Release v0.4.1 — browser choice for url-action

chore: bump VA_VER to 0.4.1
Merge feature/browser-choice-in-url into dev
2026-04-27 20:06:58 +03:00 · 2026-04-27 20:06:52 +03:00 · 2026-04-27 20:06:51 +03:00 · 2026-04-27 20:06:26 +03:00 · 2026-04-23 11:09:54 +03:00 · 2026-04-23 11:09:48 +03:00
226 changed files with 65995 additions and 12954 deletions
--- a/.gitattributes
+++ b/.gitattributes
@ -0,0 +1 @@
 *.onnx filter=lfs diff=lfs merge=lfs -text
--- a/.gitignore
+++ b/.gitignore
@ -1,28 +1,196 @@
-# Logs
+# Created by .ignore support plugin (hsz.mobi)
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+### Python template
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 .Python
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 *,cover
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 # Django stuff:
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-npm-debug.log*
+local_settings.py
 yarn-debug.log*
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+# Flask stuff:
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+instance/
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+.webassets-cache
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+.scrapy
 !.vscode/extensions.json
 .idea
 .DS_Store
 *.suo
 *.ntvs*
 *.njsproj
 *.sln
 *.sw?
-# Etc
+# Sphinx documentation
-.routify
+docs/_build/
-build
+
 # PyBuilder
 target/
 # IPython Notebook
 .ipynb_checkpoints
 # pyenv
 .python-version
 # celery beat schedule file
 celerybeat-schedule
 # dotenv
 .env
 # virtualenv
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--- a/.idea/.gitignore
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--- a/.vscode/extensions.json
+++ b/.vscode/extensions.json
@ -1,7 +0,0 @@
 {
  "recommendations": [
    "svelte.svelte-vscode",
    "tauri-apps.tauri-vscode",
    "rust-lang.rust-analyzer"
  ]
 }
--- a/LICENSE.txt
+++ b/LICENSE.txt
@ -0,0 +1,674 @@
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--- a/README.md
+++ b/README.md
@ -0,0 +1,163 @@
 # J.A.R.V.I.S (Python) — Bossiara13's fork
 Голосовой ассистент для Windows с wake-word **«jarvis»**. Распознаёт речь локально через Vosk (русская модель), отвечает голосом через Silero TTS, а свободные вопросы (фразы, начинающиеся со слова «скажи …») отправляет в LLM на Groq и зачитывает ответ.
 ## Это форк
 Форк репозитория [Priler/jarvis](https://github.com/Priler/jarvis) (автор оригинала — Abraham Tugalov, 2022). Лицензия наследуется: **CC BY-NC-SA 4.0** (см. [LICENSE.txt](LICENSE.txt)).
 ## Что отличается от оригинала
 - Из истории удалены случайно закоммиченные секреты.
 - Бэкенд LLM переключён с OpenAI на Groq (бесплатный тариф) через openai-совместимый API.
 - Код обновлён под новую версию SDK `openai` (>=1.0); старый pre-1.0 интерфейс был сломан.
 - Убрана зависимость от Picovoice Porcupine — wake-word распознаётся напрямую через Vosk с grammar-constraint (второй `KaldiRecognizer` со словарём из `WAKE_WORDS`). Ключ Picovoice больше не нужен.
 - Обновлена ветка/тэги (`dev`, `v0.0.1-import`), причёсан README и `requirements.txt`.
 ## Установка
 Требуется **Python 3.11** (на 3.13 ряд зависимостей пока ставится с бубном).
 ```bash
 git clone https://github.com/DmitryBykov-ISPO/J.A.R.V.I.S-py.git
 cd J.A.R.V.I.S-py
 py -3.11 -m venv .venv
 .venv\Scripts\activate
 pip install --upgrade pip
 pip install -r requirements.txt
 ```
 Скопируйте `dev.env.example` в `dev.env` и заполните ключ:
 - `GROQ_TOKEN` — бесплатно на [console.groq.com](https://console.groq.com/).
 Vosk-модель для русского языка лежит в `model_small/` (уже в репозитории). Запуск:
 ```bash
 python main.py
 ```
 ## Конфигурация
 - `config.py`:
  - `MICROPHONE_INDEX = -1` — индекс микрофона (`-1` означает устройство по умолчанию). Если микрофонов несколько и берётся не тот, поменяйте число.
  - `WAKE_WORDS = ('jarvis', 'джарвис')` — варианты транскрипции wake-word, которые принимает Vosk. Если ваш голос/акцент стабильно расшифровывается как, например, `жарвис` — добавьте этот вариант сюда (всё в нижнем регистре).
  - `GROQ_MODEL` — имя модели Groq (по умолчанию `llama-3.3-70b-versatile`).
  - `INTENT_SIMILARITY_THRESHOLD = 0.45` — минимальная косинусная близость для срабатывания команды (см. ниже).
  - `DENOISE_ENABLED = False` — шумоподавление перед Vosk (см. ниже).
 - `commands.yaml` — набор голосовых команд и их вариантов; матчится семантически по эмбеддингам.
 - `custom-commands/` — скомпилированные AHK-скрипты под конкретный сетап автора оригинала (переключение мониторов, управление Яндекс.Музыкой и т.п.). На вашей машине большая часть из них работать не будет, но ассистент запустится в любом случае.
 ## Использование
 1. Скажите **«Джарвис»** (или **«jarvis»**) — ассистент даст звуковой сигнал готовности.
 2. Произнесите команду — окно записи закрывается само, как только вы замолчите (см. ниже про VAD):
   - либо одну из фраз из `commands.yaml` (открыть браузер, выключить звук и т.д.);
   - либо начните со слова **«скажи …»** — остаток фразы уйдёт в Groq, ответ будет зачитан вслух.
 ## VAD (определение конца команды)
 Окно записи команды закрывается по голосовой активности (webrtcvad), а не по таймеру. Параметры в `config.py`:
 - `VAD_AGGRESSIVENESS` (0..3) — насколько агрессивно VAD режет шум; по умолчанию 2.
 - `COMMAND_END_SILENCE_MS` — длительность тишины, после которой окно закрывается (по умолчанию 1200 мс).
 - `COMMAND_MIN_SPEECH_MS` — минимальная длительность речи, иначе тишина не считается концом (500 мс).
 - `COMMAND_MIN_LISTEN_MS` — минимальное время записи, чтобы не закрыться мгновенно (1000 мс).
 - `COMMAND_MAX_LISTEN_MS` — жёсткий потолок (15000 мс).
 ## Семантический матчинг команд
 Раньше распознанная фраза сравнивалась с фразами из `commands.yaml` через `fuzzywuzzy.fuzz.ratio` — это срабатывало только на формальное совпадение букв. Теперь используется sentence-transformer `all-MiniLM-L6-v2` (ONNX, CPU) — фраза кодируется в 384-мерный вектор, считается косинусная близость с фразами всех команд, побеждает самая близкая.
 Это означает, что фраза `«запусти браузер»` сматчится с командой `open_browser`, даже если в YAML записано только `«открой браузер»` — у них близкий смысл.
 - Модель лежит в `models/all-MiniLM-L6-v2/` (87 МБ, хранится через Git LFS — `git lfs pull` после клонирования).
 - Порог `INTENT_SIMILARITY_THRESHOLD = 0.45` (косинус, диапазон [-1; 1], для близких смыслов обычно 0.7+). Ниже порога — «команда не распознана», сработает `not_found.wav` (или ветка `«скажи …»` для LLM).
 - Все фразы из `commands.yaml` эмбеддятся один раз при старте; на каждой команде эмбеддится только распознанная пользователем фраза (~1-5 мс на CPU).
 ## Шумоподавление перед STT
 Опциональный пре-процессинг аудио командного буфера через `noisereduce` (спектральное гейтирование). Помогает в шумных помещениях (кулер, кондиционер, фоновая музыка). К wake-word фазе не применяется — там важна отзывчивость.
 В `config.py`:
 - `DENOISE_ENABLED = False` — главный тумблер.
 - `DENOISE_PROP = 0.85` — доля подавления (0..1).
 - `DENOISE_STATIONARY = False` — `False` для меняющегося шума (рекомендуется), `True` для стабильного фона.
 ## Эффекты под AI-ассистента
 Silero звучит естественно, но иногда хочется лёгкой «AI-окраски» в духе J.A.R.V.I.S. — узкую полосу, еле заметную реверберацию, при желании небольшой сдвиг высоты. Это тонкий постпроцессинг, голос и sample rate не меняются.
 По умолчанию эффекты **выключены**. Включаются в `config.py`:
 - `TTS_EFFECTS_ENABLED` — главный тумблер (`False` по умолчанию).
 - `TTS_BANDPASS_LOW_HZ` / `TTS_BANDPASS_HIGH_HZ` — полоса пропускания (по умолчанию 200–7000 Гц). Сужение полосы даёт ощущение «голоса по радио».
