mirror of
https://github.com/Priler/jarvis.git
synced 2026-05-26 07:08:11 +00:00
AI models shared registry + Code cleanup + Better async handling + Some fixes, etc
This commit is contained in:
10
Cargo.lock
generated
10
Cargo.lock
generated
@@ -3322,6 +3322,7 @@ dependencies = [
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"serde_json",
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"serde_yaml",
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"sha2",
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"sys-locale",
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"tempfile",
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"tokenizers",
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"tokio",
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@@ -7013,6 +7014,15 @@ dependencies = [
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"syn 2.0.114",
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]
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[[package]]
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name = "sys-locale"
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version = "0.3.2"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "8eab9a99a024a169fe8a903cf9d4a3b3601109bcc13bd9e3c6fff259138626c4"
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dependencies = [
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"libc",
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]
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[[package]]
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name = "sysctl"
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version = "0.5.5"
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@@ -51,4 +51,5 @@ ort = { version = "=2.0.0-rc.11" }
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ndarray = "0.17"
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tokenizers = { version = "0.22", default-features = false }
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regex = "1"
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sys-locale = "0.3"
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@@ -13,12 +13,11 @@ enum VadState {
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VoiceActive,
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}
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pub fn start(text_cmd_rx: Receiver<String>) -> Result<(), ()> {
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main_loop(text_cmd_rx)
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pub fn start(text_cmd_rx: Receiver<String>, rt: &tokio::runtime::Runtime) -> Result<(), ()> {
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main_loop(text_cmd_rx, rt)
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}
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fn main_loop(text_cmd_rx: Receiver<String>) -> Result<(), ()> {
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let rt = tokio::runtime::Runtime::new().expect("Failed to create tokio runtime");
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fn main_loop(text_cmd_rx: Receiver<String>, rt: &tokio::runtime::Runtime) -> Result<(), ()> {
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let frame_length: usize = 512;
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let sample_rate: usize = 16000;
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let mut frame_buffer: Vec<i16> = vec![0; frame_length];
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@@ -1,5 +1,4 @@
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use jarvis_core::slots;
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use parking_lot::RwLock;
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use std::sync::Arc;
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use std::sync::atomic::{AtomicBool, Ordering};
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use std::sync::mpsc;
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@@ -8,7 +7,7 @@ use std::sync::mpsc;
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use jarvis_core::{
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audio, audio_processing, commands, config, db, listener, recorder, stt, intent,
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ipc::{self, IpcAction},
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i18n, voices,
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i18n, voices, models,
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APP_CONFIG_DIR, APP_LOG_DIR, COMMANDS_LIST, DB,
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};
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@@ -39,41 +38,39 @@ fn main() -> Result<(), String> {
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info!("Config directory is: {}", APP_CONFIG_DIR.get().unwrap().display());
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info!("Log directory is: {}", APP_LOG_DIR.get().unwrap().display());
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// initialize database (settings)
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DB.set(Arc::new(RwLock::new(db::init_settings())))
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// initialize settings
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let settings = db::init();
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// set global DB (for core modules that read settings at init time)
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DB.set(settings.arc().clone())
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.expect("DB already initialized");
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// init voices
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let voice_id = DB.get().unwrap().read().voice.clone();
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if let Err(e) = voices::init(&voice_id) {
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let voice_id = settings.lock().voice.clone();
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let language = settings.lock().language.clone();
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if let Err(e) = voices::init(&voice_id, &language) {
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warn!("Failed to init voices: {}", e);
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}
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// init i18n
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i18n::init(&DB.get().unwrap().read().language);
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// initialize tray
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// @TODO. macOS currently not supported for tray functionality,
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// due to the separate thread in which tray processing works,
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// but macOS requires it to be processed in the main thread only
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// The solution may be to include wake-word detection etc. in the winit event loop. (only for MacOS, though?)
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//#[cfg(not(target_os = "macos"))]
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//tray::init();
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i18n::init(&settings.lock().language);
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// init recorder
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if recorder::init().is_err() {
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app::close(1);
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}
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// init models registry (scans available AI models)
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if let Err(e) = models::init() {
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warn!("Models registry init failed: {}", e);
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}
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// init stt engine
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if stt::init().is_err() {
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// @TODO. Allow continuing even without STT, if commands is using keywords or smthng?
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app::close(1); // cannot continue without stt
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}
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// init tts engine
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// none for now (Silero-rs coming)
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// init commands
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info!("Initializing commands.");
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let cmds = match commands::parse_commands() {
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@@ -93,12 +90,17 @@ fn main() -> Result<(), String> {
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}
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// init wake-word engine
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if listener::init().is_err() {
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app::close(1); // cannot continue without wake-word engine
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if let Err(e) = listener::init() {
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error!("Wake-word engine init failed: {}", e);
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app::close(1);
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}
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// shared async runtime for intent classification, IPC, etc.
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let rt = Arc::new(
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tokio::runtime::Runtime::new().expect("Failed to create tokio runtime")
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);
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// init intent-recognition engine
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let rt = tokio::runtime::Runtime::new().expect("Failed to create tokio runtime");
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rt.block_on(async {
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if let Err(e) = intent::init(COMMANDS_LIST.get().unwrap()).await {
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error!("Failed to initialize intent classifier: {}", e);
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@@ -149,22 +151,23 @@ fn main() -> Result<(), String> {
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}
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});
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// start WebSocket server for ipc
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std::thread::spawn(|| {
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let rt = tokio::runtime::Runtime::new().expect("Failed to create tokio runtime for IPC");
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rt.block_on(ipc::start_server());
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// start WebSocket server on the shared runtime
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let ipc_rt = Arc::clone(&rt);
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std::thread::spawn(move || {
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ipc_rt.block_on(ipc::start_server());
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});
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// start the app (in the background thread)
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std::thread::spawn(|| {
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let _ = app::start(text_cmd_rx);
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let app_rt = Arc::clone(&rt);
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std::thread::spawn(move || {
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let _ = app::start(text_cmd_rx, &app_rt);
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});
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tray::init_blocking();
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tray::init_blocking(settings);
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Ok(())
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}
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pub fn should_stop() -> bool {
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SHOULD_STOP.load(Ordering::SeqCst)
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}
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}
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@@ -1,84 +1,64 @@
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mod menu;
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use tray_icon::{
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menu::{AboutMetadata, Menu, MenuEvent, MenuItem, PredefinedMenuItem},
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TrayIconBuilder, TrayIconEvent,
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menu::MenuEvent,
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TrayIconBuilder,
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};
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use winit::event_loop::{ControlFlow, EventLoopBuilder};
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use image;
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use std::process::Command;
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#[cfg(target_os="windows")]
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use winit::platform::windows::EventLoopBuilderExtWindows;
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use jarvis_core::{config, i18n, ipc::{self, IpcEvent}};
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use jarvis_core::{config, i18n, voices, ipc::{self, IpcEvent}, SettingsManager};
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const TRAY_ICON_BYTES: &[u8] = include_bytes!("../../../resources/icons/32x32.png");
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pub fn init_blocking() {
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// load tray icon
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//let icon_path = format!("{}/../../resources/icons/{}", env!("CARGO_MANIFEST_DIR"), config::TRAY_ICON);
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//let icon = load_icon(std::path::Path::new(&icon_path));
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pub fn init_blocking(settings: SettingsManager) {
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let icon = load_icon_from_bytes(TRAY_ICON_BYTES);
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// form tray menu
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// let tray_menu = Menu::with_items(&[
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// &MenuItem::new("Перезапуск", true, None),
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// &MenuItem::new("Настройки", true, None),
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// &MenuItem::new("Выход", true, None),
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// ])
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// .unwrap();
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let tray_menu = Menu::with_items(&[
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&MenuItem::with_id("restart", i18n::t("tray-restart"), true, None),
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&MenuItem::with_id("settings", i18n::t("tray-settings"), true, None),
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&MenuItem::with_id("exit", i18n::t("tray-exit"), true, None),
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]).unwrap();
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// build menu with settings submenus
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let tray_menu = menu::build(&settings);
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let menu::TrayMenu { menu, state: tray_state } = tray_menu;
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let _tray_icon = TrayIconBuilder::new()
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.with_menu(Box::new(tray_menu))
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.with_menu(Box::new(menu))
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.with_tooltip(i18n::t("tray-tooltip"))
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.with_icon(icon)
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.build()
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.unwrap();
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let menu_channel = MenuEvent::receiver();
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// let tray_channel = TrayIconEvent::receiver();
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// @TODO: Test on Linux
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// We need gtk for the tray icon to show up, we need to initialize gtk and create the tray_icon
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#[cfg(target_os = "linux")]
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{
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gtk::init().unwrap();
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glib::timeout_add_local(std::time::Duration::from_millis(100), move || {
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if let Ok(event) = menu_channel.try_recv() {
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handle_menu_event(&event);
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handle_menu_event(&event, &settings, &tray_state);
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}
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glib::ControlFlow::Continue
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});
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gtk::main();
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}
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// @TODO: Test on MacOS
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#[cfg(target_os = "macos")]
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{
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// macOS needs proper run loop - tao or winit on main thread
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use winit::event_loop::{EventLoop, ControlFlow};
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let event_loop = EventLoop::new().unwrap();
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event_loop.run(move |_event, elwt| {
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elwt.set_control_flow(ControlFlow::Wait);
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if let Ok(event) = menu_channel.try_recv() {
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handle_menu_event(&event);
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handle_menu_event(&event, &settings, &tray_state);
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}
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}).unwrap();
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}
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#[cfg(target_os = "windows")]
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{
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// simple polling works on Windows
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loop {
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if let Ok(event) = menu_channel.try_recv() {
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handle_menu_event(&event);
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handle_menu_event(&event, &settings, &tray_state);
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}
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// pump Windows messages
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@@ -101,8 +81,65 @@ pub fn init_blocking() {
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info!("Tray initialized.");
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}
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fn handle_menu_event(event: &MenuEvent) {
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match event.id.0.as_str() {
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fn handle_menu_event(event: &MenuEvent, settings: &SettingsManager, tray_state: &menu::TrayState) {
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let id = event.id.0.as_str();
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// -- radio group: "set:key:value"
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if let Some(rest) = id.strip_prefix("set:") {
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if let Some((key, value)) = rest.split_once(':') {
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match settings.write(key, value) {
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Ok(()) => {
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info!("Tray: {} = {}", key, value);
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// update check marks in the radio group
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for group in &tray_state.radio_groups {
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if group.setting_key == key {
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group.select(value);
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break;
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}
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}
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// apply side effects
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match key {
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"language" => {
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i18n::set_language(value);
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}
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"assistant_voice" => {
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voices::set_current_voice(value);
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}
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_ => {}
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}
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}
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Err(e) => {
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warn!("Tray: failed to set {} = {}: {}", key, value, e);
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}
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}
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return;
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}
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}
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// -- toggle: "toggle:key"
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if let Some(key) = id.strip_prefix("toggle:") {
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match key {
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"gain_normalizer" => {
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// CheckMenuItem auto-toggles on click, just read the new state
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let new_val = tray_state.gain_toggle.is_checked();
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let val_str = if new_val { "true" } else { "false" };
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if let Err(e) = settings.write(key, val_str) {
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warn!("Tray: failed to toggle {}: {}", key, e);
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// revert visual state on error
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tray_state.gain_toggle.set_checked(!new_val);
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} else {
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info!("Tray: {} = {}", key, val_str);
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}
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}
