feat(voice): on-device wake-word detector with a bundled "hey hermes" model

tools/wake_word.py is a shared, engine-pluggable detector (openWakeWord default, free/local; Porcupine premium) over the existing 16 kHz sounddevice capture. A background daemon thread with pause()/resume() yields the mic during a voice turn, and reset() on every (re)start keeps a resume from re-firing on stale audio. Ships a bundled "hey hermes" openWakeWord model (tools/wakewords/, Apache-2.0) as the default; a built-in name or a custom .onnx/.tflite path still works. download_models() runs for any model so a fresh install fetches the shared feature models instead of crashing on a missing melspectrogram.onnx. The wake deps lazy-install on first use, or via the [wake] extra. Packaging ships the bundled model in both wheel and sdist, guarded by a metadata test.
2026-07-23 16:36:23 +00:00 · 2026-07-23 01:48:14 -05:00 · 2026-07-23 01:48:14 -05:00 · 8ff79323d8
commit 8ff79323d8
parent 3e163d29bd
9 changed files with 1106 additions and 41 deletions
--- a/pyproject.toml
+++ b/pyproject.toml
@ -175,6 +175,16 @@ voice = [
  "sounddevice==0.5.5",
  "numpy==2.4.3",
 ]
+# "Hey Hermes" wake word — on-device hotword detection. Both engines are
+# optional; openWakeWord (ONNX) is the free default, Porcupine the premium
+# alternative. Lazy-installed on first /wake; mirrored in tools/lazy_deps.py.
+wake = [
+  "openwakeword==0.6.0",
+  "onnxruntime==1.27.0",
+  "pvporcupine==4.0.3",
+  "sounddevice==0.5.5",
+  "numpy==2.4.3",
+]
 honcho = ["honcho-ai==2.2.0"]
 # Cloud memory providers — opt-in, lazy-installed via tools/lazy_deps.py
 # (memory.supermemory / memory.mem0) at first use. Exact pins MUST match the
@ -325,6 +335,11 @@ include = ["agent", "agent.*", "tools", "tools.*", "hermes_cli", "hermes_cli.*",
 # topic-setup image disappears. Loaded via Path(__file__).parent / "assets"
 # in gateway/status_phrases.py and gateway/run.py.
 gateway = ["assets/**/*"]
+# Bundled "hey hermes" wake-word model (tools/wakewords/). It's a binary asset,
+# not a Python module, so source builds only carry it when declared here;
+# without this the default wake word resolves to a missing model on installed
+# copies. See tools/wake_word.py.
+tools = ["wakewords/*.onnx", "wakewords/*.tflite", "wakewords/*.md"]

 [tool.pytest.ini_options]
 testpaths = ["tests"]
--- a/tests/test_packaging_metadata.py
+++ b/tests/test_packaging_metadata.py
@ -56,6 +56,24 @@ def test_faster_whisper_is_not_a_base_dependency():
    assert any(dep.startswith("faster-whisper") for dep in voice_extra)


+def test_bundled_wakeword_model_ships_in_source_builds():
+    """The default "hey hermes" wake word only works if the model ships.
+
+    ``tools/wakewords/hey_hermes.onnx`` is a binary asset (not a Python
+    module), so setuptools-built installs (uv/pip from the repo) only carry it
+    when ``[tool.setuptools.package-data]`` declares it. Without that,
+    ``wake_word.openwakeword.model: hey_hermes`` resolves to a missing file on
+    installed copies.
+    """
+    # The asset must exist for the globs to match.
+    on_disk = list((REPO_ROOT / "tools" / "wakewords").glob("*.onnx"))
+    assert on_disk, "expected a bundled wake-word model under tools/wakewords/"
+
+    data = tomllib.loads((REPO_ROOT / "pyproject.toml").read_text(encoding="utf-8"))
+    tools_pkg_data = data["tool"]["setuptools"]["package-data"].get("tools", [])
+    assert any(g.endswith(".onnx") for g in tools_pkg_data), (
+        "pyproject package-data 'tools' must ship wakewords/*.onnx"
+    )
 # Minimum non-vulnerable Starlette: CVE-2026-48710 ("BadHost") was fixed in
 # 1.0.1. Anything below that lets a malformed Host header desync
 # ``request.url.path`` from the dispatched ASGI path, bypassing path-based
--- a/tests/tools/test_wake_word.py
+++ b/tests/tools/test_wake_word.py
@ -0,0 +1,326 @@
+"""Tests for tools.wake_word — the "Hey Hermes" hotword detector.