 - `TTS_REVERB_WET` (0..1) и `TTS_REVERB_DECAY_MS` — доля мокрого сигнала и длительность хвоста короткой реверберации (по умолчанию 0.20 и 100 мс).
 - `TTS_PITCH_SEMITONES` — сдвиг высоты в полутонах (по умолчанию 0, разумный диапазон ±2).
 Фильтры реализованы на `scipy.signal` (IIR, sosfiltfilt — нулевая фазовая задержка), реверберация — несколько затухающих задержанных копий, pitch — ресэмплинг по линейной интерполяции. Всё in-process, без временных файлов и лишних зависимостей.
 Быстрое A/B сравнение перед тем как переключать тумблер:
 ```bash
 .venv\Scripts\python.exe utils\preview_effects.py
 ```
 Скрипт сгенерирует `sound/_preview_silero_raw.wav` и `sound/_preview_silero_fx.wav` — откройте оба в плеере и решите, нравится ли эффект. Параметры fx-версии берутся из текущего `config.py` (независимо от `TTS_EFFECTS_ENABLED`).
 ## Схема commands.yaml
 Каждая команда — это пара `phrases` + `action`:
 ```yaml
 open_browser:
  phrases:
    - открой браузер
    - запусти браузер
  action: {type: exe, file: "Run browser.exe"}
 ```
 Типы действий:
 - `exe` — запустить `.exe` из `custom-commands/`. Поля: `file` (имя файла), необязательные `wait: true` (ждать завершения), `delay_ms` (пауза после запуска). По умолчанию после `exe` проигрывается звук подтверждения `ok` — отключается через `confirm_sound: null`.
 - `play_sound` — проиграть WAV из `sound/`. Поле `name` (без расширения). Имена `greet` и `ok` проигрываются с рандомным выбором из вариантов `greet1/2/3.wav`, `ok1/2/3.wav`.
 - `system` — встроенные операции. `op: volume_mute`, `volume_unmute`, `exit`.
 - `multi` — последовательность шагов: `steps: [...]`.
 Шаги внутри `multi` — тех же типов. Пример:
 ```yaml
 sound_off:
  phrases: [выключи звук, отключи звук]
  action:
    type: multi
    steps:
      - {type: play_sound, name: ok}
      - {type: system, op: volume_mute}
 ```
 ## Конструктор команд
 GUI для добавления команд в `commands.yaml` без ручной правки YAML.
 Запуск:
 ```
 python -m tools.command_builder
 ```
 Или из корня репо `run_builder.bat` (под Windows). Открывается окно pywebview с пошаговым мастером: фразы → тип действия → параметры → предпросмотр YAML и сохранение. На шаге «Действие» доступна вкладка «Подсказать (LLM)» — модель Groq предложит готовый блок по описанию на русском.
 После сохранения команды Jarvis нужно перезапустить, чтобы она подхватилась.
 Требования:
 - Windows 10/11 с установленным WebView2 Runtime (обычно уже стоит вместе с Edge — иначе [скачать у Microsoft](https://developer.microsoft.com/microsoft-edge/webview2/)).
 - Зависимости из `requirements.txt` (включая `pywebview`, `ruamel.yaml`, `pyautogui`).
 Подробности для разработчиков — [tools/command_builder/README.md](tools/command_builder/README.md). TODO: добавить скриншот окна.
 ## Лицензия
 CC BY-NC-SA 4.0 — см. [LICENSE.txt](LICENSE.txt). Авторство оригинала — Abraham Tugalov / Priler. Изменения в этом форке — Bossiara13 (Dmitry Bykov), 2026.
--- a/commands.yaml
+++ b/commands.yaml
@ -0,0 +1,239 @@
 open_browser:
  phrases:
    - открой браузер
    - запусти браузер
    - открой яндекс
    - яндекс браузер
  action: {type: url, href: "about:blank", browser: "yandex"}
 open_youtube:
  phrases:
    - открой ютуб
    - ютуб
    - запусти ютуб
  action: {type: url, href: "https://www.youtube.com", browser: "yandex"}
 open_google:
  phrases:
    - открой гугл
    - гугл
    - запусти гугл
  action: {type: url, href: "https://www.google.com", browser: "yandex"}
 music:
  phrases:
    - давай музыку
    - музыка
    - яндекс музыка
    - включи музыку
    - открой музыку
    - послушаем музыку
    - хочу музыку
    - врубай музло
    - включи что-то послушать
    - давай что-то послушаем
  action: {type: exe, file: "Run music.exe"}
 music_off:
  phrases:
    - выключи музыку
    - отруби музыку
    - убери музыку
    - отключи музыку
    - закрой музыку
    - останови музыку
    - хватит музыки
  action: {type: exe, file: "Stop music.exe", delay_ms: 200}
 music_save:
  phrases:
    - сохрани трек
    - мне нравится трек
    - сохрани песню
    - мне нравится песня
    - добавь трек в избранное
    - добавь песню в избранное
    - запомни мелодию
    - запомни трек
    - запомни песню
    - добавь мелодию в избранное
    - сохрани то что сейчас играет
    - добавь то что сейчас играет в избранное
    - лайкни трек
    - лайкни мелодию
    - лайкни песню
  action: {type: exe, file: "Save music.exe", delay_ms: 200}
 music_next:
  phrases:
    - следующий трек
    - следующая мелодия
    - следующая песня
    - переключи трек
    - переключи музыку
    - переключи мелодию
    - переключи песню
    - следующая музыка
  action: {type: exe, file: "Next music.exe", delay_ms: 200}
 music_prev:
  phrases:
    - предыдущая музыка
    - предыдущий трек
    - предыдущая мелодия
    - предыдущая песня
    - верни трек
    - верни мелодию
    - верни песню
    - верни прошлый трек
    - верни прошлую мелодию
    - верни прошлую песню
    - верни прошлую музыку
    - верни то что играло
    - давай предыдущий трек
    - переключи музыку обратно
    - переключи на прошлый трек
    - переключи на прошлую мелодию
    - переключи на прошлую песню
  action: {type: exe, file: "Prev music.exe", delay_ms: 200}
 sound_off:
  phrases:
    - выключи звук
    - беззвучный режим
    - режим без звука
    - отключи звук
  action:
    type: multi
    steps:
      - {type: play_sound, name: ok}
      - {type: system, op: volume_mute}
 sound_on:
  phrases:
    - включи звук
    - режим со звуком
    - верни звук
  action:
    type: multi
    steps:
      - {type: system, op: volume_unmute}
      - {type: play_sound, name: ok}
 thanks:
  phrases:
    - спасибо
    - молодец
    - респект
    - ты супер
    - отличная работа
    - ты крут
    - ты большой молодец
    - ты реально крут
    - ты афигенный
  action: {type: play_sound, name: thanks}
 stupid:
  phrases:
    - ты дурак
    - ты дебил
    - ты глупый
    - ты тупой
  action: {type: play_sound, name: stupid}
 gaming_mode_on:
  phrases:
    - включи игровой режим
    - перейди в игровой режим
    - я хочу поиграть
    - переключись на телевизор
  action:
    type: multi
    steps:
      - {type: play_sound, name: ok}
      - {type: exe, file: "Switch to gaming mode.exe", wait: true}
      - {type: play_sound, name: ready}
 gaming_mode_off:
  phrases:
    - рабочий режим
    - вернись в рабочий режим
    - переключись на компьютер
    - обратно на компьютер
    - отключи игровой режим
    - выйди из игрового режима
    - вернись на компьютер
    - выход с игрового режима
    - рабочее пространство
    - вернись в игровой режим
    - выключи игровой режим
  action:
    type: multi
    steps:
      - {type: play_sound, name: ok}
      - {type: exe, file: "Switch back to workspace.exe", wait: true}
      - {type: play_sound, name: ready}
 switch_to_headphones:
  phrases:
    - переключи на наушники
    - включи наушники
    - перейди на наушники
    - давай звук в наушники
    - давай звук на наушники
    - переключи звук в наушники
    - переключи звук на наушники
    - переключи на кракены
    - включи кракены
    - перейди на кракены
    - давай звук в кракены
    - давай звук на кракены
    - переключи звук в кракены
    - переключи звук на кракены
  action:
    type: multi
    steps:
      - {type: play_sound, name: ok}
      - {type: exe, file: "Switch to headphones.exe", wait: true, delay_ms: 500}
      - {type: play_sound, name: ready}
 switch_to_dynamics:
  phrases:
    - переключи на динамики
    - включи динамики
    - перейди на динамики
    - давай звук в динамики
    - давай звук на динамики
    - переключи звук в динамики
    - переключи звук на динамики
    - переключи на колонки
    - включи колонки
    - перейди на колонки
    - давай звук в колонки
    - давай звук на колонки
    - переключи звук в колонки
    - переключи звук на колонки
  action:
    type: multi
    steps:
      - {type: play_sound, name: ok}
      - {type: exe, file: "Switch to dynamics.exe", wait: true, delay_ms: 500}
      - {type: play_sound, name: ready}
 'off':
  phrases:
    - выключись
    - вырубись
    - завершить работу
    - закройся
    - отключись
    - заверши свою работу
    - на сегодня хватит
    - выгрузи себя из памяти
    - ты мне надоел
    - пора спать
  action:
    type: multi
    steps:
      - {type: play_sound, name: "off"}
      - {type: system, op: exit}
--- a/config.py
+++ b/config.py
@ -0,0 +1,60 @@
 from dotenv import load_dotenv
 import os
 # Find .env file with os variables
 load_dotenv("dev.env")
 # Конфигурация
 VA_NAME = 'Jarvis'
 VA_VER = "0.4.1"
 VA_ALIAS = ('джарвис',)
 VA_TBR = ('скажи', 'покажи', 'ответь', 'произнеси', 'расскажи', 'сколько', 'слушай')
