import spaces
import os
import random
import argparse

import torch
import gradio as gr
import numpy as np

import ChatTTS

print("loading TTS model...")
chat = ChatTTS.Chat()
chat.load_models()



def generate_seed():
    new_seed = random.randint(1, 100000000)
    return {
        "__type__": "update",
        "value": new_seed
        }

@spaces.GPU
def generate_audio(text, temperature, top_P, top_K, audio_seed_input, text_seed_input, refine_text_flag):

    torch.manual_seed(audio_seed_input)
    rand_spk = torch.randn(768)
    params_infer_code = {
        'spk_emb': rand_spk, 
        'temperature': temperature,
        'top_P': top_P,
        'top_K': top_K,
        }
    params_refine_text = {'prompt': '[oral_2][laugh_0][break_6]'}
    
    torch.manual_seed(text_seed_input)

    if refine_text_flag:
        text = chat.infer(text, 
                          skip_refine_text=False,
                          refine_text_only=True,
                          params_refine_text=params_refine_text,
                          params_infer_code=params_infer_code
                          )
    
    wav = chat.infer(text, 
                     skip_refine_text=True, 
                     params_refine_text=params_refine_text, 
                     params_infer_code=params_infer_code
                     )
    
    audio_data = np.array(wav[0]).flatten()
    sample_rate = 24000
    text_data = text[0] if isinstance(text, list) else text

    return [(sample_rate, audio_data), text_data]


with gr.Blocks() as demo:

    gr.Markdown("#Next Generation TTS")

    default_text = "英伟达投的Sora竞品免费了，网友挤爆服务器，120秒120帧支持垫图。这个新推出的模型名为Dream Machine，现已推出免费公开测试版，支持文生视频、图生视频。"        
    text_input = gr.Textbox(label="Input Text", lines=4, placeholder="Please Input Text...", value=default_text)

    with gr.Row():
        refine_text_checkbox = gr.Checkbox(label="Refine text", value=True, visible=False)
        temperature_slider = gr.Slider(minimum=0.00001, maximum=1.0, step=0.00001, value=0.3, label="Audio temperature", visible=False)
        top_p_slider = gr.Slider(minimum=0.1, maximum=0.9, step=0.05, value=0.7, label="top_P", visible=False)
        top_k_slider = gr.Slider(minimum=1, maximum=20, step=1, value=20, label="top_K", visible=False)

    with gr.Row():
        audio_seed_input = gr.Number(value=42, label="Audio Seed", visible=False)
        generate_audio_seed = gr.Button("\U0001F3B2", visible=False)
        text_seed_input = gr.Number(value=42, label="Text Seed", visible=False)
        generate_text_seed = gr.Button("\U0001F3B2", visible=False)

    generate_button = gr.Button("Generate")
        
    text_output = gr.Textbox(label="Output Text", interactive=False)
    audio_output = gr.Audio(label="Output Audio",autoplay=True)

    generate_audio_seed.click(generate_seed, 
                              inputs=[], 
                              outputs=audio_seed_input)
        
    generate_text_seed.click(generate_seed, 
                             inputs=[], 
                             outputs=text_seed_input)
        
    generate_button.click(generate_audio, 
                          inputs=[text_input, temperature_slider, top_p_slider, top_k_slider, audio_seed_input, text_seed_input, refine_text_checkbox], 
                          outputs=[audio_output, text_output])

parser = argparse.ArgumentParser(description='Next Generation TTS Online')
parser.add_argument('--server_name', type=str, default='0.0.0.0', help='Server name')
parser.add_argument('--server_port', type=int, default=8080, help='Server port')
args = parser.parse_args()

    # demo.launch(server_name=args.server_name, server_port=args.server_port, inbrowser=True)




if __name__ == '__main__':
    demo.launch(share=True, show_api=False)