feat: TTS backend abstraction + 4 'imba' features + Lua packs

Big push driven by user feedback ("делай имбу") and web research on what
voice assistants need to be the ideal:

TTS backend abstraction (P0.1)
  - new module crates/jarvis-core/src/tts/{mod,sapi,piper,silero}.rs
  - TtsBackend trait with SapiBackend (current PowerShell), PiperBackend
    (rhasspy/piper, neural quality), SileroBackend (python subprocess)
  - JARVIS_TTS env var picks (sapi|piper|silero). Auto-detect Piper if
    binary + voice present in tools/piper/. Falls back to SAPI on missing.
  - SpeakOpts {lang, detached, raw} replaces ad-hoc args. text_utils
    sanitiser applied unless raw=true.
  - llm_fallback + lua/api/tts both routed through tts::backend().
  - tools/piper/install.ps1 downloads piper.exe + ru_RU-irina-medium.onnx
    from rhasspy releases + huggingface. Smoke-test included.
  - tools/silero/silero_tts.py helper (PyTorch); rust spawns it as subprocess.

IMBA-1 Agentic LLM router
  - crates/jarvis-app/src/llm_router.rs
  - When fuzzy/intent matcher fails, LLM picks the closest command from the
    full registry. Returns JSON {command_id, confidence, reason}.
  - Threshold-gated re-dispatch via substitute phrase. JARVIS_LLM_ROUTER=1
    enables; JARVIS_LLM_ROUTER_THRESHOLD overrides 0.55 default.
  - Inserted in app.rs::execute_command between "no match" and existing
    llm_fallback chat fallback.

IMBA-2 Long-term memory
  - crates/jarvis-core/src/long_term_memory.rs — JSON store at
    APP_CONFIG_DIR/long_term_memory.json. Atomic write-through.
  - remember/recall/search/forget/all/build_context API.
  - Lua bindings: jarvis.memory.* (5 functions).
  - llm_fallback auto-injects relevant facts (substring search of prompt)
    into system message before LLM call.
  - Pack resources/commands/memory_pack/ with 4 commands: remember, recall,
    forget, list.

IMBA-3 Profile switching (work/game/sleep/driving/default)
  - crates/jarvis-core/src/profiles.rs — JSON profiles at APP_CONFIG_DIR/profiles/
    Auto-seeds 5 defaults on first run with personality + allow/deny lists +
    greetings + emoji icons.
  - active_profile.txt persists choice across restart.
  - Lua bindings: jarvis.profile.{active,set,list,allows,active_name}.
  - llm_fallback prepends profile personality to system prompt.
  - Pack resources/commands/profile_switch/ with 6 voice triggers.

IMBA-4 Multimodal screenshot + vision LLM
  - crates/jarvis-core/src/lua/api/vision.rs — gated on HTTP sandbox.
  - jarvis.vision.screenshot() captures via PowerShell System.Drawing.
  - jarvis.vision.describe(prompt?) sends base64 PNG to Groq vision model
    (default llama-3.2-11b-vision-preview, override via GROQ_VISION_MODEL).
  - Pack resources/commands/vision/ with 2 commands: describe + read_error.

P0.2 Continuous conversation grace window
  - config::CONVERSATION_GRACE_MS = 30_000.
  - app.rs: after command result, if grace_ms > 0 keep listening WITHOUT
    re-wake for the grace duration. Existing CMS_WAIT_DELAY back-dated so
    the existing timeout fires at start + grace_ms.

Tests: 24/24 jarvis-core unit tests pass (including 5 text_utils).
Build: cargo build --release -p jarvis-app and -p jarvis-gui both succeed
on Windows MSVC (VS 2026 Enterprise vcvars64).

Notes for setup:
  - Piper voice install: pwsh tools/piper/install.ps1 (downloads ~90 MB).
  - GROQ_TOKEN needed for IMBA-1 (router) and IMBA-4 (vision).
  - All features are opt-in via env vars or auto-detect; existing SAPI +
    fuzzy match path remains the default.

resources/commands/vision/command.toml

@@ -0,0 +1,30 @@
+# IMBA-4: Multimodal — screenshot + vision LLM.
+
+[[commands]]
+id = "vision.describe"
+type = "lua"
+script = "describe.lua"
+sandbox = "full"
+timeout = 30000
+
+[commands.phrases]
+ru = [
+    "что на экране", "опиши экран",
+    "посмотри на экран", "что у меня на экране",
+    "посмотри на мой экран", "глянь на экран",
+]
+en = ["what's on screen", "describe screen", "look at my screen"]
+ua = ["що на екрані", "поглянь на екран"]
+
+
+[[commands]]
+id = "vision.read_error"
+type = "lua"
+script = "read_error.lua"
+sandbox = "full"
+timeout = 30000
+
+[commands.phrases]
+ru = ["прочитай ошибку", "что за ошибка", "помоги с ошибкой"]
+en = ["read the error", "what's the error", "help with the error"]
+ua = ["прочитай помилку", "що за помилка"]

resources/commands/vision/describe.lua

@@ -0,0 +1,13 @@
+jarvis.speak("Сейчас посмотрю.")
+
+local desc = jarvis.vision.describe("Опиши коротко (1-3 предложения) что сейчас на экране. По-русски.")
+
+if not desc or desc == "" then
+    jarvis.speak("Не удалось разобрать экран. Проверь GROQ_TOKEN.")
+    jarvis.audio.play_error()
+    return { chain = false }
+end
+
+jarvis.speak(desc)
+jarvis.audio.play_ok()
+return { chain = false }

resources/commands/vision/read_error.lua

@@ -0,0 +1,18 @@
+jarvis.speak("Смотрю на ошибку.")
+
+local prompt = [[Найди на экране текст ошибки (сообщение об ошибке, stack trace, диалог об исключении).
+Прочитай ключевое сообщение и одним коротким предложением подскажи возможную причину.
+Если ошибки нет — скажи "ошибок не вижу".
+Отвечай по-русски. 1-3 предложения максимум.]]
+
+local desc = jarvis.vision.describe(prompt)
+
+if not desc or desc == "" then
+    jarvis.speak("Не получилось прочитать.")
+    jarvis.audio.play_error()
+    return { chain = false }
+end
+
+jarvis.speak(desc)
+jarvis.audio.play_ok()
+return { chain = false }