 # Wake-words распознаются Vosk'ом с grammar-constraint. Добавляйте сюда
 # варианты написания — Vosk с русской моделью может расшифровать "jarvis"
 # как "джарвис", "жарвис" и т.п.
 WAKE_WORDS = ('jarvis', 'джарвис')
 # ID микрофона (можете просто менять ID пока при запуске не отобразится нужный)
 # -1 это стандартное записывающее устройство
 MICROPHONE_INDEX = -1
 BROWSER_PATHS = {
    'yandex':  'C:/Program Files/Yandex/YandexBrowser/Application/browser.exe',
    'chrome':  'C:/Program Files/Google/Chrome/Application/chrome.exe',
    'firefox': 'C:/Program Files/Mozilla Firefox/firefox.exe',
    'edge':    'C:/Program Files (x86)/Microsoft/Edge/Application/msedge.exe',
 }
 # Токен Groq
 GROQ_TOKEN = os.getenv('GROQ_TOKEN')
 GROQ_BASE_URL = "https://api.groq.com/openai/v1"
 GROQ_MODEL = "llama-3.3-70b-versatile"
 # VAD (webrtcvad) — определяет конец команды по тишине вместо фиксированных 10 сек.
 # 0..3, выше — агрессивнее режет шум (но и обрезает речь).
 VAD_AGGRESSIVENESS = 2
 COMMAND_END_SILENCE_MS = 1200
 COMMAND_MIN_SPEECH_MS = 500
 COMMAND_MIN_LISTEN_MS = 1000
 COMMAND_MAX_LISTEN_MS = 15000
 TTS_EFFECTS_ENABLED = False
 TTS_BANDPASS_LOW_HZ = 200
 TTS_BANDPASS_HIGH_HZ = 7000
 TTS_REVERB_WET = 0.20
 TTS_REVERB_DECAY_MS = 100
 TTS_PITCH_SEMITONES = 0
 # Семантический матчинг команд через эмбеддинги MiniLM-L6-v2 (ONNX, CPU).
 # Порог — косинусная близость [0..1]. На вход поступает уже отфильтрованная
 # фраза (без алиасов и vа_tbr); 0.45 эмпирически отделяет валидные команды
 # от шума, оставляя запас на разговорные перефразировки.
 INTENT_SIMILARITY_THRESHOLD = 0.45
 # Шумоподавление аудио перед Vosk на этапе захвата команды (после wake-word).
 # Спектральное гейтирование через noisereduce; даёт небольшую латентность,
 # поэтому выключено по умолчанию и применяется только к буферу команды.
 DENOISE_ENABLED = False
 DENOISE_PROP = 0.85
 DENOISE_STATIONARY = False
--- a/custom-commands/Next
+++ b/custom-commands/Next
@ -0,0 +1,19 @@
 #NoEnv  ; Recommended for performance and compatibility with future AutoHotkey releases.
 ; #Warn  ; Enable warnings to assist with detecting common errors.
 SendMode Input  ; Recommended for new scripts due to its superior speed and reliability.
 SetWorkingDir %A_ScriptDir%  ; Ensures a consistent starting directory.
 Process, Exist, Y.Music.exe
 If ErrorLevel = 0
 {
 ; APP IS NOT RUNNING
 }
 Else
 {
 ; APP IS RUNNING
 ;MsgBox, Already running
 Run C:\Users\Abraham\Documents\WinStoreApps\YandexMusic
 sleep 100
 Send, {Ctrl down}f{Ctrl up}
 }
 Return
--- a/custom-commands/Next
+++ b/custom-commands/Next
--- a/custom-commands/Prev
+++ b/custom-commands/Prev
@ -0,0 +1,19 @@
 #NoEnv  ; Recommended for performance and compatibility with future AutoHotkey releases.
 ; #Warn  ; Enable warnings to assist with detecting common errors.
 SendMode Input  ; Recommended for new scripts due to its superior speed and reliability.
 SetWorkingDir %A_ScriptDir%  ; Ensures a consistent starting directory.
 Process, Exist, Y.Music.exe
 If ErrorLevel = 0
 {
 ; APP IS NOT RUNNING
 }
 Else
 {
 ; APP IS RUNNING
 ;MsgBox, Already running
 Run C:\Users\Abraham\Documents\WinStoreApps\YandexMusic
 sleep 100
 Send, {Ctrl down}b{Ctrl up}
 }
 Return
--- a/custom-commands/Prev
+++ b/custom-commands/Prev
--- a/src-tauri/commands/browser/ahk/Run
+++ b/src-tauri/commands/browser/ahk/Run
--- a/src-tauri/commands/browser/ahk/Run
+++ b/src-tauri/commands/browser/ahk/Run
--- a/src-tauri/commands/browser/ahk/Run
+++ b/src-tauri/commands/browser/ahk/Run
--- a/src-tauri/commands/browser/ahk/Run
+++ b/src-tauri/commands/browser/ahk/Run
--- a/custom-commands/Run
+++ b/custom-commands/Run
@ -0,0 +1,41 @@
 #NoEnv  ; Recommended for performance and compatibility with future AutoHotkey releases.
 ; #Warn  ; Enable warnings to assist with detecting common errors.
 SendMode Input  ; Recommended for new scripts due to its superior speed and reliability.
 SetWorkingDir %A_ScriptDir%  ; Ensures a consistent starting directory.
 Process, Exist, Y.Music.exe
 If ErrorLevel = 0
 {
 ; APP IS NOT RUNNING
 ; Run https://music.yandex.ru/home
 Run C:\Users\Abraham\Documents\WinStoreApps\YandexMusic
 ; Autoplay
 sleep 3000
 Send, {Ctrl down}p{Ctrl up}
 sleep 10
 ; Open full
 Loop, 4
 {
 Send, {Tab}
 sleep 10
 }
 Send, {Enter}
 sleep 1500
 Loop, 7
 {
 Send, {Down}
 sleep 50
 }
 sleep 1000
 Send, {Enter}
 }
 Else
 {
 ; APP IS RUNNING
 ;MsgBox, Already running
 }
 Return
--- a/custom-commands/Run
+++ b/custom-commands/Run
--- a/src-tauri/commands/browser/ahk/Run
+++ b/src-tauri/commands/browser/ahk/Run
--- a/src-tauri/commands/browser/ahk/Run
+++ b/src-tauri/commands/browser/ahk/Run
--- a/custom-commands/Save
+++ b/custom-commands/Save
@ -0,0 +1,19 @@
 #NoEnv  ; Recommended for performance and compatibility with future AutoHotkey releases.
 ; #Warn  ; Enable warnings to assist with detecting common errors.
 SendMode Input  ; Recommended for new scripts due to its superior speed and reliability.
 SetWorkingDir %A_ScriptDir%  ; Ensures a consistent starting directory.
 Process, Exist, Y.Music.exe
 If ErrorLevel = 0
 {
 ; APP IS NOT RUNNING
 }
 Else
 {
 ; APP IS RUNNING
 ;MsgBox, Already running
 Run C:\Users\Abraham\Documents\WinStoreApps\YandexMusic
 sleep 100
 Send, {Ctrl down}l{Ctrl up}
 }
 Return
--- a/custom-commands/Save
+++ b/custom-commands/Save
--- a/src-tauri/commands/volume/ahk/Mute
+++ b/src-tauri/commands/volume/ahk/Mute
@ -3,4 +3,4 @@
 SendMode Input  ; Recommended for new scripts due to its superior speed and reliability.
 SetWorkingDir %A_ScriptDir%  ; Ensures a consistent starting directory.
-Send {Volume_Mute}  ; Mute/unmute the master volume.
+Process, Close, Y.Music.exe
--- a/src-tauri/commands/volume/ahk/Mute
+++ b/src-tauri/commands/volume/ahk/Mute
--- a/custom-commands/Switch
+++ b/custom-commands/Switch
@ -0,0 +1,16 @@
 #NoEnv  ; Recommended for performance and compatibility with future AutoHotkey releases.
 ; #Warn  ; Enable warnings to assist with detecting common errors.
 SendMode Input  ; Recommended for new scripts due to its superior speed and reliability.
 SetWorkingDir %A_ScriptDir%  ; Ensures a consistent starting directory.
