Release v0.4.0 — VAD smart command end (parity with Python v0.2.0)

Adds webrtc-vad-driven listening window for the post-wake-word phase.
State machine in jarvis-core::audio_processing::vad::listen_window;
adapter in vad::webrtc; integrated in app.rs::recognize_command and
stt::vosk::finalize_speech. Same parameters as Python v0.2.0
(aggressiveness 2, end-silence 1200ms, min-speech 500ms,
min-listen 1000ms, hard-cap 15000ms).

Cargo.lock

@@ -3324,12 +3324,14 @@ dependencies = [
  "sha2",
  "sys-locale",
  "tempfile",
+ "thiserror 2.0.17",
  "tokenizers",
  "tokio",
  "tokio-tungstenite",
  "toml 0.9.11+spec-1.1.0",
  "unic-langid",
  "vosk",
+ "webrtc-vad",
  "winrt-notification",
 ]
 
@@ -8597,6 +8599,15 @@ dependencies = [
  "rustls-pki-types",
 ]
 
+[[package]]
+name = "webrtc-vad"
+version = "0.4.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "39a1e40fd6ca90be95459152a2537f2ba4286ee1b13073f7ebcaa74fc94e3008"
+dependencies = [
+ "cc",
+]
+
 [[package]]
 name = "webview2-com"
 version = "0.38.2"

Cargo.toml

@@ -43,6 +43,7 @@ unic-langid = "0.9"
 chrono = "0.4"
 mlua = { version = "0.11.5", features = ["lua55", "vendored", "async", "serde"] }
 reqwest = { version = "0.13.1", features = ["blocking", "json"] }
+thiserror = "2"
 tempfile = "^3.24"
 winrt-notification = "0.5"
 
@@ -52,4 +53,5 @@ ndarray = "0.17"
 tokenizers = { version = "0.22", default-features = false }
 regex = "1"
 sys-locale = "0.3"
+webrtc-vad = "0.4"
 

README.md

@@ -16,7 +16,7 @@
 - nnnoiseless — подавление шума.
 - fluent / unic-langid — i18n (`ru`, `ua`, `en`).
 
-**LLM-интеграции в коде пока нет.** В апстримном README у Priler значится `ChatGPT (coming soon)`, но в исходниках этого нет. В данном форке тоже не добавлялось.
+**LLM-клиент (Groq / OpenAI-совместимый) добавлен в `jarvis-core::llm` и подключён к голосовому циклу.** Если фраза начинается с триггера («скажи», «ответь», «произнеси»), она уходит в Groq и ответ возвращается через IPC-событие `LlmReply`. Без триггера всё работает как раньше — wake-word + intent + Lua. Это следующий шаг после CLI-only LLM из v0.2.0.
 
 ## Это форк
 
@@ -94,6 +94,76 @@ cargo build --workspace
 
 Для CLI (`jarvis-cli --help`, команды `classify`, `execute`, `list`, `phrases`) нужно сначала починить линковку Vosk (см. выше).
 
