import wave
import gradio as gr

pretrains = {
    "OV2-32k": {
        "D": "https://huggingface.co/poiqazwsx/Ov2Super32kfix/resolve/main/f0Ov2Super32kD.pth",
        "G": "https://huggingface.co/poiqazwsx/Ov2Super32kfix/resolve/main/f0Ov2Super32kG.pth"
    },
    "OV2-40k": {
        "D": "https://huggingface.co/ORVC/Ov2Super/resolve/main/f0Ov2Super40kD.pth",
        "G": "https://huggingface.co/ORVC/Ov2Super/resolve/main/f0Ov2Super40kG.pth"
    },
    "RIN-40k": {
        "D": "https://huggingface.co/ORVC/RIN_E3/resolve/main/RIN_E3_D.pth",
        "G": "https://huggingface.co/ORVC/RIN_E3/resolve/main/RIN_E3_G.pth"
    },
    "Snowie-40k": {
        "D": "https://huggingface.co/ORVC/Snowie_RuPretrain_40k/resolve/main/D_Snowie_RuPretrain_EnP.pth",
        "G": "https://huggingface.co/ORVC/Snowie_RuPretrain_40k/resolve/main/G_Snowie_RuPretrain_EnP.pth"
    },
    "Snowie-48k": {
        "D": "https://huggingface.co/ORVC/Snowie_RuPretrain_48k/resolve/main/D_Snowie_Rupretrain_48k_V1.2.pth",
        "G": "https://huggingface.co/ORVC/Snowie_RuPretrain_48k/resolve/main/G_Snowie_Rupretrain_48k_V1.2.pth"
    },
    "SnowieV3.1-40k": {
        "D": "https://huggingface.co/MUSTAR/SnowieV3.1-40k/resolve/main/D_SnowieV3.1_40k.pth",
        "G": "https://huggingface.co/MUSTAR/SnowieV3.1-40k/resolve/main/G_SnowieV3.1_40k.pth"
    },
    "SnowieV3.1-32k": {
        "D": "https://huggingface.co/MUSTAR/SnowieV3.1-32k/resolve/main/D_SnowieV3.1_32k.pth",
        "G": "https://huggingface.co/MUSTAR/SnowieV3.1-32k/resolve/main/G_SnowieV3.1_32k.pth"
    },
    "SnowieV3.1-48k": {
        "D": "https://huggingface.co/MUSTAR/SnowieV3.1-48k/resolve/main/D_SnowieV3.1_48k.pth",
        "G": "https://huggingface.co/MUSTAR/SnowieV3.1-48k/resolve/main/G_SnowieV3.1_48k.pth"
    },
    "SnowieV3.1-X-RinE3-40k": {
        "D": "https://huggingface.co/MUSTAR/SnowieV3.1-X-RinE3-40K/resolve/main/D_Snowie-X-Rin_40k.pth",
        "G": "https://huggingface.co/MUSTAR/SnowieV3.1-X-RinE3-40K/resolve/main/G_Snowie-X-Rin_40k.pth"
    }
}

def get_audio_duration(audio_file):
    with wave.open(audio_file, 'rb') as audio:
        frames = audio.getnframes()
        rate = audio.getframerate()
        duration = frames / float(rate)
    return duration

def get_training_info(audio_file):
    if audio_file is None:
        return 'Please provide an audio file!'
    
    duration = get_audio_duration(audio_file)
    sample_rate = wave.open(audio_file, 'rb').getframerate()

    training_info = {
        (0, 2): (150, 'OV2'),
        (2, 3): (200, 'OV2'),
        (3, 5): (250, 'OV2'),
        (5, 10): (300, 'Normal'),
        (10, 25): (500, 'Normal'),
        (25, 45): (700, 'Normal'),
        (45, 60): (1000, 'Normal')
    }

    for (min_duration, max_duration), (epochs, pretrain) in training_info.items():
        if min_duration <= duration < max_duration:
            break
    else:
        return 'Duration is not within the specified range.'

    return f'You should use the **{pretrain}** pretrain with **{epochs}** epochs at **{sample_rate/1000}kHz** sample rate. Good luck with your training!'

with gr.Blocks() as demo:
    audio_p = gr.Audio(type="filepath", label="Your Audio here")
    audio_q = gr.Textbox(label="Your Output here")
    wtar = gr.Button("Start!")
    wtar.click(get_training_info, inputs=[audio_p], outputs=[audio_q])

    demo.launch(debug=True)