 ; Step 1. Close steam.
 WinKill, AHK_exe Steam.exe
 Process, Close, Steam.exe
 ; Step 2. Switch monitor profile.
 RunWait C:\MonitorProfileSwitcher\MonitorSwitcher.exe -load:"C:\Users\Abraham\AppData\Roaming\MonitorSwitcher\Profiles\Workspace.xml"
 Sleep, 7000
 ; Step 3. Switch audio device to Luna Edifier.
 Run, nircmd setdefaultsounddevice "Luna Edifier" 1
--- a/custom-commands/Switch
+++ b/custom-commands/Switch
--- a/custom-commands/Switch
+++ b/custom-commands/Switch
@ -0,0 +1,6 @@
 #NoEnv  ; Recommended for performance and compatibility with future AutoHotkey releases.
 ; #Warn  ; Enable warnings to assist with detecting common errors.
 SendMode Input  ; Recommended for new scripts due to its superior speed and reliability.
 SetWorkingDir %A_ScriptDir%  ; Ensures a consistent starting directory.
 Run, nircmd setdefaultsounddevice "Luna Edifier" 1
--- a/custom-commands/Switch
+++ b/custom-commands/Switch
--- a/custom-commands/Switch
+++ b/custom-commands/Switch
@ -0,0 +1,19 @@
 #NoEnv  ; Recommended for performance and compatibility with future AutoHotkey releases.
 ; #Warn  ; Enable warnings to assist with detecting common errors.
 SendMode Input  ; Recommended for new scripts due to its superior speed and reliability.
 SetWorkingDir %A_ScriptDir%  ; Ensures a consistent starting directory.
 ; Step 1. Close steam.
 WinKill, AHK_exe Steam.exe
 Process, Close, Steam.exe
 ; Step 2. Switch monitor profile.
 RunWait C:\MonitorProfileSwitcher\MonitorSwitcher.exe -load:"C:\Users\Abraham\AppData\Roaming\MonitorSwitcher\Profiles\Gaming.xml"
 Sleep, 7000
 ; Step 3. Switch audio device to LG TV.
 Run, nircmd setdefaultsounddevice "LG TV" 1
 ; Step 4. Run Steam big picture.
 Run, steam://open/bigpicture
--- a/custom-commands/Switch
+++ b/custom-commands/Switch
--- a/custom-commands/Switch
+++ b/custom-commands/Switch
@ -0,0 +1,6 @@
 #NoEnv  ; Recommended for performance and compatibility with future AutoHotkey releases.
 ; #Warn  ; Enable warnings to assist with detecting common errors.
 SendMode Input  ; Recommended for new scripts due to its superior speed and reliability.
 SetWorkingDir %A_ScriptDir%  ; Ensures a consistent starting directory.
 Run, nircmd setdefaultsounddevice "Razer Kraken" 1
--- a/custom-commands/Switch
+++ b/custom-commands/Switch
--- a/custom-commands/nircmd.exe
+++ b/custom-commands/nircmd.exe
--- a/dev.env.example
+++ b/dev.env.example
@ -0,0 +1 @@
 GROQ_TOKEN=<тут ключ-groq>
--- a/effects.py
+++ b/effects.py
@ -0,0 +1,71 @@
 import numpy as np
 from scipy.signal import butter, sosfiltfilt
 def _ensure_float32_mono(audio):
    arr = np.asarray(audio, dtype=np.float32)
    if arr.ndim > 1:
        arr = arr.mean(axis=1).astype(np.float32)
    return arr
 def apply_bandpass(audio, sr, low_hz=200, high_hz=7000, order=4):
    arr = _ensure_float32_mono(audio)
    nyq = 0.5 * sr
    low = max(low_hz, 1) / nyq
    high = min(high_hz, int(nyq) - 1) / nyq
    if not (0 < low < high < 1):
        return arr
    sos = butter(order, [low, high], btype='band', output='sos')
    return sosfiltfilt(sos, arr).astype(np.float32)
 def apply_reverb(audio, sr, wet=0.20, decay_ms=100, taps=4):
    arr = _ensure_float32_mono(audio)
    if wet <= 0 or decay_ms <= 0:
        return arr
    dry = max(0.0, 1.0 - wet)
    out = dry * arr
    gap = max(1, int(sr * (decay_ms / 1000.0) / taps))
    gain = wet
    for i in range(1, taps + 1):
        delay = gap * i
        gain *= 0.6
        if delay >= len(arr):
            break
        padded = np.zeros_like(arr)
        padded[delay:] = arr[:len(arr) - delay]
        out += gain * padded
    peak = float(np.max(np.abs(out))) if out.size else 0.0
    if peak > 0.99:
        out *= 0.99 / peak
    return out.astype(np.float32)
 def apply_pitch(audio, sr, semitones=0):
    arr = _ensure_float32_mono(audio)
    if semitones == 0:
        return arr
    factor = 2.0 ** (semitones / 12.0)
    n_out = int(round(len(arr) / factor))
    if n_out <= 1:
        return arr
    src_idx = np.linspace(0, len(arr) - 1, num=n_out).astype(np.float32)
    lo = np.floor(src_idx).astype(np.int64)
    hi = np.clip(lo + 1, 0, len(arr) - 1)
    frac = (src_idx - lo).astype(np.float32)
    resampled = (1.0 - frac) * arr[lo] + frac * arr[hi]
    return resampled.astype(np.float32)
 def process(audio, sr, bandpass=None, reverb=None, pitch_semitones=0):
    out = _ensure_float32_mono(audio)
    if bandpass is not None:
        low, high = bandpass
        out = apply_bandpass(out, sr, low, high)
    if reverb is not None:
        wet, decay_ms = reverb
        out = apply_reverb(out, sr, wet=wet, decay_ms=decay_ms)
    if pitch_semitones:
        out = apply_pitch(out, sr, semitones=pitch_semitones)
    return out
--- a/index.html
+++ b/index.html
@ -1,14 +0,0 @@
 <!DOCTYPE html>
 <html lang="en">
  <head>
    <meta charset="UTF-8" />
    <link rel="icon" type="image/svg+xml" href="/vite.svg" />
    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
    <title>Tauri + Svelte + TS</title>
  </head>
  <body>
    <div id="app"></div>
    <script type="module" src="/src/main.ts"></script>
  </body>
 </html>
--- a/intent.py
+++ b/intent.py
@ -0,0 +1,79 @@
 import os
 import numpy as np
 import onnxruntime as ort
 from tokenizers import Tokenizer
 import config
 MODEL_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "models", "all-MiniLM-L6-v2")
 MAX_TOKENS = 128
 def _mean_pool(last_hidden: np.ndarray, attention_mask: np.ndarray) -> np.ndarray:
    mask = attention_mask.astype(np.float32)[..., None]
    summed = (last_hidden * mask).sum(axis=1)
    counts = np.clip(mask.sum(axis=1), a_min=1e-9, a_max=None)
    return summed / counts
 def _l2_normalize(x: np.ndarray) -> np.ndarray:
    norm = np.linalg.norm(x, axis=-1, keepdims=True)
    return x / np.clip(norm, a_min=1e-12, a_max=None)
 class IntentClassifier:
    def __init__(self, model_dir: str = MODEL_DIR):
        tok_path = os.path.join(model_dir, "tokenizer.json")
        onnx_path = os.path.join(model_dir, "model.onnx")
        self._tokenizer = Tokenizer.from_file(tok_path)
        self._tokenizer.enable_truncation(max_length=MAX_TOKENS)
        self._tokenizer.enable_padding(pad_id=0, pad_token="[PAD]")
        so = ort.SessionOptions()
        so.intra_op_num_threads = max(1, (os.cpu_count() or 2) // 2)
        so.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_ALL
        self._session = ort.InferenceSession(onnx_path, sess_options=so, providers=["CPUExecutionProvider"])
        self._input_names = {inp.name for inp in self._session.get_inputs()}
        self._cache: dict[str, np.ndarray] = {}
    def embed(self, texts: list[str]) -> np.ndarray:
        if not texts:
            return np.zeros((0, 384), dtype=np.float32)
        encs = self._tokenizer.encode_batch(texts)
        ids = np.array([e.ids for e in encs], dtype=np.int64)
        mask = np.array([e.attention_mask for e in encs], dtype=np.int64)
        feeds = {"input_ids": ids, "attention_mask": mask}
        if "token_type_ids" in self._input_names:
            feeds["token_type_ids"] = np.zeros_like(ids)
        outputs = self._session.run(None, feeds)
        last_hidden = outputs[0]
        pooled = _mean_pool(last_hidden, mask)
        return _l2_normalize(pooled).astype(np.float32)
    def prime(self, candidates: dict[str, list[str]]) -> None:
        self._cache.clear()
        for cmd_id, phrases in candidates.items():
            if not phrases:
                continue
            self._cache[cmd_id] = self.embed(list(phrases))
    def match(self, utterance: str, candidates: dict[str, list[str]]) -> dict:
        utterance = (utterance or "").strip()
        if not utterance:
            return {"cmd": "", "score": 0.0}
        for cmd_id, phrases in candidates.items():
            if cmd_id not in self._cache and phrases:
                self._cache[cmd_id] = self.embed(list(phrases))
        query = self.embed([utterance])[0]
        best_cmd = ""
        best_score = -1.0
        for cmd_id, mat in self._cache.items():
            sims = mat @ query
            top = float(sims.max()) if sims.size else -1.0
            if top > best_score:
                best_score = top
                best_cmd = cmd_id
        threshold = getattr(config, "INTENT_SIMILARITY_THRESHOLD", 0.45)
        if best_score < threshold:
            return {"cmd": "", "score": max(0.0, best_score)}
        return {"cmd": best_cmd, "score": max(0.0, best_score)}
--- a/main.py
+++ b/main.py
@ -0,0 +1,364 @@
 import datetime
 import json
 import os
 import queue
 import random
 import struct
 import subprocess
 import sys
 import time
 import webbrowser
 from ctypes import POINTER, cast
 import numpy as np
 import openai
 from openai import OpenAI
 import simpleaudio as sa
 import vosk
 import webrtcvad
 import yaml
 from comtypes import CLSCTX_ALL
 from fuzzywuzzy import fuzz
 from pvrecorder import PvRecorder
 from pycaw.pycaw import (
    AudioUtilities,
    IAudioEndpointVolume
 )
 from rich import print
 import config
 import tts
 from intent import IntentClassifier
 # some consts
 CDIR = os.getcwd()
 VA_CMD_LIST = yaml.safe_load(
    open('commands.yaml', 'rt', encoding='utf8'),
 )
 system_message = {"role": "system", "content": (
    "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."
