import pygame, os, subprocess, language, wave, pyaudio, time, numpy as np, random
from dotenv import load_dotenv
load_dotenv()

ROOT_DIR = os.getenv('ROOT_DIR', os.path.dirname(__file__))
PIPER_AUDIO_OUTPUT_FILE = os.path.join(ROOT_DIR, 'llm_media/chat_voice_out.wav')
AUDIO_INPUT_FILE = os.path.join(ROOT_DIR, 'llm_media/input_audio.wav')

def play_audio(audio_file, volume=0.5):
    # Initialize pygame mixer
    pygame.mixer.init()
    pygame.mixer.music.load(audio_file)
    pygame.mixer.music.play()
    pygame.mixer.music.set_volume(volume)
    while pygame.mixer.music.get_busy():
        continue



def piper(text, model, config):
    process1 = subprocess.run(['echo', text], stdout=subprocess.PIPE)
    subprocess.run(['piper-tts', '--sentence-silence', '0.5', '--model', model, '--config', config, '--output_file', PIPER_AUDIO_OUTPUT_FILE], input=process1.stdout)
    play_audio(PIPER_AUDIO_OUTPUT_FILE)

def eng_piper(text):
    piper(text, model = eng_piper_model, config = eng_piper_conf)



def play_prompt(fallback_prompt: str = "Missing Fallback Prompt", audio_files: list = [],  use_custom: bool = True):
    if use_custom:
        valid_files = []
        for i in audio_files:
            if os.path.exists(i):
                valid_files.append(i)
        if len(valid_files) == 0:
            eng_piper(fallback_prompt)
            return
        number_of_files = len(valid_files)
        file = random.randint(0, number_of_files-1)
        play_audio(valid_files[file], volume=1)
    else:
        eng_piper(fallback_prompt)

eng_piper_model, eng_piper_conf = language.files_language('en')



# Capture the audio input

def capture_audio_until_silence(threshold=800, silence_duration=3, output_file = AUDIO_INPUT_FILE):
    """
    Capture audio until a period of silence is detected.
    threshold: The audio level that defines silence.
    silence_duration: The duration of silence to wait for before stopping.
    output_file: The file to save the recorded audio to.
    """
    # PyAudio configuration
    p = pyaudio.PyAudio()
    chunk = 1024
    sample_format = pyaudio.paInt16
    channels = 2
    rate = 44100

    # Start recording
    stream = p.open(format=sample_format,
                    channels=channels,
                    rate=rate,
                    input=True,
                    frames_per_buffer=chunk)

    print("Listening...")

    audio_frames = []
    last_time = time.time()

    try:
        while True:
            # Read audio data
            data = stream.read(chunk)
            audio_frames.append(data)

            # Convert data to numpy array for analysis
            audio_data = np.frombuffer(data, dtype=np.int16)
            peak = np.abs(audio_data).max()

            # Check if the sound level exceeds the threshold
            if peak > threshold:
                last_time = time.time()  # Reset the silence timer
            else:
                # Check for silence
                if time.time() - last_time > silence_duration:
                    print(f"No sound detected for {silence_duration} seconds. Stopping...")
                    break

    except KeyboardInterrupt:
        print("Stopped by user.")

    finally:
        # Stop and close the stream
        stream.stop_stream()
        stream.close()
        p.terminate()
        with wave.open(output_file, 'wb') as wf:
            wf.setnchannels(channels)
            wf.setsampwidth(p.get_sample_size(sample_format))
            wf.setframerate(rate)
            wf.writeframes(b''.join(audio_frames))



if __name__ == "__main__":
    zh_piper_model, zh_piper_conf = language.files_language('zh')
    eng_piper("Hello, I am Piper. I am a text-to-speech model.")
    piper("你好，我是派珀。我是一个文本转语音模型。", model = zh_piper_model, config = zh_piper_conf)
    # capture_audio_until_silence() # you can try out whisper on the recording you have just made by running whisper.py