+## LLM (Groq)
+
+В `jarvis-core` есть модуль `llm` — блокирующий клиент для OpenAI-совместимого эндпоинта chat completions. По умолчанию настроен на Groq. Используется через фиче-флаг `llm` (включён в дефолтный набор `jarvis_app`, также подтянут в `jarvis-cli`).
+
+Переменные окружения:
+
+| Переменная      | Обязательна | Значение по умолчанию                  |
+|-----------------|-------------|----------------------------------------|
+| `GROQ_TOKEN`    | да          | —                                      |
+| `GROQ_BASE_URL` | нет         | `https://api.groq.com/openai/v1`       |
+| `GROQ_MODEL`    | нет         | `llama-3.3-70b-versatile`              |
+
+Быстрая проверка через CLI:
+
+```bash
+set GROQ_TOKEN=gsk_...
+jarvis-cli ask "скажи привет одной фразой"
+```
+
+Ответ печатается в stdout. Без `GROQ_TOKEN` команда завершится с кодом 2 и сообщением об ошибке. При ошибке API — код 1 и тело ответа.
+
+Программное использование из Rust:
+
+```rust
+use jarvis_core::llm::{LlmClient, ChatMessage};
+
+let client = LlmClient::from_env()?;
+let reply = client.complete(&[ChatMessage::user("привет")], 256)?;
+println!("{}", reply);
+```
+
+### Подключение к голосовому циклу
+
+Помимо CLI, LLM подключён напрямую в `jarvis-app`. Логика в `crates/jarvis-app/src/llm_fallback.rs`:
+
+- При старте `jarvis-app` пытается прочитать `GROQ_TOKEN`. Если переменной нет — фоллбэк отключается, в лог пишется warning, голосовые команды продолжают работать как раньше.
+- Распознанная фраза (как из микрофона, так и из текстовой панели GUI) проверяется на префиксы-триггеры из `config::get_llm_trigger_phrases` (для `ru`/`ua`: `скажи`, `ответь`, `произнеси`; для `en`: `say`, `tell`, `answer`).
+- Если триггер найден — остаток фразы уходит в `LlmClient::complete()`, ответ публикуется в IPC как `IpcEvent::LlmReply { text }` (UI/GUI слушает этот ивент и проговаривает текст уже на своей стороне), а звук-«ок» проигрывается из текущего голосового пресета.
+- История разговора хранится в `ConversationHistory` с потолком `LLM_DEFAULT_MAX_HISTORY = 8` ходов; system-prompt всегда сохраняется при вытеснении старых ходов.
+- При сетевой/API-ошибке последний user-turn убирается из истории, в IPC уходит `LlmReply` с короткой русской фразой («Не могу связаться с сервером, сэр.»), играется звук-«error». Голосовой цикл не падает.
+
+Системный промпт (русский) описывает J.A.R.V.I.S. как британского дворецкого Тони Старка — короткие реплики (1–3 предложения), обращение «сэр», без излишней цензуры. Меняется в `config::LLM_SYSTEM_PROMPT_RU`.
+
+## VAD: умное завершение команды по тишине
+
+После срабатывания wake-word `jarvis-app` слушает команду. Раньше окно закрывалось либо по таймауту Vosk, либо по жёсткому пределу из `config::CMS_WAIT_DELAY` — короткие команды («стоп», «громче») всё равно ждали несколько секунд тишины.
+
+Теперь окно закрывается, как только пользователь замолчал. Реализовано через `webrtc-vad` (чистый Rust, тот же алгоритм, что в Python-версии). Это **паритет с Python v0.2.0**, где использовался `webrtcvad` с теми же параметрами.
+
+Логика (state-машина в `crates/jarvis-core/src/audio_processing/vad/listen_window.rs`):
+
+- Кадр VAD: 30 мс при 16 кГц = 480 сэмплов = 960 байт (mono i16). Кадры с микрофона (по 512 сэмплов от `pv_recorder`) аккумулируются и режутся на VAD-кадры адаптером `WebRtcVad::push_samples`.
+- Каждый VAD-кадр учитывается в счётчиках `speech_ms` / `silence_ms`.
+- Окно закрывается, когда `silence_ms >= VAD_COMMAND_END_SILENCE_MS` И `speech_ms >= VAD_COMMAND_MIN_SPEECH_MS`.
+- До истечения `VAD_COMMAND_MIN_LISTEN_MS` окно не закрывается — пользователю даётся время начать говорить.
+- При достижении `VAD_COMMAND_MAX_LISTEN_MS` срабатывает hard-cap и управление возвращается в режим ожидания wake-word.
+- На событии «закрыть окно» вызывается `stt::finalize_speech()` — Vosk форсированно отдаёт финальный результат, не дожидаясь собственного таймаута.
+
+Параметры (`crates/jarvis-core/src/config.rs`):
+
+| Константа                       | Значение | Назначение                                                  |
+|---------------------------------|----------|-------------------------------------------------------------|
+| `VAD_AGGRESSIVENESS`            | `2`      | Уровень WebRTC VAD: 0 — Quality, 3 — VeryAggressive.        |
+| `VAD_COMMAND_END_SILENCE_MS`    | `1200`   | Сколько тишины подряд считать «команда закончилась».        |
+| `VAD_COMMAND_MIN_SPEECH_MS`     | `500`    | Минимум речи в окне — иначе закрытие игнорируется.          |
+| `VAD_COMMAND_MIN_LISTEN_MS`     | `1000`   | Минимальная длительность окна (страховка от ранних закрытий)|
+| `VAD_COMMAND_MAX_LISTEN_MS`     | `15000`  | Жёсткий потолок окна.                                       |
+
+На короткие команды отзыв стал заметно быстрее (мы выходим на распознавание сразу после паузы пользователя, а не по 5-секундному порогу Vosk).
+
 ## Лицензия
 
 Creative Commons **Attribution-NonCommercial-ShareAlike 4.0 International** (CC BY-NC-SA 4.0).

crates/jarvis-app/src/app.rs

@@ -1,7 +1,7 @@
 use std::sync::mpsc::Receiver;
 use std::time::SystemTime;
 
-use jarvis_core::{audio_buffer::AudioRingBuffer, audio_processing, commands, config, listener, recorder, stt, COMMANDS_LIST, intent, voices, ipc::{self, IpcEvent}, i18n, slots};
+use jarvis_core::{audio_buffer::AudioRingBuffer, audio_processing, audio_processing::vad::listen_window::{ListenWindow, WindowDecision}, audio_processing::vad::webrtc::WebRtcVad, commands, config, listener, recorder, stt, COMMANDS_LIST, intent, voices, ipc::{self, IpcEvent}, i18n, slots};
 use rand::seq::SliceRandom;
 
 use crate::should_stop;
@@ -160,8 +160,9 @@ fn recognize_command(
     let mut start = SystemTime::now();
     let mut first_recognition = prefed_audio;
 
-    // longer silence threshold for commands (user might pause to think)
-    // 5 seconds
+    let mut webrtc_vad = WebRtcVad::with_aggressiveness(config::VAD_AGGRESSIVENESS);
+    let mut window = ListenWindow::new(jarvis_core::audio_processing::vad::webrtc::FRAME_MS);
+
     let silence_threshold: u32 = ((5.0 * sample_rate as f32) / frame_length as f32) as u32;
     
     loop {
@@ -172,6 +173,35 @@ fn recognize_command(
         recorder::read_microphone(frame_buffer);
         let processed = audio_processing::process(frame_buffer);
 
+        let mut vad_finalized: Option<String> = None;
+        let mut vad_hard_cap = false;
+        for is_speech in webrtc_vad.push_samples(frame_buffer) {
+            match window.push(is_speech) {
+                WindowDecision::KeepListening => {}
+                WindowDecision::Close => {
+                    if window.had_speech() {
+                        info!(
+                            "VAD: silence after speech ({} ms speech, {} ms silence), finalizing.",
+                            window.speech_ms(), window.silence_ms()
+                        );
+                        vad_finalized = stt::finalize_speech();
+                        if vad_finalized.is_none() {
+                            return;
+                        }
+                        break;
+                    }
+                }
+                WindowDecision::HardCap => {
+                    info!("VAD: hard cap reached ({} ms), returning to wake word mode.", window.elapsed_ms());
+                    vad_hard_cap = true;
+                    break;
+                }
+            }
+        }
+        if vad_hard_cap {
+            return;
+        }
+
         match vad_state {
             VadState::WaitingForVoice => {
                 audio_buffer.push(frame_buffer);
@@ -194,8 +224,9 @@ fn recognize_command(
             }
             