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_ => {}
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}
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return;
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}
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// -- action items
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match id {
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"exit" => std::process::exit(0),
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"restart" => {
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info!("Restarting from tray menu...");
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@@ -116,6 +153,8 @@ fn handle_menu_event(event: &MenuEvent) {
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}
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}
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// HELPERS
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fn load_icon_from_bytes(bytes: &[u8]) -> tray_icon::Icon {
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let image = image::load_from_memory(bytes)
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.expect("Failed to load icon")
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@@ -125,20 +164,7 @@ fn load_icon_from_bytes(bytes: &[u8]) -> tray_icon::Icon {
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tray_icon::Icon::from_rgba(rgba, width, height).expect("Failed to create icon")
|
||||
}
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||||
|
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fn load_icon(path: &std::path::Path) -> tray_icon::Icon {
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let (icon_rgba, icon_width, icon_height) = {
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let image = image::open(path)
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.expect("Failed to open icon path")
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.into_rgba8();
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let (width, height) = image.dimensions();
|
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let rgba = image.into_raw();
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(rgba, width, height)
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};
|
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tray_icon::Icon::from_rgba(icon_rgba, icon_width, icon_height).expect("Failed to open icon")
|
||||
}
|
||||
|
||||
fn restart_app() {
|
||||
// get current executable path
|
||||
let exe_path = match std::env::current_exe() {
|
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Ok(path) => path,
|
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Err(e) => {
|
||||
@@ -147,7 +173,6 @@ fn restart_app() {
|
||||
}
|
||||
};
|
||||
|
||||
// spawn new instance
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||||
match Command::new(&exe_path).spawn() {
|
||||
Ok(_) => {
|
||||
info!("Spawned new instance, exiting current...");
|
||||
@@ -160,13 +185,10 @@ fn restart_app() {
|
||||
}
|
||||
|
||||
fn open_settings() {
|
||||
// check if jarvis-gui is connected via IPC
|
||||
if ipc::has_clients() {
|
||||
// gui is running, send reveal event
|
||||
info!("GUI is connected, sending reveal event");
|
||||
ipc::send(IpcEvent::RevealWindow);
|
||||
} else {
|
||||
// gui not running, launch it
|
||||
info!("GUI not connected, launching jarvis-gui");
|
||||
launch_gui();
|
||||
}
|
||||
@@ -181,7 +203,6 @@ fn launch_gui() {
|
||||
}
|
||||
};
|
||||
|
||||
// jarvis-gui should be in same directory as jarvis-app
|
||||
let gui_path = exe_path.parent()
|
||||
.map(|p| p.join(get_gui_executable_name()))
|
||||
.unwrap_or_else(|| get_gui_executable_name().into());
|
||||
@@ -189,12 +210,8 @@ fn launch_gui() {
|
||||
info!("Launching GUI: {:?}", gui_path);
|
||||
|
||||
match Command::new(&gui_path).spawn() {
|
||||
Ok(_) => {
|
||||
info!("Launched jarvis-gui");
|
||||
}
|
||||
Err(e) => {
|
||||
error!("Failed to launch jarvis-gui: {}", e);
|
||||
}
|
||||
Ok(_) => info!("Launched jarvis-gui"),
|
||||
Err(e) => error!("Failed to launch jarvis-gui: {}", e),
|
||||
}
|
||||
}
|
||||
|
||||
@@ -206,4 +223,4 @@ fn get_gui_executable_name() -> &'static str {
|
||||
#[cfg(not(target_os = "windows"))]
|
||||
fn get_gui_executable_name() -> &'static str {
|
||||
"jarvis-gui"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,15 +1,182 @@
|
||||
pub enum TrayMenuItem {
|
||||
Restart,
|
||||
Settings,
|
||||
Exit,
|
||||
use tray_icon::menu::{CheckMenuItem, Menu, MenuItem, PredefinedMenuItem, Submenu};
|
||||
|
||||
use jarvis_core::{i18n, voices, SettingsManager};
|
||||
use jarvis_core::config::structs::{WakeWordEngine, NoiseSuppressionBackend};
|
||||
|
||||
// RADIO GROUP
|
||||
|
||||
// a group of check menu items where only one can be active at a time.
|
||||
// stores (menu_item, setting_value) pairs.
|
||||
pub struct RadioGroup {
|
||||
pub setting_key: String,
|
||||
pub items: Vec<(CheckMenuItem, String)>,
|
||||
}
|
||||
|
||||
impl TrayMenuItem {
|
||||
pub fn label(&self) -> &str {
|
||||
match *self {
|
||||
TrayMenuItem::Restart => "Перезапустить",
|
||||
TrayMenuItem::Settings => "Настройки",
|
||||
TrayMenuItem::Exit => "Выход",
|
||||
impl RadioGroup {
|
||||
pub fn select(&self, value: &str) {
|
||||
for (item, val) in &self.items {
|
||||
item.set_checked(val == value);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// TRAY MENU STATE
|
||||
|
||||
pub struct TrayMenu {
|
||||
pub menu: Menu,
|
||||
pub state: TrayState,
|
||||
}
|
||||
|
||||
// holds references to menu items for updating check marks after build
|
||||
pub struct TrayState {
|
||||
pub radio_groups: Vec<RadioGroup>,
|
||||
pub gain_toggle: CheckMenuItem,
|
||||
}
|
||||
|
||||
// BUILD
|
||||
|
||||
pub fn build(settings: &SettingsManager) -> TrayMenu {
|
||||
let menu = Menu::new();
|
||||
|
||||
let mut radio_groups = Vec::new();
|
||||
|
||||
// -- language submenu
|
||||
let lang_sub = Submenu::new(i18n::t("tray-language"), true);
|
||||
let current_lang = settings.read("language").unwrap_or_default();
|
||||
let mut lang_items = Vec::new();
|
||||
for &lang in i18n::SUPPORTED_LANGUAGES {
|
||||
let label = match lang {
|
||||
"ru" => "Русский",
|
||||
"en" => "English",
|
||||
"ua" => "Українська",
|
||||
_ => lang,
|
||||
};
|
||||
let item = CheckMenuItem::with_id(
|
||||
format!("set:language:{}", lang),
|
||||
label,
|
||||
true,
|
||||
lang == current_lang,
|
||||
None,
|
||||
);
|
||||
let _ = lang_sub.append(&item);
|
||||
lang_items.push((item, lang.to_string()));
|
||||
}
|
||||
radio_groups.push(RadioGroup {
|
||||
setting_key: "language".to_string(),
|
||||
items: lang_items,
|
||||
});
|
||||
|
||||
// -- voice submenu
|
||||
let voice_sub = Submenu::new(i18n::t("tray-voice"), true);
|
||||
let current_voice = voices::get_current_voice()
|
||||
.map(|v| v.voice.id.clone())
|
||||
.unwrap_or_default();
|
||||
let mut voice_items = Vec::new();
|
||||
for voice in voices::list_voices() {
|
||||
let item = CheckMenuItem::with_id(
|
||||
format!("set:assistant_voice:{}", voice.voice.id),
|
||||
&voice.voice.name,
|
||||
true,
|
||||
voice.voice.id == current_voice,
|
||||
None,
|
||||
);
|
||||
let _ = voice_sub.append(&item);
|
||||
voice_items.push((item, voice.voice.id.clone()));
|
||||
}
|
||||
radio_groups.push(RadioGroup {
|
||||
setting_key: "assistant_voice".to_string(),
|
||||
items: voice_items,
|
||||
});
|
||||
|
||||
// -- wake word engine submenu
|
||||
let ww_sub = Submenu::new(i18n::t("tray-wake-word"), true);
|
||||
let current_ww = settings.read("selected_wake_word_engine").unwrap_or_default();
|
||||
let mut ww_items = Vec::new();
|
||||
for (label, value) in &[("Rustpotter", "Rustpotter"), ("Vosk", "Vosk")] {
|
||||
let item = CheckMenuItem::with_id(
|
||||
format!("set:selected_wake_word_engine:{}", value.to_lowercase()),
|
||||
*label,
|
||||
true,
|
||||
current_ww == *label,
|
||||
None,
|
||||
);
|
||||
let _ = ww_sub.append(&item);
|
||||
ww_items.push((item, value.to_lowercase()));
|
||||
}
|
||||
radio_groups.push(RadioGroup {
|
||||
setting_key: "selected_wake_word_engine".to_string(),
|
||||
items: ww_items,
|
||||
});
|
||||
|
||||
// -- noise suppression submenu
|
||||
let ns_sub = Submenu::new(i18n::t("tray-noise-suppression"), true);
|
||||
let current_ns = settings.read("noise_suppression").unwrap_or_default();
|
||||
let mut ns_items = Vec::new();
|
||||
for (label, value) in &[("None", "none"), ("Nnnoiseless", "nnnoiseless")] {
|
||||
let item = CheckMenuItem::with_id(
|
||||
format!("set:noise_suppression:{}", value),
|
||||
*label,
|
||||
true,
|
||||
current_ns.to_lowercase() == *value,
|
||||
None,
|
||||
);
|
||||
let _ = ns_sub.append(&item);
|
||||
ns_items.push((item, value.to_string()));
|
||||
}
|
||||
radio_groups.push(RadioGroup {
|
||||
setting_key: "noise_suppression".to_string(),
|
||||
items: ns_items,
|
||||
});
|
||||
|
||||
// -- vad submenu
|
||||
let vad_sub = Submenu::new(i18n::t("tray-vad"), true);
|
||||
let current_vad = settings.read("vad_backend").unwrap_or_default();
|
||||
let mut vad_items = Vec::new();
|
||||
for (label, value) in &[("None", "none"), ("Energy", "energy"), ("Nnnoiseless", "nnnoiseless")] {
|
||||
let item = CheckMenuItem::with_id(
|
||||
format!("set:vad_backend:{}", value),
|
||||
*label,
|
||||
true,
|
||||
current_vad == *value,
|
||||
None,
|
||||
);
|
||||
let _ = vad_sub.append(&item);
|
||||
vad_items.push((item, value.to_string()));
|
||||
}
|
||||
radio_groups.push(RadioGroup {
|
||||
setting_key: "vad_backend".to_string(),
|
||||
items: vad_items,
|
||||
});
|
||||
|
||||
// -- gain normalizer toggle
|
||||
let gain_on = settings.read("gain_normalizer")
|
||||
.map(|v| v == "true")
|
||||
.unwrap_or(true);
|
||||
let gain_toggle = CheckMenuItem::with_id(
|
||||
"toggle:gain_normalizer",
|
||||
i18n::t("tray-gain-normalizer"),
|
||||
true,
|
||||
gain_on,
|
||||
None,
|
||||
);
|
||||
|
||||
// -- assemble main menu
|
||||
let _ = menu.append(&lang_sub);
|
||||
let _ = menu.append(&voice_sub);
|
||||
let _ = menu.append(&ww_sub);
|
||||
let _ = menu.append(&ns_sub);
|
||||
let _ = menu.append(&vad_sub);
|
||||
let _ = menu.append(&gain_toggle);
|
||||
let _ = menu.append(&PredefinedMenuItem::separator());
|
||||
let _ = menu.append(&MenuItem::with_id("restart", i18n::t("tray-restart"), true, None));
|
||||
let _ = menu.append(&MenuItem::with_id("settings", i18n::t("tray-settings"), true, None));
|
||||
let _ = menu.append(&MenuItem::with_id("exit", i18n::t("tray-exit"), true, None));
|
||||
|
||||
TrayMenu {
|
||||
menu,
|
||||
state: TrayState {
|
||||
radio_groups,
|
||||
gain_toggle,
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,5 +1,4 @@
|
||||
use std::{io::{self, Write}, sync::Arc};
|
||||
use parking_lot::RwLock;
|
||||
use std::io::{self, Write};
|
||||
|
||||
use jarvis_core::{COMMANDS_LIST, DB, JCommandsList, commands, config, db, intent};
|
||||
|
||||
@@ -13,32 +12,35 @@ Commands:
|
||||
list - List all loaded commands
|
||||
phrases - List all training phrases
|
||||
hash - Show commands hash
|
||||
reload - Reload commands from disk
|
||||
settings - Dump all settings
|
||||
help - Show this help
|
||||
exit - Exit the CLI
|
||||
");
|
||||
}
|
||||
|
||||
fn list_commands(commands: &Vec<JCommandsList>) {
|
||||
fn list_commands(commands: &[JCommandsList]) {
|
||||
println!("\n[ Loaded Commands ]");
|
||||
for cmd_list in commands {
|
||||
println!(" 📁 {}", cmd_list.path.display());
|
||||
for cmd in &cmd_list.commands {
|
||||
println!(" ├─ id: {}", cmd.id);
|
||||
println!(" ├─ action: {}", cmd.action);
|
||||
println!(" └─ phrases: {} total", cmd.phrases.len());
|
||||
println!(" ├─ type: {}", cmd.cmd_type);
|
||||
println!(" └─ phrases: {} languages", cmd.phrases.len());
|
||||
}
|
||||
}
|
||||
println!();
|
||||
}
|
||||
|
||||
fn list_phrases(commands: &Vec<JCommandsList>) {
|
||||
fn list_phrases(commands: &[JCommandsList]) {
|
||||
println!("\n[ Training Phrases ]");
|
||||
for cmd_list in commands {
|
||||
for cmd in &cmd_list.commands {
|
||||
println!(" [{}]", cmd.id);
|
||||
for phrase in &cmd.phrases {
|
||||
println!(" - {}", phrase);
|
||||
for (lang, phrases) in &cmd.phrases {
|
||||
println!(" lang: {}", lang);
|
||||
for phrase in phrases {
|
||||
println!(" - {}", phrase);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -56,17 +58,17 @@ async fn classify_text(text: &str) {
|
||||
}
|
||||
}
|
||||
|
||||
async fn execute_text(commands: &'static Vec<JCommandsList>, text: &str) {
|
||||
async fn execute_text(commands: &[JCommandsList], text: &str) {
|
||||
// try intent classification first
|
||||
if let Some((intent_id, confidence)) = intent::classify(text).await {
|
||||
println!(" Intent: {} (confidence: {:.2}%)", intent_id, confidence * 100.0);
|
||||
|
||||
if let Some((cmd_path, cmd)) = intent::get_command_by_intent(commands, &intent_id) {
|
||||
println!(" Command: {:?}", cmd_path);
|
||||
println!(" Action: {}", cmd.action);
|
||||
println!(" Type: {}", cmd.cmd_type);
|
||||
println!(" Executing...");
|
||||
|
||||
match commands::execute_command(cmd_path, cmd) {
|
||||
match commands::execute_command(cmd_path, cmd, Some(text), None) {
|
||||
Ok(chain) => println!(" ✓ Success (chain: {})", chain),
|
||||
Err(e) => println!(" ✗ Error: {}", e),
|
||||
}
|
||||
@@ -78,10 +80,10 @@ async fn execute_text(commands: &'static Vec<JCommandsList>, text: &str) {
|
||||
println!(" Intent not matched, trying levenshtein fallback...");
|
||||
if let Some((cmd_path, cmd)) = commands::fetch_command(text, commands) {
|
||||
println!(" Command: {:?}", cmd_path);
|
||||
println!(" Action: {}", cmd.action);
|
||||
println!(" Type: {}", cmd.cmd_type);
|
||||
println!(" Executing...");
|
||||
|
||||
match commands::execute_command(cmd_path, cmd) {
|
||||
match commands::execute_command(cmd_path, cmd, Some(text), None) {
|
||||
Ok(chain) => println!(" ✓ Success (chain: {})", chain),
|
||||
Err(e) => println!(" ✗ Error: {}", e),
|
||||
}
|
||||
@@ -102,6 +104,11 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
|
||||
// init dirs
|
||||
config::init_dirs()?;
|
||||
|
||||
// init settings
|
||||
let settings = db::init();
|
||||
DB.set(settings.arc().clone())
|
||||
.expect("DB already initialized");
|
||||
|
||||
// parse commands
|
||||
println!("\n[*] Loading commands...");
|
||||
let cmds = match commands::parse_commands() {
|
||||
@@ -123,19 +130,14 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
|
||||
Err(e) => println!(" Warning: {}", e),
|
||||
}
|
||||
|
||||
print_help();
|
||||
|
||||
// init db
|
||||
DB.set(Arc::new(RwLock::new(db::init_settings())))
|
||||
.expect("DB already initialized");
|
||||
|
||||
|
||||
// init sound
|
||||
println!("[*] Initializing audio...");
|
||||
if let Err(e) = jarvis_core::audio::init() {
|
||||
println!(" Warning: Audio init failed: {:?}", e);
|
||||
}
|
||||
|
||||
print_help();
|
||||
|
||||
// REPL loop
|
||||
let mut input = String::new();
|
||||
loop {
|
||||
@@ -152,7 +154,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
|
||||
|
||||
let parts: Vec<&str> = input.splitn(2, ' ').collect();
|
||||
let cmd = parts[0];
|
||||
let arg = parts.get(1).map(|s| *s).unwrap_or("");
|
||||
let arg = parts.get(1).copied().unwrap_or("");
|
||||
|
||||
match cmd {
|
||||
"exit" | "quit" | "q" => {
|
||||
@@ -166,6 +168,13 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
|
||||
let hash = commands::commands_hash(COMMANDS_LIST.get().unwrap());
|
||||
println!(" Commands hash: {}", hash);
|
||||
}
|
||||
"settings" => {
|
||||
println!("\n[ Current Settings ]");
|
||||
for (key, val) in settings.dump() {
|
||||
println!(" {} = {}", key, val);
|
||||
}
|
||||
println!();
|
||||
}
|
||||
"classify" | "c" => {
|
||||
if arg.is_empty() {
|
||||
println!(" Usage: classify <text>");
|
||||
@@ -191,4 +200,4 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
@@ -30,6 +30,7 @@ fluent.workspace = true
|
||||
fluent-bundle.workspace = true
|
||||
unic-langid.workspace = true
|
||||
chrono.workspace = true
|
||||
sys-locale.workspace = true
|
||||
|
||||
# pv_recorder = { workspace = true, optional = true }
|
||||
vosk = { version = "0.3.1", optional = true }
|
||||
|
||||
@@ -2,7 +2,6 @@ mod kira;
|
||||
mod rodio;
|
||||
|
||||
use once_cell::sync::OnceCell;
|
||||
use std::cmp::Ordering;
|
||||
use std::path::PathBuf;
|
||||
|
||||
use crate::config::structs::AudioType;
|
||||
@@ -44,7 +43,7 @@ pub fn init() -> Result<(), ()> {
|
||||
Ok(_) => {
|
||||
info!("Successfully initialized Kira audio backend.");
|
||||
}
|
||||
Err(msg) => {
|
||||
Err(_msg) => {
|
||||
error!("Failed to initialize Kira audio backend.");
|
||||
|
||||
return Err(());
|
||||
|
||||
@@ -30,8 +30,8 @@ pub fn init() -> Result<(), ()> {
|
||||
|
||||
// store
|
||||
// STREAM.set(_stream).unwrap();
|
||||
STREAM_HANDLE.set(stream_handle);
|
||||
SINK.set(sink);
|
||||
let _ = STREAM_HANDLE.set(stream_handle);
|
||||
let _ = SINK.set(sink);
|
||||
|
||||
// success
|
||||
Ok(())
|
||||
|
||||
@@ -3,9 +3,9 @@ pub mod vad;
|
||||
pub mod gain_normalizer;
|
||||
|
||||
use once_cell::sync::OnceCell;
|
||||
use std::sync::Mutex;
|
||||
use parking_lot::Mutex;
|
||||
|
||||
use crate::config::structs::{NoiseSuppressionBackend, VadBackend};
|
||||
use crate::config::structs::NoiseSuppressionBackend;
|
||||
use crate::DB;
|
||||
|
||||
static PROCESSOR: OnceCell<Mutex<AudioProcessor>> = OnceCell::new();
|
||||
@@ -18,43 +18,45 @@ pub struct ProcessedAudio {
|
||||
}
|
||||
|
||||
struct AudioProcessor {
|
||||
ns_backend: NoiseSuppressionBackend,
|
||||
vad_backend: VadBackend,
|
||||
gain_enabled: bool,
|
||||
has_gain: bool,
|
||||
has_ns: bool,
|
||||
}
|
||||
|
||||
impl AudioProcessor {
|
||||
fn new(ns: NoiseSuppressionBackend, vad: VadBackend, gain: bool) -> Self {
|
||||
// init backends
|
||||
fn new(ns: NoiseSuppressionBackend, gain: bool) -> Self {
|
||||
noise_suppression::init(ns);
|
||||
vad::init(vad);
|
||||
vad::init();
|
||||
if gain {
|
||||
gain_normalizer::init();
|
||||
}
|
||||
|
||||
Self {
|
||||
ns_backend: ns,
|
||||
vad_backend: vad,
|
||||
gain_enabled: gain,
|
||||
has_gain: gain,
|
||||
has_ns: !matches!(ns, NoiseSuppressionBackend::None),
|
||||
}
|
||||
}
|
||||
|
||||
fn process(&mut self, input: &[i16]) -> ProcessedAudio {
|
||||
let mut samples = input.to_vec();
|
||||
let gained: Vec<i16>;
|
||||
let after_gain: &[i16] = if self.has_gain {
|
||||
gained = gain_normalizer::normalize(input);
|
||||
&gained
|
||||
} else {
|
||||
input
|
||||
};
|
||||
|
||||
// step 1: gain normalization (before other processing)
|
||||
if self.gain_enabled {
|
||||
samples = gain_normalizer::normalize(&samples);
|
||||
}
|
||||
let suppressed: Vec<i16>;
|
||||
let after_ns: &[i16] = if self.has_ns {
|
||||
suppressed = noise_suppression::process(after_gain);
|
||||
&suppressed
|
||||
} else {
|
||||
after_gain
|
||||
};
|
||||
|
||||
// step 2: noise suppression
|
||||
samples = noise_suppression::process(&samples);
|
||||
|
||||
// step 3: VAD
|
||||
let (is_voice, confidence) = vad::detect(&samples);
|
||||
let (is_voice, confidence) = vad::detect(after_ns);
|
||||
|
||||
ProcessedAudio {
|
||||
samples,
|
||||
samples: after_ns.to_vec(),
|
||||
is_voice,
|
||||
vad_confidence: confidence,
|
||||
}
|
||||
@@ -67,20 +69,18 @@ impl AudioProcessor {
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
pub fn init() -> Result<(), String> {
|
||||
if PROCESSOR.get().is_some() {
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
let (ns, vad, gain) = get_settings();
|
||||
info!("Initializing audio processing: NS={:?}, VAD={:?}, Gain={}", ns, vad, gain);
|
||||
let (ns, gain) = get_settings();
|
||||
info!("Initializing audio processing: NS={:?}, Gain={}", ns, gain);
|
||||
|
||||
let processor = AudioProcessor::new(ns, vad, gain);
|
||||
let processor = AudioProcessor::new(ns, gain);
|
||||
PROCESSOR
|
||||
.set(Mutex::new(processor))
|
||||
.map_err(|_| "Audio processor already initialized")?;
|
||||
.map_err(|_| "Audio processor already initialized".to_string())?;
|
||||
|
||||
info!("Audio processing initialized.");
|
||||
Ok(())
|
||||
@@ -88,7 +88,7 @@ pub fn init() -> Result<(), String> {
|
||||
|
||||
pub fn process(input: &[i16]) -> ProcessedAudio {
|
||||
match PROCESSOR.get() {
|
||||
Some(p) => p.lock().unwrap().process(input),
|
||||
Some(p) => p.lock().process(input),
|
||||
None => ProcessedAudio {
|
||||
samples: input.to_vec(),
|
||||
is_voice: true,
|
||||
@@ -99,20 +99,19 @@ pub fn process(input: &[i16]) -> ProcessedAudio {
|
||||
|
||||
pub fn reset() {
|
||||
if let Some(p) = PROCESSOR.get() {
|
||||
p.lock().unwrap().reset();
|
||||
p.lock().reset();
|
||||
}
|
||||
}
|
||||
|
||||
fn get_settings() -> (NoiseSuppressionBackend, VadBackend, bool) {
|
||||
fn get_settings() -> (NoiseSuppressionBackend, bool) {
|
||||
match DB.get() {
|
||||
Some(db) => {
|
||||
let settings = db.read();
|
||||
(settings.noise_suppression, settings.vad, settings.gain_normalizer)
|
||||
(settings.noise_suppression, settings.gain_normalizer)
|
||||
}
|
||||
None => (
|
||||
crate::config::DEFAULT_NOISE_SUPPRESSION,
|
||||
crate::config::DEFAULT_VAD,
|
||||
crate::config::DEFAULT_GAIN_NORMALIZER,
|
||||
),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
mod simple;
|
||||
|
||||
use once_cell::sync::OnceCell;
|
||||
use std::sync::Mutex;
|
||||
use parking_lot::Mutex;
|
||||
|
||||
static NORMALIZER: OnceCell<Mutex<simple::GainNormalizer>> = OnceCell::new();
|
||||
|
||||
@@ -16,13 +16,13 @@ pub fn init() {
|
||||
|
||||
pub fn normalize(input: &[i16]) -> Vec<i16> {
|
||||
match NORMALIZER.get() {
|
||||
Some(n) => n.lock().unwrap().normalize(input),
|
||||
Some(n) => n.lock().normalize(input),
|
||||
None => input.to_vec(),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn reset() {
|
||||
if let Some(n) = NORMALIZER.get() {
|
||||
n.lock().unwrap().reset();
|
||||
n.lock().reset();
|
||||
}
|
||||
}
|
||||
@@ -1,23 +1,27 @@
|
||||
mod none;
|
||||
|
||||
#[cfg(feature = "nnnoiseless")]
|
||||
mod nnnoiseless;
|
||||
|
||||
use once_cell::sync::OnceCell;
|
||||
use std::sync::Mutex;
|
||||
use parking_lot::Mutex;
|
||||
|
||||
use crate::config::structs::NoiseSuppressionBackend;
|
||||
|
||||
static BACKEND: OnceCell<NoiseSuppressionBackend> = OnceCell::new();
|
||||
|
||||
#[cfg(feature = "nnnoiseless")]
|
||||
static NNNOISELESS_STATE: OnceCell<Mutex<nnnoiseless::NnnoiselessNS>> = OnceCell::new();
|
||||
static NNNOISELESS_STATE: OnceCell<Mutex<crate::models::nnnoiseless::NnnoiselessNS>> = OnceCell::new();
|
||||
|
||||
pub fn init(backend: NoiseSuppressionBackend) {
|
||||
if BACKEND.get().is_some() {
|
||||
return;
|
||||
}
|
||||
|
||||
// fallback if nnnoiseless not compiled in
|
||||
#[cfg(not(feature = "nnnoiseless"))]
|
||||
if matches!(backend, NoiseSuppressionBackend::Nnnoiseless) {
|
||||
warn!("Nnnoiseless not compiled in, falling back to None");
|
||||
backend = NoiseSuppressionBackend::None;
|
||||
}
|
||||
|
||||
BACKEND.set(backend).ok();
|
||||
|
||||
match backend {
|
||||
@@ -26,30 +30,25 @@ pub fn init(backend: NoiseSuppressionBackend) {
|
||||
}
|
||||
#[cfg(feature = "nnnoiseless")]
|
||||
NoiseSuppressionBackend::Nnnoiseless => {
|
||||
NNNOISELESS_STATE.set(Mutex::new(nnnoiseless::NnnoiselessNS::new())).ok();
|
||||
NNNOISELESS_STATE.set(Mutex::new(crate::models::nnnoiseless::NnnoiselessNS::new())).ok();
|
||||
info!("Noise suppression: Nnnoiseless");
|
||||
}
|
||||
#[cfg(not(feature = "nnnoiseless"))]
|
||||
NoiseSuppressionBackend::Nnnoiseless => {
|
||||
warn!("Nnnoiseless not compiled in, falling back to None");
|
||||
BACKEND.set(NoiseSuppressionBackend::None).ok();
|
||||
}
|
||||
_ => {}
|
||||
}
|
||||
}
|
||||
|
||||
pub fn process(input: &[i16]) -> Vec<i16> {
|
||||
match BACKEND.get() {
|
||||
Some(NoiseSuppressionBackend::None) | None => none::process(input),
|
||||
#[cfg(feature = "nnnoiseless")]
|
||||
Some(NoiseSuppressionBackend::Nnnoiseless) => {
|
||||
