)
 # Set to false when using compositor keybindings (Hyprland, Sway) instead
 # When disabled, use `voxtype record start/stop/toggle` to control recording
 # enabled = true

 # Modifier key to select secondary model (evdev input mode only)
 # When held while pressing the hotkey, uses whisper.secondary_model instead
 # Example: model_modifier = "LEFTSHIFT"  # Shift+hotkey uses secondary model
 # model_modifier = "LEFTSHIFT"

 [audio]
 # Audio input device ("default" uses system default)
 # List devices with: pactl list sources short
 device = "default"

 # Sample rate in Hz (whisper expects 16000)
 sample_rate = 16000

 # Maximum recording duration in seconds (safety limit)
 max_duration_secs = 360

 # [audio.feedback]
 # Enable audio feedback sounds (beeps when recording starts/stops)
 # enabled = true
 #
 # Sound theme: "default", "subtle", "mechanical", or path to custom theme directory
 # theme = "default"
 #
 # Volume level (0.0 to 1.0)
 # volume = 0.7

 [whisper]
 # Transcription backend: "local" or "remote"
 # - local: Use whisper.cpp locally (default)
 # - remote: Send audio to a remote whisper.cpp server or OpenAI-compatible API
 # backend = "local"

 # Model to use for transcription (local backend)
 # Options: tiny, tiny.en, base, base.en, small, small.en, medium, medium.en, large-v3, large-v3-turbo
 # .en models are English-only but faster and more accurate for English
 # large-v3-turbo is faster than large-v3 with minimal accuracy loss (recommended for GPU)
 # Or provide absolute path to a custom .bin model file
 model = "large-v3-turbo"

 # Language for transcription
 # Options:
 #   - Single language: "en", "fr", "de", etc.
 #   - Auto-detect all: "auto"
 #   - Constrained auto-detect: ["en", "fr"] (detects from allowed set only)
 # The array form helps with multilingual users where Whisper might misdetect
 # the language, especially for short sentences.
 # See: https://github.com/openai/whisper#available-models-and-languages
 language = "en"

 # Translate non-English speech to English
 translate = true

 # Number of CPU threads for inference (omit for auto-detection)
 # threads = 4

 # Initial prompt to provide context for transcription
 # Use this to hint at terminology, proper nouns, or formatting conventions.
 # Example: "Technical discussion about Rust, TypeScript, and Kubernetes."
 # initial_prompt = ""

 # --- Multi-model settings ---
 #
 # Secondary model for difficult audio (used with hotkey.model_modifier or CLI --model)
 # secondary_model = "large-v3-turbo"
 #
 # List of available models that can be requested via CLI --model flag
 # available_models = ["large-v3-turbo", "medium.en"]
 #
 # Maximum models to keep loaded in memory (LRU eviction when exceeded)
 # Default: 2 (primary + one secondary). Only applies when gpu_isolation = false.
 # max_loaded_models = 2
 #
 # Seconds before unloading idle secondary models (0 = never auto-unload)
 # Default: 300 (5 minutes). Only applies when gpu_isolation = false.
 # cold_model_timeout_secs = 300

 # --- Eager processing settings ---
 #
 # Enable eager input processing (transcribe chunks while recording continues)
 # Reduces perceived latency on slower machines by processing audio in parallel.
 # eager_processing = false
 #
 # Duration of each audio chunk in seconds (default: 5.0)
 # eager_chunk_secs = 5.0
 #
 # Overlap between chunks in seconds (helps catch words at boundaries, default: 0.5)
 # eager_overlap_secs = 0.5

 # --- Remote backend settings (used when backend = "remote") ---
 #
 # Remote server endpoint URL (required for remote backend)
 # Examples:
 #   - whisper.cpp server: "http://192.168.1.100:8080"
 #   - OpenAI API: "https://api.openai.com"
 # remote_endpoint = "http://192.168.1.100:8080"
 #
 # Model name to send to remote server (default: "whisper-1")
 # remote_model = "whisper-1"
 #
 # API key for remote server (optional, or use VOXTYPE_WHISPER_API_KEY env var)
 # remote_api_key = ""
 #
 # Timeout for remote requests in seconds (default: 30)
 # remote_timeout_secs = 30