 )}
 message_log = [system_message]
 client = OpenAI(api_key=config.GROQ_TOKEN, base_url=config.GROQ_BASE_URL)
 model = vosk.Model("model_small")
 samplerate = 16000
 device = config.MICROPHONE_INDEX
 # wake-word phase uses a grammar-constrained recognizer so only WAKE_WORDS
 # (plus [unk] filler) can match — command phase needs full vocab, hence two.
 wake_grammar = json.dumps(list(config.WAKE_WORDS) + ["[unk]"], ensure_ascii=False)
 wake_rec = vosk.KaldiRecognizer(model, samplerate, wake_grammar)
 kaldi_rec = vosk.KaldiRecognizer(model, samplerate)
 q = queue.Queue()
 VAD_FRAME_MS = 30
 VAD_FRAME_BYTES = int(samplerate * VAD_FRAME_MS / 1000) * 2
 vad = webrtcvad.Vad(config.VAD_AGGRESSIVENESS)
 intent_classifier = IntentClassifier()
 intent_classifier.prime({c: v['phrases'] for c, v in VA_CMD_LIST.items()})
 if config.DENOISE_ENABLED:
    import noisereduce as nr
 else:
    nr = None
 def denoise_pcm(raw: bytes) -> bytes:
    if not raw or nr is None:
        return raw
    samples = np.frombuffer(raw, dtype=np.int16).astype(np.float32) / 32768.0
    reduced = nr.reduce_noise(
        y=samples,
        sr=samplerate,
        prop_decrease=config.DENOISE_PROP,
        stationary=config.DENOISE_STATIONARY,
    )
    clipped = np.clip(reduced * 32768.0, -32768, 32767).astype(np.int16)
    return clipped.tobytes()
 def gpt_answer():
    global message_log
    try:
        response = client.chat.completions.create(
            model=config.GROQ_MODEL,
            messages=message_log,
            max_tokens=256,
            temperature=0.7,
            top_p=1,
            stop=None,
        )
    except openai.BadRequestError as ex:
        code = getattr(ex, "code", None) or ""
        message = str(ex)
        if code == "context_length_exceeded" or "context_length_exceeded" in message:
            message_log = [system_message, message_log[-1]]
            return gpt_answer()
        return "Запрос отклонён моделью."
    except openai.RateLimitError:
        return "Лимит запросов исчерпан."
    except openai.APIConnectionError:
        return "Не могу связаться с сервером."
    except openai.APIError:
        return "Groq токен не рабочий."
    return response.choices[0].message.content
 # play(f'{CDIR}\\sound\\ok{random.choice([1, 2, 3, 4])}.wav')
 def play(phrase, wait_done=True):
    global recorder
    filename = f"{CDIR}\\sound\\"
    if phrase == "greet":  # for py 3.8
        filename += f"greet{random.choice([1, 2, 3])}.wav"
    elif phrase == "ok":
        filename += f"ok{random.choice([1, 2, 3])}.wav"
    elif phrase == "not_found":
        filename += "not_found.wav"
    elif phrase == "thanks":
        filename += "thanks.wav"
    elif phrase == "run":
        filename += "run.wav"
    elif phrase == "stupid":
        filename += "stupid.wav"
    elif phrase == "ready":
        filename += "ready.wav"
    elif phrase == "off":
        filename += "off.wav"
    if wait_done:
        recorder.stop()
    wave_obj = sa.WaveObject.from_wave_file(filename)
    play_obj = wave_obj.play()
    if wait_done:
        play_obj.wait_done()
        # time.sleep((len(wave_obj.audio_data) / wave_obj.sample_rate) + 0.5)
        # print("END")
        # time.sleep(0.5)
        recorder.start()
 def q_callback(indata, frames, time, status):
    if status:
        print(status, file=sys.stderr)
    q.put(bytes(indata))
 def va_respond(voice: str):
    global recorder, message_log, first_request
    print(f"Распознано: {voice}")
    cmd = recognize_cmd(filter_cmd(voice))
    print(cmd)
    min_percent = int(round(config.INTENT_SIMILARITY_THRESHOLD * 100))
    if len(cmd['cmd'].strip()) <= 0:
        return False
    elif cmd['percent'] < min_percent or cmd['cmd'] not in VA_CMD_LIST.keys():
        # play("not_found")
        # tts.va_speak("Что?")
        if fuzz.ratio(voice.join(voice.split()[:1]).strip(), "скажи") > 75:
            message_log.append({"role": "user", "content": voice})
            response = gpt_answer()
            message_log.append({"role": "assistant", "content": response})
            recorder.stop()
            tts.va_speak(response)
            time.sleep(0.5)
            recorder.start()
            return False
        else:
            play("not_found")
            time.sleep(1)
        return False
    else:
        execute_cmd(cmd['cmd'], voice)
        return True
 def filter_cmd(raw_voice: str):
    cmd = raw_voice
    for x in config.VA_ALIAS:
        cmd = cmd.replace(x, "").strip()
    for x in config.VA_TBR:
        cmd = cmd.replace(x, "").strip()
    return cmd
 def recognize_cmd(cmd: str):
    candidates = {c: v['phrases'] for c, v in VA_CMD_LIST.items()}
    res = intent_classifier.match(cmd, candidates)
    return {'cmd': res['cmd'], 'percent': int(round(res['score'] * 100))}
 def _set_mute(state: int):
    devices = AudioUtilities.GetSpeakers()
    interface = devices.Activate(IAudioEndpointVolume._iid_, CLSCTX_ALL, None)
    volume = cast(interface, POINTER(IAudioEndpointVolume))
    volume.SetMute(state, None)
 def _shutdown():
    try:
        recorder.stop()
        recorder.delete()
    finally:
        sys.exit(0)
 def run_action(action):
    t = action['type']
    if t == 'exe':
        path = f"{CDIR}\\custom-commands\\{action['file']}"
        if action.get('wait'):
            subprocess.check_call([path])
        else:
            subprocess.Popen([path])
        if 'delay_ms' in action:
            time.sleep(action['delay_ms'] / 1000)
    elif t == 'play_sound':
        play(action['name'])
    elif t == 'system':
        op = action['op']
        if op == 'volume_mute':
            _set_mute(1)
        elif op == 'volume_unmute':
            _set_mute(0)
        elif op == 'exit':
            _shutdown()
    elif t == 'sleep':
        time.sleep(action['ms'] / 1000)
    elif t == 'shell':
        if action.get('wait'):
            subprocess.check_call(action['cmd'], shell=True)
        else:
            subprocess.Popen(action['cmd'], shell=True)
    elif t == 'url':
        browser = action.get('browser')
        if browser:
            exe = config.BROWSER_PATHS.get(browser)
            if exe and os.path.isfile(exe):
                subprocess.Popen([exe, action['href']])
                return
        webbrowser.open(action['href'])
    elif t == 'keys':
        import pyautogui
        if action.get('sequence'):
            keys = [k.strip() for k in action['sequence'].split('+') if k.strip()]
            pyautogui.hotkey(*keys)
        elif action.get('text'):
            pyautogui.typewrite(action['text'], interval=0.02)
    elif t == 'multi':
        for step in action['steps']:
            run_action(step)
 def execute_cmd(cmd: str, voice: str):
    spec = VA_CMD_LIST.get(cmd)
    if not spec:
        return
    action = spec['action']
    run_action(action)
    confirm = spec.get('confirm_sound')
    if confirm is None and action['type'] == 'exe':
        confirm = 'ok'
    if confirm:
        play(confirm)
 recorder = PvRecorder(device_index=config.MICROPHONE_INDEX, frame_length=512)
 recorder.start()
 print('Using device: %s' % recorder.selected_device)
 print(f"Jarvis (v{config.VA_VER}) начал свою работу ...")
