feat(voice): bundle the trained "hey hermes" model as the out-of-the-box default

From #53378: ships hey_hermes.onnx/.tflite (openWakeWord pipeline, Apache-2.0) under tools/wakewords/, resolves the default (and hey_hermes aliases) to the bundled file, ensures openWakeWord base feature models are fetched for custom paths too, and updates config defaults + docs from hey_jarvis to hey hermes.
2026-07-29 18:46:59 +00:00 · 2026-07-23 20:15:29 -07:00 · 2026-07-23 20:15:29 -07:00 · 9f84bc30bd
commit 9f84bc30bd
parent 5839aad13d
9 changed files with 476 additions and 158 deletions
--- a/hermes_cli/config.py
+++ b/hermes_cli/config.py
@ -2381,14 +2381,15 @@ DEFAULT_CONFIG = {
        "enabled": False,
        "surface": "auto",            # eligible surface: "auto" (first claimant) | "cli" | "tui" | "gui"
        "provider": "openwakeword",   # "openwakeword" (free, local) | "porcupine" (premium; needs PORCUPINE_ACCESS_KEY)
-        "phrase": "hey jarvis",       # cosmetic label only; detection is keyed by the engine model/keyword below
+        "phrase": "hey hermes",       # cosmetic label only; detection is keyed by the engine model/keyword below
        "sensitivity": 0.5,           # 0.0-1.0 detection threshold (higher = stricter)
        "start_new_session": True,    # start a fresh session on wake vs. continue the current one
        "openwakeword": {
-            # Built-in model name ("hey_jarvis", "alexa", "hey_mycroft", ...) or
-            # a path to a custom .onnx/.tflite model. Train a "hey hermes" model
-            # and point this at it — see the wake-word docs.
-            "model": "hey_jarvis",
+            # "hey_hermes" (the bundled, works-out-of-the-box default) OR a
+            # built-in openWakeWord name ("hey_jarvis", "alexa", "hey_mycroft",
+            # ...) OR a path to a custom .onnx/.tflite model for another phrase.
+            # See the wake-word docs for the custom-model training guide.
+            "model": "hey_hermes",
            "inference_framework": "onnx",  # "onnx" | "tflite"
        },
        "porcupine": {
--- a/tests/tools/test_wake_word.py
+++ b/tests/tools/test_wake_word.py
@ -7,6 +7,8 @@ process-wide singleton lifecycle.
 """

 import multiprocessing
+import os
+import sys
 import threading
 import time
 import types
@ -27,7 +29,7 @@ def test_config_defaults_and_clamping():
    assert ww._sensitivity({"sensitivity": -1}) == 0.0
    assert ww._sensitivity({"sensitivity": "nope"}) == 0.5
    assert ww.wake_phrase({"phrase": "hey hermes"}) == "hey hermes"
-    assert ww.wake_phrase({}) == "hey jarvis"
+    assert ww.wake_phrase({}) == "hey hermes"


 def test_wake_surface_enabled_gate():
@ -110,6 +112,88 @@ def test_requirements_unavailable_without_audio(monkeypatch):
    assert r["audio_available"] is False


+# ── openWakeWord engine (bundled model + 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 ────────────────────────────────────────────────────────


--- a/tools/wake_word.py
+++ b/tools/wake_word.py
@ -8,10 +8,10 @@ pipeline, then answers.

 Two engines, both fully on-device (no audio leaves the machine for detection):

-* **openwakeword** (default, free, no API key) — loads a pretrained or custom
-  ONNX model. Ships with ``hey_jarvis``, ``alexa``, ``hey_mycroft``, … ; point
-  ``wake_word.openwakeword.model`` at a custom ``.onnx`` to detect a real
-  "hey hermes" (training guide in the wake-word docs).
+* **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.
@ -57,11 +57,22 @@ _DEFAULTS: Dict[str, Any] = {
    "enabled": False,
    "surface": "auto",
    "provider": "openwakeword",
-    "phrase": "hey jarvis",
+    "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."""
@ -95,7 +106,7 @@ def _sensitivity(cfg: Dict[str, Any]) -> float:
 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 jarvis"
+    return str(_get(cfg, "phrase")) or "hey hermes"


 def wake_surface_enabled(surface: str, cfg: Optional[Dict[str, Any]] = None) -> bool:
@ -174,20 +185,25 @@ class _OpenWakeWordEngine(_Engine):
        from openwakeword.model import Model

        sub = cfg.get("openwakeword") if isinstance(cfg.get("openwakeword"), dict) else {}
-        model_ref = str(sub.get("model") or "hey_jarvis").strip()
+        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)

