#!/usr/bin/env python3
"""Listen for the 'alexa' wakeword via openwakeword. Beep on detection.

Pass criteria (per spec):
- "alexa" at normal volume from ~1 m triggers within ~1 s (>= 8/10 attempts).
- During ~1 minute of unrelated speech, <= ~1 false positive.
- Python process < 50% of one core (check with htop).
"""
import os
os.environ.setdefault("PA_ALSA_PLUGHW", "1")

import sys
import time

import numpy as np
import sounddevice as sd
import openwakeword.utils
from openwakeword.model import Model

SAMPLE_RATE = 16_000
FRAME_SAMPLES = 1280
CHANNELS = 1
DTYPE = "int16"
WAKEWORD = "alexa"
THRESHOLD = 0.5
COOLDOWN_S = 1.0
BEEP_FREQ_HZ = 880.0
BEEP_DURATION_S = 0.2


def find_usb_device() -> int:
    for idx, dev in enumerate(sd.query_devices()):
        name = dev["name"].lower()
        if "usb" in name and dev["max_input_channels"] >= 1:
            return idx
    print("USB audio device not found. Devices:", file=sys.stderr)
    print(sd.query_devices(), file=sys.stderr)
    sys.exit(1)


def beep(device: int) -> None:
    t = np.arange(int(SAMPLE_RATE * BEEP_DURATION_S)) / SAMPLE_RATE
    tone = (0.3 * np.sin(2 * np.pi * BEEP_FREQ_HZ * t)).astype(np.float32)
    sd.play(tone, samplerate=SAMPLE_RATE, device=device)
    sd.wait()


def main() -> int:
    print("Ensuring openwakeword onnx models are downloaded (idempotent)...")
    openwakeword.utils.download_models()

    print("Loading openwakeword model...")
    t0 = time.monotonic()
    model = Model(wakeword_models=[WAKEWORD], inference_framework="onnx")
    print(f"Model loaded in {time.monotonic() - t0:.2f}s.")

    device = find_usb_device()
    print(
        f"Listening on device {device} ({sd.query_devices(device)['name']!r}). "
        f"Say '{WAKEWORD}'. Ctrl-C to exit."
    )

    last_trigger = 0.0
    start = time.monotonic()

    with sd.InputStream(
        samplerate=SAMPLE_RATE,
        channels=CHANNELS,
        dtype=DTYPE,
        device=device,
        blocksize=FRAME_SAMPLES,
    ) as stream:
        while True:
            frame, overflowed = stream.read(FRAME_SAMPLES)
            if overflowed:
                print("[status] input overflow", file=sys.stderr)
            mono = frame[:, 0]
            scores = model.predict(mono)
            score = float(scores.get(WAKEWORD, 0.0))
            now = time.monotonic()
            if score >= THRESHOLD and (now - last_trigger) >= COOLDOWN_S:
                print(f"DETECTED {WAKEWORD} score={score:.3f} t={now - start:.1f}s")
                last_trigger = now
                beep(device)


if __name__ == "__main__":
    try:
        sys.exit(main())
    except KeyboardInterrupt:
        print("\nbye")
        sys.exit(0)