 play("run")
 time.sleep(0.5)
 def heard_wake_word(text: str) -> bool:
    if not text:
        return False
    lowered = text.lower()
    return any(w in lowered for w in config.WAKE_WORDS)
 while True:
    try:
        pcm = recorder.read()
        sp = struct.pack("h" * len(pcm), *pcm)
        if not wake_rec.AcceptWaveform(sp):
            continue
        result_text = json.loads(wake_rec.Result()).get("text", "")
        if not heard_wake_word(result_text):
            continue
        play("greet", True)
        print("Yes, sir.")
        kaldi_rec.Reset()
        listen_started = time.time()
        speech_ms = 0
        silence_ms = 0
        vad_buf = b""
        finalize = False
        cmd_buf = b"" if config.DENOISE_ENABLED else None
        while True:
            elapsed_ms = (time.time() - listen_started) * 1000
            if elapsed_ms >= config.COMMAND_MAX_LISTEN_MS:
                break
            pcm = recorder.read()
            sp = struct.pack("h" * len(pcm), *pcm)
            if cmd_buf is None:
                kaldi_rec.AcceptWaveform(sp)
            else:
                cmd_buf += sp
            vad_buf += sp
            while len(vad_buf) >= VAD_FRAME_BYTES:
                frame = vad_buf[:VAD_FRAME_BYTES]
                vad_buf = vad_buf[VAD_FRAME_BYTES:]
                if vad.is_speech(frame, samplerate):
                    speech_ms += VAD_FRAME_MS
                    silence_ms = 0
                else:
                    silence_ms += VAD_FRAME_MS
            if elapsed_ms < config.COMMAND_MIN_LISTEN_MS:
                continue
            if speech_ms >= config.COMMAND_MIN_SPEECH_MS and silence_ms >= config.COMMAND_END_SILENCE_MS:
                finalize = True
                break
        if finalize or speech_ms > 0:
            if cmd_buf is not None:
                kaldi_rec.AcceptWaveform(denoise_pcm(cmd_buf))
            text = json.loads(kaldi_rec.FinalResult()).get("text", "")
            if text:
                va_respond(text)
        wake_rec.Reset()
    except Exception as err:
        print(f"Unexpected {err=}, {type(err)=}")
        raise
--- a/src-tauri/vosk/model_small/README
+++ b/src-tauri/vosk/model_small/README
--- a/src-tauri/vosk/model_small/am/final.mdl
+++ b/src-tauri/vosk/model_small/am/final.mdl
--- a/src-tauri/vosk/model_small/conf/mfcc.conf
+++ b/src-tauri/vosk/model_small/conf/mfcc.conf
--- a/src-tauri/vosk/model_small/conf/model.conf
+++ b/src-tauri/vosk/model_small/conf/model.conf
--- a/src-tauri/vosk/model_small/graph/Gr.fst
+++ b/src-tauri/vosk/model_small/graph/Gr.fst
--- a/src-tauri/vosk/model_small/graph/HCLr.fst
+++ b/src-tauri/vosk/model_small/graph/HCLr.fst
--- a/src-tauri/vosk/model_small/graph/disambig_tid.int
+++ b/src-tauri/vosk/model_small/graph/disambig_tid.int
--- a/src-tauri/vosk/model_small/graph/phones/word_boundary.int
+++ b/src-tauri/vosk/model_small/graph/phones/word_boundary.int
--- a/src-tauri/vosk/model_small/ivector/final.dubm
+++ b/src-tauri/vosk/model_small/ivector/final.dubm
--- a/src-tauri/vosk/model_small/ivector/final.ie
+++ b/src-tauri/vosk/model_small/ivector/final.ie
--- a/src-tauri/vosk/model_small/ivector/final.mat
+++ b/src-tauri/vosk/model_small/ivector/final.mat
--- a/src-tauri/vosk/model_small/ivector/global_cmvn.stats
+++ b/src-tauri/vosk/model_small/ivector/global_cmvn.stats
--- a/src-tauri/vosk/model_small/ivector/online_cmvn.conf
+++ b/src-tauri/vosk/model_small/ivector/online_cmvn.conf
--- a/src-tauri/vosk/model_small/ivector/splice.conf
+++ b/src-tauri/vosk/model_small/ivector/splice.conf
--- a/models/all-MiniLM-L6-v2/README.md
+++ b/models/all-MiniLM-L6-v2/README.md
@ -0,0 +1,35 @@
 ---
 license: apache-2.0
 pipeline_tag: sentence-similarity
 ---
 ONNX port of [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) for text classification and similarity searches.
 ### Usage
 Here's an example of performing inference using the model with [FastEmbed](https://github.com/qdrant/fastembed).
 ```py
 from fastembed import TextEmbedding
 documents = [
    "You should stay, study and sprint.",
    "History can only prepare us to be surprised yet again.",
 ]
 model = TextEmbedding(model_name="sentence-transformers/all-MiniLM-L6-v2")
 embeddings = list(model.embed(documents))
 # [
 #     array([
 #         0.00611658, 0.00068912, -0.0203846, ..., -0.01751488, -0.01174267,
 #         0.01463472
 #     ],
 #           dtype=float32),
 #     array([
 #         0.00173448, -0.00329958, 0.01557874, ..., -0.01473586, 0.0281806,
 #         -0.00448205
 #     ],
 #           dtype=float32)
 # ]
 ```
--- a/models/all-MiniLM-L6-v2/config.json
+++ b/models/all-MiniLM-L6-v2/config.json
@ -0,0 +1,25 @@
 {
  "_name_or_path": "sentence-transformers/all-MiniLM-L6-v2",
  "architectures": [
    "BertModel"
  ],
  "attention_probs_dropout_prob": 0.1,
  "classifier_dropout": null,
  "gradient_checkpointing": false,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 384,
  "initializer_range": 0.02,
  "intermediate_size": 1536,
  "layer_norm_eps": 1e-12,
  "max_position_embeddings": 512,
  "model_type": "bert",
  "num_attention_heads": 12,
  "num_hidden_layers": 6,
  "pad_token_id": 0,
  "position_embedding_type": "absolute",
  "transformers_version": "4.36.2",
  "type_vocab_size": 2,
  "use_cache": true,
  "vocab_size": 30522
 }
--- a/models/all-MiniLM-L6-v2/model.onnx
+++ b/models/all-MiniLM-L6-v2/model.onnx
--- a/models/all-MiniLM-L6-v2/special_tokens_map.json
+++ b/models/all-MiniLM-L6-v2/special_tokens_map.json
@ -0,0 +1,37 @@
 {
  "cls_token": {
    "content": "[CLS]",
    "lstrip": false,
    "normalized": false,
    "rstrip": false,
    "single_word": false
  },
  "mask_token": {
    "content": "[MASK]",
    "lstrip": false,
    "normalized": false,
    "rstrip": false,
    "single_word": false
  },
  "pad_token": {
    "content": "[PAD]",
    "lstrip": false,
    "normalized": false,
    "rstrip": false,
    "single_word": false
  },
  "sep_token": {
    "content": "[SEP]",
    "lstrip": false,
    "normalized": false,
    "rstrip": false,
    "single_word": false
  },
  "unk_token": {
    "content": "[UNK]",
    "lstrip": false,
    "normalized": false,
    "rstrip": false,
    "single_word": false
  }
 }
--- a/models/all-MiniLM-L6-v2/tokenizer.json
+++ b/models/all-MiniLM-L6-v2/tokenizer.json
--- a/models/all-MiniLM-L6-v2/tokenizer_config.json
+++ b/models/all-MiniLM-L6-v2/tokenizer_config.json
@ -0,0 +1,64 @@
 {
  "added_tokens_decoder": {
    "0": {
      "content": "[PAD]",
      "lstrip": false,
      "normalized": false,
      "rstrip": false,
      "single_word": false,
      "special": true
    },
    "100": {
      "content": "[UNK]",
      "lstrip": false,
      "normalized": false,
      "rstrip": false,
      "single_word": false,
      "special": true
    },
    "101": {
      "content": "[CLS]",
      "lstrip": false,
      "normalized": false,
      "rstrip": false,
      "single_word": false,
      "special": true
    },
    "102": {
      "content": "[SEP]",
      "lstrip": false,
      "normalized": false,
      "rstrip": false,
      "single_word": false,
      "special": true
    },
    "103": {
      "content": "[MASK]",
      "lstrip": false,
      "normalized": false,
      "rstrip": false,
      "single_word": false,
      "special": true
    }
  },