if let Some(state) = NNNOISELESS_STATE.get() {
|
||||
state.lock().unwrap().process(input)
|
||||
state.lock().process(input)
|
||||
} else {
|
||||
none::process(input)
|
||||
}
|
||||
}
|
||||
#[cfg(not(feature = "nnnoiseless"))]
|
||||
Some(NoiseSuppressionBackend::Nnnoiseless) => none::process(input),
|
||||
_ => none::process(input),
|
||||
}
|
||||
}
|
||||
|
||||
@@ -58,9 +57,9 @@ pub fn reset() {
|
||||
#[cfg(feature = "nnnoiseless")]
|
||||
Some(NoiseSuppressionBackend::Nnnoiseless) => {
|
||||
if let Some(state) = NNNOISELESS_STATE.get() {
|
||||
state.lock().unwrap().reset();
|
||||
state.lock().reset();
|
||||
}
|
||||
}
|
||||
_ => {}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,53 +0,0 @@
|
||||
use nnnoiseless::DenoiseState;
|
||||
use crate::config;
|
||||
|
||||
pub struct NnnoiselessNS {
|
||||
state: Box<DenoiseState<'static>>,
|
||||
buffer: Vec<f32>,
|
||||
}
|
||||
|
||||
impl NnnoiselessNS {
|
||||
pub fn new() -> Self {
|
||||
Self {
|
||||
state: DenoiseState::new(),
|
||||
buffer: Vec::with_capacity(config::NNNOISELESS_FRAME_SIZE * 2),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn process(&mut self, input: &[i16]) -> Vec<i16> {
|
||||
for &sample in input {
|
||||
self.buffer.push(sample as f32);
|
||||
}
|
||||
|
||||
let mut output: Vec<i16> = Vec::with_capacity(input.len());
|
||||
|
||||
while self.buffer.len() >= config::NNNOISELESS_FRAME_SIZE {
|
||||
let mut input_frame = [0.0f32; 480];
|
||||
let mut output_frame = [0.0f32; 480];
|
||||
|
||||
input_frame.copy_from_slice(&self.buffer[..config::NNNOISELESS_FRAME_SIZE]);
|
||||
self.buffer.drain(..config::NNNOISELESS_FRAME_SIZE);
|
||||
|
||||
// process: input -> output (denoised)
|
||||
let _ = self.state.process_frame(&mut output_frame, &input_frame);
|
||||
|
||||
for &sample in &output_frame {
|
||||
let clamped = sample.clamp(i16::MIN as f32, i16::MAX as f32);
|
||||
output.push(clamped as i16);
|
||||
}
|
||||
}
|
||||
|
||||
if output.is_empty() {
|
||||
return input.to_vec();
|
||||
}
|
||||
|
||||
output
|
||||
}
|
||||
|
||||
pub fn reset(&mut self) {
|
||||
// self.state = DenoiseState::new();
|
||||
// self.buffer.clear();
|
||||
|
||||
self.buffer.clear();
|
||||
}
|
||||
}
|
||||
@@ -1,72 +1,72 @@
|
||||
mod none;
|
||||
mod energy;
|
||||
|
||||
#[cfg(feature = "nnnoiseless")]
|
||||
mod nnnoiseless;
|
||||
|
||||
use once_cell::sync::OnceCell;
|
||||
use std::sync::Mutex;
|
||||
use parking_lot::Mutex;
|
||||
|
||||
use crate::config::structs::VadBackend;
|
||||
use crate::DB;
|
||||
|
||||
static BACKEND: OnceCell<VadBackend> = OnceCell::new();
|
||||
static BACKEND: OnceCell<String> = OnceCell::new();
|
||||
|
||||
#[cfg(feature = "nnnoiseless")]
|
||||
static NNNOISELESS_STATE: OnceCell<Mutex<nnnoiseless::NnnoiselessVAD>> = OnceCell::new();
|
||||
static NNNOISELESS_STATE: OnceCell<Mutex<crate::models::nnnoiseless::NnnoiselessVAD>> = OnceCell::new();
|
||||
|
||||
pub fn init(backend: VadBackend) {
|
||||
pub fn init() {
|
||||
if BACKEND.get().is_some() {
|
||||
return;
|
||||
}
|
||||
|
||||
BACKEND.set(backend).ok();
|
||||
let backend = DB.get()
|
||||
.map(|db| db.read().vad_backend.clone())
|
||||
.unwrap_or_else(|| "energy".to_string());
|
||||
|
||||
match backend {
|
||||
VadBackend::None => {
|
||||
BACKEND.set(backend.clone()).ok();
|
||||
|
||||
match backend.as_str() {
|
||||
"none" => {
|
||||
info!("VAD: disabled");
|
||||
}
|
||||
VadBackend::Energy => {
|
||||
"energy" => {
|
||||
info!("VAD: Energy-based");
|
||||
}
|
||||
#[cfg(feature = "nnnoiseless")]
|
||||
VadBackend::Nnnoiseless => {
|
||||
NNNOISELESS_STATE.set(Mutex::new(nnnoiseless::NnnoiselessVAD::new())).ok();
|
||||
"nnnoiseless" => {
|
||||
NNNOISELESS_STATE.set(Mutex::new(crate::models::nnnoiseless::NnnoiselessVAD::new())).ok();
|
||||
info!("VAD: Nnnoiseless");
|
||||
}
|
||||
#[cfg(not(feature = "nnnoiseless"))]
|
||||
VadBackend::Nnnoiseless => {
|
||||
warn!("Nnnoiseless not compiled in, falling back to Energy");
|
||||
BACKEND.set(VadBackend::Energy).ok();
|
||||
other => {
|
||||
warn!("Unknown VAD backend '{}', falling back to energy", other);
|
||||
// overwrite with energy
|
||||
// (BACKEND already set, so energy::detect will be used via fallthrough)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Returns (is_voice, confidence)
|
||||
// returns (is_voice, confidence)
|
||||
pub fn detect(input: &[i16]) -> (bool, f32) {
|
||||
match BACKEND.get() {
|
||||
Some(VadBackend::None) | None => none::detect(input),
|
||||
Some(VadBackend::Energy) => energy::detect(input),
|
||||
match BACKEND.get().map(|s| s.as_str()) {
|
||||
Some("none") | None => none::detect(input),
|
||||
Some("energy") => energy::detect(input),
|
||||
#[cfg(feature = "nnnoiseless")]
|
||||
Some(VadBackend::Nnnoiseless) => {
|
||||
Some("nnnoiseless") => {
|
||||
if let Some(state) = NNNOISELESS_STATE.get() {
|
||||
state.lock().unwrap().detect(input)
|
||||
state.lock().detect(input)
|
||||
} else {
|
||||
energy::detect(input)
|
||||
}
|
||||
}
|
||||
#[cfg(not(feature = "nnnoiseless"))]
|
||||
Some(VadBackend::Nnnoiseless) => energy::detect(input),
|
||||
_ => energy::detect(input),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn reset() {
|
||||
match BACKEND.get() {
|
||||
match BACKEND.get().map(|s| s.as_str()) {
|
||||
#[cfg(feature = "nnnoiseless")]
|
||||
Some(VadBackend::Nnnoiseless) => {
|
||||
Some("nnnoiseless") => {
|
||||
if let Some(state) = NNNOISELESS_STATE.get() {
|
||||
state.lock().unwrap().reset();
|
||||
state.lock().reset();
|
||||
}
|
||||
}
|
||||
_ => {}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,51 +0,0 @@
|
||||
use nnnoiseless::DenoiseState;
|
||||
use crate::config;
|
||||
|
||||
pub struct NnnoiselessVAD {
|
||||
state: Box<DenoiseState<'static>>,
|
||||
buffer: Vec<f32>,
|
||||
}
|
||||
|
||||
impl NnnoiselessVAD {
|
||||
pub fn new() -> Self {
|
||||
Self {
|
||||
state: DenoiseState::new(),
|
||||
buffer: Vec::with_capacity(config::NNNOISELESS_FRAME_SIZE * 2),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn detect(&mut self, input: &[i16]) -> (bool, f32) {
|
||||
for &sample in input {
|
||||
self.buffer.push(sample as f32);
|
||||
}
|
||||
|
||||
let mut total_vad = 0.0f32;
|
||||
let mut frame_count = 0u32;
|
||||
|
||||
while self.buffer.len() >= config::NNNOISELESS_FRAME_SIZE {
|
||||
let mut input_frame = [0.0f32; 480];
|
||||
let mut output_frame = [0.0f32; 480];
|
||||
|
||||
input_frame.copy_from_slice(&self.buffer[..config::NNNOISELESS_FRAME_SIZE]);
|
||||
self.buffer.drain(..config::NNNOISELESS_FRAME_SIZE);
|
||||
|
||||
let vad_prob = self.state.process_frame(&mut output_frame, &input_frame);
|
||||
total_vad += vad_prob;
|
||||
frame_count += 1;
|
||||
}
|
||||
|
||||
if frame_count == 0 {
|
||||
return (true, 0.5);
|
||||
}
|
||||
|
||||
let avg_vad = total_vad / frame_count as f32;
|
||||
let is_voice = avg_vad >= config::VAD_NNNOISELESS_THRESHOLD;
|
||||
|
||||
(is_voice, avg_vad)
|
||||
}
|
||||
|
||||
pub fn reset(&mut self) {
|
||||
self.state = DenoiseState::new();
|
||||
self.buffer.clear();
|
||||
}
|
||||
}
|
||||
@@ -247,6 +247,21 @@ pub fn execute_command(cmd_path: &PathBuf, cmd_config: &JCommand, phrase: Option
|
||||
}
|
||||
}
|
||||
|
||||
// look up a command by its ID
|
||||
pub fn get_command_by_id<'a>(
|
||||
commands: &'a [JCommandsList],
|
||||
id: &str,
|
||||
) -> Option<(&'a PathBuf, &'a JCommand)> {
|
||||
for cmd_list in commands {
|
||||
for cmd in &cmd_list.commands {
|
||||
if cmd.id == id {
|
||||
return Some((&cmd_list.path, cmd));
|
||||
}
|
||||
}
|
||||
}
|
||||
None
|
||||
}
|
||||
|
||||
pub fn list_paths(commands: &[JCommandsList]) -> Vec<&Path> {
|
||||
commands.iter().map(|x| x.path.as_path()).collect()
|
||||
}
|
||||
|
||||
@@ -17,10 +17,7 @@ use rustpotter::{
|
||||
RustpotterConfig, ScoreMode,
|
||||
};
|
||||
|
||||
use crate::IntentRecognitionEngine;
|
||||
use crate::SlotExtractionEngine;
|
||||
use crate::config::structs::NoiseSuppressionBackend;
|
||||
use crate::config::structs::VadBackend;
|
||||
use crate::{APP_CONFIG_DIR, APP_DIRS, APP_LOG_DIR};
|
||||
|
||||
#[allow(dead_code)]
|
||||
@@ -68,9 +65,13 @@ pub fn init_dirs() -> Result<(), String> {
|
||||
pub const DEFAULT_AUDIO_TYPE: AudioType = AudioType::Kira;
|
||||
pub const DEFAULT_RECORDER_TYPE: RecorderType = RecorderType::PvRecorder;
|
||||
pub const DEFAULT_WAKE_WORD_ENGINE: WakeWordEngine = WakeWordEngine::Vosk;
|
||||
pub const DEFAULT_INTENT_RECOGNITION_ENGINE: IntentRecognitionEngine = IntentRecognitionEngine::IntentClassifier;
|
||||
pub const DEFAULT_SPEECH_TO_TEXT_ENGINE: SpeechToTextEngine = SpeechToTextEngine::Vosk;
|
||||
|
||||
// backend defaults (string IDs)
|
||||
pub const DEFAULT_INTENT_BACKEND: &str = "intent-classifier";
|
||||
pub const DEFAULT_SLOTS_BACKEND: &str = "none";
|
||||
pub const DEFAULT_VAD_BACKEND: &str = "energy";
|
||||
|
||||
pub const DEFAULT_VOICE: &str = "jarvis-remaster";
|
||||
pub const SOUND_PATH: &str = "resources/sound"; // extended from SOUND_DIR (resources/sound)
|
||||
pub const VOICES_PATH: &str = "voices"; // extended from SOUND_PATH (resources/sound)
|
||||
@@ -157,15 +158,12 @@ pub const VOSK_SPEECH_PARTIAL_WORDS: bool = false;
|
||||
// IRE (intents recognition)
|
||||
pub const INTENT_CLASSIFIER_MIN_CONFIDENCE: f64 = 0.75;
|
||||
|
||||
// SLOTS EXTRACTION
|
||||
pub const DEFAULT_SLOT_EXTRACTION_ENGINE: SlotExtractionEngine = SlotExtractionEngine::None;
|
||||
|
||||
// embedding classifier
|
||||
pub const EMBEDDING_MIN_CONFIDENCE: f64 = 0.70;
|
||||
|
||||
// AUDIO PROCESSING DEFAULTS
|
||||
pub const DEFAULT_NOISE_SUPPRESSION: NoiseSuppressionBackend = NoiseSuppressionBackend::None;
|
||||
pub const DEFAULT_VAD: VadBackend = VadBackend::Energy;
|
||||
pub const DEFAULT_GAIN_NORMALIZER: bool = false;
|
||||
|
||||
// VAD settings
|
||||
|
||||
@@ -8,25 +8,12 @@ pub enum WakeWordEngine {
|
||||
Porcupine,
|
||||
}
|
||||
|
||||
#[derive(Clone, Copy, Serialize, Deserialize, Debug, PartialEq)]
|
||||
pub enum IntentRecognitionEngine {
|
||||
IntentClassifier,
|
||||
EmbeddingClassifier,
|
||||
}
|
||||
|
||||
#[derive(Clone, Copy, Serialize, Deserialize, Debug, PartialEq)]
|
||||
pub enum NoiseSuppressionBackend {
|
||||
None,
|
||||
Nnnoiseless,
|
||||
}
|
||||
|
||||
#[derive(Clone, Copy, Serialize, Deserialize, Debug, PartialEq)]
|
||||
pub enum VadBackend {
|
||||
None,
|
||||
Energy,
|
||||
Nnnoiseless,
|
||||
}
|
||||
|
||||
#[derive(Serialize, Deserialize, Debug, Clone)]
|
||||
pub enum SpeechToTextEngine {
|
||||
Vosk,
|
||||
@@ -45,13 +32,6 @@ pub enum AudioType {
|
||||
Kira,
|
||||
}
|
||||
|
||||
#[derive(Clone, Copy, Serialize, Deserialize, Debug, PartialEq)]
|
||||
pub enum SlotExtractionEngine {
|
||||
None,
|
||||
GLiNER,
|
||||
}
|
||||
|
||||
|
||||
impl fmt::Display for WakeWordEngine {
|
||||
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
|
||||
write!(f, "{:?}", self)
|
||||
@@ -64,30 +44,8 @@ impl fmt::Display for SpeechToTextEngine {
|
||||
}
|
||||
}
|
||||
|
||||
impl fmt::Display for IntentRecognitionEngine {
|
||||
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
|
||||
write!(f, "{:?}", self)
|
||||
}
|
||||
}
|
||||
|
||||
impl fmt::Display for NoiseSuppressionBackend {
|
||||
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
|
||||
write!(f, "{:?}", self)
|
||||
}
|
||||
}
|
||||
|
||||
impl fmt::Display for VadBackend {
|
||||
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
|
||||
write!(f, "{:?}", self)
|
||||
}
|
||||
}
|
||||
|
||||
impl fmt::Display for SlotExtractionEngine {
|
||||
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
|
||||
write!(f, "{:?}", self)
|
||||
}
|
||||
}
|
||||
|
||||
// pub enum TextToSpeechEngine {}
|
||||
|
||||
// pub enum IntentRecognitionEngine {}
|
||||
|
||||
@@ -1,12 +1,14 @@
|
||||
pub mod structs;
|
||||
pub mod manager;
|
||||
|
||||
use crate::{config, APP_CONFIG_DIR};
|
||||
|
||||
use log::info;
|
||||
use std::fs::File;
|
||||
use std::io::{BufReader, Read};
|
||||
use std::io::BufReader;
|
||||
use std::path::PathBuf;
|
||||
|
||||
use serde_json;
|
||||
pub use manager::SettingsManager;
|
||||
|
||||
fn get_db_file_path() -> PathBuf {
|
||||
PathBuf::from(format!(
|
||||
@@ -17,7 +19,6 @@ fn get_db_file_path() -> PathBuf {
|
||||
}
|
||||
|
||||
pub fn init_settings() -> structs::Settings {
|
||||
let mut db = None;
|
||||
let db_file_path = get_db_file_path();
|
||||
|
||||
info!(
|
||||
@@ -26,23 +27,23 @@ pub fn init_settings() -> structs::Settings {
|
||||
);
|
||||
|
||||
if db_file_path.exists() {
|
||||
// try load existing settings
|
||||
if let Ok(mut db_file) = File::open(db_file_path) {
|
||||
if let Ok(db_file) = File::open(&db_file_path) {
|
||||
let reader = BufReader::new(db_file);
|
||||
if let Ok(parsed_json) = serde_json::from_reader(reader) {
|
||||
if let Ok(settings) = serde_json::from_reader(reader) {
|
||||
info!("Settings loaded.");
|
||||
db = Some(parsed_json);
|
||||
return settings;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if db.is_none() {
|
||||
// create default settings db file
|
||||
warn!("No settings file found or there was an error parsing it. Creating default struct.");
|
||||
db = Some(structs::Settings::default());
|
||||
}
|
||||
warn!("No settings file found or there was an error parsing it. Creating default struct.");
|
||||
structs::Settings::default()
|
||||
}
|
||||
|
||||
db.unwrap()
|
||||
/// init settings and return a SettingsManager ready to use
|
||||
pub fn init() -> SettingsManager {
|
||||
let settings = init_settings();
|
||||
SettingsManager::new(settings)
|
||||
}
|
||||
|
||||
pub fn save_settings(settings: &structs::Settings) -> Result<(), std::io::Error> {
|
||||
|
||||
87
crates/jarvis-core/src/db/manager.rs
Normal file
87
crates/jarvis-core/src/db/manager.rs
Normal file
@@ -0,0 +1,87 @@
|
||||
use std::sync::Arc;
|
||||
use parking_lot::RwLock;
|
||||
|
||||
use super::structs::Settings;
|
||||
use super::save_settings;
|
||||
|
||||
// centralized settings manager.
|
||||
// wraps Arc<RwLock<Settings>> and handles locking + auto-save
|
||||
// can be used anywhere, ex. from GUI, tray, IPC, CLI, etc.
|
||||
#[derive(Clone)]
|
||||
pub struct SettingsManager {
|
||||
inner: Arc<RwLock<Settings>>,
|
||||
}
|
||||
|
||||
impl SettingsManager {
|
||||
pub fn new(settings: Settings) -> Self {
|
||||
Self {
|
||||
inner: Arc::new(RwLock::new(settings)),
|
||||
}
|
||||
}
|
||||
|
||||
// wrap an existing Arc<RwLock<Settings>>
|
||||
pub fn from_arc(arc: Arc<RwLock<Settings>>) -> Self {
|
||||
Self { inner: arc }
|
||||
}
|
||||
|
||||
// read a setting by key
|
||||
pub fn read(&self, key: &str) -> Option<String> {
|
||||
self.inner.read().get(key)
|
||||
}
|
||||
|
||||
// write a setting by key, auto-saves to disk
|
||||
pub fn write(&self, key: &str, val: &str) -> Result<(), String> {
|
||||
let snapshot = {
|
||||
let mut settings = self.inner.write();
|
||||
settings.set(key, val)?;
|
||||
settings.clone()
|
||||
};
|
||||
|
||||
save_settings(&snapshot)
|
||||
.map_err(|e| format!("failed to save settings: {}", e))?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// write multiple settings at once, single save
|
||||
pub fn write_many(&self, pairs: &[(&str, &str)]) -> Result<(), String> {
|
||||
let snapshot = {
|
||||
let mut settings = self.inner.write();
|
||||
for (key, val) in pairs {
|
||||
settings.set(key, val)?;
|
||||
}
|
||||
settings.clone()
|
||||
};
|
||||
|
||||
save_settings(&snapshot)
|
||||
.map_err(|e| format!("failed to save settings: {}", e))?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// direct read access to the full Settings struct (for init code that
|
||||
// needs to read multiple fields at once without key-based access)
|
||||
pub fn lock(&self) -> parking_lot::RwLockReadGuard<'_, Settings> {
|
||||
self.inner.read()
|
||||
}
|
||||
|
||||
// direct write access (for bulk operations not covered by set())
|
||||
pub fn lock_mut(&self) -> parking_lot::RwLockWriteGuard<'_, Settings> {
|
||||
self.inner.write()
|
||||
}
|
||||
|
||||
// get the underlying Arc
|
||||
pub fn arc(&self) -> &Arc<RwLock<Settings>> {
|
||||
&self.inner
|
||||
}
|
||||
|
||||
// dump all settings as key-value pairs (for debugging)
|
||||
pub fn dump(&self) -> Vec<(String, String)> {
|
||||
let settings = self.inner.read();
|
||||
Settings::keys().iter()
|
||||
.filter_map(|&key| {
|
||||
settings.get(key).map(|val| (key.to_string(), val))
|
||||
})
|
||||
.collect()
|
||||
}
|
||||
}
|
||||
@@ -3,10 +3,7 @@ use serde::{Deserialize, Serialize};
|
||||
|
||||
use crate::config::structs::SpeechToTextEngine;
|
||||
use crate::config::structs::WakeWordEngine;
|
||||
use crate::config::structs::IntentRecognitionEngine;
|
||||
use crate::config::structs::NoiseSuppressionBackend;
|
||||
use crate::config::structs::VadBackend;
|
||||
use crate::config::structs::SlotExtractionEngine;
|
||||
|
||||
#[derive(Serialize, Deserialize, Debug, Clone)]
|
||||
pub struct Settings {
|
||||
@@ -14,9 +11,15 @@ pub struct Settings {
|
||||
pub voice: String,
|
||||
|
||||
pub wake_word_engine: WakeWordEngine,
|
||||
pub intent_recognition_engine: IntentRecognitionEngine,
|
||||
|
||||
pub slot_extraction_engine: SlotExtractionEngine,
|
||||
// backend selections (string IDs matching model or code backend IDs)
|
||||
#[serde(default = "default_intent_backend")]
|
||||
pub intent_backend: String,
|
||||
#[serde(default = "default_slots_backend")]
|
||||
pub slots_backend: String,
|
||||
#[serde(default = "default_vad_backend")]
|
||||
pub vad_backend: String,
|
||||
|
||||
pub gliner_model: String,
|
||||
|
||||
pub speech_to_text_engine: SpeechToTextEngine,
|
||||
@@ -24,14 +27,127 @@ pub struct Settings {
|
||||
|
||||
// audio processing
|
||||
pub noise_suppression: NoiseSuppressionBackend,
|
||||
pub vad: VadBackend,
|
||||
pub gain_normalizer: bool,
|
||||
|
||||
#[serde(default = "default_language")]
|
||||
pub language: String,
|
||||
|
||||
pub api_keys: ApiKeys,
|
||||
}
|
||||
|
||||
fn default_intent_backend() -> String { config::DEFAULT_INTENT_BACKEND.to_string() }
|
||||
fn default_slots_backend() -> String { config::DEFAULT_SLOTS_BACKEND.to_string() }
|
||||
fn default_vad_backend() -> String { config::DEFAULT_VAD_BACKEND.to_string() }
|
||||
fn default_language() -> String { crate::i18n::detect_system_language().to_string() }
|
||||
|
||||
// ### KEY-VALUE ACCESS
|
||||
|
||||
impl Settings {
|
||||
/// read a setting by key. returns None for unknown keys.
|
||||
pub fn get(&self, key: &str) -> Option<String> {
|
||||
match key {
|
||||
"selected_microphone" => Some(self.microphone.to_string()),
|
||||
"assistant_voice" => Some(self.voice.clone()),
|
||||
"selected_wake_word_engine" => Some(format!("{:?}", self.wake_word_engine)),
|
||||
"intent_backend" => Some(self.intent_backend.clone()),
|
||||
"slots_backend" => Some(self.slots_backend.clone()),
|
||||
"vad_backend" => Some(self.vad_backend.clone()),
|
||||
"selected_gliner_model" => Some(self.gliner_model.clone()),
|
||||
"selected_vosk_model" => Some(self.vosk_model.clone()),
|
||||
"speech_to_text_engine" => Some(format!("{:?}", self.speech_to_text_engine)),
|
||||
"noise_suppression" => Some(format!("{:?}", self.noise_suppression)),
|
||||
"gain_normalizer" => Some(self.gain_normalizer.to_string()),
|
||||
"language" => Some(self.language.clone()),
|
||||
"api_key__picovoice" => Some(self.api_keys.picovoice.clone()),
|
||||
"api_key__openai" => Some(self.api_keys.openai.clone()),
|
||||
_ => None,
|
||||
}
|
||||
}
|
||||
|
||||
/// write a setting by key. returns Err for unknown keys or invalid values.
|
||||
pub fn set(&mut self, key: &str, val: &str) -> Result<(), String> {
|
||||
match key {
|
||||
"selected_microphone" => {
|
||||
self.microphone = val.parse::<i32>()
|
||||
.map_err(|_| format!("invalid integer: '{}'", val))?;
|
||||
}
|
||||
"assistant_voice" => {
|
||||
self.voice = val.to_string();
|
||||
}
|
||||
"selected_wake_word_engine" => {
|
||||
self.wake_word_engine = match val.to_lowercase().as_str() {
|
||||
"rustpotter" => WakeWordEngine::Rustpotter,
|
||||
"vosk" => WakeWordEngine::Vosk,
|
||||
"porcupine" => WakeWordEngine::Porcupine,
|
||||
_ => return Err(format!("unknown wake word engine: '{}'", val)),
|
||||
};
|
||||
}
|
||||
"intent_backend" => {
|
||||
self.intent_backend = val.to_string();
|
||||
}
|
||||
"slots_backend" => {
|
||||
self.slots_backend = val.to_string();
|
||||
}
|
||||
"vad_backend" => {
|
||||
self.vad_backend = val.to_string();
|
||||
}
|
||||
"selected_gliner_model" => {
|
||||
self.gliner_model = val.to_string();
|
||||
}
|
||||
"selected_vosk_model" => {
|
||||
self.vosk_model = val.to_string();
|
||||
}
|
||||
"noise_suppression" => {
|
||||
self.noise_suppression = match val.to_lowercase().as_str() {
|
||||
"none" => NoiseSuppressionBackend::None,
|
||||
"nnnoiseless" => NoiseSuppressionBackend::Nnnoiseless,
|
||||
_ => return Err(format!("unknown noise suppression backend: '{}'", val)),
|
||||
};
|
||||
}
|
||||
"gain_normalizer" => {
|
||||
self.gain_normalizer = match val.to_lowercase().as_str() {
|
||||
"true" => true,
|
||||
"false" => false,
|
||||
_ => return Err(format!("expected 'true' or 'false', got: '{}'", val)),
|
||||
};
|
||||
}
|
||||
"language" => {
|
||||
self.language = val.to_string();
|
||||
}
|
||||
"api_key__picovoice" => {
|
||||
self.api_keys.picovoice = val.to_string();
|
||||
}
|
||||
"api_key__openai" => {
|
||||
self.api_keys.openai = val.to_string();
|
||||
}
|
||||
_ => return Err(format!("unknown setting: '{}'", key)),
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// all valid setting keys (for enumeration, debugging, etc.)
|
||||
pub fn keys() -> &'static [&'static str] {
|
||||
&[
|
||||
"selected_microphone",
|
||||
"assistant_voice",
|
||||
"selected_wake_word_engine",
|
||||
"intent_backend",
|
||||
"slots_backend",
|
||||
"vad_backend",
|
||||
"selected_gliner_model",
|
||||
"selected_vosk_model",
|
||||
"speech_to_text_engine",
|
||||
"noise_suppression",
|
||||
"gain_normalizer",
|
||||
"language",
|
||||
"api_key__picovoice",
|
||||
"api_key__openai",
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
// ### DEFAULT
|
||||
|
||||
impl Default for Settings {
|
||||
fn default() -> Settings {
|
||||
Settings {
|
||||
@@ -39,18 +155,19 @@ impl Default for Settings {
|
||||
voice: String::from(""),
|
||||
|
||||
wake_word_engine: config::DEFAULT_WAKE_WORD_ENGINE,
|
||||
intent_recognition_engine: config::DEFAULT_INTENT_RECOGNITION_ENGINE,
|
||||
slot_extraction_engine: SlotExtractionEngine::None,
|
||||
|
||||
intent_backend: config::DEFAULT_INTENT_BACKEND.to_string(),
|
||||
slots_backend: config::DEFAULT_SLOTS_BACKEND.to_string(),
|
||||
vad_backend: config::DEFAULT_VAD_BACKEND.to_string(),
|
||||
|
||||
gliner_model: String::new(),
|
||||
speech_to_text_engine: config::DEFAULT_SPEECH_TO_TEXT_ENGINE,
|
||||
vosk_model: String::from(""), // auto detect first available
|
||||
vosk_model: String::from(""),
|
||||
|
||||
// audio processing defaults
|
||||
noise_suppression: config::DEFAULT_NOISE_SUPPRESSION,
|
||||
vad: config::DEFAULT_VAD,
|
||||
gain_normalizer: config::DEFAULT_GAIN_NORMALIZER,
|
||||
|
||||
language: String::from("ru"),
|
||||
language: crate::i18n::detect_system_language().to_string(),
|
||||
|
||||
api_keys: ApiKeys {
|
||||
picovoice: String::from(""),
|
||||
|
||||
@@ -11,7 +11,33 @@ const LOCALE_EN: &str = include_str!("i18n/locales/en.ftl");
|
||||
const LOCALE_UA: &str = include_str!("i18n/locales/ua.ftl");
|
||||
|
||||
pub const SUPPORTED_LANGUAGES: &[&str] = &["ru", "en", "ua"];
|
||||
pub const DEFAULT_LANGUAGE: &str = "ru";
|
||||
pub const DEFAULT_LANGUAGE: &str = "en";
|
||||
|
||||
// detect the OS language and map it to a supported language.
|
||||
// falls back to DEFAULT_LANGUAGE if not supported.
|
||||
pub fn detect_system_language() -> &'static str {
|
||||
if let Some(locale) = sys_locale::get_locale() {
|
||||
// locale can be "en-US", "ru-RU", "uk-UA", etc.