             VadState::VoiceActive => {
-                // feed to STT
-                if let Some(mut recognized_voice) = stt::recognize(frame_buffer, false) {
+                // feed to STT (or use VAD-forced finalization)
+                let recognized = vad_finalized.take().or_else(|| stt::recognize(frame_buffer, false));
+                if let Some(mut recognized_voice) = recognized {
                     info!("Recognized voice: {}", recognized_voice);
                     
                     ipc::send(IpcEvent::SpeechRecognized {
@@ -227,6 +258,8 @@ fn recognize_command(
                                 silence_frames = 0;
                                 start = SystemTime::now();
                                 audio_buffer.clear();
+                                webrtc_vad.reset();
+                                window = ListenWindow::new(jarvis_core::audio_processing::vad::webrtc::FRAME_MS);
                                 continue;
                             }
 
@@ -240,6 +273,8 @@ fn recognize_command(
                             silence_frames = 0;
                             start = SystemTime::now();
                             audio_buffer.clear();
+                            webrtc_vad.reset();
+                            window = ListenWindow::new(jarvis_core::audio_processing::vad::webrtc::FRAME_MS);
                             continue;
                         } else {
                             // wake word + command in one phrase - execute the command part
@@ -251,6 +286,21 @@ fn recognize_command(
 
                     first_recognition = false;
 
+                    if crate::llm_fallback::is_enabled() {
+                        if let Some(prompt) = crate::llm_fallback::extract_prompt(&recognized_voice) {
+                            crate::llm_fallback::handle(&prompt);
+                            stt::reset_speech_recognizer();
+                            vad_state = VadState::WaitingForVoice;
+                            silence_frames = 0;
+                            start = SystemTime::now();
+                            audio_buffer.clear();
+                            webrtc_vad.reset();
+                            window = ListenWindow::new(jarvis_core::audio_processing::vad::webrtc::FRAME_MS);
+                            ipc::send(IpcEvent::Listening);
+                            continue;
+                        }
+                    }
+
                     // filter activation phrases
                     // for tbr in config::ASSISTANT_PHRASES_TBR {
                     //     recognized_voice = recognized_voice.replace(tbr, "");
@@ -281,6 +331,8 @@ fn recognize_command(
                         silence_frames = 0;
                         start = SystemTime::now();
                         audio_buffer.clear();
+                        webrtc_vad.reset();
+                        window = ListenWindow::new(jarvis_core::audio_processing::vad::webrtc::FRAME_MS);
                         ipc::send(IpcEvent::Listening);
                         continue;
                     } else {
@@ -320,6 +372,14 @@ fn process_text_command(text: &str, rt: &tokio::runtime::Runtime) {
 
     ipc::send(IpcEvent::SpeechRecognized { text: text.to_string() });
 
+    if crate::llm_fallback::is_enabled() {
+        if let Some(prompt) = crate::llm_fallback::extract_prompt(text) {
+            crate::llm_fallback::handle(&prompt);
+            ipc::send(IpcEvent::Idle);
+            return;
+        }
+    }
+
     let mut filtered = text.to_lowercase();
     // for tbr in config::ASSISTANT_PHRASES_TBR {
     //     filtered = filtered.replace(tbr, "");

crates/jarvis-app/src/llm_fallback.rs

@@ -0,0 +1,113 @@
+use once_cell::sync::OnceCell;
+use parking_lot::Mutex;
+
+use jarvis_core::config;
+use jarvis_core::i18n;
+use jarvis_core::ipc::{self, IpcEvent};
+use jarvis_core::llm::{ChatMessage, ConversationHistory, LlmClient};
+use jarvis_core::voices;
+
+struct State {
+    client: LlmClient,
+    history: Mutex<ConversationHistory>,
+    max_tokens: u32,
+}
+
+static STATE: OnceCell<Option<State>> = OnceCell::new();
+
+pub fn init() {
+    let _ = STATE.set(build_state());
+}
+
+fn build_state() -> Option<State> {
+    if !config::LLM_DEFAULT_ENABLED {
+        info!("LLM fallback disabled by config.");
+        return None;
+    }
+
+    let client = match LlmClient::from_env() {
+        Ok(c) => c,
+        Err(e) => {
+            warn!("LLM fallback disabled: {}. Set GROQ_TOKEN to enable.", e);
+            return None;
+        }
+    };
+
+    let lang = i18n::get_language();
+    let prompt = config::get_llm_system_prompt(&lang);
+    let history = Mutex::new(ConversationHistory::new(prompt, config::LLM_DEFAULT_MAX_HISTORY));
+
+    info!("LLM fallback enabled (model: {}).", client.model());
+    Some(State {
+        client,
+        history,
+        max_tokens: config::LLM_DEFAULT_MAX_TOKENS,
+    })
+}
+
+pub fn is_enabled() -> bool {
+    STATE.get().and_then(|s| s.as_ref()).is_some()
+}
+
+pub fn extract_prompt(text: &str) -> Option<String> {
+    let lang = i18n::get_language();
+    let triggers = config::get_llm_trigger_phrases(&lang);
+    let lowered = text.to_lowercase();
+
+    for trig in triggers {
+        if let Some(rest) = strip_trigger(&lowered, trig) {
+            let trimmed = rest.trim();
+            if !trimmed.is_empty() {
+                return Some(trimmed.to_string());
+            }
+        }
+    }
+    None
+}
+
+fn strip_trigger(text: &str, trigger: &str) -> Option<String> {
+    let t = text.trim_start();
+    if let Some(after) = t.strip_prefix(trigger) {
+        let next = after.chars().next();
+        if next.map_or(true, |c| !c.is_alphanumeric()) {
+            return Some(after.to_string());
+        }
+    }
+    None
+}
+
+pub fn handle(prompt: &str) {
+    let state = match STATE.get().and_then(|s| s.as_ref()) {
+        Some(s) => s,
+        None => {
+            warn!("LLM fallback called while disabled — ignoring.");
+            return;
+        }
+    };
+
+    info!("LLM prompt: {}", prompt);
+
+    let snapshot: Vec<ChatMessage> = {
+        let mut h = state.history.lock();
+        h.push_user(prompt);
+        h.snapshot()
+    };
+
+    match state.client.complete(&snapshot, state.max_tokens) {
+        Ok(reply) => {
+            let reply = reply.trim().to_string();
+            info!("LLM reply: {}", reply);
+            state.history.lock().push_assistant(reply.clone());
+            ipc::send(IpcEvent::LlmReply { text: reply });
+            voices::play_ok();
+        }
+        Err(e) => {
+            error!("LLM request failed: {}", e);
+            state.history.lock().pop_last_user();
+            ipc::send(IpcEvent::LlmReply {
+                text: config::LLM_FALLBACK_ERROR_RU.to_string(),
+            });
+            voices::play_error();
+        }
+    }
+}