  "clean_up_tokenization_spaces": true,
  "cls_token": "[CLS]",
  "do_basic_tokenize": true,
  "do_lower_case": true,
  "mask_token": "[MASK]",
  "max_length": 128,
  "model_max_length": 512,
  "never_split": null,
  "pad_to_multiple_of": null,
  "pad_token": "[PAD]",
  "pad_token_type_id": 0,
  "padding_side": "right",
  "sep_token": "[SEP]",
  "stride": 0,
  "strip_accents": null,
  "tokenize_chinese_chars": true,
  "tokenizer_class": "BertTokenizer",
  "truncation_side": "right",
  "truncation_strategy": "longest_first",
  "unk_token": "[UNK]"
 }
--- a/models/all-MiniLM-L6-v2/vocab.txt
+++ b/models/all-MiniLM-L6-v2/vocab.txt
--- a/package-lock.json
+++ b/package-lock.json
--- a/package.json
+++ b/package.json
@ -1,39 +0,0 @@
 {
  "name": "jarvis-app",
  "private": true,
  "version": "0.0.0",
  "type": "module",
  "scripts": {
    "dev": "routify -c dev:vite",
    "dev:routify": "routify",
    "dev:vite": "vite",
    "build": "svelte-check && routify -b && vite build",
    "preview": "vite preview",
    "check": "svelte-check --tsconfig ./tsconfig.json",
    "tauri": "tauri"
  },
  "dependencies": {
    "@svelteuidev/composables": "^0.11.1",
    "@svelteuidev/core": "^0.11.1",
    "@svelteuidev/motion": "^0.11.1",
    "@tauri-apps/api": "^1.2.0",
    "howler": "^2.2.3",
    "radix-icons-svelte": "^1.2.1",
    "worker-timers": "^7.0.64"
  },
  "devDependencies": {
    "@roxi/routify": "^2.18.11",
    "@sveltejs/vite-plugin-svelte": "^2.0.0",
    "@tauri-apps/cli": "^1.2.2",
    "@tsconfig/svelte": "^3.0.0",
    "@types/node": "^18.7.10",
    "sass": "^1.62.0",
    "svelte": "^3.54.0",
    "svelte-check": "^3.0.0",
    "svelte-preprocess": "^5.0.0",
    "tslib": "^2.4.1",
    "typescript": "^4.9.5",
    "vite": "^4.2.1",
    "vite-tsconfig-paths": "^4.2.0"
  }
 }
--- a/public/media/app-logo.png
+++ b/public/media/app-logo.png
--- a/public/media/images/bg/bg1.gif
+++ b/public/media/images/bg/bg1.gif
--- a/public/media/images/bg/bg10.gif
+++ b/public/media/images/bg/bg10.gif
--- a/public/media/images/bg/bg11.gif
+++ b/public/media/images/bg/bg11.gif
--- a/public/media/images/bg/bg12.gif
+++ b/public/media/images/bg/bg12.gif
--- a/public/media/images/bg/bg13.gif
+++ b/public/media/images/bg/bg13.gif
--- a/public/media/images/bg/bg18.gif
+++ b/public/media/images/bg/bg18.gif
--- a/public/media/images/bg/bg19.gif
+++ b/public/media/images/bg/bg19.gif
--- a/public/media/images/bg/bg2.gif
+++ b/public/media/images/bg/bg2.gif
--- a/public/media/images/bg/bg20.gif
+++ b/public/media/images/bg/bg20.gif
--- a/public/media/images/bg/bg21.gif
+++ b/public/media/images/bg/bg21.gif
--- a/public/media/images/bg/bg22.gif
+++ b/public/media/images/bg/bg22.gif
--- a/public/media/images/bg/bg24.gif
+++ b/public/media/images/bg/bg24.gif
--- a/public/media/images/bg/bg25.gif
+++ b/public/media/images/bg/bg25.gif
--- a/public/media/images/bg/bg26.gif
+++ b/public/media/images/bg/bg26.gif
--- a/public/media/images/bg/bg3.gif
+++ b/public/media/images/bg/bg3.gif
--- a/public/media/images/bg/bg4.gif
+++ b/public/media/images/bg/bg4.gif
--- a/public/media/images/bg/bg5.gif
+++ b/public/media/images/bg/bg5.gif
--- a/public/media/images/bg/bg6.gif
+++ b/public/media/images/bg/bg6.gif
--- a/public/media/images/bg/bg7.gif
+++ b/public/media/images/bg/bg7.gif
--- a/public/media/images/bg/bg8.gif
+++ b/public/media/images/bg/bg8.gif
--- a/public/media/images/bg/bg9.gif
+++ b/public/media/images/bg/bg9.gif
--- a/public/media/images/cote1.gif
+++ b/public/media/images/cote1.gif
--- a/public/media/images/decor.png
+++ b/public/media/images/decor.png
--- a/public/media/images/man-1.png
+++ b/public/media/images/man-1.png
--- a/public/media/images/nero.png
+++ b/public/media/images/nero.png
--- a/public/media/images/preloaders/loader-hd.gif
+++ b/public/media/images/preloaders/loader-hd.gif
--- a/public/media/images/preloaders/loader.gif
+++ b/public/media/images/preloaders/loader.gif
--- a/public/media/images/preloaders/spinner.gif
+++ b/public/media/images/preloaders/spinner.gif
--- a/public/media/images/tenor.gif
+++ b/public/media/images/tenor.gif
--- a/public/media/images/vk.png
+++ b/public/media/images/vk.png
--- a/public/media/images/youtube.png
+++ b/public/media/images/youtube.png
--- a/requirements.txt
+++ b/requirements.txt
@ -0,0 +1,40 @@
 # mic capture
 pvrecorder
 # Vosk
 vosk
 # Voice activity detection (smart command-end)
 webrtcvad-wheels
 # Groq / OpenAI-compatible LLM
 openai>=1.0
 # Silero stuff
 torch
 torchaudio
 omegaconf
 # etc
 numpy
 simpleaudio
 rich
 fuzzywuzzy
 python-Levenshtein
 comtypes
 pycaw
 sounddevice
 PyYAML
 python-dotenv
 # Semantic intent classifier (MiniLM-L6-v2 ONNX)
 onnxruntime>=1.17
 tokenizers>=0.15
 # Noise suppression before STT (optional, off by default)
 noisereduce>=3.0
 # GUI command constructor (tools/command_builder)
 ruamel.yaml
 pywebview
 pyautogui
--- a/Show more
+++ b/Show more
Author	SHA1	Message	Date
Bossiara13	53678fbdfa	Release v0.4.1 — browser choice for url-action	2026-04-27 20:06:58 +03:00
Bossiara13	b8fc7b4eb7	chore: bump VA_VER to 0.4.1	2026-04-27 20:06:52 +03:00
Bossiara13	d0eac79275	Merge feature/browser-choice-in-url into dev	2026-04-27 20:06:51 +03:00
Bossiara13	a4171ec6b1	feat(url): optional browser field (yandex/chrome/firefox/edge) Adds optional 'browser' field to url-action; runtime resolves it via config.BROWSER_PATHS (subprocess.Popen with the chosen exe). When omitted, falls back to webbrowser.open (system default). Constructor GUI gains a browser dropdown on URL action and on multi-step URL. Existing open_browser/youtube/google updated to use yandex by default since user prefers Yandex Browser.	2026-04-27 20:06:26 +03:00
Bossiara13	47927fcf41	Release v0.4.0 — semantic intent (ONNX MiniLM) + optional denoise	2026-04-23 11:09:54 +03:00
Bossiara13	d22a35c9c7	chore: bump VA_VER to 0.4.0	2026-04-23 11:09:48 +03:00
Bossiara13	59aece53da	Merge feature/onnx-intent-and-denoise into dev Replaces fuzzywuzzy intent matching with ONNX MiniLM-L6-v2 sentence embeddings (cosine similarity, threshold 0.45). Now triggers on semantically equivalent phrases not literally in commands.yaml. Adds optional noisereduce preprocessing before Vosk (off by default, DENOISE_ENABLED config flag). Inference latency: 2.5ms median CPU.	2026-04-23 11:09:46 +03:00
Bossiara13	8655b4fc69	docs: README — semantic intent + denoise	2026-04-23 10:55:07 +03:00
Bossiara13	cc3fa60c28	chore: pin onnxruntime / tokenizers / noisereduce in requirements	2026-04-23 10:54:38 +03:00
Bossiara13	13370da5b7	feat: optional noisereduce preprocessing before vosk	2026-04-23 10:54:20 +03:00
Bossiara13	6a710c55b8	feat: onnx intent classifier replacing fuzzy match	2026-04-23 10:53:18 +03:00
Bossiara13	9cb55f4730	chore: vendor MiniLM-L6-v2 onnx model from Qdrant	2026-04-23 10:51:53 +03:00
Bossiara13	31a2dd1a6c	chore: enable git lfs for .onnx files	2026-04-23 10:51:29 +03:00
Bossiara13	e7d4304a62	Release v0.3.0 — TTS effects + GUI command constructor	2026-04-23 02:17:09 +03:00
Bossiara13	1eaaf9eddc	Merge feature/command-builder into dev GUI command constructor (pywebview, Russian, dark theme matching Rust GUI palette). 3-step stepper + LLM-suggest tab. Writes to commands.yaml with ruamel-preserved comments and .bak backup. Three new action types: shell / url / keys (pyautogui-based).	2026-04-23 02:17:02 +03:00