-        if _looks_like_path(model_ref):
-            models = [model_ref]
-        else:
-            # Pretrained name (e.g. "hey_jarvis"). Best-effort one-time fetch
-            # of the bundled models; harmless if already present / offline.
-            try:
-                openwakeword.utils.download_models([model_ref])
-            except Exception as e:  # pragma: no cover - network/path dependent
-                logger.debug("openwakeword model download skipped: %s", e)
-            models = [model_ref]
+        # 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 model download skipped: %s", e)
+        models = [model_ref]

        self._model = Model(wakeword_models=models, inference_framework=framework)
        self._labels = list(self._model.models.keys())
--- 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/ui-tui/src/tests/createGatewayEventHandler.test.ts
+++ b/ui-tui/src/tests/createGatewayEventHandler.test.ts
@ -779,7 +779,6 @@ describe('createGatewayEventHandler', () => {
    expect(ctx.gateway.rpc).not.toHaveBeenCalled()
  })

-<<<<<<< HEAD
  it('picks the polarity-matching paired palette from gateway.ready skins', async () => {
    const appended: Msg[] = []

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--- a/website/docs/user-guide/features/wake-word.md
+++ b/website/docs/user-guide/features/wake-word.md
@ -32,14 +32,18 @@ It is **off by default** — nothing listens until you turn it on.

 | Engine | Cost | API key | Notes |
 |--------|------|---------|-------|
-| **openWakeWord** (default) | Free | None | Local ONNX models. Ships with `hey_jarvis`, `alexa`, `hey_mycroft`, … |
+| **openWakeWord** (default) | Free | None | Local ONNX models. Ships a bundled **"hey hermes"** model (default); also supports `hey_jarvis`, `alexa`, `hey_mycroft`, … and custom models |
 | **Porcupine** | Free tier / paid | `PORCUPINE_ACCESS_KEY` | Picovoice engine; built-in keywords + custom `.ppn` files |

+By default the phrase is **"hey hermes"** — a model for it ships with Hermes, so
+it works out of the box with no training. (On first use, openWakeWord downloads
+its shared feature-extraction models — a small one-time fetch.)
+
 Both are lazy-installed the first time you enable the wake word. To install ahead
 of time:

 ```bash
-uv pip install 'hermes-agent[wake]'   # or: pip install 'hermes-agent[wake]'
+cd ~/.hermes/hermes-agent && uv pip install -e ".[wake]"
 ```

 ## Quick start
@ -65,11 +69,11 @@ wake_word:
  enabled: false
  surface: auto               # eligible surface: "auto" | "cli" | "tui" | "gui"
  provider: openwakeword      # "openwakeword" (free, local) | "porcupine"
-  phrase: "hey jarvis"        # cosmetic label only — detection is keyed by the model/keyword below
+  phrase: "hey hermes"        # cosmetic label only — detection is keyed by the model/keyword below
  sensitivity: 0.5            # 0.0-1.0 — raise to reduce false triggers
  start_new_session: true     # start a fresh session on wake vs. continue the current one
  openwakeword:
-    model: hey_jarvis         # built-in name OR path to a custom .onnx/.tflite
+    model: hey_hermes         # bundled default; OR a built-in name OR a path to a custom .onnx/.tflite
    inference_framework: onnx # "onnx" | "tflite"
  porcupine:
    keyword: jarvis           # built-in keyword OR path to a custom .ppn
@ -99,24 +103,25 @@ The TUI and desktop GUI share the same Python backend (`tui_gateway`), which
 runs the detector server-side and yields the mic to voice capture while a
 command records.

-## Using a real "Hey Hermes"
+## Using a different phrase

-The bundled openWakeWord models do **not** include "hey hermes" — `hey_jarvis`
-is the free, instantly-working default. To detect the literal phrase you supply
-your own model and point the config at it:
+"Hey Hermes" works out of the box — the bundled openWakeWord model
+(`model: hey_hermes`) is the default. To wake on something else, either name a
+built-in openWakeWord model or supply your own:

 ### Option A — openWakeWord (free)

-Train a custom model (≈75–90 min on a free/Colab GPU), then drop the `.onnx`
-file somewhere and reference it:
+Name a built-in model (`hey_jarvis`, `alexa`, `hey_mycroft`, …), or train a
+custom model (≈75–90 min on a free/Colab GPU), drop the `.onnx` file somewhere,
+and reference it:

 ```yaml
 wake_word:
  enabled: true
  provider: openwakeword
-  phrase: "hey hermes"
+  phrase: "computer"
  openwakeword:
-    model: ~/.hermes/wakewords/hey_hermes.onnx
+    model: ~/.hermes/wakewords/computer.onnx   # or a built-in name like hey_jarvis
 ```

 Training references: