Complete P2 (LLM) and P3 (voice pipeline) implementation

P2 — homeai-llm:
- Fix ollama launchd plist path for Apple Silicon (/opt/homebrew/bin/ollama)
- Add Modelfiles for local GGUF models: llama3.3:70b, qwen3:32b, codestral:22b
  (registered via `ollama create` — no re-download needed)

P3 — homeai-voice:
- Wyoming STT: wyoming-faster-whisper, large-v3 model, port 10300
- Wyoming TTS: custom Kokoro ONNX server (wyoming_kokoro_server.py), port 10301
  Voice af_heart; models at ~/models/kokoro/
- Wake word: openWakeWord daemon (hey_jarvis), notifies OpenClaw at /wake
- launchd plists for all three services + load-all-launchd.sh helper
- Smoke test: wyoming/test-pipeline.sh — 3/3 passing

HA Wyoming integration pending manual UI config (STT 10.0.0.200:10300,
TTS 10.0.0.200:10301).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

homeai-voice/wyoming/wakeword_daemon.py

@@ -0,0 +1,110 @@
+#!/usr/bin/env python3
+"""Always-on wake word detection daemon using openWakeWord.
+
+Listens on the default microphone, fires an HTTP POST to --notify-url
+when the wake word is detected.
+
+Usage:
+    python wakeword_daemon.py --wake-word hey_jarvis --notify-url http://localhost:8080/wake
+"""
+
+import argparse
+import logging
+import time
+import urllib.request
+import json
+import numpy as np
+
+_LOGGER = logging.getLogger(__name__)
+
+SAMPLE_RATE = 16000
+CHUNK_SIZE = 1280  # ~80ms at 16kHz — recommended by openWakeWord
+
+
+def notify(url: str, wake_word: str, score: float):
+    payload = json.dumps({"wake_word": wake_word, "score": float(score)}).encode()
+    try:
+        req = urllib.request.Request(
+            url,
+            data=payload,
+            headers={"Content-Type": "application/json"},
+            method="POST",
+        )
+        with urllib.request.urlopen(req, timeout=2):
+            pass
+        _LOGGER.info("Wake word '%s' detected (score=%.3f) — notified %s", wake_word, score, url)
+    except Exception as e:
+        _LOGGER.warning("Failed to notify %s: %s", url, e)
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--wake-word", default="hey_jarvis")
+    parser.add_argument("--notify-url", default="http://localhost:8080/wake")
+    parser.add_argument("--threshold", type=float, default=0.5)
+    parser.add_argument("--cooldown", type=float, default=3.0, help="Seconds between triggers")
+    parser.add_argument("--model-dir", default=None, help="Path to custom .onnx wake word model")
+    parser.add_argument("--debug", action="store_true")
+    args = parser.parse_args()
+
+    logging.basicConfig(
+        level=logging.DEBUG if args.debug else logging.INFO,
+        format="%(asctime)s %(levelname)s %(message)s",
+    )
+
+    try:
+        import pyaudio
+    except ImportError:
+        _LOGGER.error("pyaudio not installed. Run: pip install pyaudio")
+        raise SystemExit(1)
+
+    import openwakeword
+    from openwakeword.model import Model
+
+    _LOGGER.info("Loading wake word model: %s", args.wake_word)
+
+    model_paths = []
+    if args.model_dir:
+        import os, glob
+        model_paths = glob.glob(os.path.join(args.model_dir, "*.onnx"))
+
+    oww = Model(
+        wakeword_models=model_paths if model_paths else [args.wake_word],
+        inference_framework="onnx",
+    )
+
+    audio = pyaudio.PyAudio()
+    stream = audio.open(
+        rate=SAMPLE_RATE,
+        channels=1,
+        format=pyaudio.paInt16,
+        input=True,
+        frames_per_buffer=CHUNK_SIZE,
+    )
+
+    _LOGGER.info("Listening for wake word '%s'...", args.wake_word)
+    last_trigger = 0.0
+
+    try:
+        while True:
+            raw = stream.read(CHUNK_SIZE, exception_on_overflow=False)
+            chunk = np.frombuffer(raw, dtype=np.int16)
+            oww.predict(chunk)
+
+            for ww, scores in oww.prediction_buffer.items():
+                score = scores[-1] if scores else 0.0
+                if score >= args.threshold:
+                    now = time.time()
+                    if now - last_trigger >= args.cooldown:
+                        last_trigger = now
+                        notify(args.notify_url, ww, score)
+    except KeyboardInterrupt:
+        pass
+    finally:
+        stream.stop_stream()
+        stream.close()
+        audio.terminate()
+
+
+if __name__ == "__main__":
+    main()