 [output]
 # Primary output mode: "type" or "clipboard"
 # - type: Simulates keyboard input at cursor position (requires ydotool)
 # - clipboard: Copies text to clipboard (requires wl-copy)
 mode = "type"

 # Fall back to clipboard if typing fails
 fallback_to_clipboard = true

 # Custom driver order for type mode (optional)
 # Default order: wtype -> dotool -> ydotool -> clipboard
 # Customize to prefer a specific driver or change the fallback order.
 # Available drivers: wtype, dotool, ydotool, clipboard
 # Example: prefer ydotool over dotool:
 #   driver_order = ["wtype", "ydotool", "dotool", "clipboard"]
 # Example: use only ydotool, no fallback:
 driver_order = ["ydotool", "dotool", "clipboard"]
 # driver_order = ["wtype", "dotool", "ydotool", "clipboard"]

 # Delay between typed characters in milliseconds
 # 0 = fastest possible, increase if characters are dropped
 type_delay_ms = 0

 # Automatically submit (send Enter key) after outputting transcribed text
 # Useful for chat applications, command lines, or forms where you want
 # to auto-submit after dictation
 # auto_submit = true

 # Convert newlines to Shift+Enter instead of regular Enter
 # Useful for applications where Enter submits (e.g., Cursor IDE, Slack, Discord)
 # shift_enter_newlines = false

 # Restore clipboard content after paste mode (default: false)
 # Saves clipboard before transcription, restores it after paste keystroke
 # Only applies to mode = "paste". Useful when you want to preserve your
 # existing clipboard content across dictation operations.
 # restore_clipboard = false

 # Delay after paste before restoring clipboard (milliseconds)
 # Allows time for the paste operation to complete (default: 200)
 # restore_clipboard_delay_ms = 200

 # Pre/post output hooks (optional)
 # Commands to run before and after typing output. Useful for compositor integration.
 # Example: Block modifier keys during typing with Hyprland submap:
 #   pre_output_command = "hyprctl dispatch submap voxtype_suppress"
 #   post_output_command = "hyprctl dispatch submap reset"
 # See troubleshooting docs for the required Hyprland submap configuration.

 # Post-processing command (optional)
 # Pipe transcribed text through an external command for cleanup before output.
 # The command receives text on stdin and outputs processed text on stdout.
 # Useful for LLM-based text cleanup, grammar correction, filler word removal.
 # On any failure (timeout, error), falls back to original transcription.
 #
 # [output.post_process]
 # command = "ollama run llama3.2:1b 'Clean up this dictation. Fix grammar, remove filler words. Output only the cleaned text:'"
 # timeout_ms = 30000  # 30 second timeout (generous for LLM)

 [output.notification]
 # Show notification when recording starts (hotkey pressed)
 on_recording_start = false

 # Show notification when recording stops (transcription beginning)
 on_recording_stop = false

 # Show notification with transcribed text after transcription completes
 on_transcription = true

 # [text]
 # Text processing options (word replacements, spoken punctuation)
 #
 # Enable spoken punctuation conversion (e.g., say "period" to get ".")
 # spoken_punctuation = false
 #
 # Custom word replacements (case-insensitive)
 # replacements = { "vox type" = "voxtype" }

 # [vad]
 # Voice Activity Detection - filters silence-only recordings
 # Prevents Whisper hallucinations on silent audio
 #
 # enabled = false      # Enable VAD (off by default)
 # threshold = 0.5      # 0.0 = sensitive, 1.0 = aggressive
 # min_speech_duration_ms = 100  # Minimum speech required

