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0d42f1bafe
* Try with voxtype * Update delay to prevent skipped characters * Add removal of voxtype * Use -bin package * Fix for yay * Nerdicons! * Use new, subtle nerdfont glyphs instead of standard icons * Do this in the waybar config instead * Make voxtype a permanent fixture so it is not lost on waybar resets * Record purpose * Add Dictation hotkeys * Tweak wording and point to config * Reuse the same help * Better communication * Anticipate moving the package to OPR * Clarify where the packages are coming from * input group not needed when using hyprland hotkey * Explain hotkey off * Allow for changing of the model on right click * Allow config on right click * Be more specific * Focus on config editing with waybar clicks --------- Co-authored-by: Ryan Hughes <ryan@heyoodle.com>
98 lines
3.2 KiB
TOML
98 lines
3.2 KiB
TOML
# Voxtype Configuration
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#
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# Location: ~/.config/voxtype/config.toml
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# All settings can be overridden via CLI flags
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#
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# State file for external integrations (Waybar, polybar, etc.)
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# Use "auto" for default location ($XDG_RUNTIME_DIR/voxtype/state),
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# a custom path, or "disabled" to turn off. The daemon writes state
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# ("idle", "recording", "transcribing") to this file whenever it changes.
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# Required for `voxtype record toggle` and `voxtype status` commands.
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state_file = "auto"
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[hotkey]
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# Hotkey is configured in Hyprland. Default is Super + Ctrl + X
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enabled = false
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[audio]
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# Audio input device ("default" uses system default)
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# List devices with: pactl list sources short
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device = "default"
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# Sample rate in Hz (whisper expects 16000)
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sample_rate = 16000
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# Maximum recording duration in seconds (safety limit)
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max_duration_secs = 60
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# [audio.feedback]
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# Enable audio feedback sounds (beeps when recording starts/stops)
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# enabled = true
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#
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# Sound theme: "default", "subtle", "mechanical", or path to custom theme directory
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# theme = "default"
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#
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# Volume level (0.0 to 1.0)
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# volume = 0.7
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[whisper]
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# Model to use for transcription
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# Options: tiny, tiny.en, base, base.en, small, small.en, medium, medium.en, large-v3, large-v3-turbo
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# .en models are English-only but faster and more accurate for English
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# large-v3-turbo is faster than large-v3 with minimal accuracy loss (recommended for GPU)
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# Or provide absolute path to a custom .bin model file
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model = "base.en"
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# Language for transcription
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# Use "en" for English, "auto" for auto-detection
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# See: https://github.com/openai/whisper#available-models-and-languages
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language = "en"
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# Translate non-English speech to English
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translate = false
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# Number of CPU threads for inference (omit for auto-detection)
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# threads = 4
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[output]
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# Primary output mode: "type" or "clipboard"
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# - type: Simulates keyboard input at cursor position (requires ydotool)
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# - clipboard: Copies text to clipboard (requires wl-copy)
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mode = "type"
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# Fall back to clipboard if typing fails
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fallback_to_clipboard = true
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# Delay between typed characters in milliseconds
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# 0 = fastest possible, increase if characters are dropped
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type_delay_ms = 1
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# Post-processing command (optional)
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# Pipe transcribed text through an external command for cleanup before output.
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# The command receives text on stdin and outputs processed text on stdout.
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# Useful for LLM-based text cleanup, grammar correction, filler word removal.
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# On any failure (timeout, error), falls back to original transcription.
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#
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# [output.post_process]
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# command = "ollama run llama3.2:1b 'Clean up this dictation. Fix grammar, remove filler words. Output only the cleaned text:'"
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# timeout_ms = 30000 # 30 second timeout (generous for LLM)
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[output.notification]
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# Show notification when recording starts (hotkey pressed)
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on_recording_start = false
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# Show notification when recording stops (transcription beginning)
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on_recording_stop = false
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# Show notification with transcribed text after transcription completes
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on_transcription = false
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# [text]
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# Text processing options (word replacements, spoken punctuation)
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#
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# Enable spoken punctuation conversion (e.g., say "period" to get ".")
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# spoken_punctuation = false
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#
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# Custom word replacements (case-insensitive)
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# replacements = { "hyperwhisper" = "hyprwhspr" }
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