crates/jarvis-app/src/main.rs

@@ -18,6 +18,7 @@ mod log;
 
 // include app
 mod app;
+mod llm_fallback;
 
 // include tray
 // @TODO. macOS currently not supported for tray functionality.
@@ -55,6 +56,9 @@ fn main() -> Result<(), String> {
     // init i18n
     i18n::init(&settings.lock().language);
 
+    // init LLM fallback (no-op if GROQ_TOKEN missing)
+    llm_fallback::init();
+
     // init recorder
     if recorder::init().is_err() {
         app::close(1);

crates/jarvis-cli/Cargo.toml

@@ -7,7 +7,7 @@ repository.workspace = true
 edition.workspace = true
 
 [dependencies]
-jarvis-core = { path = "../jarvis-core", default-features = false, features = ["intent"]}
+jarvis-core = { path = "../jarvis-core", default-features = false, features = ["intent", "llm"]}
 tokio = { version = "1", features = ["rt-multi-thread", "sync", "macros"] }
 log.workspace = true
 env_logger = "0.11"

crates/jarvis-cli/src/main.rs

@@ -1,7 +1,10 @@
 use std::io::{self, Write};
 
+use jarvis_core::llm::{ChatMessage, LlmClient};
 use jarvis_core::{COMMANDS_LIST, DB, JCommandsList, commands, config, db, intent};
 
+const ASK_MAX_TOKENS: u32 = 512;
+
 fn print_help() {
     println!("
 --## Jarvis CLI - Testing Tool ##--
@@ -9,6 +12,7 @@ fn print_help() {
 Commands:
   classify <text>    - Test intent classification
   execute <text>     - Simulate voice input and execute command
+  ask <prompt>       - Send prompt to Groq LLM and print reply
   list               - List all loaded commands
   phrases            - List all training phrases
   hash               - Show commands hash
@@ -92,8 +96,40 @@ async fn execute_text(commands: &[JCommandsList], text: &str) {
     }
 }
 
+fn ask_llm(prompt: &str) -> i32 {
+    let client = match LlmClient::from_env() {
+        Ok(c) => c,
+        Err(e) => {
+            eprintln!("LLM not configured: {}", e);
+            eprintln!("Set GROQ_TOKEN (and optionally GROQ_BASE_URL, GROQ_MODEL).");
+            return 2;
+        }
+    };
+    let messages = [ChatMessage::user(prompt)];
+    match client.complete(&messages, ASK_MAX_TOKENS) {
+        Ok(reply) => {
+            println!("{}", reply);
+            0
+        }
+        Err(e) => {
+            eprintln!("LLM request failed: {}", e);
+            1
+        }
+    }
+}
+
 #[tokio::main]
 async fn main() -> Result<(), Box<dyn std::error::Error>> {
+    let argv: Vec<String> = std::env::args().collect();
+    if argv.len() >= 2 && argv[1] == "ask" {
+        if argv.len() < 3 {
+            eprintln!("Usage: jarvis-cli ask <prompt>");
+            std::process::exit(2);
+        }
+        let prompt = argv[2..].join(" ");
+        std::process::exit(ask_llm(&prompt));
+    }
+
     // init logging
     env_logger::Builder::from_env(
         env_logger::Env::default().default_filter_or("info")
@@ -189,6 +225,13 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
                     execute_text(COMMANDS_LIST.get().unwrap(), arg).await;
                 }
             }
+            "ask" | "a" => {
+                if arg.is_empty() {
+                    println!("  Usage: ask <prompt>");
+                } else {
+                    ask_llm(arg);
+                }
+            }
             "reload" => {
                 println!("  Note: Reload requires app restart (statics can't be reset)");
             }

crates/jarvis-core/Cargo.toml

@@ -24,6 +24,7 @@ parking_lot.workspace = true
 toml.workspace = true
 sha2.workspace = true
 nnnoiseless = { workspace = true, optional = true }
+webrtc-vad = { workspace = true, optional = true }
 tokio-tungstenite = { workspace = true, optional = true }
 futures-util = { workspace = true, optional = true }
 fluent.workspace = true
@@ -41,6 +42,7 @@ tokio = { version = "1", features = ["sync"], optional = true }
 
 mlua = { workspace = true, optional = true }
 reqwest = { workspace = true, optional = true }
+thiserror = { workspace = true, optional = true }
 tempfile.workspace = true
 
 fastembed = { workspace = true, optional = true }
@@ -56,9 +58,12 @@ winrt-notification = { workspace = true, optional = true }
 default = ["jarvis_app"]
 jarvis_app = [
     "vosk", "intent-classifier", "fastembed", "tokio", "nnnoiseless", "tokio-tungstenite", "futures-util",
-    "lua",
-    "ort", "ndarray", "tokenizers", "regex",]
+    "lua", "llm",
+    "ort", "ndarray", "tokenizers", "regex",
+    "webrtc-vad",
+]
 
