app.py

import os
import random
import argparse

import torch
import gradio as gr
import numpy as np
import spaces

import ChatTTS

print("loading ChatTTS 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

def check_and_generate(text, temperature, top_P, top_K, audio_seed_input, text_seed_input, refine_text_flag):
    if len(text) > 100:
        return None, "", "Text is too long, please input text with less than 100 characters."
    audio, generated_text = generate_audio(text, temperature, top_P, top_K, audio_seed_input, text_seed_input, refine_text_flag)
    return audio, generated_text, ""

def main():
    with gr.Blocks() as demo:
        gr.Markdown("# Deployed by [chattts.dev](https://chattts.dev?refer=hf)")

        default_text = "四川美食确实以辣闻名，但也有不辣的选择。比如甜水面、赖汤圆、蛋烘糕、叶儿粑等，这些小吃口味温和，甜而不腻，也很受欢迎。"
        text_input = gr.Textbox(label="Input Text", lines=4, placeholder="Please Input Text...", value=default_text)
        text_length_warning = gr.Markdown("")

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

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

        generate_button = gr.Button("Generate")

        text_output = gr.Textbox(label="Output Text", interactive=False)
        audio_output = gr.Audio(label="Output Audio")

        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(check_and_generate, 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, text_length_warning])

    parser = argparse.ArgumentParser(description='ChatTTS demo Launch')
    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.queue(max_size=1).launch(server_name=args.server_name, server_port=args.server_port, inbrowser=True)
    demo.queue(max_size=4).launch()

if __name__ == '__main__':
    main()