|
||||
let lang_code = locale.split(&['-', '_'][..]).next().unwrap_or("");
|
||||
|
||||
// map OS locale codes to our supported languages
|
||||
let mapped = match lang_code {
|
||||
"uk" => "ua", // ISO 639-1 "uk" (ukrainian) -> our "ua"
|
||||
other => other,
|
||||
};
|
||||
|
||||
if SUPPORTED_LANGUAGES.contains(&mapped) {
|
||||
info!("Detected system language: {} (from locale '{}')", mapped, locale);
|
||||
return SUPPORTED_LANGUAGES.iter()
|
||||
.find(|&&l| l == mapped)
|
||||
.unwrap();
|
||||
}
|
||||
|
||||
info!("System locale '{}' not supported, using default '{}'", locale, DEFAULT_LANGUAGE);
|
||||
}
|
||||
|
||||
DEFAULT_LANGUAGE
|
||||
}
|
||||
|
||||
// use concurrent bundle (thread-safe)
|
||||
type Bundle = ConcurrentFluentBundle<FluentResource>;
|
||||
@@ -126,7 +152,7 @@ pub fn get_all_translations() -> HashMap<String, String> {
|
||||
get_translations_for(&lang)
|
||||
}
|
||||
|
||||
/// Get all translations for a specific language
|
||||
// Get all translations for a specific language
|
||||
pub fn get_translations_for(lang: &str) -> HashMap<String, String> {
|
||||
let mut result = HashMap::new();
|
||||
|
||||
|
||||
@@ -7,6 +7,12 @@ tray-restart = Restart
|
||||
tray-settings = Settings
|
||||
tray-exit = Exit
|
||||
tray-tooltip = JARVIS - Voice Assistant
|
||||
tray-language = Language
|
||||
tray-voice = Voice
|
||||
tray-wake-word = Wake Word Engine
|
||||
tray-noise-suppression = Noise Suppression
|
||||
tray-vad = Voice Activity Detection
|
||||
tray-gain-normalizer = Gain Normalizer
|
||||
|
||||
# ### HEADER
|
||||
header-commands = COMMANDS
|
||||
|
||||
@@ -1,33 +1,39 @@
|
||||
# ### APP INFO
|
||||
# APP INFO
|
||||
app-name = JARVIS
|
||||
app-description = Голосовой ассистент
|
||||
|
||||
# ### TRAY MENU
|
||||
# TRAY MENU
|
||||
tray-restart = Перезапустить
|
||||
tray-settings = Настройки
|
||||
tray-exit = Выход
|
||||
tray-tooltip = JARVIS - Голосовой ассистент
|
||||
tray-language = Язык
|
||||
tray-voice = Голос
|
||||
tray-wake-word = Движок wake-word
|
||||
tray-noise-suppression = Шумоподавление
|
||||
tray-vad = Детекция голоса (VAD)
|
||||
tray-gain-normalizer = Нормализация громкости
|
||||
|
||||
# ### HEADER
|
||||
# HEADER
|
||||
header-commands = КОМАНДЫ
|
||||
header-settings = НАСТРОЙКИ
|
||||
|
||||
# ### SEARCH
|
||||
# SEARCH
|
||||
search-placeholder = Введите команду вручную или произнесите «Джарвис» ...
|
||||
|
||||
# ### MAIN PAGE
|
||||
# MAIN PAGE
|
||||
assistant-not-running = АССИСТЕНТ НЕ ЗАПУЩЕН
|
||||
assistant-offline-hint = Настроить его можно не запуская.
|
||||
btn-start = ЗАПУСТИТЬ
|
||||
btn-starting = ЗАПУСК...
|
||||
|
||||
# ### STATUS
|
||||
# STATUS
|
||||
status-disconnected = Отключен
|
||||
status-standby = Ожидание
|
||||
status-listening = Слушаю...
|
||||
status-processing = Обработка...
|
||||
|
||||
# ### STATS
|
||||
# STATS
|
||||
stats-microphone = МИКРОФОН
|
||||
stats-neural-networks = НЕЙРОСЕТИ
|
||||
stats-resources = РЕСУРСЫ
|
||||
@@ -35,13 +41,13 @@ stats-system-default = Системный
|
||||
stats-not-selected = Не выбран
|
||||
stats-loading = Загрузка...
|
||||
|
||||
# ### FOOTER
|
||||
# FOOTER
|
||||
footer-author = Автор проекта
|
||||
footer-telegram = Наш телеграм канал
|
||||
footer-github = Github репозиторий проекта
|
||||
footer-support = Поддержать проект на
|
||||
|
||||
# ### SETTINGS
|
||||
# SETTINGS
|
||||
settings-title = Настройки
|
||||
settings-general = Основные
|
||||
settings-devices = Устройства
|
||||
@@ -102,7 +108,7 @@ settings-models-hint = Поместите модели Vosk в папку resour
|
||||
settings-openai-key = Ключ OpenAI
|
||||
settings-openai-not-supported = В данный момент ChatGPT не поддерживается. Он будет добавлен в ближайших обновлениях.
|
||||
|
||||
# ### COMMANDS PAGE
|
||||
# COMMANDS PAGE
|
||||
commands-title = Команды
|
||||
commands-search = Поиск команд...
|
||||
commands-count = { $count } команд
|
||||
@@ -111,12 +117,12 @@ commands-wip-desc = Тут будет список команд + полноце
|
||||
commands-wip-follow = Следите за обновлениями в
|
||||
commands-wip-channel = нашем телеграм канале
|
||||
|
||||
# ### ERRORS
|
||||
# ERRORS
|
||||
error-generic = Произошла ошибка
|
||||
error-connection = Ошибка подключения
|
||||
error-not-found = Не найдено
|
||||
|
||||
# ### NOTIFICATIONS
|
||||
# NOTIFICATIONS
|
||||
notification-saved = Настройки сохранены!
|
||||
notification-error = Ошибка
|
||||
notification-assistant-started = Ассистент запущен
|
||||
|
||||
@@ -7,6 +7,12 @@ tray-restart = Перезапустити
|
||||
tray-settings = Налаштування
|
||||
tray-exit = Вихід
|
||||
tray-tooltip = JARVIS - Голосовий асистент
|
||||
tray-language = Мова
|
||||
tray-voice = Голос
|
||||
tray-wake-word = Рушій детекції
|
||||
tray-noise-suppression = Шумозаглушення
|
||||
tray-vad = Детекцiя голосу (VAD)
|
||||
tray-gain-normalizer = Нормалізація гучності
|
||||
|
||||
# ### HEADER
|
||||
header-commands = КОМАНДИ
|
||||
|
||||
@@ -3,47 +3,47 @@ mod embeddingclassifier;
|
||||
|
||||
use std::path::PathBuf;
|
||||
|
||||
use crate::{JCommandsList, commands::JCommand, config};
|
||||
use crate::{commands::{self, JCommandsList, JCommand}, config, models};
|
||||
use once_cell::sync::OnceCell;
|
||||
use crate::config::structs::IntentRecognitionEngine;
|
||||
|
||||
use crate::DB;
|
||||
|
||||
static IRE_TYPE: OnceCell<IntentRecognitionEngine> = OnceCell::new();
|
||||
static BACKEND: OnceCell<String> = OnceCell::new();
|
||||
|
||||
pub async fn init(commands: &Vec<JCommandsList>) -> Result<(), String> {
|
||||
if IRE_TYPE.get().is_some() {
|
||||
if BACKEND.get().is_some() {
|
||||
return Ok(());
|
||||
} // already initialized
|
||||
}
|
||||
|
||||
// set default ire type
|
||||
// IRE_TYPE.set(config::DEFAULT_INTENT_RECOGNITION_ENGINE).unwrap();
|
||||
let backend = DB.get().unwrap().read().intent_backend.clone();
|
||||
|
||||
// store current ire type
|
||||
IRE_TYPE
|
||||
.set(DB.get().unwrap().read().intent_recognition_engine)
|
||||
.unwrap();
|
||||
BACKEND.set(backend.clone()).map_err(|_| "Backend already set")?;
|
||||
|
||||
// load given recorder
|
||||
match IRE_TYPE.get().unwrap() {
|
||||
IntentRecognitionEngine::IntentClassifier => {
|
||||
info!("Initializing IntentClassifier IRE backend.");
|
||||
match backend.as_str() {
|
||||
"none" => {
|
||||
info!("Intent recognition disabled");
|
||||
}
|
||||
"intent-classifier" => {
|
||||
info!("Initializing IntentClassifier backend.");
|
||||
intentclassifier::init(&commands).await?;
|
||||
info!("IntentClassifier IRE backend initialized.");
|
||||
},
|
||||
IntentRecognitionEngine::EmbeddingClassifier => {
|
||||
info!("Initializing EmbeddingClassifier IRE backend.");
|
||||
embeddingclassifier::init(&commands)?;
|
||||
info!("EmbeddingClassifier IRE backend initialized.");
|
||||
},
|
||||
info!("IntentClassifier backend initialized.");
|
||||
}
|
||||
// any other value is treated as a model ID for embedding classification
|
||||
model_id => {
|
||||
info!("Initializing EmbeddingClassifier with model '{}'.", model_id);
|
||||
let model = models::embedding::load(models::registry(), model_id)?;
|
||||
embeddingclassifier::init_with_model(model, &commands)?;
|
||||
info!("EmbeddingClassifier backend initialized.");
|
||||
}
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
pub async fn classify(text: &str) -> Option<(String, f64)> {
|
||||
match IRE_TYPE.get()? {
|
||||
IntentRecognitionEngine::IntentClassifier => {
|
||||
match BACKEND.get()?.as_str() {
|
||||
"none" => None,
|
||||
"intent-classifier" => {
|
||||
match intentclassifier::classify(text).await {
|
||||
Ok(prediction) => {
|
||||
let confidence = prediction.confidence.value();
|
||||
@@ -59,7 +59,7 @@ pub async fn classify(text: &str) -> Option<(String, f64)> {
|
||||
}
|
||||
}
|
||||
}
|
||||
IntentRecognitionEngine::EmbeddingClassifier => {
|
||||
_ => {
|
||||
match embeddingclassifier::classify(text) {
|
||||
Ok((intent_id, confidence)) => {
|
||||
if confidence >= config::EMBEDDING_MIN_CONFIDENCE {
|
||||
@@ -77,13 +77,13 @@ pub async fn classify(text: &str) -> Option<(String, f64)> {
|
||||
}
|
||||
}
|
||||
|
||||
pub fn get_command_by_intent(commands: &'static Vec<JCommandsList>, intent_id: &str) -> Option<(&'static PathBuf, &'static JCommand)> {
|
||||
match IRE_TYPE.get()? {
|
||||
IntentRecognitionEngine::IntentClassifier => {
|
||||
intentclassifier::get_command(commands, intent_id)
|
||||
}
|
||||
IntentRecognitionEngine::EmbeddingClassifier => {
|
||||
embeddingclassifier::get_command(commands, intent_id)
|
||||
}
|
||||
// unified command lookup by intent ID - works for all backends
|
||||
pub fn get_command_by_intent<'a>(
|
||||
commands: &'a [JCommandsList],
|
||||
intent_id: &str,
|
||||
) -> Option<(&'a PathBuf, &'a JCommand)> {
|
||||
if matches!(BACKEND.get().map(|s| s.as_str()), Some("none")) {
|
||||
return None;
|
||||
}
|
||||
}
|
||||
commands::get_command_by_id(commands, intent_id)
|
||||
}
|
||||
|
||||
@@ -1,79 +1,42 @@
|
||||
use parking_lot::Mutex;
|
||||
use std::path::PathBuf;
|
||||
use std::sync::Arc;
|
||||
use std::fs;
|
||||
|
||||
// use fastembed::{TextEmbedding, InitOptions, EmbeddingModel};
|
||||
use fastembed::{TextEmbedding, UserDefinedEmbeddingModel, TokenizerFiles, InitOptionsUserDefined, Pooling, QuantizationMode, OutputKey};
|
||||
use once_cell::sync::OnceCell;
|
||||
|
||||
use crate::commands::JCommandsList;
|
||||
use crate::i18n::get_language;
|
||||
use crate::{APP_CONFIG_DIR, APP_DIR, i18n};
|
||||
use crate::i18n;
|
||||
use crate::APP_CONFIG_DIR;
|
||||
use crate::models::embedding::EmbeddingModel;
|
||||
|
||||
static CLASSIFIER: OnceCell<Mutex<EmbeddingClassifier>> = OnceCell::new();
|
||||
// no outer Mutex needed - state is immutable after init.
|
||||
// the embedding model has its own internal Mutex.
|
||||
static CLASSIFIER: OnceCell<EmbeddingClassifierState> = OnceCell::new();
|
||||
|
||||
struct IntentVector {
|
||||
id: String,
|
||||
vector: Vec<f32>,
|
||||
}
|
||||
|
||||
struct EmbeddingClassifier {
|
||||
model: TextEmbedding,
|
||||
struct EmbeddingClassifierState {
|
||||
model: Arc<EmbeddingModel>,
|
||||
intents: Vec<IntentVector>,
|
||||
}
|
||||
|
||||
// model is Arc (Send+Sync), intents are read-only after init
|
||||
unsafe impl Send for EmbeddingClassifierState {}
|
||||
unsafe impl Sync for EmbeddingClassifierState {}
|
||||
|
||||
const CACHE_FILE: &str = "embedding_intents.json";
|
||||
const HASH_FILE: &str = "embedding_hash.txt";
|
||||
|
||||
pub fn init(commands: &[JCommandsList]) -> Result<(), String> {
|
||||
// init with a model loaded through the registry
|
||||
pub fn init_with_model(model: Arc<EmbeddingModel>, commands: &[JCommandsList]) -> Result<(), String> {
|
||||
if CLASSIFIER.get().is_some() {
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
info!("Initializing embedding model...");
|
||||
|
||||
// let mut model = TextEmbedding::try_new(
|
||||
// InitOptions::new(EmbeddingModel::AllMiniLML6V2).with_show_download_progress(true),
|
||||
// ).map_err(|e| format!("Failed to load embedding model: {}", e))?;
|
||||
|
||||
let model_dir;
|
||||
match i18n::get_language().as_str() {
|
||||
"en" => {
|
||||
// smaller model for English
|
||||
info!("Loading all-MiniLM-L6-v2 ...");
|
||||
model_dir = APP_DIR.join("resources").join("models").join("all-MiniLM-L6-v2");
|
||||
},
|
||||
_ => {
|
||||
// bigger model for any other languages (multilingual)
|
||||
info!("Loading paraphrase-multilingual-MiniLM-L12-v2-onnx-Q ...");
|
||||
model_dir = APP_DIR.join("resources").join("models").join("paraphrase-multilingual-MiniLM-L12-v2-onnx-Q");
|
||||
}
|
||||
}
|
||||
|
||||
// info!("{}", model_dir.display());
|
||||
|
||||
let user_model = UserDefinedEmbeddingModel {
|
||||
onnx_file: std::fs::read(model_dir.join("model.onnx"))
|
||||
.map_err(|e| format!("Failed to read model.onnx: {}", e))?,
|
||||
tokenizer_files: TokenizerFiles {
|
||||
tokenizer_file: std::fs::read(model_dir.join("tokenizer.json"))
|
||||
.map_err(|e| format!("Failed to read tokenizer.json: {}", e))?,
|
||||
config_file: std::fs::read(model_dir.join("config.json"))
|
||||
.map_err(|e| format!("Failed to read config.json: {}", e))?,
|
||||
special_tokens_map_file: std::fs::read(model_dir.join("special_tokens_map.json"))
|
||||
.map_err(|e| format!("Failed to read special_tokens_map.json: {}", e))?,
|
||||
tokenizer_config_file: std::fs::read(model_dir.join("tokenizer_config.json"))
|
||||
.map_err(|e| format!("Failed to read tokenizer_config.json: {}", e))?,
|
||||
},
|
||||
pooling: Some(Pooling::Mean),
|
||||
quantization: QuantizationMode::None,
|
||||
output_key: Some(OutputKey::ByName("last_hidden_state")),
|
||||
};
|
||||
|
||||
let mut model = TextEmbedding::try_new_from_user_defined(user_model, Default::default())
|
||||
.map_err(|e| format!("Failed to load embedding model: {}", e))?;
|
||||
|
||||
info!("Embedding model loaded");
|
||||
info!("Initializing embedding classifier...");
|
||||
|
||||
let current_hash = crate::commands::commands_hash(commands);
|
||||
let config_dir = APP_CONFIG_DIR.get().ok_or("Config dir not set")?;
|
||||
@@ -90,7 +53,7 @@ pub fn init(commands: &[JCommandsList]) -> Result<(), String> {
|
||||
|
||||
let intents = if should_retrain {
|
||||
info!("Building intent vectors from commands...");
|
||||
let intents = build_intent_vectors(&mut model, commands)?;
|
||||
let intents = build_intent_vectors(&model, commands)?;
|
||||
|
||||
// cache to disk
|
||||
if let Ok(json) = serde_json::to_string(&intents_to_cache(&intents)) {
|
||||
@@ -107,14 +70,14 @@ pub fn init(commands: &[JCommandsList]) -> Result<(), String> {
|
||||
|
||||
info!("Embedding classifier ready with {} intents", intents.len());
|
||||
|
||||
CLASSIFIER.set(Mutex::new(EmbeddingClassifier { model, intents }))
|
||||
.map_err(|_| "Classifier already set")?;
|
||||
CLASSIFIER.set(EmbeddingClassifierState { model, intents })
|
||||
.map_err(|_| "Classifier already set".to_string())?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn build_intent_vectors(
|
||||
model: &mut TextEmbedding,
|
||||
model: &EmbeddingModel,
|
||||
commands: &[JCommandsList],
|
||||
) -> Result<Vec<IntentVector>, String> {
|
||||
let lang = i18n::get_language();
|
||||
@@ -129,7 +92,7 @@ fn build_intent_vectors(
|
||||
|
||||
let texts: Vec<&str> = phrases.iter().map(|s| s.as_str()).collect();
|
||||
|
||||
let embeddings = model.embed(texts, None)
|
||||
let embeddings = model.embedding.lock().embed(texts, None)
|
||||
.map_err(|e| format!("Embedding failed for '{}': {}", cmd.id, e))?;
|
||||
|
||||
// average all phrase vectors into one intent vector
|
||||
@@ -166,9 +129,10 @@ fn build_intent_vectors(
|
||||
}
|
||||
|
||||
pub fn classify(text: &str) -> Result<(String, f64), String> {
|
||||
let mut classifier = CLASSIFIER.get().ok_or("Classifier not initialized")?.lock();
|
||||
let state = CLASSIFIER.get().ok_or("Classifier not initialized")?;
|
||||
|
||||
let embeddings = classifier.model.embed(vec![text], None)
|
||||
// only the embedding model needs locking, intents are read-only
|
||||
let embeddings = state.model.embedding.lock().embed(vec![text], None)
|
||||
.map_err(|e| format!("Failed to embed query: {}", e))?;
|
||||
|
||||
let mut query_vec = embeddings.into_iter().next()
|
||||
@@ -182,11 +146,11 @@ pub fn classify(text: &str) -> Result<(String, f64), String> {
|
||||
}
|
||||
}
|
||||
|
||||
// cosine similarity against all intents (dot product of normalized vectors)
|
||||
let mut best_id = String::new();
|
||||
// cosine similarity - track index, clone only the winner
|
||||
let mut best_idx: usize = 0;
|
||||
let mut best_score: f64 = -1.0;
|
||||
|
||||
for intent in &classifier.intents {
|
||||
for (i, intent) in state.intents.iter().enumerate() {
|
||||
let score: f64 = query_vec.iter()
|
||||
.zip(intent.vector.iter())
|
||||
.map(|(a, b)| (*a as f64) * (*b as f64))
|
||||
@@ -194,31 +158,16 @@ pub fn classify(text: &str) -> Result<(String, f64), String> {
|
||||
|
||||
if score > best_score {
|
||||
best_score = score;
|
||||
best_id = intent.id.clone();
|
||||
best_idx = i;
|
||||
}
|
||||
}
|
||||
|
||||
let best_id = state.intents[best_idx].id.clone();
|
||||
debug!("Embedding classify: '{}' -> '{}' ({:.2}%)", text, best_id, best_score * 100.0);
|
||||
|
||||
Ok((best_id, best_score))
|
||||
}
|
||||
|
||||
pub fn get_command<'a>(
|
||||
commands: &'a [JCommandsList],
|
||||
intent_id: &str,
|
||||
) -> Option<(&'a PathBuf, &'a crate::commands::JCommand)> {
|
||||
for cmd_list in commands {
|
||||
for cmd in &cmd_list.commands {
|
||||
if cmd.id == intent_id {
|
||||
return Some((&cmd_list.path, cmd));
|
||||
}
|
||||
}
|
||||
}
|
||||
None
|
||||
}
|
||||
|
||||
// ### CACHE HELPERS
|
||||
|
||||
#[derive(serde::Serialize, serde::Deserialize)]
|
||||
struct CachedIntent {
|
||||
id: String,
|
||||
@@ -243,4 +192,4 @@ fn load_cached_intents(path: &PathBuf) -> Result<Vec<IntentVector>, String> {
|
||||
id: c.id,
|
||||
vector: c.vector,
|
||||
}).collect())
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,29 +1,27 @@
|
||||
use intent_classifier::{
|
||||
IntentClassifier, IntentPrediction, IntentError,
|
||||
IntentPrediction, IntentError,
|
||||
TrainingExample, TrainingSource, IntentId
|
||||
};
|
||||
|
||||
use tokio::sync::OnceCell;
|
||||
use std::path::PathBuf;
|
||||
use std::sync::Arc;
|
||||
use std::fs;
|
||||
|
||||
use crate::commands::{self, JCommand, JCommandsList};
|
||||
use crate::commands::{self, JCommandsList};
|
||||
use crate::models;
|
||||
use crate::models::intent_classifier::IntentClassifierModel;
|
||||
use crate::{APP_CONFIG_DIR, i18n};
|
||||
|
||||
static CLASSIFIER: OnceCell<IntentClassifier> = OnceCell::const_new();
|
||||
// static COMMANDS_MAP: OnceCell<Vec<JCommandsList>> = OnceCell::const_new();
|
||||
use once_cell::sync::OnceCell;
|
||||
|
||||
static MODEL: OnceCell<Arc<IntentClassifierModel>> = OnceCell::new();
|
||||
|
||||
const TRAINING_CACHE_FILE: &str = "intent_training.json";
|
||||
const COMMANDS_HASH_FILE: &str = "commands_hash.txt";
|
||||
|
||||
pub async fn init(commands: &[JCommandsList]) -> Result<(), String> {
|
||||
// parse commands first
|
||||
// let commands = commands::parse_commands()?;
|
||||
let current_hash = commands::commands_hash(&commands); // regen hash for current commands set
|
||||
let current_hash = commands::commands_hash(&commands);
|
||||
|
||||
// init classifier
|
||||
let classifier = IntentClassifier::new().await
|
||||
.map_err(|e| format!("Failed to init IntentClassifier: {}", e))?;
|
||||
let model = models::intent_classifier::load(models::registry(), "intent-classifier").await?;
|
||||
|
||||
// check if we can use cached training data
|
||||
let config_dir = APP_CONFIG_DIR.get().ok_or("Config dir not set")?;
|
||||
@@ -39,10 +37,9 @@ pub async fn init(commands: &[JCommandsList]) -> Result<(), String> {
|
||||
|
||||
if should_retrain {
|
||||
info!("Training intent classifier with {} commands...", commands.len());
|
||||
train_classifier(&classifier, &commands).await?;
|
||||
train_classifier(&model.classifier, &commands).await?;
|
||||
|
||||
// save training data and hash
|
||||
if let Ok(export) = classifier.export_training_data().await {
|
||||
if let Ok(export) = model.classifier.export_training_data().await {
|
||||
let _ = fs::write(&cache_path, export);
|
||||
let _ = fs::write(&hash_path, ¤t_hash);
|
||||
info!("Training data cached.");
|
||||
@@ -50,41 +47,23 @@ pub async fn init(commands: &[JCommandsList]) -> Result<(), String> {
|
||||
} else {
|
||||
info!("Loading cached training data...");
|
||||
if let Ok(data) = fs::read_to_string(&cache_path) {
|
||||
classifier.import_training_data(&data).await
|
||||
model.classifier.import_training_data(&data).await
|
||||
.map_err(|e| format!("Failed to import training data: {}", e))?;
|
||||
}
|
||||
}
|
||||
|
||||
// store data
|
||||
CLASSIFIER.set(classifier).map_err(|_| "Classifier already set")?;
|
||||
// COMMANDS_MAP.set(commands).map_err(|_| "Commands map already set")?;
|
||||
MODEL.set(model).map_err(|_| "Model already set")?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
pub async fn classify(text: &str) -> Result<IntentPrediction, IntentError> {
|
||||
let classifier = CLASSIFIER.get().expect("IntentClassifier not initialized");
|
||||
classifier.predict_intent(text).await
|
||||
let model = MODEL.get().expect("IntentClassifier not initialized");
|
||||
model.classifier.predict_intent(text).await
|
||||
}
|
||||
|
||||
// get command by intent ID
|
||||
pub fn get_command(commands: &'static [JCommandsList], intent_id: &str) -> Option<(&'static PathBuf, &'static JCommand)> {
|
||||
// let commands = COMMANDS_MAP.get()?;
|
||||
|
||||
for assistant_cmd in commands {
|
||||
for cmd in &assistant_cmd.commands {
|
||||
if cmd.id == intent_id {
|
||||
return Some((&assistant_cmd.path, cmd));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
None
|
||||
}
|
||||
|
||||
// based on: https://github.com/ciresnave/intent-classifier/blob/main/examples/basic_usage.rs
|
||||
async fn train_classifier(
|
||||
classifier: &IntentClassifier,
|
||||
classifier: &intent_classifier::IntentClassifier,
|
||||
commands: &[JCommandsList]
|
||||
) -> Result<(), String> {
|
||||
let lang = i18n::get_language();
|
||||
@@ -94,7 +73,6 @@ async fn train_classifier(
|
||||
|
||||
for assistant_cmd in commands {
|
||||
for cmd in &assistant_cmd.commands {
|
||||
// use language-specific phrases
|
||||
let phrases = cmd.get_phrases(&lang);
|
||||
|
||||
for phrase in phrases.iter() {
|
||||
@@ -115,4 +93,4 @@ async fn train_classifier(
|
||||
|
||||
info!("Added {} training examples for language '{}'", total_examples, lang);
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
@@ -29,8 +29,11 @@ pub mod intent;
|
||||
#[cfg(feature = "jarvis_app")]
|
||||
pub mod slots;
|
||||
|
||||
pub mod vosk_models;
|
||||
pub mod gliner_models;
|
||||
pub mod models;
|
||||
|
||||
// re-exported from models/
|
||||
pub use models::vosk_models;
|
||||
pub use models::gliner_models;
|
||||
|
||||
#[cfg(feature = "jarvis_app")]
|
||||
pub mod audio_processing;
|
||||
@@ -64,5 +67,6 @@ pub static COMMANDS_LIST: OnceCell<Vec<JCommandsList>> = OnceCell::new();
|
||||
pub use commands::JCommandsList;
|
||||
pub use config::structs::*;
|
||||
pub use db::structs::Settings;
|
||||
pub use db::SettingsManager;
|
||||
|
||||
// use crate::commands::{JComandsList, JCommand};
|
||||
@@ -1,64 +1,45 @@
|
||||
// mod porcupine;
|
||||
|
||||
mod rustpotter;
|
||||
|
||||
mod vosk;
|
||||
|
||||
use once_cell::sync::OnceCell;
|
||||
use std::sync::atomic::{AtomicBool, Ordering};
|
||||
|
||||
use crate::config::structs::WakeWordEngine;
|
||||
use crate::{config, stt};
|
||||
|
||||
use crate::DB;
|
||||
|
||||
// store wake-word engine being used
|
||||
static WAKE_WORD_ENGINE: OnceCell<WakeWordEngine> = OnceCell::new();
|
||||
|
||||
// track listening state
|
||||
static LISTENING: AtomicBool = AtomicBool::new(false);
|
||||
|
||||
pub fn init() -> Result<(), ()> {
|
||||
pub fn init() -> Result<(), String> {
|
||||
if WAKE_WORD_ENGINE.get().is_some() {
|
||||
return Ok(());
|
||||
} // already initialized
|
||||
}
|
||||
|
||||
// store current engine
|
||||
WAKE_WORD_ENGINE
|
||||
.set(DB.get().unwrap().read().wake_word_engine)
|
||||
.unwrap();
|
||||
let engine = DB.get().unwrap().read().wake_word_engine;
|
||||
|
||||
// load given wake-word engine
|
||||
match WAKE_WORD_ENGINE.get().unwrap() {
|
||||
WAKE_WORD_ENGINE.set(engine)
|
||||
.map_err(|_| "Wake word engine already set".to_string())?;
|
||||
|
||||
match engine {
|
||||
WakeWordEngine::Porcupine => {
|
||||
// Init Porcupine wake-word engine
|
||||
info!("Initializing Porcupine wake-word engine.");
|
||||
|
||||
// return porcupine::init();
|
||||
unimplemented!("f*ck picovoice");
|
||||
Err("Porcupine wake-word engine is not supported".to_string())
|
||||
}
|
||||
WakeWordEngine::Rustpotter => {
|
||||
// Init Rustpotter wake-word engine
|
||||
info!("Initializing Rustpotter wake-word engine.");
|
||||
|
||||
return rustpotter::init();
|
||||
rustpotter::init()
|
||||
.map_err(|_| "Failed to init Rustpotter".to_string())
|
||||
}
|
||||
WakeWordEngine::Vosk => {
|
||||
// Init Vosk as wake-word engine (very slow, though)
|
||||
info!("Initializing Vosk as wake-word engine.");
|
||||
warn!("Using Vosk as wake-word engine is highly not recommended, because it's very slow for this task.");
|
||||
|
||||
return vosk::init();
|
||||
vosk::init()
|
||||
.map_err(|_| "Failed to init Vosk wake-word".to_string())
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub fn data_callback(frame_buffer: &[i16]) -> Option<i32> {
|
||||
match WAKE_WORD_ENGINE.get().unwrap() {
|
||||
WakeWordEngine::Porcupine => {
|
||||
// porcupine::data_callback(frame_buffer)
|
||||
unimplemented!("f*ck picovoice");
|
||||
},
|
||||
match WAKE_WORD_ENGINE.get()? {
|
||||
WakeWordEngine::Porcupine => None,
|
||||
WakeWordEngine::Rustpotter => rustpotter::data_callback(frame_buffer),
|
||||
WakeWordEngine::Vosk => vosk::data_callback(frame_buffer),
|
||||
}
|
||||
|
||||
@@ -1,14 +1,9 @@
|
||||
use std::path::Path;
|
||||
use std::sync::Mutex;
|
||||
|
||||
use once_cell::sync::OnceCell;
|
||||
use rustpotter::{
|
||||
AudioFmt, BandPassConfig, DetectorConfig, FiltersConfig, GainNormalizationConfig, Rustpotter,
|
||||
RustpotterConfig, ScoreMode,
|
||||
};
|
||||
use rustpotter::Rustpotter;
|
||||
|
||||
use crate::config;
|
||||
use crate::DB;
|
||||
|
||||
// store rustpotter instance
|
||||
static RUSTPOTTER: OnceCell<Mutex<Rustpotter>> = OnceCell::new();
|
||||
@@ -40,7 +35,7 @@ pub fn init() -> Result<(), ()> {
|
||||
}
|
||||
|
||||
// store
|
||||
RUSTPOTTER.set(Mutex::new(rinstance));
|
||||
let _ = RUSTPOTTER.set(Mutex::new(rinstance));
|
||||
}
|
||||
Err(msg) => {
|
||||
error!("Rustpotter failed to initialize.\nError details: {}", msg);
|
||||
|
||||
@@ -148,7 +148,7 @@ fn http_request_with_headers(
|
||||
|
||||
// Convert Lua table to serde_json::Value
|
||||
fn table_to_json(lua: &Lua, table: Table) -> mlua::Result<serde_json::Value> {
|
||||
use serde_json::{Value as JsonValue, Map, Number};
|
||||
use serde_json::{Value as JsonValue, Map};
|
||||
|
||||
// check if it's an array (sequential integer keys starting from 1)
|
||||
let is_array = table.clone().pairs::<i64, Value>()
|
||||
|
||||
@@ -1,9 +1,7 @@
|
||||
use mlua::{Lua, Result as LuaResult, Value, StdLib};
|
||||
use mlua::{Lua, Value, StdLib};
|
||||
use std::path::PathBuf;
|
||||
use std::time::{Duration, Instant};
|
||||
use std::time::Duration;
|
||||
use std::fs;
|
||||
use std::sync::atomic::{AtomicBool, Ordering};
|
||||
use std::sync::{Arc, mpsc};
|
||||
|
||||
use super::sandbox::SandboxLevel;
|
||||
use super::error::LuaError;
|
||||
|
||||
67
crates/jarvis-core/src/models.rs
Normal file
67
crates/jarvis-core/src/models.rs
Normal file
@@ -0,0 +1,67 @@
|
||||
mod registry;
|
||||
mod catalog;
|
||||
pub mod structs;
|
||||
pub mod loaders;
|
||||
|
||||
pub mod vosk_models;
|
||||
pub mod gliner_models;
|
||||
|
||||
// re-export loaders
|
||||
#[cfg(feature = "jarvis_app")]
|
||||
pub use loaders::embedding;
|
||||
|
||||
#[cfg(feature = "jarvis_app")]
|
||||
pub use loaders::gliner;
|
||||
|
||||
#[cfg(feature = "jarvis_app")]
|
||||
pub use loaders::ort_model;
|
||||
|
||||
#[cfg(feature = "jarvis_app")]
|
||||
pub use loaders::intent_classifier;
|
||||
|
||||
#[cfg(feature = "vosk")]
|
||||
pub use loaders::vosk;
|
||||
|
||||
#[cfg(feature = "nnnoiseless")]
|
||||
pub use loaders::nnnoiseless;
|
||||
|
||||
pub use registry::ModelRegistry;
|
||||
pub use structs::{Task, ModelDef, BackendOption};
|
||||
|
||||
use once_cell::sync::OnceCell;
|
||||
|
||||
use crate::APP_DIR;
|
||||
|
||||
pub const MODELS_PATH: &str = "resources/models";
|
||||
|
||||
static REGISTRY: OnceCell<ModelRegistry> = OnceCell::new();
|
||||
|
||||
pub fn init() -> Result<(), String> {
|
||||
if REGISTRY.get().is_some() {
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
let registry = ModelRegistry::new();
|
||||
|
||||
let models_dir = APP_DIR.join(MODELS_PATH);
|
||||
let models = catalog::scan_models(&models_dir);
|
||||
info!("Found {} model(s) in {:?}", models.len(), models_dir);
|
||||
registry.set_catalog(models);
|
||||
|
||||
REGISTRY.set(registry)
|
||||
.map_err(|_| "Models registry already initialized".to_string())?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
pub fn registry() -> &'static ModelRegistry {
|
||||
REGISTRY.get().expect("Models registry not initialized - call models::init() first")
|
||||
}
|
||||
|
||||
pub fn get_options(task: Task) -> Vec<BackendOption> {
|
||||
registry().with_catalog(|models| catalog::get_options(task, models))
|
||||
}
|
||||
|
||||
pub fn is_valid_backend(task: Task, backend_id: &str) -> bool {
|
||||
registry().with_catalog(|models| catalog::is_valid_backend(task, backend_id, models))
|
||||
}
|
||||
140
crates/jarvis-core/src/models/catalog.rs
Normal file
140
crates/jarvis-core/src/models/catalog.rs
Normal file
@@ -0,0 +1,140 @@
|
||||
use std::fs;
|
||||
use std::path::Path;
|
||||
|
||||
use super::structs::{Task, ModelDef, BackendOption};
|
||||
|
||||
// scan the models directory for folders containing model.toml
|
||||
pub fn scan_models(models_dir: &Path) -> Vec<ModelDef> {
|
||||
let mut models = Vec::new();
|
||||
|
||||
if !models_dir.exists() {
|
||||
warn!("Models directory not found: {:?}", models_dir);
|
||||
return models;
|
||||
}
|
||||
|
||||
let entries = match fs::read_dir(models_dir) {
|
||||
Ok(e) => e,
|
||||
Err(e) => {
|
||||
warn!("Failed to read models dir: {}", e);
|
||||
return models;
|
||||
}
|
||||
};
|
||||
|
||||
for entry in entries.flatten() {
|
||||
let path = entry.path();
|
||||
if !path.is_dir() {
|
||||
continue;
|
||||
}
|
||||
|
||||
let toml_path = path.join("model.toml");
|
||||
if !toml_path.exists() {
|
||||
continue;
|
||||
}
|
||||
|
||||
match load_model_def(&toml_path, &path) {
|
||||
Ok(def) => {
|
||||
info!("Found model: {} ({}) - tasks: {:?}", def.name, def.id, def.tasks);
|
||||
models.push(def);
|
||||
}
|
||||
Err(e) => warn!("Failed to load model from {:?}: {}", path, e),
|
||||
}
|
||||
}
|
||||
|
||||
models
|
||||
}
|
||||
|
||||
fn load_model_def(toml_path: &Path, model_dir: &Path) -> Result<ModelDef, String> {
|
||||
let content = fs::read_to_string(toml_path)
|
||||
.map_err(|e| format!("read error: {}", e))?;
|
||||
|
||||
let parsed: ModelToml = toml::from_str(&content)
|
||||
.map_err(|e| format!("parse error: {}", e))?;
|
||||
|
||||
let mut def = parsed.model;
|
||||
def.path = model_dir.to_path_buf();
|
||||
|
||||
Ok(def)
|
||||
}
|
||||
|
||||
#[derive(serde::Deserialize)]
|
||||
struct ModelToml {
|
||||
model: ModelDef,
|
||||
}
|
||||
|
||||
// Code backends per task
|
||||
pub fn code_backends(task: Task) -> Vec<BackendOption> {
|
||||
match task {
|
||||
Task::Intent => vec![
|
||||
BackendOption {
|
||||
id: "intent-classifier".into(),
|
||||
name: "Intent Classifier".into(),
|
||||
model_id: None,
|
||||
},
|
||||
],
|
||||
Task::Slots => vec![],
|
||||
Task::Vad => vec![
|
||||
BackendOption {
|
||||
id: "energy".into(),
|
||||
name: "Energy-based".into(),
|
||||
model_id: None,
|
||||
},
|
||||
BackendOption {
|
||||
id: "nnnoiseless".into(),
|
||||
name: "Nnnoiseless".into(),
|
||||
model_id: None,
|
||||
},
|
||||
],
|
||||
Task::NoiseSuppression => vec![
|
||||
BackendOption {
|
||||
id: "nnnoiseless".into(),
|
||||
name: "Nnnoiseless".into(),
|
||||
model_id: None,
|
||||
},
|
||||
],
|
||||
Task::Stt => vec![
|
||||
BackendOption {
|
||||
id: "vosk".into(),
|
||||
name: "Vosk".into(),
|
||||
model_id: None,
|
||||
},
|
||||
],
|
||||
}
|
||||
}
|
||||
|
||||
// get all available options for a task:
|
||||
// "none" first, then code backends, then AI models from catalog
|
||||
pub fn get_options(task: Task, models: &[ModelDef]) -> Vec<BackendOption> {
|
||||
let mut options = vec![
|
||||
BackendOption {
|
||||
id: "none".into(),
|
||||
name: "Disabled".into(),
|
||||
model_id: None,
|
||||
},
|
||||
];
|
||||
|
||||
options.extend(code_backends(task));
|
||||
|
||||
for model in models {
|
||||
if model.tasks.contains(&task) {
|
||||
options.push(BackendOption {
|
||||
id: model.id.clone(),
|
||||
name: model.name.clone(),
|
||||
model_id: Some(model.id.clone()),
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
options
|
||||
}
|
||||
|
||||
pub fn is_valid_backend(task: Task, backend_id: &str, models: &[ModelDef]) -> bool {
|
||||
if backend_id == "none" {
|
||||
return true;
|
||||
}
|
||||
|
||||
if code_backends(task).iter().any(|b| b.id == backend_id) {
|
||||
return true;
|
||||
}
|
||||
|
||||
models.iter().any(|m| m.id == backend_id && m.tasks.contains(&task))
|
||||
}
|
||||
47
crates/jarvis-core/src/models/loaders/embedding.rs
Normal file
47
crates/jarvis-core/src/models/loaders/embedding.rs
Normal file
@@ -0,0 +1,47 @@
|
||||
// fastembed embedding model (all-MiniLM-L6-v2, paraphrase-multilingual, etc.)
|
||||
|
||||
use std::sync::Arc;
|
||||
use parking_lot::Mutex;
|
||||
use fastembed::{TextEmbedding, UserDefinedEmbeddingModel, TokenizerFiles, Pooling, QuantizationMode, OutputKey};
|
||||
|
||||
use crate::models::registry::ModelRegistry;
|
||||
|
||||
pub struct EmbeddingModel {
|
||||
pub embedding: Mutex<TextEmbedding>,
|
||||
}
|
||||
|
||||
// fastembed uses ORT internally which is thread-safe
|
||||
unsafe impl Send for EmbeddingModel {}
|
||||
unsafe impl Sync for EmbeddingModel {}
|
||||
|
||||
pub fn load(registry: &ModelRegistry, model_id: &str) -> Result<Arc<EmbeddingModel>, String> {
|
||||
registry.get_or_load::<EmbeddingModel>(model_id, |def| {
|
||||
let model_dir = &def.path;
|
||||
|
||||
info!("Loading embedding model from: {}", model_dir.display());
|
||||
|
||||
let user_model = UserDefinedEmbeddingModel {
|
||||
onnx_file: std::fs::read(model_dir.join("model.onnx"))
|
||||
.map_err(|e| format!("Failed to read model.onnx: {}", e))?,
|
||||
tokenizer_files: TokenizerFiles {
|
||||
tokenizer_file: std::fs::read(model_dir.join("tokenizer.json"))
|
||||
.map_err(|e| format!("Failed to read tokenizer.json: {}", e))?,
|
||||
config_file: std::fs::read(model_dir.join("config.json"))
|
||||
.map_err(|e| format!("Failed to read config.json: {}", e))?,
|
||||
special_tokens_map_file: std::fs::read(model_dir.join("special_tokens_map.json"))
|
||||
.map_err(|e| format!("Failed to read special_tokens_map.json: {}", e))?,
|
||||
tokenizer_config_file: std::fs::read(model_dir.join("tokenizer_config.json"))
|
||||
.map_err(|e| format!("Failed to read tokenizer_config.json: {}", e))?,
|
||||
},
|
||||
pooling: Some(Pooling::Mean),
|
||||
quantization: QuantizationMode::None,
|
||||
output_key: Some(OutputKey::ByName("last_hidden_state")),
|
||||
};
|
||||
|
||||
let model = TextEmbedding::try_new_from_user_defined(user_model, Default::default())
|
||||
.map_err(|e| format!("Failed to load embedding model: {}", e))?;
|
||||
|
||||
info!("Embedding model loaded: {}", def.name);
|
||||
Ok(EmbeddingModel { embedding: Mutex::new(model) })
|
||||
})
|
||||
}
|
||||
51
crates/jarvis-core/src/models/loaders/gliner.rs
Normal file
51
crates/jarvis-core/src/models/loaders/gliner.rs
Normal file
@@ -0,0 +1,51 @@
|
||||
// GLiNER model for named entity recognition / slot extraction
|
||||
|
||||
use std::sync::Arc;
|
||||
use parking_lot::Mutex;
|
||||
use regex::Regex;
|
||||
use tokenizers::Tokenizer;
|
||||
|
||||
use crate::models::registry::ModelRegistry;
|
||||
|
||||
const WORD_REGEX: &str = r"\w+(?:[-_]\w+)*|\S";
|
||||
|
||||
pub struct GlinerModel {
|
||||
pub session: Mutex<ort::session::Session>,
|
||||
pub tokenizer: Tokenizer,
|
||||
pub splitter: Regex,
|
||||
}
|
||||
|
||||
unsafe impl Send for GlinerModel {}
|
||||
unsafe impl Sync for GlinerModel {}
|
||||
|
||||
pub fn load(registry: &ModelRegistry, model_id: &str) -> Result<Arc<GlinerModel>, String> {
|
||||
registry.get_or_load::<GlinerModel>(model_id, |def| {
|
||||
let model_dir = &def.path;
|
||||
|
||||
// GLiNER models keep onnx files in an "onnx" subfolder
|
||||
let onnx_dir = model_dir.join("onnx");
|
||||
let model_path = if onnx_dir.exists() {
|
||||
onnx_dir.join("model.onnx")
|
||||
} else {
|
||||
model_dir.join("model.onnx")
|
||||
};
|
||||
|
||||
let tokenizer_path = model_dir.join("tokenizer.json");
|
||||
|
||||
info!("Loading GLiNER model from: {}", model_dir.display());
|
||||
|
||||
let session = ort::session::Session::builder()
|
||||
.map_err(|e| format!("Failed to create ORT session builder: {}", e))?
|
||||
.commit_from_file(&model_path)
|
||||
.map_err(|e| format!("Failed to load ONNX model: {}", e))?;
|
||||
|
||||
let tokenizer = Tokenizer::from_file(&tokenizer_path)
|
||||
.map_err(|e| format!("Failed to load tokenizer: {}", e))?;
|
||||
|
||||
let splitter = Regex::new(WORD_REGEX)
|
||||
.map_err(|e| format!("Failed to compile word regex: {}", e))?;
|
||||
|
||||
info!("GLiNER model loaded: {}", def.name);
|
||||
Ok(GlinerModel { session: Mutex::new(session), tokenizer, splitter })
|
||||
})
|
||||
}
|
||||
30
crates/jarvis-core/src/models/loaders/intent_classifier.rs
Normal file
30
crates/jarvis-core/src/models/loaders/intent_classifier.rs
Normal file
@@ -0,0 +1,30 @@
|
||||
// intent-classifier crate wrapper
|
||||
|
||||
use std::sync::Arc;
|
||||
use intent_classifier::IntentClassifier;
|
||||
|
||||
use crate::models::registry::ModelRegistry;
|
||||
|
||||
pub struct IntentClassifierModel {
|
||||
pub classifier: IntentClassifier,
|
||||
}
|
||||
|
||||
unsafe impl Send for IntentClassifierModel {}
|
||||
unsafe impl Sync for IntentClassifierModel {}
|
||||
|
||||
// init is async (IntentClassifier::new().await), so we create it
|
||||
// outside the registry and insert it after
|
||||
pub async fn load(registry: &ModelRegistry, model_id: &str) -> Result<Arc<IntentClassifierModel>, String> {
|
||||
if let Some(existing) = registry.get::<IntentClassifierModel>(model_id) {
|
||||
info!("IntentClassifier '{}' already loaded, reusing", model_id);
|
||||
return Ok(existing);
|
||||
}
|
||||
|
||||
info!("Initializing IntentClassifier...");
|
||||
|
||||
let classifier = IntentClassifier::new().await
|
||||
.map_err(|e| format!("Failed to init IntentClassifier: {}", e))?;
|
||||
|
||||
info!("IntentClassifier initialized");
|
||||
Ok(registry.insert(model_id, IntentClassifierModel { classifier }))
|
||||
}
|
||||
12
crates/jarvis-core/src/models/loaders/mod.rs
Normal file
12
crates/jarvis-core/src/models/loaders/mod.rs
Normal file
@@ -0,0 +1,12 @@
|
||||
#[cfg(feature = "jarvis_app")]
|
||||
pub mod embedding;
|
||||
#[cfg(feature = "jarvis_app")]
|
||||
pub mod gliner;
|
||||
#[cfg(feature = "jarvis_app")]
|
||||
pub mod ort_model;
|
||||
#[cfg(feature = "jarvis_app")]
|
||||
pub mod intent_classifier;
|
||||
#[cfg(feature = "vosk")]
|
||||
pub mod vosk;
|
||||
#[cfg(feature = "nnnoiseless")]
|
||||
pub mod nnnoiseless;
|
||||
110
crates/jarvis-core/src/models/loaders/nnnoiseless.rs
Normal file
110
crates/jarvis-core/src/models/loaders/nnnoiseless.rs
Normal file
@@ -0,0 +1,110 @@
|
||||
// nnnoiseless - used for both noise suppression and VAD.
