#!/usr/bin/env python3
"""
openWakeWord to MQTT publisher
Publishes wake word detections to Home Assistant MQTT broker
"""

import time
import json
import paho.mqtt.client as mqtt
import openwakeword
from openwakeword.model import Model
import numpy as np
import sounddevice as sd

# MQTT Configuration
MQTT_HOST = "192.168.0.39"  # Home Assistant IP
MQTT_PORT = 1883
MQTT_USER = "your_mqtt_username"  # Replace with your MQTT username
MQTT_PASS = "your_mqtt_password"  # Replace with your MQTT password
MQTT_TOPIC = "homeassistant/openwakeword/detection"

# Wake word detection threshold (0.0 - 1.0)
THRESHOLD = 0.5

# Audio settings
CHUNK_SIZE = 1600  # 100ms of audio @ 16kHz

def on_connect(client, userdata, flags, rc):
    if rc == 0:
        print(f"Connected to MQTT broker at {MQTT_HOST}")
    else:
        print(f"Failed to connect, return code {rc}")

def publish_detection(wake_word, confidence):
    payload = json.dumps({
        "wake_word": wake_word,
        "confidence": float(confidence),
        "timestamp": time.time()
    })
    client.publish(MQTT_TOPIC, payload)
    print(f"Published: {wake_word} ({confidence:.2f})")

def main():
    global client

    # Initialize MQTT client
    client = mqtt.Client(client_id="openwakeword")
    client.username_pw_set(MQTT_USER, MQTT_PASS)
    client.on_connect = on_connect
    client.connect(MQTT_HOST, MQTT_PORT, 60)
    client.loop_start()

    # Initialize openwakeword model
    print("Loading openwakeword models...")
    oww_model = Model()

    # Get audio stream (adjust for your microphone)
    # Using sounddevice for microphone input
    import sounddevice as sd

    def audio_callback(indata, frames, time, status):
        if status:
            print(status)
        # Process audio for wake word detection
        audio_data = indata.flatten()
        predictions = oww_model.predict(audio_data)

        # Check for detections
        for wake_word, score in predictions.items():
            if score >= THRESHOLD:
                publish_detection(wake_word, score)

    print("Listening for wake words...")
    print("Press Ctrl+C to stop")

    # Start streaming from microphone
    with sd.InputStream(
        channels=1,
        samplerate=16000,
        dtype='int16',
        blocksize=CHUNK_SIZE,
        callback=audio_callback
    ):
        try:
            while True:
                time.sleep(0.1)
        except KeyboardInterrupt:
            print("\nStopping...")
            client.loop_stop()
            client.disconnect()

if __name__ == "__main__":
    main()