Bossiara13	e86906801a	Merge feature/ai-style-postproc into dev Optional bandpass + short reverb on Silero TTS output. Off by default (TTS_EFFECTS_ENABLED in config.py). Preview script in utils/.	2026-04-23 02:17:02 +03:00
Bossiara13	fbfe3a7ff6	chore: bump VA_VER to 0.3.0	2026-04-23 02:13:49 +03:00
Bossiara13	b535d025f3	docs: command builder README + user-facing README section + run_builder.bat	2026-04-23 02:13:47 +03:00
Bossiara13	521b124f05	feat(ui): keyboard nav (Enter advances step) + yaml-health warning on launch	2026-04-23 02:13:43 +03:00
Bossiara13	0b1604e018	feat(tools): llm-suggest via groq with JSON response format	2026-04-23 02:11:45 +03:00
Bossiara13	e4d4bf7a08	feat(ui): steps 1-3 (trigger / action / params) with live YAML preview	2026-04-23 02:11:01 +03:00
Bossiara13	232490d9fa	chore: vendor js-yaml.min.js	2026-04-23 02:10:57 +03:00
Bossiara13	9814181d1a	feat(tools): pywebview bootstrap + python bridge API Single window (900x720, dark background) loading web/index.html with a Python bridge exposing list_existing_commands, list_exes, list_sound_names, preview_sound, slugify, validate_draft, save_command, plus llm_suggest hook for M3. Sound preview spawned on a daemon thread so the GUI does not block.	2026-04-22 23:21:20 +03:00
Bossiara13	80d9eedead	chore: add ruamel.yaml + pyautogui deps ruamel.yaml is needed by tools/command_builder/yaml_writer to round-trip commands.yaml without losing comments. pyautogui drives the new keys action. pywebview is added now too so M2's GUI bootstrap can land without another deps bump.	2026-04-22 23:17:44 +03:00
Bossiara13	7b8cd31cf3	feat: add shell / url / keys action types to runtime dispatcher shell uses subprocess (with shell=True so user can write a normal command line); url uses webbrowser.open; keys uses pyautogui.hotkey for combinations or pyautogui.typewrite for raw text. pyautogui is imported lazily so the bot still starts on machines without a GUI.	2026-04-22 23:17:40 +03:00
Bossiara13	0f6b794db9	feat(tools): yaml writer with ruamel (preserves comments, atomic + backup) Uses ruamel.yaml so existing comments / formatting in commands.yaml survive a save. Each write creates commands.yaml.bak first, then atomically renames a .tmp file into place. Tests cover round-trip for all action types plus comment-preservation on append.	2026-04-22 23:17:24 +03:00
Bossiara13	68e73b3c53	feat(tools): scaffold command builder schema Dataclass-based schema mirroring commands.yaml plus new action types (shell, url, keys). Round-trip dict<->dataclass with validation. Russian-aware slugify for auto-generating command IDs.	2026-04-22 23:17:17 +03:00
Bossiara13	f9e1e2468f	chore: gitignore voice_ref/ and sound/_*.wav experiments	2026-04-22 23:10:54 +03:00
Bossiara13	e5903d8076	docs: README — TTS effects section	2026-04-22 20:00:04 +03:00
Bossiara13	34f5cd4f5a	chore: add utils/preview_effects.py for A/B comparison	2026-04-22 19:59:45 +03:00
Bossiara13	64ad7b963e	feat: wire effects into va_speak behind config.TTS_EFFECTS_ENABLED	2026-04-22 19:58:42 +03:00
Bossiara13	bd6bc294ad	feat: add tts effects module (bandpass + reverb + optional pitch)	2026-04-22 19:58:20 +03:00
Bossiara13	f45ac77a2e	Release v0.2.0 — VAD + YAML plugin commands	2026-04-22 19:43:57 +03:00
Bossiara13	4f3b827a47	Merge feature/vad-and-yaml-plugins into dev Adds webrtcvad-based smart command-end detection (fixed 10s window replaced by VAD with configurable silence/min/max thresholds) and migrates execute_cmd to a YAML-driven plugin system with typed actions (exe, play_sound, system, multi, sleep). 17 commands migrated; all original behavior preserved.	2026-04-22 19:43:52 +03:00
Bossiara13	7855c5da37	docs: README — document VAD + YAML plugin schema	2026-04-22 19:35:45 +03:00
Bossiara13	63cb64ef21	chore: update commands.yaml to new action schema All 17 voice commands migrated from a flat phrase list to the phrases/action shape. Behaviour preserved 1:1 with the previous elif chain — including the 200ms post-Popen pause for music_* controls and the 500ms pause before the 'ready' chime on the audio-device switch commands.	2026-04-22 19:35:16 +03:00
Bossiara13	a1a2be309b	refactor: drive execute_cmd from commands.yaml action schema Replaces the 100-line elif chain with a small dispatcher. Each entry in commands.yaml now carries both 'phrases' (existing trigger list) and 'action' describing how to run it. Action types: exe, play_sound, system (volume_mute/unmute/exit), sleep, multi. The data migration lives in the next commit; the dispatcher in this commit assumes the new schema.	2026-04-22 19:34:00 +03:00
Bossiara13	794d923bf9	feat: add webrtcvad-based smart command-end detection Replace the fixed 10s post-wake-word listen window with a VAD-driven loop. Once at least 500ms of speech have been seen, 1.2s of silence closes the window. Hard cap at 15s as a safety net. Tunable in config.py via VAD_AGGRESSIVENESS, COMMAND_END_SILENCE_MS, COMMAND_MIN_SPEECH_MS, COMMAND_MIN_LISTEN_MS, COMMAND_MAX_LISTEN_MS.	2026-04-22 19:32:30 +03:00
Bossiara13	1c1c63e5f0	Release v0.1.0 — first usable Jarvis fork (Groq + Vosk wake-word, no Picovoice)	2026-04-22 17:50:47 +03:00
Bossiara13	277921ce14	Merge feature/vosk-wakeword into dev — kills Picovoice dep	2026-04-22 17:50:38 +03:00
Bossiara13	6dc8a85bf6	Merge feature/rebrand-and-groq into dev	2026-04-22 17:50:37 +03:00
Bossiara13	dfdfd9418b	feat: tighten system prompt — explicit Jarvis persona, not Friday/Vision - Names the assistant as J.A.R.V.I.S. (acronym + MCU pre-Age-of-Ultron) - British butler tone, addresses user as «сэр» - Brief replies (1-3 sentences) - No prudish censorship	2026-04-22 17:50:32 +03:00
Bossiara13	d56a096267	chore: align VA_VER with v0.1.0 release tag	2026-04-22 17:49:26 +03:00
Bossiara13	1078b2daa3	docs: drop picovoice mentions, document WAKE_WORDS config README no longer lists PICOVOICE_TOKEN as a required key, and the configuration section explains the new WAKE_WORDS tuple.	2026-04-22 17:48:15 +03:00
Bossiara13	d8a2862ace	chore: drop pvporcupine dep and PICOVOICE_TOKEN from env template wake-word is now handled by vosk, so the picovoice access key is no longer needed. config.py already had PICOVOICE_TOKEN removed in the previous commit.	2026-04-22 17:47:22 +03:00
Bossiara13	a4b919c11e	refactor: replace porcupine wake-word with vosk grammar-constrained recognizer uses a second KaldiRecognizer with a JSON grammar of WAKE_WORDS + [unk] for the wake phase, then hands off to the full-vocab recognizer for the 10s command window. drops the pvporcupine dependency entirely.	2026-04-22 17:46:44 +03:00
Bossiara13	8019ee0baa	security: untrack dev.env, add template dev.env.example Real secrets now live in untracked dev.env (gitignored). dev.env.example holds placeholders and is the canonical template — copy it to dev.env on fresh checkout and fill in real keys.	2026-04-22 17:33:07 +03:00
Bossiara13	b3867603ff	docs: write fresh README for the fork	2026-04-22 17:32:49 +03:00
Bossiara13	c961143fd4	chore: re-save requirements.txt as plain utf-8	2026-04-22 17:32:48 +03:00
Bossiara13	9b7c08b088	chore: pin openai>=1.0 and rewrite requirements.txt as utf-8	2026-04-22 17:32:47 +03:00
Bossiara13	7f5ca81c71	feat: swap openai for Groq via openai-compatible base_url	2026-04-22 17:32:46 +03:00
Bossiara13	377016478e	chore: rebrand to Bossiara13 fork bump version 3.0 -> 0.1.0	2026-04-22 17:32:45 +03:00