|
||||
// each consumer needs its own DenoiseState (stateful per-stream),
|
||||
// so this doesn't go through the registry. just centralizes creation.
|
||||
|
||||
use nnnoiseless::DenoiseState;
|
||||
use crate::config;
|
||||
|
||||
// noise suppression instance
|
||||
pub struct NnnoiselessNS {
|
||||
state: Box<DenoiseState<'static>>,
|
||||
buffer: Vec<f32>,
|
||||
}
|
||||
|
||||
impl NnnoiselessNS {
|
||||
pub fn new() -> Self {
|
||||
Self {
|
||||
state: DenoiseState::new(),
|
||||
buffer: Vec::with_capacity(config::NNNOISELESS_FRAME_SIZE * 2),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn process(&mut self, input: &[i16]) -> Vec<i16> {
|
||||
self.buffer.extend(input.iter().map(|&s| s as f32));
|
||||
|
||||
let frame_size = config::NNNOISELESS_FRAME_SIZE;
|
||||
let full_frames = self.buffer.len() / frame_size;
|
||||
|
||||
if full_frames == 0 {
|
||||
return input.to_vec();
|
||||
}
|
||||
|
||||
let mut output: Vec<i16> = Vec::with_capacity(full_frames * frame_size);
|
||||
let mut input_frame = [0.0f32; 480];
|
||||
let mut output_frame = [0.0f32; 480];
|
||||
|
||||
let consumed = full_frames * frame_size;
|
||||
for i in 0..full_frames {
|
||||
let offset = i * frame_size;
|
||||
input_frame.copy_from_slice(&self.buffer[offset..offset + frame_size]);
|
||||
|
||||
let _ = self.state.process_frame(&mut output_frame, &input_frame);
|
||||
|
||||
for &sample in &output_frame {
|
||||
let clamped = sample.clamp(i16::MIN as f32, i16::MAX as f32);
|
||||
output.push(clamped as i16);
|
||||
}
|
||||
}
|
||||
|
||||
// keep leftover samples (single drain at the end)
|
||||
self.buffer.drain(..consumed);
|
||||
|
||||
output
|
||||
}
|
||||
|
||||
pub fn reset(&mut self) {
|
||||
self.buffer.clear();
|
||||
}
|
||||
}
|
||||
|
||||
// VAD instance
|
||||
pub struct NnnoiselessVAD {
|
||||
state: Box<DenoiseState<'static>>,
|
||||
buffer: Vec<f32>,
|
||||
}
|
||||
|
||||
impl NnnoiselessVAD {
|
||||
pub fn new() -> Self {
|
||||
Self {
|
||||
state: DenoiseState::new(),
|
||||
buffer: Vec::with_capacity(config::NNNOISELESS_FRAME_SIZE * 2),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn detect(&mut self, input: &[i16]) -> (bool, f32) {
|
||||
self.buffer.extend(input.iter().map(|&s| s as f32));
|
||||
|
||||
let frame_size = config::NNNOISELESS_FRAME_SIZE;
|
||||
let full_frames = self.buffer.len() / frame_size;
|
||||
|
||||
if full_frames == 0 {
|
||||
return (true, 0.5);
|
||||
}
|
||||
|
||||
let mut total_vad = 0.0f32;
|
||||
let mut input_frame = [0.0f32; 480];
|
||||
let mut output_frame = [0.0f32; 480];
|
||||
|
||||
let consumed = full_frames * frame_size;
|
||||
for i in 0..full_frames {
|
||||
let offset = i * frame_size;
|
||||
input_frame.copy_from_slice(&self.buffer[offset..offset + frame_size]);
|
||||
|
||||
let vad_prob = self.state.process_frame(&mut output_frame, &input_frame);
|
||||
total_vad += vad_prob;
|
||||
}
|
||||
|
||||
// single drain
|
||||
self.buffer.drain(..consumed);
|
||||
|
||||
let avg_vad = total_vad / full_frames as f32;
|
||||
let is_voice = avg_vad >= config::VAD_NNNOISELESS_THRESHOLD;
|
||||
|
||||
(is_voice, avg_vad)
|
||||
}
|
||||
|
||||
pub fn reset(&mut self) {
|
||||
self.state = DenoiseState::new();
|
||||
self.buffer.clear();
|
||||
}
|
||||
}
|
||||
44
crates/jarvis-core/src/models/loaders/ort_model.rs
Normal file
44
crates/jarvis-core/src/models/loaders/ort_model.rs
Normal file
@@ -0,0 +1,44 @@
|
||||
// generic ORT model - session + optional tokenizer.
|
||||
// for models like BERT (tiny, distil, mini) that can serve
|
||||
// multiple tasks (intent, NER, text classification, etc.)
|
||||
|
||||
use std::sync::Arc;
|
||||
use parking_lot::Mutex;
|
||||
use tokenizers::Tokenizer;
|
||||
|
||||
use crate::models::registry::ModelRegistry;
|
||||
|
||||
pub struct OrtModel {
|
||||
pub session: Mutex<ort::session::Session>,
|
||||
pub tokenizer: Option<Tokenizer>,
|
||||
}
|
||||
|
||||
unsafe impl Send for OrtModel {}
|
||||
unsafe impl Sync for OrtModel {}
|
||||
|
||||
pub fn load(registry: &ModelRegistry, model_id: &str) -> Result<Arc<OrtModel>, String> {
|
||||
registry.get_or_load::<OrtModel>(model_id, |def| {
|
||||
let model_dir = &def.path;
|
||||
let onnx_path = model_dir.join("model.onnx");
|
||||
|
||||
info!("Loading ORT model from: {}", model_dir.display());
|
||||
|
||||
let session = ort::session::Session::builder()
|
||||
.map_err(|e| format!("ORT session builder error: {}", e))?
|
||||
.commit_from_file(&onnx_path)
|
||||
.map_err(|e| format!("Failed to load ONNX model '{}': {}", onnx_path.display(), e))?;
|
||||
|
||||
let tokenizer_path = model_dir.join("tokenizer.json");
|
||||
let tokenizer = if tokenizer_path.exists() {
|
||||
Some(
|
||||
Tokenizer::from_file(&tokenizer_path)
|
||||
.map_err(|e| format!("Failed to load tokenizer: {}", e))?
|
||||
)
|
||||
} else {
|
||||
None
|
||||
};
|
||||
|
||||
info!("ORT model loaded: {}", def.name);
|
||||
Ok(OrtModel { session: Mutex::new(session), tokenizer })
|
||||
})
|
||||
}
|
||||
33
crates/jarvis-core/src/models/loaders/vosk.rs
Normal file
33
crates/jarvis-core/src/models/loaders/vosk.rs
Normal file
@@ -0,0 +1,33 @@
|
||||
// vosk speech recognition model
|
||||
|
||||
use std::sync::Arc;
|
||||
use vosk::Model;
|
||||
|
||||
use crate::models::registry::ModelRegistry;
|
||||
|
||||
pub struct VoskModel {
|
||||
pub model: Model,
|
||||
}
|
||||
|
||||
unsafe impl Send for VoskModel {}
|
||||
unsafe impl Sync for VoskModel {}
|
||||
|
||||
// load a vosk model by path through the registry.
|
||||
// vosk models aren't in the catalog (they use their own directory structure),
|
||||
// so we pass the path directly and use model_id for dedup.
|
||||
// @ToDo: Consider moving to catalog
|
||||
pub fn load(registry: &ModelRegistry, model_id: &str, model_path: &str) -> Result<Arc<VoskModel>, String> {
|
||||
// check if already loaded
|
||||
if let Some(existing) = registry.get::<VoskModel>(model_id) {
|
||||
info!("Vosk model '{}' already loaded, reusing", model_id);
|
||||
return Ok(existing);
|
||||
}
|
||||
|
||||
info!("Loading Vosk model from: {}", model_path);
|
||||
|
||||
let model = Model::new(model_path)
|
||||
.ok_or_else(|| format!("Failed to load Vosk model from: {}", model_path))?;
|
||||
|
||||
info!("Vosk model loaded: {}", model_id);
|
||||
Ok(registry.insert(model_id, VoskModel { model }))
|
||||
}
|
||||
108
crates/jarvis-core/src/models/registry.rs
Normal file
108
crates/jarvis-core/src/models/registry.rs
Normal file
@@ -0,0 +1,108 @@
|
||||
use std::any::Any;
|
||||
use std::collections::HashMap;
|
||||
use std::sync::Arc;
|
||||
use parking_lot::{Mutex, RwLock};
|
||||
|
||||
use super::structs::ModelDef;
|
||||
|
||||
// central model registry. loads models once and shares them between components.
|
||||
// completely type-agnostic
|
||||
pub struct ModelRegistry {
|
||||
loaded: Mutex<HashMap<String, Arc<dyn Any + Send + Sync>>>,
|
||||
catalog: RwLock<Vec<ModelDef>>,
|
||||
}
|
||||
|
||||
impl ModelRegistry {
|
||||
pub fn new() -> Self {
|
||||
Self {
|
||||
loaded: Mutex::new(HashMap::new()),
|
||||
catalog: RwLock::new(Vec::new()),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn set_catalog(&self, defs: Vec<ModelDef>) {
|
||||
*self.catalog.write() = defs;
|
||||
}
|
||||
|
||||
// read access to catalog without cloning the whole vec
|
||||
pub fn with_catalog<R>(&self, f: impl FnOnce(&[ModelDef]) -> R) -> R {
|
||||
f(&self.catalog.read())
|
||||
}
|
||||
|
||||
pub fn get_model_def(&self, id: &str) -> Option<ModelDef> {
|
||||
self.catalog.read().iter().find(|m| m.id == id).cloned()
|
||||
}
|
||||
|
||||
// get a loaded model, downcasted to the expected type
|
||||
pub fn get<T: 'static + Send + Sync>(&self, id: &str) -> Option<Arc<T>> {
|
||||
self.loaded.lock()
|
||||
.get(id)?
|
||||
.clone()
|
||||
.downcast::<T>()
|
||||
.ok()
|
||||
}
|
||||
|
||||
// get or load a model. if two components request the same id,
|
||||
// the model only loads once.
|
||||
//
|
||||
// the lock is released before calling the loader to avoid deadlocks
|
||||
// if the loader tries to load a dependency through the registry.
|
||||
pub fn get_or_load<T: 'static + Send + Sync>(
|
||||
&self,
|
||||
id: &str,
|
||||
loader: impl FnOnce(&ModelDef) -> Result<T, String>,
|
||||
) -> Result<Arc<T>, String> {
|
||||
// fast path: already loaded
|
||||
if let Some(existing) = self.get::<T>(id) {
|
||||
info!("Model '{}' already loaded, reusing", id);
|
||||
return Ok(existing);
|
||||
}
|
||||
|
||||
// grab model def (releases catalog lock immediately)
|
||||
let def = self.get_model_def(id)
|
||||
.ok_or_else(|| format!("Model '{}' not found in catalog", id))?;
|
||||
|
||||
// run loader without holding any lock
|
||||
info!("Loading model '{}' from {:?}...", id, def.path);
|
||||
let model = loader(&def)?;
|
||||
let arc = Arc::new(model);
|
||||
|
||||
// insert (check again in case another thread loaded it meanwhile)
|
||||
let mut map = self.loaded.lock();
|
||||
if let Some(existing) = map.get(id) {
|
||||
if let Ok(typed) = existing.clone().downcast::<T>() {
|
||||
info!("Model '{}' was loaded by another thread, reusing", id);
|
||||
return Ok(typed);
|
||||
}
|
||||
}
|
||||
|
||||
map.insert(id.to_string(), arc.clone());
|
||||
info!("Model '{}' loaded and registered", id);
|
||||
|
||||
Ok(arc)
|
||||
}
|
||||
|
||||
// insert a model directly (for models not in the catalog,
|
||||
// or loaded through non-standard means like async init)
|
||||
pub fn insert<T: 'static + Send + Sync>(&self, id: &str, model: T) -> Arc<T> {
|
||||
let arc = Arc::new(model);
|
||||
self.loaded.lock().insert(id.to_string(), arc.clone());
|
||||
arc
|
||||
}
|
||||
|
||||
pub fn unload(&self, id: &str) -> bool {
|
||||
let removed = self.loaded.lock().remove(id).is_some();
|
||||
if removed {
|
||||
info!("Model '{}' unloaded from registry", id);
|
||||
}
|
||||
removed
|
||||
}
|
||||
|
||||
pub fn is_loaded(&self, id: &str) -> bool {
|
||||
self.loaded.lock().contains_key(id)
|
||||
}
|
||||
|
||||
pub fn loaded_ids(&self) -> Vec<String> {
|
||||
self.loaded.lock().keys().cloned().collect()
|
||||
}
|
||||
}
|
||||
38
crates/jarvis-core/src/models/structs.rs
Normal file
38
crates/jarvis-core/src/models/structs.rs
Normal file
@@ -0,0 +1,38 @@
|
||||
use std::path::PathBuf;
|
||||
use serde::{Serialize, Deserialize};
|
||||
|
||||
// tasks that components can request a backend for
|
||||
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash, Serialize, Deserialize)]
|
||||
#[serde(rename_all = "snake_case")]
|
||||
pub enum Task {
|
||||
Intent,
|
||||
Slots,
|
||||
Vad,
|
||||
NoiseSuppression,
|
||||
Stt,
|
||||
}
|
||||
|
||||
// metadata about a model, parsed from model.toml on disk
|
||||
#[derive(Debug, Clone, Serialize, Deserialize)]
|
||||
pub struct ModelDef {
|
||||
pub id: String,
|
||||
pub name: String,
|
||||
pub tasks: Vec<Task>,
|
||||
|
||||
#[serde(default)]
|
||||
pub description: String,
|
||||
|
||||
// set at runtime after scanning the folder
|
||||
#[serde(skip)]
|
||||
pub path: PathBuf,
|
||||
}
|
||||
|
||||
// a selectable option for a task (shown in UI / stored in settings)
|
||||
#[derive(Debug, Clone, Serialize)]
|
||||
pub struct BackendOption {
|
||||
pub id: String,
|
||||
pub name: String,
|
||||
// if Some, this option uses a model from the registry.
|
||||
// if None, it's a code-only backend (like energy VAD) or disabled.
|
||||
pub model_id: Option<String>,
|
||||
}
|
||||
@@ -19,7 +19,7 @@ pub fn init_microphone(device_index: i32, frame_length: u32) -> bool {
|
||||
match pv_recorder {
|
||||
Ok(pv) => {
|
||||
// store
|
||||
RECORDER.set(pv);
|
||||
let _ = RECORDER.set(pv);
|
||||
|
||||
// success
|
||||
true
|
||||
|
||||
@@ -4,37 +4,37 @@ use std::collections::HashMap;
|
||||
use once_cell::sync::OnceCell;
|
||||
|
||||
use crate::commands::{SlotDefinition, SlotValue};
|
||||
use crate::config::structs::SlotExtractionEngine;
|
||||
use crate::DB;
|
||||
use crate::{models, DB};
|
||||
|
||||
static SLOT_ENGINE: OnceCell<SlotExtractionEngine> = OnceCell::new();
|
||||
static BACKEND: OnceCell<String> = OnceCell::new();
|
||||
|
||||
pub fn init() -> Result<(), String> {
|
||||
if SLOT_ENGINE.get().is_some() {
|
||||
if BACKEND.get().is_some() {
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
let engine = DB.get()
|
||||
.map(|db| db.read().slot_extraction_engine)
|
||||
.unwrap_or(SlotExtractionEngine::None);
|
||||
let backend = DB.get()
|
||||
.map(|db| db.read().slots_backend.clone())
|
||||
.unwrap_or_else(|| "none".to_string());
|
||||
|
||||
SLOT_ENGINE.set(engine).map_err(|_| "Slot engine already set")?;
|
||||
BACKEND.set(backend.clone()).map_err(|_| "Slot backend already set")?;
|
||||
|
||||
match engine {
|
||||
SlotExtractionEngine::None => {
|
||||
match backend.as_str() {
|
||||
"none" => {
|
||||
info!("Slot extraction disabled");
|
||||
}
|
||||
SlotExtractionEngine::GLiNER => {
|
||||
info!("Initializing GLiNER slot extraction backend.");
|
||||
gliner::init()?;
|
||||
info!("GLiNER slot extraction backend initialized.");
|
||||
// any model ID is treated as a GLiNER model for now
|
||||
model_id => {
|
||||
info!("Initializing GLiNER slot extraction with model '{}'.", model_id);
|
||||
let model = models::gliner::load(models::registry(), model_id)?;
|
||||
gliner::init_with_model(model)?;
|
||||
info!("GLiNER slot extraction initialized.");
|
||||
}
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// Extract slot values from text using the configured engine
|
||||
pub fn extract(
|
||||
text: &str,
|
||||
slots: &HashMap<String, SlotDefinition>,
|
||||
@@ -43,9 +43,9 @@ pub fn extract(
|
||||
return HashMap::new();
|
||||
}
|
||||
|
||||
match SLOT_ENGINE.get().unwrap_or(&SlotExtractionEngine::None) {
|
||||
SlotExtractionEngine::None => HashMap::new(),
|
||||
SlotExtractionEngine::GLiNER => {
|
||||
match BACKEND.get().map(|s| s.as_str()).unwrap_or("none") {
|
||||
"none" => HashMap::new(),
|
||||
_ => {
|
||||
match gliner::extract(text, slots) {
|
||||
Ok(result) => result,
|
||||
Err(e) => {
|
||||
@@ -55,4 +55,4 @@ pub fn extract(
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -2,123 +2,43 @@
|
||||
// https://github.com/fbilhaut/gline-rs
|
||||
|
||||
use std::collections::HashMap;
|
||||
use std::path::PathBuf;
|
||||
use std::sync::Arc;
|
||||
use once_cell::sync::OnceCell;
|
||||
use parking_lot::Mutex;
|
||||
use ndarray::Array;
|
||||
use regex::Regex;
|
||||
use tokenizers::Tokenizer;
|
||||
use ort::value::Tensor;
|
||||
|
||||
pub mod structs;
|
||||
use structs::GlinerModelInfo;
|
||||
|
||||
use std::fs;
|
||||
|
||||
use crate::commands::{SlotDefinition, SlotValue};
|
||||
use crate::{APP_DIR, i18n};
|
||||
use crate::models::gliner::GlinerModel;
|
||||
|
||||
// MODEL STATE
|
||||
static MODEL: OnceCell<Arc<GlinerModel>> = OnceCell::new();
|
||||
|
||||
struct GlinerModel {
|
||||
session: ort::session::Session,
|
||||
tokenizer: Tokenizer,
|
||||
splitter: Regex,
|
||||
}
|
||||
|
||||
unsafe impl Send for GlinerModel {}
|
||||
unsafe impl Sync for GlinerModel {}
|
||||
|
||||
static MODEL: OnceCell<Mutex<GlinerModel>> = OnceCell::new();
|
||||
|
||||
// GLiNER defaults (same as gline-rs Parameters::default())
|
||||
// GLiNER defaults
|
||||
const THRESHOLD: f32 = 0.3;
|
||||
const MAX_WIDTH: usize = 12;
|
||||
const MAX_LENGTH: usize = 512;
|
||||
|
||||
// applied after decoding
|
||||
const MIN_CONFIDENCE: f32 = 0.4;
|
||||
|
||||
// word splitting regex (gline-rs RegexSplitter default)
|
||||
const WORD_REGEX: &str = r"\w+(?:[-_]\w+)*|\S";
|
||||
|
||||
// INIT
|
||||
|
||||
pub fn init() -> Result<(), String> {
|
||||
if MODEL.get().is_some() {
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
let variant = crate::DB.get()
|
||||
.map(|db| db.read().gliner_model.clone())
|
||||
.unwrap_or_default();
|
||||
|
||||
let language = i18n::get_language();
|
||||
|
||||
let (model_dir, onnx_file) = if variant.is_empty() {
|
||||
(select_model_dir(), "model.onnx".to_string())
|
||||
} else {
|
||||
crate::gliner_models::resolve_model(&variant, &language)
|
||||
.unwrap_or_else(|| (select_model_dir(), "model.onnx".to_string()))
|
||||
};
|
||||
|
||||
let model_path = model_dir.join("onnx").join(&onnx_file);
|
||||
let tokenizer_path = model_dir.join("tokenizer.json");
|
||||
|
||||
info!("Loading GLiNER model from: {}, variant {}", model_dir.display(), variant);
|
||||
|
||||
let session = ort::session::Session::builder()
|
||||
.map_err(|e| format!("Failed to create ort session builder: {}", e))?
|
||||
.commit_from_file(&model_path)
|
||||
.map_err(|e| format!("Failed to load ONNX model: {}", e))?;
|
||||
|
||||
let tokenizer = Tokenizer::from_file(&tokenizer_path)
|
||||
.map_err(|e| format!("Failed to load tokenizer: {}", e))?;
|
||||
|
||||
let splitter = Regex::new(WORD_REGEX)
|
||||
.map_err(|e| format!("Failed to compile word regex: {}", e))?;
|
||||
|
||||
MODEL.set(Mutex::new(GlinerModel { session, tokenizer, splitter }))
|
||||
.map_err(|_| "GLiNER model already initialized".to_string())?;
|
||||
|
||||
info!("GLiNER model loaded");
|
||||
pub fn init_with_model(model: Arc<GlinerModel>) -> Result<(), String> {
|
||||
MODEL.set(model).map_err(|_| "GLiNER model already initialized".to_string())?;
|
||||
info!("GLiNER slot extraction ready");
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn select_model_dir() -> PathBuf {
|
||||
let base = APP_DIR.join("resources").join("models");
|
||||
// word splitting
|
||||
|
||||
match i18n::get_language().as_str() {
|
||||
"en" => {
|
||||
let path = base.join("gliner_small-v2.1");
|
||||
if path.exists() { return path; }
|
||||
}
|
||||
_ => {}
|
||||
}
|
||||
|
||||
// multilingual (covers RU, UA, EN)
|
||||
let multi = base.join("gliner_multi-v2.1");
|
||||
if multi.exists() { return multi; }
|
||||
|
||||
// fallback
|
||||
base.join("gliner_small-v2.1")
|
||||
}
|
||||
|
||||
// WORD SPLITTING
|
||||
|
||||
struct WordToken {
|
||||
struct WordToken<'a> {
|
||||
start: usize,
|
||||
end: usize,
|
||||
text: String,
|
||||
text: &'a str,
|
||||
}
|
||||
|
||||
fn split_words(splitter: &Regex, text: &str, limit: Option<usize>) -> Vec<WordToken> {
|
||||
fn split_words<'a>(text: &'a str, model: &GlinerModel, limit: Option<usize>) -> Vec<WordToken<'a>> {
|
||||
let mut tokens = Vec::new();
|
||||
for m in splitter.find_iter(text) {
|
||||
for m in model.splitter.find_iter(text) {
|
||||
tokens.push(WordToken {
|
||||
start: m.start(),
|
||||
end: m.end(),
|
||||
text: m.as_str().to_string(),
|
||||
text: m.as_str(),
|
||||
});
|
||||
if let Some(lim) = limit {
|
||||
if tokens.len() >= lim { break; }
|
||||
@@ -127,7 +47,7 @@ fn split_words(splitter: &Regex, text: &str, limit: Option<usize>) -> Vec<WordTo
|
||||
tokens
|
||||
}
|
||||
|
||||
// PROMPT CONSTRUCTION
|
||||
// prompt construction
|
||||
//
|
||||
// GLiNER prompt format:
|
||||
// [<<ENT>>, label1_w1, label1_w2, <<ENT>>, label2_w1, ..., <<SEP>>, word1, word2, ..., wordN]
|
||||
@@ -137,20 +57,20 @@ fn build_prompt(entities: &[&str], words: &[WordToken]) -> (Vec<String>, usize)
|
||||
|
||||
for entity in entities {
|
||||
prompt.push("<<ENT>>".to_string());
|
||||
prompt.push(entity.to_string()); // whole string, no split
|
||||
prompt.push(entity.to_string());
|
||||
}
|
||||
prompt.push("<<SEP>>".to_string());
|
||||
|
||||
let entities_len = prompt.len();
|
||||
|
||||
for w in words {
|
||||
prompt.push(w.text.clone());
|
||||
prompt.push(w.text.to_string());
|
||||
}
|
||||
|
||||
(prompt, entities_len)
|
||||
}
|
||||
|
||||
// ENCODING
|
||||
// encoding
|
||||
|
||||
struct EncodedBatch {
|
||||
input_ids: ndarray::Array2<i64>,
|
||||
@@ -161,8 +81,7 @@ struct EncodedBatch {
|
||||
}
|
||||
|
||||
fn encode_single(
|
||||
tokenizer: &Tokenizer,
|
||||
_text: &str,
|
||||
model: &GlinerModel,
|
||||
entities: &[&str],
|
||||
words: &[WordToken],
|
||||
) -> Result<EncodedBatch, String> {
|
||||
@@ -174,7 +93,7 @@ fn encode_single(
|
||||
let mut entity_tokens: usize = 0;
|
||||
|
||||
for (pos, word) in prompt.iter().enumerate() {
|
||||
let encoding = tokenizer.encode(word.as_str(), false)
|
||||
let encoding = model.tokenizer.encode(word.as_str(), false)
|
||||
.map_err(|e| format!("Tokenizer encode error: {}", e))?;
|
||||
let ids = encoding.get_ids().to_vec();
|
||||
total_tokens += ids.len();
|
||||
@@ -184,13 +103,13 @@ fn encode_single(
|
||||
word_encodings.push(ids);
|
||||
}
|
||||
|
||||
// text_offset: index where text tokens start (after BOS + entity tokens)
|
||||
let text_offset = entity_tokens + 1;
|
||||
|
||||
// DEBUG
|
||||
debug!("GLiNER prompt ({} total, ent_len={}, text_offset={}):", prompt.len(), ent_len, text_offset);
|
||||
for (i, (word, enc)) in prompt.iter().zip(word_encodings.iter()).enumerate() {
|
||||
debug!(" [{}]{} '{}' -> {:?}", i, if i < ent_len { " ENT" } else { " TXT" }, word, enc);
|
||||
if log::log_enabled!(log::Level::Debug) {
|
||||
debug!("GLiNER prompt ({} total, ent_len={}, text_offset={}):", prompt.len(), ent_len, text_offset);
|
||||
for (i, (word, enc)) in prompt.iter().zip(word_encodings.iter()).enumerate() {
|
||||
debug!(" [{}]{} '{}' -> {:?}", i, if i < ent_len { " ENT" } else { " TXT" }, word, enc);
|
||||
}
|
||||
}
|
||||
|
||||
let mut input_ids = Array::zeros((1, total_tokens));
|
||||
@@ -205,18 +124,15 @@ fn encode_single(
|
||||
attention_masks[[0, idx]] = 1;
|
||||
idx += 1;
|
||||
|
||||
// encode each word - matching gline-rs idx-based logic exactly
|
||||
for word_enc in word_encodings.iter() {
|
||||
for (token_idx, &token_id) in word_enc.iter().enumerate() {
|
||||
input_ids[[0, idx]] = token_id as i64;
|
||||
attention_masks[[0, idx]] = 1;
|
||||
// word mask: only for text tokens (past text_offset), first sub-token only
|
||||
if idx >= text_offset && token_idx == 0 {
|
||||
word_masks[[0, idx]] = word_id;
|
||||
}
|
||||
idx += 1;
|
||||
}
|
||||
// increment word_id for any word whose tokens end past text_offset
|
||||
if idx >= text_offset {
|
||||
word_id += 1;
|
||||
}
|
||||
@@ -229,9 +145,11 @@ fn encode_single(
|
||||
let mut text_lengths = Array::zeros((1, 1));
|
||||
text_lengths[[0, 0]] = (text_word_count + 1) as i64;
|
||||
|
||||
debug!("GLiNER input_ids: {:?}", input_ids.as_slice().unwrap());
|
||||
debug!("GLiNER word_masks: {:?}", word_masks.as_slice().unwrap());
|
||||
debug!("GLiNER text_lengths: {}", text_word_count);
|
||||
if log::log_enabled!(log::Level::Debug) {
|
||||
debug!("GLiNER input_ids: {:?}", input_ids.as_slice().unwrap());
|
||||
debug!("GLiNER word_masks: {:?}", word_masks.as_slice().unwrap());
|
||||
debug!("GLiNER text_lengths: {}", text_word_count);
|
||||
}
|
||||
|
||||
Ok(EncodedBatch {
|
||||
input_ids,
|
||||
@@ -242,7 +160,7 @@ fn encode_single(
|
||||
})
|
||||
}
|
||||
|
||||
// SPAN TENSORS
|
||||
// span tensors
|
||||
|
||||
fn make_span_tensors(num_words: usize, max_width: usize) -> (ndarray::Array3<i64>, ndarray::Array2<bool>) {
|
||||
let num_spans = num_words * max_width;
|
||||
@@ -264,7 +182,7 @@ fn make_span_tensors(num_words: usize, max_width: usize) -> (ndarray::Array3<i64
|
||||
(span_idx, span_mask)
|
||||
}
|
||||
|
||||
// DECODE + GREEDY SEARCH
|
||||
// decode + greedy search
|
||||
|
||||
fn sigmoid(x: f32) -> f32 {
|
||||
1.0 / (1.0 + (-x).exp())
|
||||
@@ -323,56 +241,43 @@ fn decode_and_search(
|
||||
}
|
||||
|
||||
spans.sort_unstable_by(|a, b| (a.start, a.end).cmp(&(b.start, b.end)));
|
||||
greedy_flat(&spans)
|
||||
greedy_flat(spans)
|
||||
}
|
||||
|
||||
fn greedy_flat(spans: &[Entity]) -> Vec<Entity> {
|
||||
if spans.is_empty() {
|
||||
return Vec::new();
|
||||
// takes ownership, filters in place - no cloning
|
||||
fn greedy_flat(mut spans: Vec<Entity>) -> Vec<Entity> {
|
||||
if spans.len() <= 1 {
|
||||
return spans;
|
||||
}
|
||||
|
||||
let mut result: Vec<Entity> = Vec::new();
|
||||
let mut keep = vec![false; spans.len()];
|
||||
let mut prev = 0usize;
|
||||
let mut next = 1usize;
|
||||
|
||||
while next < spans.len() {
|
||||
let p = &spans[prev];
|
||||
let n = &spans[next];
|
||||
for next in 1..spans.len() {
|
||||
let no_overlap = spans[next].start >= spans[prev].end
|
||||
|| spans[prev].start >= spans[next].end;
|
||||
|
||||
if n.start >= p.end || p.start >= n.end {
|
||||
result.push(Entity {
|
||||
text: p.text.clone(),
|
||||
label: p.label.clone(),
|
||||
prob: p.prob,
|
||||
start: p.start,
|
||||
end: p.end,
|
||||
});
|
||||
if no_overlap {
|
||||
keep[prev] = true;
|
||||
prev = next;
|
||||
} else if p.prob < n.prob {
|
||||
} else if spans[prev].prob < spans[next].prob {
|
||||
prev = next;
|
||||
}
|
||||
next += 1;
|
||||
}
|
||||
keep[prev] = true;
|
||||
|
||||
let last = &spans[prev];
|
||||
result.push(Entity {
|
||||
text: last.text.clone(),
|
||||
label: last.label.clone(),
|
||||
prob: last.prob,
|
||||
start: last.start,
|
||||
end: last.end,
|
||||
});
|
||||
|
||||
result
|
||||
let mut idx = 0;
|
||||
spans.retain(|_| { let k = keep[idx]; idx += 1; k });
|
||||
spans
|
||||
}
|
||||
|
||||
// PUBLIC API
|
||||
// public extract API
|
||||
|
||||
pub fn extract(
|
||||
text: &str,
|
||||
slots: &HashMap<String, SlotDefinition>,
|
||||
) -> Result<HashMap<String, SlotValue>, String> {
|
||||
let mut model = MODEL.get().ok_or("GLiNER not initialized")?.lock();
|
||||
let model = MODEL.get().ok_or("GLiNER not initialized")?;
|
||||
|
||||
let mut label_to_slots: HashMap<&str, Vec<&str>> = HashMap::new();
|
||||
for (slot_name, def) in slots {
|
||||
@@ -392,12 +297,12 @@ pub fn extract(
|
||||
|
||||
debug!("GLiNER extract: text='{}', labels={:?}", text, labels);
|
||||
|
||||
let words = split_words(&model.splitter, text, Some(MAX_LENGTH));
|
||||
let words = split_words(text, &model, Some(MAX_LENGTH));
|
||||
if words.is_empty() {
|
||||
return Ok(HashMap::new());
|
||||
}
|
||||
|
||||
let encoded = encode_single(&model.tokenizer, text, &labels, &words)?;
|
||||
let encoded = encode_single(&model, &labels, &words)?;
|
||||
|
||||
let (span_idx, span_mask) = make_span_tensors(encoded.num_words, MAX_WIDTH);
|
||||
|
||||
@@ -408,7 +313,8 @@ pub fn extract(
|
||||
let t_span_idx = Tensor::from_array(span_idx).map_err(|e| format!("tensor: {}", e))?;
|
||||
let t_span_mask = Tensor::from_array(span_mask).map_err(|e| format!("tensor: {}", e))?;
|
||||
|
||||
let outputs = model.session.run(
|
||||
let mut session = model.session.lock();
|
||||
let outputs = session.run(
|
||||
ort::inputs! {
|
||||
"input_ids" => t_input_ids,
|
||||
"attention_mask" => t_attn,
|
||||
@@ -425,27 +331,29 @@ pub fn extract(
|
||||
|
||||
let logits_shape: Vec<usize> = shape.iter().map(|&d| d as usize).collect();
|
||||
|
||||
debug!("GLiNER logits shape: {:?}, data len: {}", logits_shape, logits_data.len());
|
||||
let max_logit = logits_data.iter().cloned().fold(f32::NEG_INFINITY, f32::max);
|
||||
debug!("GLiNER max logit: {:.4}, sigmoid: {:.4}", max_logit, sigmoid(max_logit));
|
||||
// debug dump - gated so sigmoid/loop don't run in release
|
||||
if log::log_enabled!(log::Level::Debug) {
|
||||
debug!("GLiNER logits shape: {:?}, data len: {}", logits_shape, logits_data.len());
|
||||
let max_logit = logits_data.iter().cloned().fold(f32::NEG_INFINITY, f32::max);
|
||||
debug!("GLiNER max logit: {:.4}, sigmoid: {:.4}", max_logit, sigmoid(max_logit));
|
||||
|
||||
// dump all scores above 5%
|
||||
let num_words = logits_shape.get(1).copied().unwrap_or(0);
|
||||
let dim_mw = logits_shape.get(2).copied().unwrap_or(0);
|
||||
let dim_e = logits_shape.get(3).copied().unwrap_or(0);
|
||||
for start in 0..num_words {
|
||||
for width in 0..dim_mw.min(num_words - start) {
|
||||
for class_idx in 0..dim_e {
|
||||
let flat_idx = start * dim_mw * dim_e + width * dim_e + class_idx;
|
||||
if flat_idx < logits_data.len() {
|
||||
let score = logits_data[flat_idx];
|
||||
let prob = sigmoid(score);
|
||||
if prob > 0.05 {
|
||||
let end = start + width;
|
||||
let w_start = if start < words.len() { &words[start].text } else { "?" };
|
||||
let w_end = if end < words.len() { &words[end].text } else { "?" };
|
||||
debug!(" span[{}..{}] '{}'->'{}' label={} score={:.3} prob={:.3}",
|
||||
start, end, w_start, w_end, labels.get(class_idx).unwrap_or(&"?"), score, prob);
|
||||
let num_words = logits_shape.get(1).copied().unwrap_or(0);
|
||||
let dim_mw = logits_shape.get(2).copied().unwrap_or(0);
|
||||
let dim_e = logits_shape.get(3).copied().unwrap_or(0);
|
||||
for start in 0..num_words {
|
||||
for width in 0..dim_mw.min(num_words - start) {
|
||||
for class_idx in 0..dim_e {
|
||||
let flat_idx = start * dim_mw * dim_e + width * dim_e + class_idx;
|
||||
if flat_idx < logits_data.len() {
|
||||
let score = logits_data[flat_idx];
|
||||
let prob = sigmoid(score);
|
||||
if prob > 0.05 {
|
||||
let end = start + width;
|
||||
let w_start = if start < words.len() { words[start].text } else { "?" };
|
||||
let w_end = if end < words.len() { words[end].text } else { "?" };
|
||||
debug!(" span[{}..{}] '{}'->'{}' label={} score={:.3} prob={:.3}",
|
||||
start, end, w_start, w_end, labels.get(class_idx).unwrap_or(&"?"), score, prob);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -484,4 +392,4 @@ fn parse_slot_value(text: &str) -> SlotValue {
|
||||
return SlotValue::Number(n);
|
||||
}
|
||||
SlotValue::Text(text.to_string())
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,7 +0,0 @@
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct GlinerModelInfo {
|
||||
pub model_dir: String,
|
||||
pub file_name: String,
|
||||
pub display_name: String,
|
||||
pub value: String,
|
||||
}
|
||||
@@ -5,9 +5,6 @@ use crate::config;
|
||||
use once_cell::sync::OnceCell;
|
||||
|
||||
use crate::config::structs::SpeechToTextEngine;
|
||||
|
||||
use crate::vosk_models;
|
||||
// use vosk_models::{scan_vosk_models, get_model_path, VoskModelInfo};
|
||||
pub use self::vosk::init_vosk;
|
||||
pub use self::vosk::recognize_wake_word;
|
||||
pub use self::vosk::recognize_speech;
|
||||
@@ -16,21 +13,18 @@ pub use self::vosk::reset_wake_recognizer;
|
||||
|
||||
static STT_TYPE: OnceCell<SpeechToTextEngine> = OnceCell::new();
|
||||
|
||||
pub fn init() -> Result<(), ()> {
|
||||
pub fn init() -> Result<(), String> {
|
||||
if STT_TYPE.get().is_some() {
|
||||
return Ok(());
|
||||
} // already initialized
|
||||
}
|
||||
|
||||
// set default stt type
|
||||
// @TODO. Make it configurable?
|
||||
STT_TYPE.set(config::DEFAULT_SPEECH_TO_TEXT_ENGINE).unwrap();
|
||||
STT_TYPE.set(config::DEFAULT_SPEECH_TO_TEXT_ENGINE)
|
||||
.map_err(|_| "STT type already set".to_string())?;
|
||||
|
||||
// load given recorder
|
||||
match STT_TYPE.get().unwrap() {
|
||||
SpeechToTextEngine::Vosk => {
|
||||
// Init Vosk
|
||||
info!("Initializing Vosk STT backend.");
|
||||
vosk::init_vosk();
|
||||
vosk::init_vosk()?;
|
||||
info!("STT backend initialized.");
|
||||
}
|
||||
}
|
||||
@@ -45,9 +39,3 @@ pub fn recognize(data: &[i16], include_partial: bool) -> Option<String> {
|
||||
vosk::recognize_speech(data)
|
||||
}
|
||||
}
|
||||
|
||||
// pub fn recognize(data: &[i16], partial: bool) -> Option<String> {
|
||||
// match STT_TYPE.get().unwrap() {
|
||||
// SpeechToTextEngine::Vosk => vosk::recognize(data, partial),
|
||||
// }
|
||||
// }
|
||||
|
||||
@@ -1,47 +1,50 @@
|
||||
use once_cell::sync::OnceCell;
|
||||
use vosk::{DecodingState, Model, Recognizer};
|
||||
use vosk::{DecodingState, Recognizer};
|
||||
use std::sync::Arc;
|
||||
use parking_lot::Mutex;
|
||||
|
||||
use std::sync::Mutex;
|
||||
|
||||
// use crate::config::VOSK_MODEL_PATH;
|
||||
use crate::{stt::vosk_models, i18n, config};
|
||||
use crate::{vosk_models, i18n, config, models};
|
||||
use crate::models::vosk::VoskModel;
|
||||
use crate::DB;
|
||||
|
||||
static MODEL: OnceCell<Model> = OnceCell::new();
|
||||
// the model Arc keeps the vosk::Model alive for the recognizers
|
||||
static VOSK_MODEL: OnceCell<Arc<VoskModel>> = OnceCell::new();
|
||||
static WAKE_RECOGNIZER: OnceCell<Mutex<Recognizer>> = OnceCell::new();
|
||||
static SPEECH_RECOGNIZER: OnceCell<Mutex<Recognizer>> = OnceCell::new();
|
||||
|
||||
pub fn init_vosk() -> Result<(), String> {
|
||||
if MODEL.get().is_some() {
|
||||
if VOSK_MODEL.get().is_some() {
|
||||
return Ok(());
|
||||
} // already initialized
|
||||
}
|
||||
|
||||
let model_path = get_configured_model_path()?;
|
||||
info!("Loading Vosk model from: {}", model_path.display());
|
||||
let model_id = format!("vosk:{}", model_path.display());
|
||||
|
||||
let model = Model::new(model_path.to_str().unwrap())
|
||||
.ok_or_else(|| format!("Failed to load Vosk model from: {}", model_path.display()))?;
|
||||
// load through registry (shared if anything else needs the same model)
|
||||
let vosk = models::vosk::load(
|
||||
models::registry(),
|
||||
&model_id,
|
||||
model_path.to_str().unwrap(),
|
||||
)?;
|
||||
|
||||
// language-specific wake grammar
|
||||
let lang = i18n::get_language();
|
||||
let wake_grammar = config::get_wake_grammar(&lang);
|
||||
info!("Wake grammar for '{}': {:?}", lang, wake_grammar);
|
||||
|
||||
//let mut recognizer = Recognizer::new(&model, 16000.0)
|
||||
// .ok_or("Failed to create Vosk recognizer")?;
|
||||
let mut wake_recognizer = Recognizer::new_with_grammar(&model, 16000.0, wake_grammar)
|
||||
let mut wake_recognizer = Recognizer::new_with_grammar(&vosk.model, 16000.0, wake_grammar)
|
||||
.ok_or("Failed to create wake word recognizer")?;
|
||||
|
||||
wake_recognizer.set_max_alternatives(1); // required for confidence check later on
|
||||
wake_recognizer.set_max_alternatives(1);
|
||||
|
||||
let mut speech_recognizer = Recognizer::new(&model, 16000.0)
|
||||
let mut speech_recognizer = Recognizer::new(&vosk.model, 16000.0)
|
||||
.ok_or("Failed to create speech recognizer")?;
|
||||
|
||||
speech_recognizer.set_max_alternatives(config::VOSK_SPEECH_RECOGNIZER_MAX_ALTERNATIVES);
|
||||
speech_recognizer.set_words(config::VOSK_SPEECH_RECOGNIZER_WORDS);
|
||||
speech_recognizer.set_partial_words(config::VOSK_SPEECH_PARTIAL_WORDS);
|
||||
|
||||
MODEL.set(model).map_err(|_| "Model already set")?;
|
||||
VOSK_MODEL.set(vosk).map_err(|_| "Model already set")?;
|
||||
WAKE_RECOGNIZER.set(Mutex::new(wake_recognizer)).map_err(|_| "Wake recognizer already set")?;
|
||||
SPEECH_RECOGNIZER.set(Mutex::new(speech_recognizer)).map_err(|_| "Speech recognizer already set")?;
|
||||
|
||||
@@ -50,17 +53,15 @@ pub fn init_vosk() -> Result<(), String> {
|
||||
|
||||
|
||||
pub fn recognize_wake_word(data: &[i16]) -> Option<(String, f32)> {
|
||||
let mut recognizer = WAKE_RECOGNIZER.get()?.lock().unwrap();
|
||||
let mut recognizer = WAKE_RECOGNIZER.get()?.lock();
|
||||
|
||||
match recognizer.accept_waveform(data) {
|
||||
Ok(DecodingState::Running) => {
|
||||
// partials don't have confidence, skip them
|
||||
None
|
||||
}
|
||||
Ok(DecodingState::Finalized) => {
|
||||
let result = recognizer.result();
|
||||
|
||||
// compensate confidence issues
|
||||
if let Some(alternatives) = result.multiple() {
|
||||
if let Some(best) = alternatives.alternatives.first() {
|
||||
if !best.text.is_empty() {
|
||||
@@ -77,7 +78,7 @@ pub fn recognize_wake_word(data: &[i16]) -> Option<(String, f32)> {
|
||||
|
||||
|
||||
pub fn recognize_speech(data: &[i16]) -> Option<String> {
|
||||
let mut recognizer = SPEECH_RECOGNIZER.get()?.lock().unwrap();
|
||||
let mut recognizer = SPEECH_RECOGNIZER.get()?.lock();
|
||||
|
||||
match recognizer.accept_waveform(data) {
|
||||
Ok(DecodingState::Finalized) => {
|
||||
@@ -92,65 +93,16 @@ pub fn recognize_speech(data: &[i16]) -> Option<String> {
|
||||
|
||||
pub fn reset_speech_recognizer() {
|
||||
if let Some(recognizer) = SPEECH_RECOGNIZER.get() {
|
||||
recognizer.lock().unwrap().reset();
|
||||
recognizer.lock().reset();
|
||||
}
|
||||
}
|
||||
|
||||
pub fn reset_wake_recognizer() {
|
||||
if let Some(recognizer) = WAKE_RECOGNIZER.get() {
|
||||
recognizer.lock().unwrap().reset();
|
||||
recognizer.lock().reset();
|
||||
}
|
||||
}
|
||||
|
||||
// pub fn recognize(data: &[i16], include_partial: bool) -> Option<String> {
|
||||
// let state = RECOGNIZER
|
||||
// .get()
|
||||
// .unwrap()
|
||||
// .lock()
|
||||
// .unwrap()
|
||||
// .accept_waveform(data);
|
||||
|
||||
// match state {
|
||||
// Ok(ds) => {
|
||||
// match ds {
|
||||
// DecodingState::Running => {
|
||||
// if include_partial {
|
||||
// Some(
|
||||
// RECOGNIZER
|
||||
// .get()
|
||||
// .unwrap()
|
||||
// .lock()
|
||||
// .unwrap()
|
||||
// .partial_result()
|
||||
// .partial
|
||||
// .into(),
|
||||
// )
|
||||
// } else {
|
||||
// None
|
||||
// }
|
||||
// }
|
||||
// DecodingState::Finalized => {
|
||||
// // Result will always be multiple because we called set_max_alternatives
|
||||
// RECOGNIZER
|
||||
// .get()
|
||||
// .unwrap()
|
||||
// .lock()
|
||||
// .unwrap()
|
||||
// .result()
|
||||
// .multiple()
|
||||
// .and_then(|m| m.alternatives.first().map(|a| a.text.to_string()))
|
||||
// }
|
||||
// DecodingState::Failed => None,
|
||||
// }
|
||||
// },
|
||||
// Err(err) => {
|
||||
// error!("Vosk accept waveform error.\nError details: {}", err);
|
||||
|
||||
// None
|
||||
// }
|
||||
// }
|
||||
// }
|
||||
|
||||
fn get_configured_model_path() -> Result<std::path::PathBuf, String> {
|
||||
// try to get from settings
|
||||
if let Some(db) = DB.get() {
|
||||
@@ -167,11 +119,10 @@ fn get_configured_model_path() -> Result<std::path::PathBuf, String> {
|
||||
let available = vosk_models::scan_vosk_models();
|
||||
let language = i18n::get_language();
|
||||
|
||||
// try language match first
|
||||
let lang_code = match language.as_str() {
|
||||
"ru" => "ru",
|
||||
"en" => "us", // vosk uses "us" not "en"
|
||||
"ua" => "uk", // vosk uses "uk" not "ua"
|
||||
"en" => "us",
|
||||
"ua" => "uk",
|
||||
other => other,
|
||||
};
|
||||
|
||||
@@ -180,7 +131,6 @@ fn get_configured_model_path() -> Result<std::path::PathBuf, String> {
|
||||
return Ok(matched.path.clone());
|
||||
}
|
||||
|
||||
// fallback to first available
|
||||
if let Some(first) = available.first() {
|
||||
info!("Auto-detected Vosk model (no language match): {}", first.name);
|
||||
return Ok(first.path.clone());
|
||||
@@ -194,14 +144,3 @@ fn get_configured_model_path() -> Result<std::path::PathBuf, String> {
|
||||
|
||||
Err("No Vosk models found".into())
|
||||
}
|
||||
|
||||
// pub fn stereo_to_mono(input_data: &[i16]) -> Vec<i16> {
|
||||
// let mut result = Vec::with_capacity(input_data.len() / 2);
|
||||
// result.extend(
|
||||
// input_data
|
||||
// .chunks_exact(2)
|
||||
// .map(|chunk| chunk[0] / 2 + chunk[1] / 2),
|
||||
// );
|
||||
|
||||
// result
|
||||
// }
|
||||
|
||||
@@ -13,9 +13,7 @@ pub use structs::*;
|
||||
static VOICES: OnceCell<Vec<structs::VoiceConfig>> = OnceCell::new();
|
||||
static CURRENT_VOICE_ID: OnceCell<RwLock<String>> = OnceCell::new();
|
||||
|
||||
pub fn init(default_voice: &str) -> Result<(), String> {
|
||||
CURRENT_VOICE_ID.get_or_init(|| RwLock::new(default_voice.to_string()));
|
||||
|
||||
pub fn init(default_voice: &str, language: &str) -> Result<(), String> {
|
||||
let voices = scan_voices()?;
|
||||
|
||||
if voices.is_empty() {
|
||||
@@ -26,7 +24,30 @@ pub fn init(default_voice: &str) -> Result<(), String> {
|
||||
voices.len(),
|
||||
voices.iter().map(|v| &v.voice.id).collect::<Vec<_>>()
|
||||
);
|
||||
|
||||
|
||||
// resolve which voice to use
|
||||
let voice_id = if !default_voice.is_empty() && voices.iter().any(|v| v.voice.id == default_voice) {
|
||||
default_voice.to_string()
|
||||
} else {
|
||||
// auto-detect: pick the first voice that supports the active language
|
||||
let auto = voices.iter()
|
||||
.find(|v| v.voice.languages.contains(&language.to_string()))
|
||||
.or_else(|| voices.first());
|
||||
|
||||
match auto {
|
||||
Some(v) => {
|
||||
if default_voice.is_empty() {
|
||||
info!("No voice configured, auto-selected '{}' for language '{}'", v.voice.id, language);
|
||||
} else {
|
||||
warn!("Voice '{}' not found, auto-selected '{}'", default_voice, v.voice.id);
|
||||
}
|
||||
v.voice.id.clone()
|
||||
}
|
||||
None => return Err("No compatible voice found".into()),
|
||||
}
|
||||
};
|
||||
|
||||
CURRENT_VOICE_ID.get_or_init(|| RwLock::new(voice_id));
|
||||
VOICES.set(voices).map_err(|_| "Voices already initialized")?;
|
||||
|
||||
Ok(())
|
||||
|
||||
@@ -1,10 +1,7 @@
|
||||
// Prevents additional console window on Windows in release, DO NOT REMOVE!!