+
+No live audio or network: the sounddevice import is faked, engines are stubbed,
+and lazy-dep availability is monkeypatched. Covers config resolution, engine
+dispatch, the requirements probe, the detector fire/cooldown loop, and the
+process-wide singleton lifecycle.
+"""
+
+import os
+import sys
+import time
+import types
+
+import pytest
+
+import tools.wake_word as ww
+
+
+# ── Config helpers ───────────────────────────────────────────────────────
+
+
+def test_config_defaults_and_clamping():
+    assert ww._provider({}) == "openwakeword"
+    assert ww._provider({"provider": "Porcupine"}) == "porcupine"
+    assert ww._sensitivity({"sensitivity": 5}) == 1.0
+    assert ww._sensitivity({"sensitivity": -1}) == 0.0
+    assert ww._sensitivity({"sensitivity": "nope"}) == 0.5
+    assert ww.wake_phrase({"phrase": "hey jarvis"}) == "hey jarvis"
+    assert ww.wake_phrase({}) == "hey hermes"
+
+
+def test_wake_surface_enabled_gate():
+    # Disabled → never, regardless of surface.
+    assert ww.wake_surface_enabled("cli", {"enabled": False, "surface": "cli"}) is False
+    # auto → every surface.
+    for s in ("cli", "tui", "gui"):
+        assert ww.wake_surface_enabled(s, {"enabled": True, "surface": "auto"}) is True
+    # Pinned surface → only that one.
+    cfg = {"enabled": True, "surface": "tui"}
+    assert ww.wake_surface_enabled("tui", cfg) is True
+    assert ww.wake_surface_enabled("cli", cfg) is False
+    assert ww.wake_surface_enabled("gui", cfg) is False
+    # Missing/blank surface defaults to auto.
+    assert ww.wake_surface_enabled("gui", {"enabled": True}) is True
+
+
+def test_looks_like_path():
+    assert ww._looks_like_path("models/hey_hermes.onnx")
+    assert ww._looks_like_path("custom.ppn")
+    assert not ww._looks_like_path("hey_jarvis")
+
+
+def test_load_wake_word_config_is_a_dict_with_defaults():
+    # Wired into DEFAULT_CONFIG, so a real load returns the section shape.
+    cfg = ww.load_wake_word_config()
+    assert isinstance(cfg, dict)
+    assert cfg.get("enabled") is False
+    assert cfg.get("provider") == "openwakeword"
+
+
+def test_load_wake_word_config_guards_non_dict(monkeypatch):
+    monkeypatch.setattr(
+        "hermes_cli.config.load_config", lambda: {"wake_word": "oops"}
+    )
+    assert ww.load_wake_word_config() == {}
+
+
+# ── Engine dispatch ──────────────────────────────────────────────────────
+
+
+def test_build_engine_dispatch(monkeypatch):
+    monkeypatch.setattr(ww, "_OpenWakeWordEngine", lambda cfg: "oww")
+    monkeypatch.setattr(ww, "_PorcupineEngine", lambda cfg: "pv")
+    assert ww._build_engine({"provider": "openwakeword"}) == "oww"
+    assert ww._build_engine({"provider": "porcupine"}) == "pv"
+    with pytest.raises(ValueError):
+        ww._build_engine({"provider": "bogus"})
+
+
+# ── Requirements probe ───────────────────────────────────────────────────
+
+
+def test_requirements_openwakeword_available(monkeypatch):
+    monkeypatch.setattr(ww, "_audio_available", lambda: True)
+    monkeypatch.setattr("tools.lazy_deps.is_available", lambda f: True)
+    r = ww.check_wake_word_requirements(
+        {"provider": "openwakeword", "phrase": "hey hermes"}
+    )
+    assert r["available"] is True
+    assert r["provider"] == "openwakeword"
+    assert r["phrase"] == "hey hermes"
+
+
+def test_requirements_porcupine_needs_access_key(monkeypatch):
+    monkeypatch.delenv("PORCUPINE_ACCESS_KEY", raising=False)
+    monkeypatch.setattr(ww, "_audio_available", lambda: True)
+    monkeypatch.setattr("tools.lazy_deps.is_available", lambda f: True)
+    r = ww.check_wake_word_requirements({"provider": "porcupine"})
+    assert r["available"] is False
+    assert r["access_key_set"] is False
+    assert "PORCUPINE_ACCESS_KEY" in r["hint"]
+
+
+def test_requirements_unavailable_without_audio(monkeypatch):
+    monkeypatch.setattr(ww, "_audio_available", lambda: False)
+    monkeypatch.setattr("tools.lazy_deps.is_available", lambda f: True)
+    r = ww.check_wake_word_requirements({"provider": "openwakeword"})
+    assert r["available"] is False
+    assert r["audio_available"] is False
+
+
+# ── openWakeWord engine (base-model fetch) ───────────────────────────────
+
+
+def _install_fake_openwakeword(monkeypatch):
+    """Swap in a fake ``openwakeword`` so the engine builds with no network.
+
+    Returns a ``calls`` dict recording every ``download_models`` invocation.
+    """
+    calls = {"download": []}
+
+    class _FakeModel:
+        def __init__(self, wakeword_models, inference_framework="onnx"):
+            self.wakeword_models = list(wakeword_models)
+            self.models = {"hey_hermes": object()}
+
+        def predict(self, frame):
+            return {"hey_hermes": 0.0}
+
+        def reset(self):
+            pass
+
+    oww = types.ModuleType("openwakeword")
+    oww.utils = types.SimpleNamespace(
+        download_models=lambda names=[]: calls["download"].append(list(names))
+    )
+    model_mod = types.ModuleType("openwakeword.model")
+    model_mod.Model = _FakeModel
+
+    monkeypatch.setitem(sys.modules, "openwakeword", oww)
+    monkeypatch.setitem(sys.modules, "openwakeword.model", model_mod)
+    monkeypatch.setattr("tools.lazy_deps.ensure", lambda *a, **k: None)
+    return calls
+
+
+def test_openwakeword_ensures_base_models_for_custom_path(monkeypatch):
+    # Regression: a custom ``.onnx`` path used to skip download_models entirely,
+    # so a fresh install crashed at load time on a missing melspectrogram.onnx.
+    # The base feature models must be ensured for a custom path too.
+    calls = _install_fake_openwakeword(monkeypatch)
+    eng = ww._OpenWakeWordEngine(
+        {"provider": "openwakeword", "openwakeword": {"model": "/models/hey_hermes.onnx"}}
+    )
+    assert calls["download"] == [["/models/hey_hermes.onnx"]]
+    assert eng._labels == ["hey_hermes"]
+
+
+def test_openwakeword_fetches_builtin_by_name(monkeypatch):
+    calls = _install_fake_openwakeword(monkeypatch)
+    ww._OpenWakeWordEngine({"provider": "openwakeword", "openwakeword": {"model": "hey_jarvis"}})
+    assert calls["download"] == [["hey_jarvis"]]
+
+
+def test_bundled_hey_hermes_model_ships_on_disk():
+    # The "hey hermes" wake word works out of the box only if the model is
+    # actually bundled. Both framework artifacts must exist and be non-trivial.
+    for framework in ("onnx", "tflite"):
+        path = ww._bundled_wakeword_path(framework)
+        assert os.path.exists(path), path
+        assert os.path.getsize(path) > 1024, path
+
+
+@pytest.mark.parametrize("model_value", [None, "", "hey_hermes", "hey hermes", "HEY_HERMES"])
+def test_openwakeword_default_resolves_to_bundled_model(monkeypatch, model_value):
+    # The default (and any "hey_hermes" alias) must load the bundled file, not be
+    # passed through as a bogus built-in name that openWakeWord can't resolve.
+    calls = _install_fake_openwakeword(monkeypatch)
+    sub = {} if model_value is None else {"model": model_value}
+    ww._OpenWakeWordEngine({"provider": "openwakeword", "openwakeword": sub})
+    (downloaded,) = calls["download"]
+    assert downloaded == [ww._bundled_wakeword_path("onnx")]
+
+
+def test_openwakeword_bundled_model_matches_framework(monkeypatch):
+    calls = _install_fake_openwakeword(monkeypatch)
+    ww._OpenWakeWordEngine(
+        {"provider": "openwakeword", "openwakeword": {"inference_framework": "tflite"}}
+    )
+    (downloaded,) = calls["download"]
+    assert downloaded == [ww._bundled_wakeword_path("tflite")]
+    assert downloaded[0].endswith(".tflite")
+
+
+# ── Detector loop ────────────────────────────────────────────────────────
+
+
+class _FakeStream:
+    """Always-readable input stream that yields trivial frames."""
+
+    def __init__(self, **_kw):
+        self.closed = False
+
+    def start(self):
+        pass
+
+    def read(self, n):
+        time.sleep(0.01)
+        return [0] * n, False
+
+    def stop(self):
+        pass
+
+    def close(self):
+        self.closed = True
+
+
+class _FakeEngine:
+    frame_length = 4
+
+    def __init__(self, fire=True):
+        self._fire = fire
+        self.closed = False
+        self.resets = 0
+
+    def process(self, frame):
+        return self._fire
+
+    def reset(self):
+        self.resets += 1
+
+    def close(self):
+        self.closed = True
+
+
+def _fake_audio(monkeypatch):
+    fake_sd = types.SimpleNamespace(InputStream=lambda **kw: _FakeStream(**kw))
+    monkeypatch.setattr(ww, "_import_audio", lambda: (fake_sd, None))
+
+
+def test_detector_fires_once_under_cooldown(monkeypatch):
+    _fake_audio(monkeypatch)
+    calls = []
+    eng = _FakeEngine(fire=True)
+    det = ww.WakeWordDetector(eng, lambda: calls.append(1), cooldown=10.0)
+    det.start()
+    time.sleep(0.25)
+    det.stop()
+    assert len(calls) == 1  # high cooldown suppresses repeats
+    assert eng.closed is True
+    assert det.running is False
+
+
+def test_detector_refires_after_cooldown(monkeypatch):
+    _fake_audio(monkeypatch)
+    calls = []
+    det = ww.WakeWordDetector(_FakeEngine(fire=True), lambda: calls.append(1), cooldown=0.05)
+    det.start()
+    time.sleep(0.3)
+    det.stop()
+    assert len(calls) >= 2
+
+
+def test_detector_no_fire_when_engine_quiet(monkeypatch):
+    _fake_audio(monkeypatch)
+    calls = []
+    det = ww.WakeWordDetector(_FakeEngine(fire=False), lambda: calls.append(1))
+    det.start()
+    time.sleep(0.15)
+    det.stop()
+    assert calls == []
+
+
+def test_detector_resets_engine_on_each_start(monkeypatch):
+    # Clearing the engine buffer on (re)start is what stops a resume right after
+    # a voice turn from re-firing on stale audio (the runaway wake loop).
+    _fake_audio(monkeypatch)
+    eng = _FakeEngine(fire=False)
+    det = ww.WakeWordDetector(eng, lambda: None)
+    det.start()
+    time.sleep(0.05)
+    det.pause()
+    det.resume()
+    time.sleep(0.05)
+    det.stop()
+    assert eng.resets >= 2  # initial start + resume
+
+
+def test_detector_pause_resume(monkeypatch):
+    _fake_audio(monkeypatch)
+    det = ww.WakeWordDetector(_FakeEngine(fire=False), lambda: None)
+    det.start()
+    time.sleep(0.05)
+    assert det.running is True
+    det.pause()
+    assert det.running is False
+    det.resume()
+    time.sleep(0.05)
+    assert det.running is True
+    det.stop()
+    assert det.running is False
+
+
+# ── Singleton lifecycle ──────────────────────────────────────────────────
+
+
+def test_singleton_lifecycle(monkeypatch):
+    _fake_audio(monkeypatch)
+    monkeypatch.setattr(ww, "_build_engine", lambda cfg: _FakeEngine(fire=False))
+
+    assert ww.is_listening() is False
+    det = ww.start_listening(lambda: None, config={})
+    time.sleep(0.05)
+    assert ww.is_listening() is True
+
+    # Re-entrant start returns the same detector and re-arms it.
+    det2 = ww.start_listening(lambda: None, config={})
+    assert det2 is det
+
+    ww.pause_listening()
+    assert ww.is_listening() is False
+    ww.resume_listening()
+    time.sleep(0.05)
+    assert ww.is_listening() is True
+
+    ww.stop_listening()
+    assert ww.is_listening() is False
--- a/tools/lazy_deps.py
+++ b/tools/lazy_deps.py
@ -135,6 +135,21 @@ LAZY_DEPS: dict[str, tuple[str, ...]] = {
        "numpy==2.4.3",
    ),

+    # ─── Wake word ("Hey Hermes") engines ──────────────────────────────────
+    # Keep in sync with the `wake` extra in pyproject.toml. openWakeWord is the
+    # free, local default (ONNX runtime); Porcupine is the premium engine.
+    "wake.openwakeword": (
+        "openwakeword==0.6.0",
+        "onnxruntime==1.27.0",
+        "sounddevice==0.5.5",
+        "numpy==2.4.3",
+    ),
+    "wake.porcupine": (
+        "pvporcupine==4.0.3",
+        "sounddevice==0.5.5",
+        "numpy==2.4.3",
+    ),
+
    # ─── Image generation backends ─────────────────────────────────────────
    "image.fal": ("fal-client==0.13.1",),

--- a/tools/wake_word.py
+++ b/tools/wake_word.py
@ -0,0 +1,482 @@
+"""Wake-word ("Hey Hermes") detection — hands-free session trigger.
+
+A lightweight, always-on hotword listener that fires a callback when a wake
+phrase is spoken — the "Hey Siri" / "Alexa" pattern. Shared by the CLI, TUI, and
+desktop GUI (one of them owns it, gated by ``wake_surface_enabled``): say the
+wake word, Hermes opens a fresh session and captures voice via the existing
+pipeline, then answers.
+
+Two engines, both fully on-device (no audio leaves the machine for detection):
+
+* **openwakeword** (default, free, no API key) — loads an ONNX model. Defaults
+  to the bundled "hey hermes" model (``tools/wakewords/``) so the wake word
+  works out of the box; or point ``wake_word.openwakeword.model`` at a built-in
+  name (``hey_jarvis``, ``alexa``, …) or a custom ``.onnx`` for another phrase.
+* **porcupine** (premium) — Picovoice's engine. Needs ``PORCUPINE_ACCESS_KEY``;
+  supports built-in keywords and custom ``.ppn`` files from the Picovoice
+  Console.
+
+Audio capture reuses the same 16 kHz mono int16 ``sounddevice`` path as voice
+mode. The detector runs on its own daemon thread; callers ``pause()`` it while a
+voice turn holds the microphone and ``resume()`` it once the system is idle
+again (two input streams on one device is unreliable cross-platform).
+
+Nothing here mutates agent context or the prompt cache — on wake we hand a plain
+string to the caller, exactly like a voice transcript.
+"""
+
+from __future__ import annotations
+
+import logging
+import os
+import threading
+import time
+from typing import Any, Callable, Dict, Optional
+
+logger = logging.getLogger(__name__)
+
+# 16 kHz mono int16 — Whisper-native and what both engines expect.
+SAMPLE_RATE = 16000
+
+# Minimum gap between two consecutive wake fires, so one "hey hermes" can't
+# retrigger across several frames while the caller is still reacting.
+_FIRE_COOLDOWN_SECONDS = 2.0
+
+
+# ---------------------------------------------------------------------------
+# Config
+# ---------------------------------------------------------------------------
+
+_DEFAULTS: Dict[str, Any] = {
+    "enabled": False,
+    "surface": "auto",
+    "provider": "openwakeword",
+    "phrase": "hey hermes",
+    "sensitivity": 0.5,
+    "start_new_session": True,
+}
+
+# Bundled "hey hermes" model (tools/wakewords/) — the default, so the wake word
+# works out of the box. Config names in _ALIASES resolve to it, not a built-in.
+_BUNDLED_MODEL_NAME = "hey_hermes"
+_BUNDLED_MODEL_ALIASES = frozenset({"", "hey_hermes", "hey hermes", "hermes"})
+
+
+def _bundled_wakeword_path(framework: str = "onnx") -> str:
+    """Path to the shipped hey_hermes model (.onnx/.tflite) for ``framework``."""
+    ext = "tflite" if str(framework).strip().lower() == "tflite" else "onnx"
+    return os.path.join(os.path.dirname(__file__), "wakewords", f"{_BUNDLED_MODEL_NAME}.{ext}")
+
+
+def load_wake_word_config() -> Dict[str, Any]:
+    """Return the ``wake_word`` config section, shape-guarded to a dict."""
+    try:
+        from hermes_cli.config import load_config
+
+        cfg = load_config().get("wake_word")
+    except Exception:
+        cfg = None
+    return cfg if isinstance(cfg, dict) else {}
+
+
+def _get(cfg: Dict[str, Any], key: str) -> Any:
+    val = cfg.get(key, _DEFAULTS.get(key))
+    return _DEFAULTS.get(key) if val is None else val
+
+
+def _provider(cfg: Dict[str, Any]) -> str:
+    return str(_get(cfg, "provider")).strip().lower() or "openwakeword"
+
+
+def _sensitivity(cfg: Dict[str, Any]) -> float:
+    raw = _get(cfg, "sensitivity")
+    try:
+        s = float(raw)
+    except (TypeError, ValueError):
+        s = 0.5
+    return min(max(s, 0.0), 1.0)
+
+
+def wake_phrase(cfg: Optional[Dict[str, Any]] = None) -> str:
+    """Human-facing wake phrase label (purely cosmetic; engine keys detection)."""
+    cfg = cfg if cfg is not None else load_wake_word_config()
+    return str(_get(cfg, "phrase")) or "hey hermes"
+
+
+def wake_surface_enabled(surface: str, cfg: Optional[Dict[str, Any]] = None) -> bool:
+    """Should ``surface`` (``cli`` / ``tui`` / ``gui``) host the listener?
+
+    True when the wake word is enabled and the configured ``surface`` is either
+    ``auto`` or this exact surface — the single gate every surface consults so
+    only one place owns the wake word and the new session it opens.