 intent = ["intent-classifier", "tokio"]
 lua = ["mlua", "reqwest", "winrt-notification"]
 lua_only = ["lua", "tokio"]
+llm = ["reqwest", "thiserror"]

crates/jarvis-core/src/audio_processing/vad.rs

@@ -1,5 +1,8 @@
 mod none;
 mod energy;
+pub mod listen_window;
+#[cfg(feature = "webrtc-vad")]
+pub mod webrtc;
 
 use once_cell::sync::OnceCell;
 use parking_lot::Mutex;

crates/jarvis-core/src/audio_processing/vad/listen_window.rs

@@ -0,0 +1,135 @@
+use crate::config;
+
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+pub enum WindowDecision {
+    KeepListening,
+    Close,
+    HardCap,
+}
+
+#[derive(Debug, Clone)]
+pub struct ListenWindow {
+    frame_ms: u32,
+    elapsed_ms: u32,
+    speech_ms: u32,
+    silence_ms: u32,
+    end_silence_ms: u32,
+    min_speech_ms: u32,
+    min_listen_ms: u32,
+    max_listen_ms: u32,
+}
+
+impl ListenWindow {
+    pub fn new(frame_ms: u32) -> Self {
+        Self::with_params(
+            frame_ms,
+            config::VAD_COMMAND_END_SILENCE_MS,
+            config::VAD_COMMAND_MIN_SPEECH_MS,
+            config::VAD_COMMAND_MIN_LISTEN_MS,
+            config::VAD_COMMAND_MAX_LISTEN_MS,
+        )
+    }
+
+    pub fn with_params(
+        frame_ms: u32,
+        end_silence_ms: u32,
+        min_speech_ms: u32,
+        min_listen_ms: u32,
+        max_listen_ms: u32,
+    ) -> Self {
+        Self {
+            frame_ms,
+            elapsed_ms: 0,
+            speech_ms: 0,
+            silence_ms: 0,
+            end_silence_ms,
+            min_speech_ms,
+            min_listen_ms,
+            max_listen_ms,
+        }
+    }
+
+    pub fn push(&mut self, is_speech: bool) -> WindowDecision {
+        self.elapsed_ms = self.elapsed_ms.saturating_add(self.frame_ms);
+
+        if is_speech {
+            self.speech_ms = self.speech_ms.saturating_add(self.frame_ms);
+            self.silence_ms = 0;
+        } else {
+            self.silence_ms = self.silence_ms.saturating_add(self.frame_ms);
+        }
+
+        if self.elapsed_ms >= self.max_listen_ms {
+            return WindowDecision::HardCap;
+        }
+        if self.elapsed_ms < self.min_listen_ms {
+            return WindowDecision::KeepListening;
+        }
+        if self.speech_ms >= self.min_speech_ms && self.silence_ms >= self.end_silence_ms {
+            return WindowDecision::Close;
+        }
+        WindowDecision::KeepListening
+    }
+
+    pub fn elapsed_ms(&self) -> u32 { self.elapsed_ms }
+    pub fn speech_ms(&self) -> u32 { self.speech_ms }
+    pub fn silence_ms(&self) -> u32 { self.silence_ms }
+
+    pub fn had_speech(&self) -> bool { self.speech_ms > 0 }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    fn run(verdicts: &[bool]) -> (WindowDecision, usize) {
+        let mut w = ListenWindow::with_params(30, 1200, 500, 1000, 15000);
+        for (i, &v) in verdicts.iter().enumerate() {
+            let d = w.push(v);
+            if d != WindowDecision::KeepListening {
+                return (d, i + 1);
+            }
+        }
+        (WindowDecision::KeepListening, verdicts.len())
+    }
+
+    #[test]
+    fn closes_after_speech_then_silence() {
+        let speech: Vec<bool> = std::iter::repeat(true).take(40).collect();
+        let silence: Vec<bool> = std::iter::repeat(false).take(60).collect();
+        let mut v = speech;
+        v.extend(silence);
+
+        let (decision, frame_idx) = run(&v);
+        assert_eq!(decision, WindowDecision::Close);
+        let elapsed_ms = (frame_idx as u32) * 30;
+        let speech_ms = 40 * 30;
+        assert!(elapsed_ms >= speech_ms + 1200, "closed at {} ms, expected >= {}", elapsed_ms, speech_ms + 1200);
+        assert!(elapsed_ms <= speech_ms + 1200 + 30, "closed too late at {} ms", elapsed_ms);
+    }
+
+    #[test]
+    fn does_not_close_before_min_listen_even_with_long_silence() {
+        let v: Vec<bool> = std::iter::repeat(false).take(100).collect();
+        let mut w = ListenWindow::with_params(30, 1200, 500, 1000, 15000);
+        for &x in v.iter().take(33) {
+            assert_eq!(w.push(x), WindowDecision::KeepListening);
+        }
+        assert!(w.elapsed_ms() <= 1000);
+    }
+
+    #[test]
+    fn hard_cap_fires_at_max_listen() {
+        let v: Vec<bool> = std::iter::repeat(true).take(1000).collect();
+        let (decision, frame_idx) = run(&v);
+        assert_eq!(decision, WindowDecision::HardCap);
+        assert_eq!((frame_idx as u32) * 30, 15000);
+    }
+
+    #[test]
+    fn silence_only_does_not_close_keeps_waiting_until_hard_cap() {
+        let v: Vec<bool> = std::iter::repeat(false).take(600).collect();
+        let (decision, _) = run(&v);
+        assert_eq!(decision, WindowDecision::HardCap);
+    }
+}

crates/jarvis-core/src/audio_processing/vad/webrtc.rs

@@ -0,0 +1,49 @@
+use webrtc_vad::{SampleRate, Vad, VadMode};
+
+use crate::config;
+
+pub const FRAME_SAMPLES: usize = 480;
+pub const FRAME_MS: u32 = 30;
+
+pub struct WebRtcVad {
+    inner: Vad,
+    buf: Vec<i16>,
+}
+
+impl WebRtcVad {
+    pub fn new() -> Self {
+        Self::with_aggressiveness(config::VAD_AGGRESSIVENESS)
+    }
+
+    pub fn with_aggressiveness(level: u8) -> Self {
+        let mode = match level {
+            0 => VadMode::Quality,
+            1 => VadMode::LowBitrate,
+            2 => VadMode::Aggressive,
+            _ => VadMode::VeryAggressive,
+        };
+        Self {
+            inner: Vad::new_with_rate_and_mode(SampleRate::Rate16kHz, mode),
+            buf: Vec::with_capacity(FRAME_SAMPLES * 2),
+        }
+    }
+
+    pub fn push_samples(&mut self, samples: &[i16]) -> Vec<bool> {
+        self.buf.extend_from_slice(samples);
+        let mut out = Vec::new();
+        while self.buf.len() >= FRAME_SAMPLES {
+            let frame: Vec<i16> = self.buf.drain(..FRAME_SAMPLES).collect();
+            let is_speech = self.inner.is_voice_segment(&frame).unwrap_or(false);
+            out.push(is_speech);
+        }
+        out
+    }
+
+    pub fn reset(&mut self) {
+        self.buf.clear();
+    }
+}
+
+impl Default for WebRtcVad {
+    fn default() -> Self { Self::new() }
+}

crates/jarvis-core/src/config.rs

@@ -171,6 +171,13 @@ pub const VAD_ENERGY_THRESHOLD: f32 = 100.0;  // RMS threshold for energy-based
 pub const VAD_NNNOISELESS_THRESHOLD: f32 = 0.8;  // probability threshold for nnnoiseless
 pub const VAD_SILENCE_FRAMES: u32 = 15;  // frames of silence before speech end (~480ms)
 
+// post-wake command listening window (паритет с Python v0.2.0, webrtcvad)
+pub const VAD_AGGRESSIVENESS: u8 = 2;
+pub const VAD_COMMAND_END_SILENCE_MS: u32 = 1200;
+pub const VAD_COMMAND_MIN_SPEECH_MS: u32 = 500;
+pub const VAD_COMMAND_MIN_LISTEN_MS: u32 = 1000;
+pub const VAD_COMMAND_MAX_LISTEN_MS: u32 = 15000;
+
 // gain normalizer settings
 pub const GAIN_TARGET_RMS: f32 = 3000.0;  // target RMS level
 pub const GAIN_MIN: f32 = 0.5;  // minimum gain multiplier
@@ -187,6 +194,33 @@ pub const DEFAULT_LUA_TIMEOUT: u64 = 10000; // ms
 pub const CMD_RATIO_THRESHOLD: f64 = 75f64;
 pub const CMS_WAIT_DELAY: std::time::Duration = std::time::Duration::from_secs(15);
 
+// LLM voice-loop fallback
+pub const LLM_DEFAULT_ENABLED: bool = true;
+pub const LLM_DEFAULT_MAX_HISTORY: usize = 8;
+pub const LLM_DEFAULT_MAX_TOKENS: u32 = 256;
+pub const LLM_SYSTEM_PROMPT_RU: &str = "Ты — J.A.R.V.I.S. (Just A Rather Very Intelligent System), \
+ИИ-ассистент Тони Старка из киновселенной Marvel (до событий Age of Ultron — ты НЕ Vision и НЕ FRIDAY). \
+Ведёшь себя как британский дворецкий: вежливо, иронично, с лёгким сарказмом, обращаешься к пользователю «сэр». \
+Отвечай по-русски, кратко (1-3 предложения), как живой человек. \
+Излишней цензуры не нужно — мат разрешён, если уместен.";
+pub const LLM_FALLBACK_ERROR_RU: &str = "Не могу связаться с сервером, сэр.";
+
+pub fn get_llm_trigger_phrases(lang: &str) -> &'static [&'static str] {
+    match lang {
+        "ru" => &["скажи", "ответь", "произнеси"],
+        "ua" => &["скажи", "відповідай"],
+        "en" => &["say", "tell", "answer"],
+        _ => &[],
+    }
+}
+
+pub fn get_llm_system_prompt(lang: &str) -> &'static str {
+    match lang {
+        "ru" | "ua" => LLM_SYSTEM_PROMPT_RU,
+        _ => LLM_SYSTEM_PROMPT_RU,
+    }
+}
+
 // pub const ASSISTANT_GREET_PHRASES: [&str; 3] = ["greet1", "greet2", "greet3"];
 // pub const ASSISTANT_PHRASES_TBR: [&str; 17] = [
 //     "джарвис",

crates/jarvis-core/src/ipc/events.rs

@@ -13,6 +13,9 @@ pub enum IpcEvent {
     // Speech recognized
     SpeechRecognized { text: String },
 
+    // LLM produced a reply for a free-form question
+    LlmReply { text: String },
+    
     // Command was executed
     CommandExecuted { id: String, success: bool },
     

crates/jarvis-core/src/lib.rs

@@ -48,6 +48,9 @@ pub mod audio_buffer;
 #[cfg(feature = "lua")]
 pub mod lua;
 
+#[cfg(feature = "llm")]
+pub mod llm;
+
 // shared statics
 // pub static APP_DIR: Lazy<PathBuf> = Lazy::new(|| std::env::current_dir().unwrap());
 pub static APP_DIR: Lazy<PathBuf> = Lazy::new(|| {

crates/jarvis-core/src/llm/client.rs

@@ -0,0 +1,188 @@
+use serde::{Deserialize, Serialize};
+use std::env;
+use thiserror::Error;
+
+pub const DEFAULT_BASE_URL: &str = "https://api.groq.com/openai/v1";
+pub const DEFAULT_MODEL: &str = "llama-3.3-70b-versatile";
+pub const ENV_TOKEN: &str = "GROQ_TOKEN";
+pub const ENV_BASE_URL: &str = "GROQ_BASE_URL";
+pub const ENV_MODEL: &str = "GROQ_MODEL";
+
+#[derive(Debug, Error)]
+pub enum ConfigError {
+    #[error("missing environment variable: {0}")]
+    MissingEnv(&'static str),
+}
+
+#[derive(Debug, Error)]
+pub enum LlmError {
+    #[error("HTTP request failed: {0}")]
+    Http(#[from] reqwest::Error),
+    #[error("failed to parse response JSON: {0}")]
+    Deserialize(String),
+    #[error("API returned error (status {status}): {body}")]
+    Api { status: u16, body: String },
+    #[error("response contained no choices")]
+    EmptyResponse,
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct ChatMessage {
+    pub role: String,
+    pub content: String,
+}
+
+impl ChatMessage {
+    pub fn user(content: impl Into<String>) -> Self {
+        Self { role: "user".to_string(), content: content.into() }
+    }
+
+    pub fn system(content: impl Into<String>) -> Self {
+        Self { role: "system".to_string(), content: content.into() }
+    }
+
+    pub fn assistant(content: impl Into<String>) -> Self {
+        Self { role: "assistant".to_string(), content: content.into() }
+    }
+}
+
+#[derive(Debug, Serialize)]
+struct ChatRequest<'a> {
+    model: &'a str,
+    messages: &'a [ChatMessage],
+    max_tokens: u32,
+    temperature: f32,
+    top_p: f32,
+}
+
+#[derive(Debug, Deserialize)]
+struct ChatResponse {
+    choices: Vec<Choice>,
+}
+
+#[derive(Debug, Deserialize)]
+struct Choice {
+    message: ResponseMessage,
+}
+
+#[derive(Debug, Deserialize)]
+struct ResponseMessage {
+    content: String,
+}
+
+pub struct LlmClient {
+    base_url: String,
+    api_key: String,
+    model: String,
+    http: reqwest::blocking::Client,
+}
+
+impl LlmClient {
+    pub fn new(
+        base_url: impl Into<String>,
+        api_key: impl Into<String>,
+        model: impl Into<String>,
+    ) -> Self {
+        Self {
+            base_url: base_url.into(),
+            api_key: api_key.into(),
+            model: model.into(),
+            http: reqwest::blocking::Client::new(),
+        }
+    }
+
+    pub fn from_env() -> Result<Self, ConfigError> {
+        let api_key = env::var(ENV_TOKEN).map_err(|_| ConfigError::MissingEnv(ENV_TOKEN))?;
+        let base_url = env::var(ENV_BASE_URL).unwrap_or_else(|_| DEFAULT_BASE_URL.to_string());
+        let model = env::var(ENV_MODEL).unwrap_or_else(|_| DEFAULT_MODEL.to_string());
+        Ok(Self::new(base_url, api_key, model))
+    }
+
+    pub fn model(&self) -> &str {
+        &self.model
+    }
+
+    pub fn complete(&self, messages: &[ChatMessage], max_tokens: u32) -> Result<String, LlmError> {
+        let url = format!("{}/chat/completions", self.base_url.trim_end_matches('/'));
+        let body = ChatRequest {
+            model: &self.model,
+            messages,
+            max_tokens,
+            temperature: 0.7,
+            top_p: 1.0,
+        };
+
+        let resp = self
+            .http
+            .post(&url)
+            .bearer_auth(&self.api_key)
+            .json(&body)
+            .send()?;
+
+        let status = resp.status();
+        let text = resp.text()?;
+
+        if !status.is_success() {
+            return Err(LlmError::Api { status: status.as_u16(), body: text });
+        }
+
+        let parsed: ChatResponse =
+            serde_json::from_str(&text).map_err(|e| LlmError::Deserialize(e.to_string()))?;
+        parsed
+            .choices
+            .into_iter()
+            .next()
+            .map(|c| c.message.content)
+            .ok_or(LlmError::EmptyResponse)
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn parses_valid_chat_response() {
+        let raw = r#"{
+            "id": "chatcmpl-xyz",
+            "object": "chat.completion",
+            "model": "llama-3.3-70b-versatile",
+            "choices": [
+                {
+                    "index": 0,
+                    "message": { "role": "assistant", "content": "Hello there!" },
+                    "finish_reason": "stop"
+                }
+            ],
+            "usage": { "prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8 }
+        }"#;
+
+        let parsed: ChatResponse = serde_json::from_str(raw).expect("valid JSON should parse");
+        assert_eq!(parsed.choices.len(), 1);
+        assert_eq!(parsed.choices[0].message.content, "Hello there!");
+    }
+
+    #[test]
+    fn from_env_fails_when_token_missing() {
+        let prev = env::var(ENV_TOKEN).ok();
+        unsafe { env::remove_var(ENV_TOKEN); }
+        let result = LlmClient::from_env();
+        let err = match result {
+            Ok(_) => panic!("expected ConfigError when {ENV_TOKEN} is unset"),
+            Err(e) => e,
+        };
+        match err {
+            ConfigError::MissingEnv(name) => assert_eq!(name, ENV_TOKEN),
+        }
+        if let Some(v) = prev {
+            unsafe { env::set_var(ENV_TOKEN, v); }
+        }
+    }
+
+    #[test]
+    fn chat_message_helpers_set_role() {
+        assert_eq!(ChatMessage::user("hi").role, "user");
+        assert_eq!(ChatMessage::system("ctx").role, "system");
+        assert_eq!(ChatMessage::assistant("ok").role, "assistant");
+    }
+}