|
||||
#![cfg_attr(not(debug_assertions), windows_subsystem = "windows")]
|
||||
|
||||
use jarvis_core::{config, db, i18n, voices, APP_CONFIG_DIR, APP_LOG_DIR, DB};
|
||||
|
||||
use parking_lot::RwLock;
|
||||
use std::sync::Arc;
|
||||
use jarvis_core::{config, db, i18n, voices, DB, SettingsManager};
|
||||
|
||||
#[macro_use]
|
||||
extern crate simple_log;
|
||||
@@ -15,7 +12,7 @@ mod tauri_commands;
|
||||
|
||||
#[derive(Clone)]
|
||||
pub struct AppState {
|
||||
pub db: Arc<RwLock<db::structs::Settings>>,
|
||||
pub settings: SettingsManager,
|
||||
}
|
||||
|
||||
fn main() {
|
||||
@@ -24,14 +21,14 @@ fn main() {
|
||||
// basic logging setup (simpler for GUI)
|
||||
simple_log::quick!("info");
|
||||
|
||||
// init db
|
||||
let settings = db::init_settings();
|
||||
// init settings
|
||||
let manager = db::init();
|
||||
|
||||
// init i18n
|
||||
i18n::init(&settings.language);
|
||||
i18n::init(&manager.lock().language);
|
||||
|
||||
// init voices
|
||||
if let Err(e) = voices::init(&settings.voice) {
|
||||
if let Err(e) = voices::init(&manager.lock().voice, &manager.lock().language) {
|
||||
eprintln!("Failed to init voices: {}", e);
|
||||
}
|
||||
|
||||
@@ -40,13 +37,12 @@ fn main() {
|
||||
eprintln!("Failed to init audio: {:?}", e);
|
||||
}
|
||||
|
||||
// set db
|
||||
DB.set(Arc::new(RwLock::new(settings)))
|
||||
// set global DB (for core modules that read settings at init time)
|
||||
DB.set(manager.arc().clone())
|
||||
.expect("DB already initialized");
|
||||
let db_arc = DB.get().unwrap().clone();
|
||||
|
||||
tauri::Builder::default()
|
||||
.manage(AppState { db: db_arc })
|
||||
.manage(AppState { settings: manager })
|
||||
.plugin(tauri_plugin_shell::init())
|
||||
.plugin(tauri_plugin_dialog::init())
|
||||
.plugin(tauri_plugin_fs::init())
|
||||
@@ -106,4 +102,4 @@ fn main() {
|
||||
])
|
||||
.run(tauri::generate_context!())
|
||||
.expect("error while running tauri application");
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,115 +1,17 @@
|
||||
use jarvis_core::{db, DB};
|
||||
use crate::AppState;
|
||||
|
||||
#[tauri::command]
|
||||
pub fn db_read(state: tauri::State<'_, AppState>, key: &str) -> String {
|
||||
let settings = state.db.read();
|
||||
|
||||
match key {
|
||||
"selected_microphone" => settings.microphone.to_string(),
|
||||
"assistant_voice" => settings.voice.clone(),
|
||||
"selected_wake_word_engine" => format!("{:?}", settings.wake_word_engine),
|
||||
"selected_intent_recognition_engine" => format!("{:?}", settings.intent_recognition_engine),
|
||||
"selected_slot_extraction_engine" => format!("{:?}", settings.slot_extraction_engine),
|
||||
"selected_gliner_model" => settings.gliner_model.clone(),
|
||||
"selected_vosk_model" => settings.vosk_model.clone(),
|
||||
"speech_to_text_engine" => format!("{:?}", settings.speech_to_text_engine),
|
||||
"noise_suppression" => format!("{:?}", settings.noise_suppression),
|
||||
"vad" => format!("{:?}", settings.vad),
|
||||
"gain_normalizer" => settings.gain_normalizer.to_string(),
|
||||
"language" => settings.language.to_string(),
|
||||
"api_key__picovoice" => settings.api_keys.picovoice.clone(),
|
||||
"api_key__openai" => settings.api_keys.openai.clone(),
|
||||
_ => String::new(),
|
||||
}
|
||||
state.settings.read(key).unwrap_or_default()
|
||||
}
|
||||
|
||||
#[tauri::command]
|
||||
pub fn db_write(state: tauri::State<'_, AppState>, key: &str, val: &str) -> bool {
|
||||
let snapshot = {
|
||||
let mut settings = state.db.write();
|
||||
|
||||
match key {
|
||||
"selected_microphone" => {
|
||||
if let Ok(v) = val.parse::<i32>() {
|
||||
// info!("MICROPHONE changed: {}", v);
|
||||
settings.microphone = v;
|
||||
} else {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
"assistant_voice" => {
|
||||
settings.voice = val.to_string();
|
||||
}
|
||||
"selected_wake_word_engine" => {
|
||||
match val.to_lowercase().as_str() {
|
||||
"rustpotter" => settings.wake_word_engine = jarvis_core::config::structs::WakeWordEngine::Rustpotter,
|
||||
"vosk" => settings.wake_word_engine = jarvis_core::config::structs::WakeWordEngine::Vosk,
|
||||
"porcupine" => settings.wake_word_engine = jarvis_core::config::structs::WakeWordEngine::Porcupine,
|
||||
_ => return false,
|
||||
}
|
||||
}
|
||||
"selected_intent_recognition_engine" => {
|
||||
match val.to_lowercase().as_str() {
|
||||
"intentclassifier" => settings.intent_recognition_engine = jarvis_core::config::structs::IntentRecognitionEngine::IntentClassifier,
|
||||
"embeddingclassifier" => settings.intent_recognition_engine = jarvis_core::config::structs::IntentRecognitionEngine::EmbeddingClassifier,
|
||||
_ => return false,
|
||||
}
|
||||
}
|
||||
"selected_slot_extraction_engine" => {
|
||||
match val.to_lowercase().as_str() {
|
||||
"none" => settings.slot_extraction_engine = jarvis_core::config::structs::SlotExtractionEngine::None,
|
||||
"gliner" => settings.slot_extraction_engine = jarvis_core::config::structs::SlotExtractionEngine::GLiNER,
|
||||
_ => return false,
|
||||
}
|
||||
}
|
||||
"selected_gliner_model" => {
|
||||
settings.gliner_model = val.to_string();
|
||||
}
|
||||
"selected_vosk_model" => {
|
||||
settings.vosk_model = val.to_string();
|
||||
}
|
||||
"noise_suppression" => {
|
||||
match val.to_lowercase().as_str() {
|
||||
"none" => settings.noise_suppression = jarvis_core::config::structs::NoiseSuppressionBackend::None,
|
||||
"nnnoiseless" => settings.noise_suppression = jarvis_core::config::structs::NoiseSuppressionBackend::Nnnoiseless,
|
||||
_ => return false,
|
||||
}
|
||||
}
|
||||
"vad" => {
|
||||
match val.to_lowercase().as_str() {
|
||||
"none" => settings.vad = jarvis_core::config::structs::VadBackend::None,
|
||||
"energy" => settings.vad = jarvis_core::config::structs::VadBackend::Energy,
|
||||
"nnnoiseless" => settings.vad = jarvis_core::config::structs::VadBackend::Nnnoiseless,
|
||||
_ => return false,
|
||||
}
|
||||
}
|
||||
"gain_normalizer" => {
|
||||
match val.to_lowercase().as_str() {
|
||||
"true" => settings.gain_normalizer = true,
|
||||
"false" => settings.gain_normalizer = false,
|
||||
_ => return false,
|
||||
}
|
||||
}
|
||||
"language" => {
|
||||
settings.language = val.to_string();
|
||||
}
|
||||
"api_key__picovoice" => {
|
||||
settings.api_keys.picovoice = val.to_string();
|
||||
}
|
||||
"api_key__openai" => {
|
||||
settings.api_keys.openai = val.to_string();
|
||||
}
|
||||
_ => return false,
|
||||
match state.settings.write(key, val) {
|
||||
Ok(()) => true,
|
||||
Err(e) => {
|
||||
log::warn!("db_write('{}', '{}'): {}", key, val, e);
|
||||
false
|
||||
}
|
||||
|
||||
settings.clone()
|
||||
};
|
||||
|
||||
// save to disk
|
||||
if let Err(e) = db::save_settings(&snapshot) {
|
||||
info!("SETTINGS NOT SAVED");
|
||||
}
|
||||
|
||||
true
|
||||
}
|
||||
|
||||
@@ -25,20 +25,12 @@ pub fn get_current_language() -> String {
|
||||
pub fn set_language(state: tauri::State<'_, AppState>, lang: &str) -> HashMap<String, String> {
|
||||
// update i18n
|
||||
i18n::set_language(lang);
|
||||
|
||||
// also save to db
|
||||
{
|
||||
let mut settings = state.db.write();
|
||||
settings.language = lang.to_string();
|
||||
|
||||
if let Err(e) = state.settings.write("language", lang) {
|
||||
log::error!("Failed to save language setting: {}", e);
|
||||
}
|
||||
|
||||
// save to disk
|
||||
let snapshot = state.db.read().clone();
|
||||
if let Err(e) = jarvis_core::db::save_settings(&snapshot) {
|
||||
log::error!("Failed to save settings: {}", e);
|
||||
}
|
||||
|
||||
// return new translations
|
||||
|
||||
// return new translations
|
||||
i18n::get_all_translations()
|
||||
}
|
||||
|
||||
|
||||
@@ -1,40 +0,0 @@
|
||||
// vite.config.ts
|
||||
import { defineConfig } from "file:///D:/Rust/jarvis-app/frontend/node_modules/vite/dist/node/index.js";
|
||||
import { svelte } from "file:///D:/Rust/jarvis-app/frontend/node_modules/@sveltejs/vite-plugin-svelte/src/index.js";
|
||||
import sveltePreprocess from "file:///D:/Rust/jarvis-app/frontend/node_modules/svelte-preprocess/dist/index.js";
|
||||
import tsconfigPaths from "file:///D:/Rust/jarvis-app/frontend/node_modules/vite-tsconfig-paths/dist/index.mjs";
|
||||
import routify from "file:///D:/Rust/jarvis-app/frontend/node_modules/@roxi/routify/lib/extra/vite-plugin/vite-plugin.js";
|
||||
var vite_config_default = defineConfig({
|
||||
plugins: [
|
||||
svelte({
|
||||
preprocess: [
|
||||
sveltePreprocess({
|
||||
typescript: true
|
||||
})
|
||||
],
|
||||
onwarn: (warning, handler) => {
|
||||
const { code, frame } = warning;
|
||||
if (code === "css-unused-selector")
|
||||
return;
|
||||
handler(warning);
|
||||
}
|
||||
}),
|
||||
routify(),
|
||||
tsconfigPaths()
|
||||
],
|
||||
clearScreen: false,
|
||||
server: {
|
||||
port: 1420,
|
||||
strictPort: true
|
||||
},
|
||||
envPrefix: ["VITE_", "TAURI_"],
|
||||
build: {
|
||||
target: process.env.TAURI_PLATFORM == "windows" ? "chrome105" : "safari13",
|
||||
minify: !process.env.TAURI_DEBUG ? "esbuild" : false,
|
||||
sourcemap: !!process.env.TAURI_DEBUG
|
||||
}
|
||||
});
|
||||
export {
|
||||
vite_config_default as default
|
||||
};
|
||||
//# sourceMappingURL=data:application/json;base64,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
|
||||
@@ -1,40 +0,0 @@
|
||||
// vite.config.ts
|
||||
import { defineConfig } from "file:///D:/Rust/jarvis-app/frontend/node_modules/vite/dist/node/index.js";
|
||||
import { svelte } from "file:///D:/Rust/jarvis-app/frontend/node_modules/@sveltejs/vite-plugin-svelte/src/index.js";
|
||||
import sveltePreprocess from "file:///D:/Rust/jarvis-app/frontend/node_modules/svelte-preprocess/dist/index.js";
|
||||
import tsconfigPaths from "file:///D:/Rust/jarvis-app/frontend/node_modules/vite-tsconfig-paths/dist/index.mjs";
|
||||
import routify from "file:///D:/Rust/jarvis-app/frontend/node_modules/@roxi/routify/lib/extra/vite-plugin/vite-plugin.js";
|
||||
var vite_config_default = defineConfig({
|
||||
plugins: [
|
||||
svelte({
|
||||
preprocess: [
|
||||
sveltePreprocess({
|
||||
typescript: true
|
||||
})
|
||||
],
|
||||
onwarn: (warning, handler) => {
|
||||
const { code, frame } = warning;
|
||||
if (code === "css-unused-selector")
|
||||
return;
|
||||
handler(warning);
|
||||
}
|
||||
}),
|
||||
routify(),
|
||||
tsconfigPaths()
|
||||
],
|
||||
clearScreen: false,
|
||||
server: {
|
||||
port: 1420,
|
||||
strictPort: true
|
||||
},
|
||||
envPrefix: ["VITE_", "TAURI_"],
|
||||
build: {
|
||||
target: process.env.TAURI_PLATFORM == "windows" ? "chrome105" : "safari13",
|
||||
minify: !process.env.TAURI_DEBUG ? "esbuild" : false,
|
||||
sourcemap: !!process.env.TAURI_DEBUG
|
||||
}
|
||||
});
|
||||
export {
|
||||
vite_config_default as default
|
||||
};
|
||||
//# sourceMappingURL=data:application/json;base64,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
|
||||
@@ -1,40 +0,0 @@
|
||||
// vite.config.ts
|
||||
import { defineConfig } from "file:///D:/Rust/jarvis-app/frontend/node_modules/vite/dist/node/index.js";
|
||||
import { svelte } from "file:///D:/Rust/jarvis-app/frontend/node_modules/@sveltejs/vite-plugin-svelte/src/index.js";
|
||||
import sveltePreprocess from "file:///D:/Rust/jarvis-app/frontend/node_modules/svelte-preprocess/dist/index.js";
|
||||
import tsconfigPaths from "file:///D:/Rust/jarvis-app/frontend/node_modules/vite-tsconfig-paths/dist/index.mjs";
|
||||
import routify from "file:///D:/Rust/jarvis-app/frontend/node_modules/@roxi/routify/lib/extra/vite-plugin/vite-plugin.js";
|
||||
var vite_config_default = defineConfig({
|
||||
plugins: [
|
||||
svelte({
|
||||
preprocess: [
|
||||
sveltePreprocess({
|
||||
typescript: true
|
||||
})
|
||||
],
|
||||
onwarn: (warning, handler) => {
|
||||
const { code, frame } = warning;
|
||||
if (code === "css-unused-selector")
|
||||
return;
|
||||
handler(warning);
|
||||
}
|
||||
}),
|
||||
routify(),
|
||||
tsconfigPaths()
|
||||
],
|
||||
clearScreen: false,
|
||||
server: {
|
||||
port: 1420,
|
||||
strictPort: true
|
||||
},
|
||||
envPrefix: ["VITE_", "TAURI_"],
|
||||
build: {
|
||||
target: process.env.TAURI_PLATFORM == "windows" ? "chrome105" : "safari13",
|
||||
minify: !process.env.TAURI_DEBUG ? "esbuild" : false,
|
||||
sourcemap: !!process.env.TAURI_DEBUG
|
||||
}
|
||||
});
|
||||
export {
|
||||
vite_config_default as default
|
||||
};
|
||||
//# sourceMappingURL=data:application/json;base64,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
|
||||
@@ -1,40 +0,0 @@
|
||||
// vite.config.ts
|
||||
import { defineConfig } from "file:///D:/Rust/jarvis-app/frontend/node_modules/vite/dist/node/index.js";
|
||||
import { svelte } from "file:///D:/Rust/jarvis-app/frontend/node_modules/@sveltejs/vite-plugin-svelte/src/index.js";
|
||||
import sveltePreprocess from "file:///D:/Rust/jarvis-app/frontend/node_modules/svelte-preprocess/dist/index.js";
|
||||
import tsconfigPaths from "file:///D:/Rust/jarvis-app/frontend/node_modules/vite-tsconfig-paths/dist/index.mjs";
|
||||
import routify from "file:///D:/Rust/jarvis-app/frontend/node_modules/@roxi/routify/lib/extra/vite-plugin/vite-plugin.js";
|
||||
var vite_config_default = defineConfig({
|
||||
plugins: [
|
||||
svelte({
|
||||
preprocess: [
|
||||
sveltePreprocess({
|
||||
typescript: true
|
||||
})
|
||||
],
|
||||
onwarn: (warning, handler) => {
|
||||
const { code, frame } = warning;
|
||||
if (code === "css-unused-selector")
|
||||
return;
|
||||
handler(warning);
|
||||
}
|
||||
}),
|
||||
routify(),
|
||||
tsconfigPaths()
|
||||
],
|
||||
clearScreen: false,
|
||||
server: {
|
||||
port: 1420,
|
||||
strictPort: true
|
||||
},
|
||||
envPrefix: ["VITE_", "TAURI_"],
|
||||
build: {
|
||||
target: process.env.TAURI_PLATFORM == "windows" ? "chrome105" : "safari13",
|
||||
minify: !process.env.TAURI_DEBUG ? "esbuild" : false,
|
||||
sourcemap: !!process.env.TAURI_DEBUG
|
||||
}
|
||||
});
|
||||
export {
|
||||
vite_config_default as default
|
||||
};
|
||||
//# sourceMappingURL=data:application/json;base64,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
|
||||
@@ -1,40 +0,0 @@
|
||||
// vite.config.ts
|
||||
import { defineConfig } from "file:///D:/Rust/jarvis-app/frontend/node_modules/vite/dist/node/index.js";
|
||||
import { svelte } from "file:///D:/Rust/jarvis-app/frontend/node_modules/@sveltejs/vite-plugin-svelte/src/index.js";
|
||||
import sveltePreprocess from "file:///D:/Rust/jarvis-app/frontend/node_modules/svelte-preprocess/dist/index.js";
|
||||
import tsconfigPaths from "file:///D:/Rust/jarvis-app/frontend/node_modules/vite-tsconfig-paths/dist/index.mjs";
|
||||
import routify from "file:///D:/Rust/jarvis-app/frontend/node_modules/@roxi/routify/lib/extra/vite-plugin/vite-plugin.js";
|
||||
var vite_config_default = defineConfig({
|
||||
plugins: [
|
||||
svelte({
|
||||
preprocess: [
|
||||
sveltePreprocess({
|
||||
typescript: true
|
||||
})
|
||||
],
|
||||
onwarn: (warning, handler) => {
|
||||
const { code, frame } = warning;
|
||||
if (code === "css-unused-selector")
|
||||
return;
|
||||
handler(warning);
|
||||
}
|
||||
}),
|
||||
routify(),
|
||||
tsconfigPaths()
|
||||
],
|
||||
clearScreen: false,
|
||||
server: {
|
||||
port: 1420,
|
||||
strictPort: true
|
||||
},
|
||||
envPrefix: ["VITE_", "TAURI_"],
|
||||
build: {
|
||||
target: process.env.TAURI_PLATFORM == "windows" ? "chrome105" : "safari13",
|
||||
minify: !process.env.TAURI_DEBUG ? "esbuild" : false,
|
||||
sourcemap: !!process.env.TAURI_DEBUG
|
||||
}
|
||||
});
|
||||
export {
|
||||
vite_config_default as default
|
||||
};
|
||||
//# sourceMappingURL=data:application/json;base64,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
|
||||
Reference in New Issue
Block a user