+    """
+    cfg = cfg if cfg is not None else load_wake_word_config()
+    if not cfg.get("enabled"):
+        return False
+    want = str(_get(cfg, "surface")).strip().lower() or "auto"
+    return want == "auto" or want == surface.strip().lower()
+
+
+# ---------------------------------------------------------------------------
+# Audio capture (lazy — never import sounddevice at module load)
+# ---------------------------------------------------------------------------
+
+def _import_audio():
+    import numpy as np
+    import sounddevice as sd
+
+    return sd, np
+
+
+def _audio_available() -> bool:
+    try:
+        _import_audio()
+        return True
+    except (ImportError, OSError):
+        return False
+
+
+# ---------------------------------------------------------------------------
+# Engines
+# ---------------------------------------------------------------------------
+
+class _Engine:
+    """Minimal hotword-engine contract: feed int16 frames, get a bool."""
+
+    frame_length: int = 1280  # 80 ms at 16 kHz
+
+    def process(self, frame) -> bool:  # frame: 1-D int16 ndarray
+        raise NotImplementedError
+
+    def reset(self) -> None:
+        """Clear any internal audio/feature buffer (called on every (re)start)."""
+        pass
+
+    def close(self) -> None:
+        pass
+
+
+def _looks_like_path(value: str) -> bool:
+    return (
+        os.sep in value
+        or value.endswith((".onnx", ".tflite", ".ppn"))
+        or os.path.exists(value)
+    )
+
+
+class _OpenWakeWordEngine(_Engine):
+    """openWakeWord — free, local ONNX hotword detection."""
+
+    # openWakeWord recommends 80 ms frames (1280 samples) for efficiency.
+    frame_length = 1280
+
+    def __init__(self, cfg: Dict[str, Any]):
+        from tools import lazy_deps
+
+        lazy_deps.ensure("wake.openwakeword", prompt=False)
+
+        import openwakeword
+        from openwakeword.model import Model
+
+        sub = cfg.get("openwakeword") if isinstance(cfg.get("openwakeword"), dict) else {}
+        model_ref = str(sub.get("model") or _BUNDLED_MODEL_NAME).strip()
+        framework = str(sub.get("inference_framework") or "onnx").strip().lower()
+        self._threshold = _sensitivity(cfg)
+
+        # Default (or explicit "hey_hermes") → the bundled model; a built-in name
+        # or custom path is used as-is.
+        if model_ref.lower() in _BUNDLED_MODEL_ALIASES:
+            model_ref = _bundled_wakeword_path(framework)
+
+        # openWakeWord needs its shared feature models (melspectrogram + embedding)
+        # for ANY model — download_models() fetches those first on every call, so a
+        # custom path must call it too, else a fresh install crashes on a missing
+        # melspectrogram.onnx. A built-in name additionally pulls that pretrained
+        # model; a path matches nothing in the catalog and is a no-op beyond base.
+        try:
+            openwakeword.utils.download_models([model_ref])
+        except Exception as e:  # pragma: no cover - network/path dependent
+            logger.debug("openwakeword base-model fetch skipped: %s", e)
+
+        models = [model_ref]
+        self._model = Model(wakeword_models=models, inference_framework=framework)
+        self._labels = list(self._model.models.keys())
+
+    def process(self, frame) -> bool:
+        scores = self._model.predict(frame)
+        return any(score >= self._threshold for score in scores.values())
+
+    def reset(self) -> None:
+        # Clears openWakeWord's rolling feature/prediction buffer so stale audio
+        # captured before a pause can't re-fire the moment we resume.
+        try:
+            self._model.reset()
+        except Exception:
+            pass
+
+    def close(self) -> None:
+        self.reset()
+
+
+class _PorcupineEngine(_Engine):
+    """Picovoice Porcupine — premium, on-device, needs an access key."""
+
+    def __init__(self, cfg: Dict[str, Any]):
+        from tools import lazy_deps
+
+        lazy_deps.ensure("wake.porcupine", prompt=False)
+
+        import pvporcupine
+
+        access_key = (os.getenv("PORCUPINE_ACCESS_KEY") or "").strip()
+        if not access_key:
+            raise RuntimeError(
+                "Porcupine wake word requires PORCUPINE_ACCESS_KEY "
+                "(get a free key at https://console.picovoice.ai)."
+            )
+
+        sub = cfg.get("porcupine") if isinstance(cfg.get("porcupine"), dict) else {}
+        keyword = str(sub.get("keyword") or "jarvis").strip()
+        sensitivity = _sensitivity(cfg)
+
+        kwargs: Dict[str, Any] = {"access_key": access_key, "sensitivities": [sensitivity]}
+        if _looks_like_path(keyword):
+            kwargs["keyword_paths"] = [keyword]
+        else:
+            kwargs["keywords"] = [keyword]
+
+        self._porcupine = pvporcupine.create(**kwargs)
+        self.frame_length = self._porcupine.frame_length
+
+    def process(self, frame) -> bool:
+        # pvporcupine wants a plain list/sequence of int16 samples.