 # [status]
 # Status display icons for Waybar/tray integrations
 #
 # Icon theme (or path to custom theme file):
 #   Font-based (require specific fonts):
 #     - "emoji"     - Default emoji icons (🎙️ 🎤 ⏳)
 #     - "nerd-font" - Nerd Font icons (requires Nerd Font)
 #     - "material"  - Material Design Icons (requires MDI font)
 #     - "phosphor"  - Phosphor Icons (requires Phosphor font)
 #     - "codicons"  - VS Code icons (requires Codicons font)
 #     - "omarchy"   - Omarchy distro icons
 #   Universal (no special fonts needed):
 #     - "minimal"   - Simple Unicode (○ ● ◐ ×)
 #     - "dots"      - Geometric shapes (◯ ⬤ ◔ ◌)
 #     - "arrows"    - Media player style (▶ ● ↻ ■)
 #     - "text"      - Plain text ([MIC] [REC] [...] [OFF])
 # icon_theme = "emoji"
 #
 # Per-state icon overrides (optional, takes precedence over theme)
 # [status.icons]
 # idle = "🎙️"
 # recording = "🎤"
 # transcribing = "⏳"
 # stopped = ""

 # [profiles]
 # Named profiles for context-specific post-processing
 # Use with: voxtype record start --profile slack
 #
 # [profiles.slack]
 # post_process_command = "ollama run llama3.2:1b 'Format for Slack...'"
 #
 # [profiles.code]
 # post_process_command = "ollama run llama3.2:1b 'Format as code comment...'"
 # output_mode = "clipboard"
 #[hotkey]
 #enabled = false
 #state_file = "auto"
	# Voxtype Configuration
	#
	# Location: ~/.config/voxtype/config.toml
	# All settings can be overridden via CLI flags

	# State file for external integrations (Waybar, polybar, etc.)
	# Use "auto" for default location ($XDG_RUNTIME_DIR/voxtype/state),
	# a custom path, or "disabled" to turn off. The daemon writes state
	# ("idle", "recording", "transcribing") to this file whenever it changes.
	# Required for `voxtype record toggle` and `voxtype status` commands.
	state_file = "auto"

	[hotkey]
	# Key to hold for push-to-talk
	# Common choices: SCROLLLOCK, PAUSE, RIGHTALT, F13-F24
	# Use `evtest` to find key names for your keyboard
	key = "KEY_F9"

	# Optional modifier keys that must also be held
	# Example: modifiers = ["LEFTCTRL", "LEFTALT"]
	modifiers = []

	# Activation mode: "push_to_talk" or "toggle"
	# - push_to_talk: Hold hotkey to record, release to transcribe (default)
	# - toggle: Press hotkey once to start recording, press again to stop
	# mode = "push_to_talk"

	# Enable built-in hotkey detection (default: true)
	# Set to false when using compositor keybindings (Hyprland, Sway) instead
	# When disabled, use `voxtype record start/stop/toggle` to control recording
	# enabled = true

	# Modifier key to select secondary model (evdev input mode only)
	# When held while pressing the hotkey, uses whisper.secondary_model instead
	# Example: model_modifier = "LEFTSHIFT" # Shift+hotkey uses secondary model
	# model_modifier = "LEFTSHIFT"

	[audio]
	# Audio input device ("default" uses system default)
	# List devices with: pactl list sources short
	device = "default"

	# Sample rate in Hz (whisper expects 16000)
	sample_rate = 16000

	# Maximum recording duration in seconds (safety limit)
	max_duration_secs = 360

	# [audio.feedback]
	# Enable audio feedback sounds (beeps when recording starts/stops)
	# enabled = true
	#
	# Sound theme: "default", "subtle", "mechanical", or path to custom theme directory
	# theme = "default"
	#
	# Volume level (0.0 to 1.0)
	# volume = 0.7

	[whisper]
	# Transcription backend: "local" or "remote"
	# - local: Use whisper.cpp locally (default)
	# - remote: Send audio to a remote whisper.cpp server or OpenAI-compatible API
	# backend = "local"