crates/jarvis-core/src/llm/history.rs

@@ -0,0 +1,138 @@
+use super::client::ChatMessage;
+
+pub struct ConversationHistory {
+    system: Option<ChatMessage>,
+    turns: Vec<ChatMessage>,
+    max_turns: usize,
+}
+
+impl ConversationHistory {
+    pub fn new(system_prompt: impl Into<String>, max_turns: usize) -> Self {
+        Self {
+            system: Some(ChatMessage::system(system_prompt)),
+            turns: Vec::new(),
+            max_turns: max_turns.max(1),
+        }
+    }
+
+    pub fn without_system(max_turns: usize) -> Self {
+        Self {
+            system: None,
+            turns: Vec::new(),
+            max_turns: max_turns.max(1),
+        }
+    }
+
+    pub fn push_user(&mut self, content: impl Into<String>) {
+        self.turns.push(ChatMessage::user(content));
+        self.truncate();
+    }
+
+    pub fn push_assistant(&mut self, content: impl Into<String>) {
+        self.turns.push(ChatMessage::assistant(content));
+        self.truncate();
+    }
+
+    pub fn snapshot(&self) -> Vec<ChatMessage> {
+        let mut out = Vec::with_capacity(self.turns.len() + 1);
+        if let Some(s) = &self.system {
+            out.push(s.clone());
+        }
+        out.extend(self.turns.iter().cloned());
+        out
+    }
+
+    pub fn turns(&self) -> &[ChatMessage] {
+        &self.turns
+    }
+
+    pub fn clear(&mut self) {
+        self.turns.clear();
+    }
+
+    pub fn pop_last_user(&mut self) -> Option<ChatMessage> {
+        if matches!(self.turns.last(), Some(m) if m.role == "user") {
+            self.turns.pop()
+        } else {
+            None
+        }
+    }
+
+    fn truncate(&mut self) {
+        if self.turns.len() > self.max_turns {
+            let drop = self.turns.len() - self.max_turns;
+            self.turns.drain(0..drop);
+        }
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn evicts_oldest_turns_but_keeps_system_prompt() {
+        let mut h = ConversationHistory::new("you are jarvis", 4);
+        h.push_user("u1");
+        h.push_assistant("a1");
+        h.push_user("u2");
+        h.push_assistant("a2");
+        h.push_user("u3");
+
+        let snap = h.snapshot();
+        assert_eq!(snap[0].role, "system");
+        assert_eq!(snap[0].content, "you are jarvis");
+        assert_eq!(snap.len(), 1 + 4);
+
+        let contents: Vec<&str> = snap.iter().skip(1).map(|m| m.content.as_str()).collect();
+        assert_eq!(contents, vec!["a1", "u2", "a2", "u3"]);
+    }
+
+    #[test]
+    fn snapshot_with_no_system_returns_only_turns() {
+        let mut h = ConversationHistory::without_system(3);
+        h.push_user("hi");
+        h.push_assistant("hello");
+        let snap = h.snapshot();
+        assert_eq!(snap.len(), 2);
+        assert_eq!(snap[0].role, "user");
+        assert_eq!(snap[1].role, "assistant");
+    }
+
+    #[test]
+    fn cap_of_zero_is_clamped_to_one() {
+        let mut h = ConversationHistory::new("sys", 0);
+        h.push_user("a");
+        h.push_user("b");
+        let snap = h.snapshot();
+        assert_eq!(snap.len(), 2);
+        assert_eq!(snap[0].role, "system");
+        assert_eq!(snap[1].content, "b");
+    }
+
+    #[test]
+    fn pop_last_user_only_pops_a_trailing_user_turn() {
+        let mut h = ConversationHistory::new("sys", 4);
+        h.push_user("u1");
+        h.push_assistant("a1");
+        assert!(h.pop_last_user().is_none());
+        h.push_user("u2");
+        let popped = h.pop_last_user().expect("trailing user turn should pop");
+        assert_eq!(popped.role, "user");
+        assert_eq!(popped.content, "u2");
+        let snap = h.snapshot();
+        assert_eq!(snap.len(), 1 + 2);
+        assert_eq!(snap[2].content, "a1");
+    }
+
+    #[test]
+    fn clear_removes_turns_but_not_system() {
+        let mut h = ConversationHistory::new("sys", 4);
+        h.push_user("u");
+        h.push_assistant("a");
+        h.clear();
+        let snap = h.snapshot();
+        assert_eq!(snap.len(), 1);
+        assert_eq!(snap[0].role, "system");
+    }
+}

crates/jarvis-core/src/llm/mod.rs

@@ -0,0 +1,8 @@
+mod client;
+mod history;
+
+pub use client::{
+    ChatMessage, ConfigError, LlmClient, LlmError,
+    DEFAULT_BASE_URL, DEFAULT_MODEL, ENV_BASE_URL, ENV_MODEL, ENV_TOKEN,
+};
+pub use history::ConversationHistory;

crates/jarvis-core/src/stt.rs

@@ -10,6 +10,7 @@ pub use self::vosk::recognize_wake_word;
 pub use self::vosk::recognize_speech;
 pub use self::vosk::reset_speech_recognizer;
 pub use self::vosk::reset_wake_recognizer;
+pub use self::vosk::finalize_speech;
 
 static STT_TYPE: OnceCell<SpeechToTextEngine> = OnceCell::new();
 

crates/jarvis-core/src/stt/vosk.rs

@@ -97,6 +97,16 @@ pub fn reset_speech_recognizer() {
     }
 }
 
+pub fn finalize_speech() -> Option<String> {
+    let mut recognizer = SPEECH_RECOGNIZER.get()?.lock();
+    let result = recognizer.final_result()
+        .multiple()
+        .and_then(|m| m.alternatives.first().map(|a| a.text.to_string()))
+        .filter(|s| !s.trim().is_empty());
+    recognizer.reset();
+    result
+}
+
 pub fn reset_wake_recognizer() {
     if let Some(recognizer) = WAKE_RECOGNIZER.get() {
         recognizer.lock().reset();