+        return self._porcupine.process(frame) >= 0
+
+    def close(self) -> None:
+        try:
+            self._porcupine.delete()
+        except Exception:
+            pass
+
+
+def _build_engine(cfg: Dict[str, Any]) -> _Engine:
+    provider = _provider(cfg)
+    if provider == "porcupine":
+        return _PorcupineEngine(cfg)
+    if provider in ("openwakeword", "oww", "local"):
+        return _OpenWakeWordEngine(cfg)
+    raise ValueError(f"Unknown wake_word provider: {provider!r}")
+
+
+# ---------------------------------------------------------------------------
+# Requirements probe (for /wake status + enable path)
+# ---------------------------------------------------------------------------
+
+def check_wake_word_requirements(cfg: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
+    """Report whether wake-word detection can run, with a remediation hint."""
+    cfg = cfg if cfg is not None else load_wake_word_config()
+    provider = _provider(cfg)
+    from tools import lazy_deps
+
+    feature = "wake.porcupine" if provider == "porcupine" else "wake.openwakeword"
+    deps_ok = lazy_deps.is_available(feature)
+    audio_ok = _audio_available()
+    key_ok = True
+    hint = ""
+
+    if provider == "porcupine" and not (os.getenv("PORCUPINE_ACCESS_KEY") or "").strip():
+        key_ok = False
+        hint = "Set PORCUPINE_ACCESS_KEY (free key at https://console.picovoice.ai)."
+    elif not deps_ok:
+        hint = lazy_deps.feature_install_command(feature) or ""
+    elif not audio_ok:
+        hint = "Microphone capture needs sounddevice + numpy and a working audio device."
+
+    return {
+        "available": audio_ok and (deps_ok or lazy_deps._allow_lazy_installs()) and key_ok,
+        "provider": provider,
+        "deps_available": deps_ok,
+        "audio_available": audio_ok,
+        "access_key_set": key_ok,
+        "phrase": wake_phrase(cfg),
+        "hint": hint,
+    }
+
+
+# ---------------------------------------------------------------------------
+# Detector
+# ---------------------------------------------------------------------------
+
+class WakeWordDetector:
+    """Background hotword listener. Fires ``on_wake()`` when the phrase is heard.
+
+    The engine is built once and kept alive across pause/resume; only the audio
+    stream + reader thread cycle, so toggling the mic for a voice turn is cheap.
+    """
+
+    def __init__(self, engine: _Engine, on_wake: Callable[[], None],
+                 cooldown: float = _FIRE_COOLDOWN_SECONDS):
+        self.engine = engine
+        self.on_wake = on_wake
+        self.cooldown = cooldown
+        self._thread: Optional[threading.Thread] = None
+        self._stop = threading.Event()
+        self._last_fire = 0.0
+        self._lock = threading.Lock()
+
+    @property
+    def running(self) -> bool:
+        t = self._thread
+        return t is not None and t.is_alive()
+
+    def start(self) -> None:
+        """Open the mic and begin listening. Idempotent."""
+        with self._lock:
+            if self._thread is not None and self._thread.is_alive():
+                return
+            self._stop.clear()
+            self._thread = threading.Thread(
+                target=self._run, daemon=True, name="wake-word"
+            )
+            self._thread.start()
+
+    # pause/resume keep the engine; stop tears it down.
+    def pause(self) -> None:
+        self._halt_thread()
+
+    def resume(self) -> None:
+        self.start()
+
+    def stop(self) -> None:
+        self._halt_thread()
+        self.engine.close()
+
+    def _halt_thread(self) -> None:
+        with self._lock:
+            t, self._thread = self._thread, None
+        if t is not None and t is not threading.current_thread():
+            self._stop.set()
+            t.join(timeout=2.0)
+
+    def _run(self) -> None:
+        try:
+            sd, _ = _import_audio()
+        except (ImportError, OSError) as e:
+            logger.error("wake word: audio libraries unavailable: %s", e)
+            return
+
+        frame_length = self.engine.frame_length
+        try:
+            stream = sd.InputStream(
+                samplerate=SAMPLE_RATE,
+                channels=1,
+                dtype="int16",
+                blocksize=frame_length,
+            )
+            stream.start()
+        except Exception as e:
+            logger.error("wake word: failed to open microphone: %s", e)
+            return
+
+        # Drop any buffered audio/feature state so a resume right after a voice
+        # turn can't immediately re-fire on audio captured before the pause (the
+        # wake → voice → resume → wake runaway loop).