	# Model to use for transcription (local backend)
	# Options: tiny, tiny.en, base, base.en, small, small.en, medium, medium.en, large-v3, large-v3-turbo
	# .en models are English-only but faster and more accurate for English
	# large-v3-turbo is faster than large-v3 with minimal accuracy loss (recommended for GPU)
	# Or provide absolute path to a custom .bin model file
	model = "large-v3-turbo"

	# Language for transcription
	# Options:
	# - Single language: "en", "fr", "de", etc.
	# - Auto-detect all: "auto"
	# - Constrained auto-detect: ["en", "fr"] (detects from allowed set only)
	# The array form helps with multilingual users where Whisper might misdetect
	# the language, especially for short sentences.
	# See: https://github.com/openai/whisper#available-models-and-languages
	language = "en"

	# Translate non-English speech to English
	translate = true

	# Number of CPU threads for inference (omit for auto-detection)
	# threads = 4

	# Initial prompt to provide context for transcription
	# Use this to hint at terminology, proper nouns, or formatting conventions.
	# Example: "Technical discussion about Rust, TypeScript, and Kubernetes."
	# initial_prompt = ""

	# --- Multi-model settings ---
	#
	# Secondary model for difficult audio (used with hotkey.model_modifier or CLI --model)
	# secondary_model = "large-v3-turbo"
	#
	# List of available models that can be requested via CLI --model flag
	# available_models = ["large-v3-turbo", "medium.en"]
	#
	# Maximum models to keep loaded in memory (LRU eviction when exceeded)
	# Default: 2 (primary + one secondary). Only applies when gpu_isolation = false.
	# max_loaded_models = 2
	#
	# Seconds before unloading idle secondary models (0 = never auto-unload)
	# Default: 300 (5 minutes). Only applies when gpu_isolation = false.
	# cold_model_timeout_secs = 300

	# --- Eager processing settings ---
	#
	# Enable eager input processing (transcribe chunks while recording continues)
	# Reduces perceived latency on slower machines by processing audio in parallel.
	# eager_processing = false
	#
	# Duration of each audio chunk in seconds (default: 5.0)
	# eager_chunk_secs = 5.0
	#
	# Overlap between chunks in seconds (helps catch words at boundaries, default: 0.5)
	# eager_overlap_secs = 0.5

	# --- Remote backend settings (used when backend = "remote") ---
	#
	# Remote server endpoint URL (required for remote backend)
	# Examples:
	# - whisper.cpp server: "http://192.168.1.100:8080"
	# - OpenAI API: "https://api.openai.com"
	# remote_endpoint = "http://192.168.1.100:8080"
	#
	# Model name to send to remote server (default: "whisper-1")
	# remote_model = "whisper-1"
	#
	# API key for remote server (optional, or use VOXTYPE_WHISPER_API_KEY env var)
	# remote_api_key = ""
	#
	# Timeout for remote requests in seconds (default: 30)
	# remote_timeout_secs = 30

	[output]
	# Primary output mode: "type" or "clipboard"
	# - type: Simulates keyboard input at cursor position (requires ydotool)
	# - clipboard: Copies text to clipboard (requires wl-copy)
	mode = "type"

	# Fall back to clipboard if typing fails
	fallback_to_clipboard = true

	# Custom driver order for type mode (optional)
	# Default order: wtype -> dotool -> ydotool -> clipboard
	# Customize to prefer a specific driver or change the fallback order.
	# Available drivers: wtype, dotool, ydotool, clipboard
	# Example: prefer ydotool over dotool:
	# driver_order = ["wtype", "ydotool", "dotool", "clipboard"]
	# Example: use only ydotool, no fallback:
	driver_order = ["ydotool", "dotool", "clipboard"]
	# driver_order = ["wtype", "dotool", "ydotool", "clipboard"]

	# Delay between typed characters in milliseconds
	# 0 = fastest possible, increase if characters are dropped
	type_delay_ms = 0

	# Automatically submit (send Enter key) after outputting transcribed text
	# Useful for chat applications, command lines, or forms where you want
	# to auto-submit after dictation
	# auto_submit = true

	# Convert newlines to Shift+Enter instead of regular Enter
	# Useful for applications where Enter submits (e.g., Cursor IDE, Slack, Discord)
	# shift_enter_newlines = false

	# Restore clipboard content after paste mode (default: false)
	# Saves clipboard before transcription, restores it after paste keystroke
	# Only applies to mode = "paste". Useful when you want to preserve your
	# existing clipboard content across dictation operations.
	# restore_clipboard = false

	# Delay after paste before restoring clipboard (milliseconds)
	# Allows time for the paste operation to complete (default: 200)
	# restore_clipboard_delay_ms = 200

	# Pre/post output hooks (optional)
	# Commands to run before and after typing output. Useful for compositor integration.
	# Example: Block modifier keys during typing with Hyprland submap:
	# pre_output_command = "hyprctl dispatch submap voxtype_suppress"
	# post_output_command = "hyprctl dispatch submap reset"
	# See troubleshooting docs for the required Hyprland submap configuration.

	# Post-processing command (optional)
	# Pipe transcribed text through an external command for cleanup before output.
	# The command receives text on stdin and outputs processed text on stdout.
	# Useful for LLM-based text cleanup, grammar correction, filler word removal.
	# On any failure (timeout, error), falls back to original transcription.
	#
	# [output.post_process]
	# command = "ollama run llama3.2:1b 'Clean up this dictation. Fix grammar, remove filler words. Output only the cleaned text:'"
	# timeout_ms = 30000 # 30 second timeout (generous for LLM)

	[output.notification]
	# Show notification when recording starts (hotkey pressed)
	on_recording_start = false

	# Show notification when recording stops (transcription beginning)
	on_recording_stop = false

	# Show notification with transcribed text after transcription completes
	on_transcription = true

	# [text]
	# Text processing options (word replacements, spoken punctuation)
	#
	# Enable spoken punctuation conversion (e.g., say "period" to get ".")
	# spoken_punctuation = false
	#
	# Custom word replacements (case-insensitive)
	# replacements = { "vox type" = "voxtype" }

	# [vad]
	# Voice Activity Detection - filters silence-only recordings
	# Prevents Whisper hallucinations on silent audio
	#
	# enabled = false # Enable VAD (off by default)
	# threshold = 0.5 # 0.0 = sensitive, 1.0 = aggressive
	# min_speech_duration_ms = 100 # Minimum speech required

	# [status]
	# Status display icons for Waybar/tray integrations
	#
	# Icon theme (or path to custom theme file):
	# Font-based (require specific fonts):
	# - "emoji" - Default emoji icons (🎙️ 🎤 ⏳)
	# - "nerd-font" - Nerd Font icons (requires Nerd Font)
	# - "material" - Material Design Icons (requires MDI font)
	# - "phosphor" - Phosphor Icons (requires Phosphor font)
	# - "codicons" - VS Code icons (requires Codicons font)
	# - "omarchy" - Omarchy distro icons
	# Universal (no special fonts needed):
	# - "minimal" - Simple Unicode (○ ● ◐ ×)
	# - "dots" - Geometric shapes (◯ ⬤ ◔ ◌)
	# - "arrows" - Media player style (▶ ● ↻ ■)
	# - "text" - Plain text ([MIC] [REC] [...] [OFF])
	# icon_theme = "emoji"
	#
	# Per-state icon overrides (optional, takes precedence over theme)
	# [status.icons]
	# idle = "🎙️"
	# recording = "🎤"
	# transcribing = "⏳"
	# stopped = ""

	# [profiles]
	# Named profiles for context-specific post-processing
	# Use with: voxtype record start --profile slack
	#
	# [profiles.slack]
	# post_process_command = "ollama run llama3.2:1b 'Format for Slack...'"
	#
	# [profiles.code]
	# post_process_command = "ollama run llama3.2:1b 'Format as code comment...'"
	# output_mode = "clipboard"
	#[hotkey]
	#enabled = false
	#state_file = "auto"
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