+        try:
+            self.engine.reset()
+        except Exception:
+            pass
+
+        logger.info("wake word: listening (frame=%d, rate=%d)", frame_length, SAMPLE_RATE)
+        try:
+            while not self._stop.is_set():
+                try:
+                    data, _overflow = stream.read(frame_length)
+                except Exception as e:
+                    logger.warning("wake word: stream read error: %s", e)
+                    break
+                frame = data[:, 0] if getattr(data, "ndim", 1) == 2 else data
+                try:
+                    fired = self.engine.process(frame)
+                except Exception as e:
+                    logger.debug("wake word: engine error: %s", e)
+                    continue
+                if fired:
+                    now = time.monotonic()
+                    if now - self._last_fire >= self.cooldown:
+                        self._last_fire = now
+                        logger.info("wake word: phrase detected — firing callback")
+                        try:
+                            self.on_wake()
+                        except Exception as e:
+                            logger.warning("wake word callback failed: %s", e)
+                    else:
+                        logger.debug("wake word: detection within cooldown — ignored")
+        finally:
+            try:
+                stream.stop()
+                stream.close()
+            except Exception:
+                pass
+            logger.info("wake word: stream closed")
+
+
+# ---------------------------------------------------------------------------
+# Process-wide singleton (mirrors hermes_cli.voice's continuous API)
+# ---------------------------------------------------------------------------
+
+_detector: Optional[WakeWordDetector] = None
+_detector_lock = threading.Lock()
+
+
+def start_listening(
+    on_wake: Callable[[], None],
+    *,
+    config: Optional[Dict[str, Any]] = None,
+) -> WakeWordDetector:
+    """Build (once) and start the wake-word detector. Idempotent.
+
+    Raises if engine construction fails (missing deps / access key / model);
+    callers should probe :func:`check_wake_word_requirements` first.
+    """
+    global _detector
+    with _detector_lock:
+        if _detector is not None:
+            _detector.on_wake = on_wake
+            _detector.resume()
+            return _detector
+        cfg = config if config is not None else load_wake_word_config()
+        engine = _build_engine(cfg)
+        _detector = WakeWordDetector(engine, on_wake)
+    _detector.start()
+    return _detector
+
+
+def pause_listening() -> None:
+    """Release the microphone without tearing down the engine."""
+    with _detector_lock:
+        det = _detector
+    if det is not None:
+        det.pause()
+
+
+def resume_listening() -> None:
+    """Re-open the microphone after a pause. No-op if not initialised."""
+    with _detector_lock:
+        det = _detector
+    if det is not None:
+        det.resume()
+
+
+def stop_listening() -> None:
+    """Fully stop and discard the detector (closes the engine)."""
+    global _detector
+    with _detector_lock:
+        det, _detector = _detector, None
+    if det is not None:
+        det.stop()
+
+
+def is_listening() -> bool:
+    with _detector_lock:
+        det = _detector
+    return det is not None and det.running
--- a/tools/wakewords/README.md
+++ b/tools/wakewords/README.md
@ -0,0 +1,20 @@
+# Bundled wake-word models
+
+`hey_hermes.onnx` / `hey_hermes.tflite` — the on-device "Hey Hermes" hotword
+model. This is the default detector for the wake word feature (see
+`website/docs/user-guide/features/wake-word.md`); no training or setup is
+required to say "hey hermes".
+
+- **Engine:** [openWakeWord](https://github.com/dscripka/openWakeWord) (Apache-2.0).
+- **Provenance:** trained with the openWakeWord training pipeline (synthetic
+  TTS-generated speech), which produces both the `.onnx` and `.tflite` artifacts.
+  Redistribution is permitted under the openWakeWord license.
+- **Label:** the model registers as `hey_hermes` (matches the filename).
+- **Runtime:** openWakeWord's shared feature-extraction models (melspectrogram +
+  embedding) are NOT bundled here — they are fetched once on first use by
+  `tools/wake_word.py` via `openwakeword.utils.download_models()`.
+
+To use a different phrase, train your own model and point
+`wake_word.openwakeword.model` at its path, or set a built-in openWakeWord name
+(`hey_jarvis`, `alexa`, `hey_mycroft`, …). See the wake-word docs for the
+training guide.
--- a/tools/wakewords/hey_hermes.onnx
+++ b/tools/wakewords/hey_hermes.onnx
--- a/tools/wakewords/hey_hermes.tflite
+++ b/tools/wakewords/hey_hermes.tflite
--- a/uv.lock
+++ b/uv.lock
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