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import spaces |
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import os |
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import random |
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import argparse |
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import torch |
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import gradio as gr |
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import numpy as np |
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import ChatTTS |
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print("loading ChatTTS model...") |
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chat = ChatTTS.Chat() |
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chat.load_models() |
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def generate_seed(): |
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new_seed = random.randint(1, 100000000) |
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return { |
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"__type__": "update", |
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"value": new_seed |
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} |
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@spaces.GPU |
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def generate_audio(text, temperature, top_P, top_K, audio_seed_input, text_seed_input, refine_text_flag, refine_text_input): |
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torch.manual_seed(audio_seed_input) |
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rand_spk = torch.randn(768) |
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params_infer_code = { |
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'spk_emb': rand_spk, |
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'temperature': temperature, |
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'top_P': top_P, |
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'top_K': top_K, |
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} |
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params_refine_text = {'prompt': '[oral_2][laugh_0][break_6]'} |
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torch.manual_seed(text_seed_input) |
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if refine_text_flag: |
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if refine_text_input: |
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params_refine_text['prompt'] = refine_text_input |
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text = chat.infer(text, |
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skip_refine_text=False, |
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refine_text_only=True, |
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params_refine_text=params_refine_text, |
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params_infer_code=params_infer_code |
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) |
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wav = chat.infer(text, |
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skip_refine_text=True, |
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params_refine_text=params_refine_text, |
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params_infer_code=params_infer_code |
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) |
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audio_data = np.array(wav[0]).flatten() |
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sample_rate = 24000 |
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text_data = text[0] if isinstance(text, list) else text |
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return [(sample_rate, audio_data), text_data] |
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with gr.Blocks() as demo: |
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gr.Markdown("# Enjoy chatting with your ai friends on website, telegram and so on! (https://linkin.love)") |
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default_text = "Today a man knocked on my door and asked for a small donation toward the local swimming pool. I gave him a glass of water." |
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text_input = gr.Textbox(label="Input Text", lines=4, placeholder="Please Input Text...", value=default_text) |
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default_refine_text = "[oral_2][laugh_0][break_6]" |
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refine_text_checkbox = gr.Checkbox(label="Refine text：'oral' means add filler words, 'laugh' means add laughter, and 'break' means add a pause. (0-10) ", value=True) |
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refine_text_input = gr.Textbox(label="Refine Prompt", lines=1, placeholder="Please Refine Prompt...", value=default_refine_text) |
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with gr.Row(): |
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temperature_slider = gr.Slider(minimum=0.00001, maximum=1.0, step=0.00001, value=0.3, label="Audio temperature") |
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top_p_slider = gr.Slider(minimum=0.1, maximum=0.9, step=0.05, value=0.7, label="top_P") |
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top_k_slider = gr.Slider(minimum=1, maximum=20, step=1, value=20, label="top_K") |
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with gr.Row(): |
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audio_seed_input = gr.Number(value=42, label="Speaker Seed") |
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generate_audio_seed = gr.Button("\U0001F3B2") |
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text_seed_input = gr.Number(value=42, label="Text Seed") |
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generate_text_seed = gr.Button("\U0001F3B2") |
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generate_button = gr.Button("Generate") |
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text_output = gr.Textbox(label="Refined Text", interactive=False) |
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audio_output = gr.Audio(label="Output Audio") |
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generate_audio_seed.click(generate_seed, |
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inputs=[], |
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outputs=audio_seed_input) |
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generate_text_seed.click(generate_seed, |
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inputs=[], |
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outputs=text_seed_input) |
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generate_button.click(generate_audio, |
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inputs=[text_input, temperature_slider, top_p_slider, top_k_slider, audio_seed_input, text_seed_input, refine_text_checkbox, refine_text_input], |
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outputs=[audio_output, text_output]) |
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parser = argparse.ArgumentParser(description='ChatTTS demo Launch') |
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parser.add_argument('--server_name', type=str, default='0.0.0.0', help='Server name') |
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parser.add_argument('--server_port', type=int, default=8080, help='Server port') |
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args = parser.parse_args() |
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if __name__ == '__main__': |
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demo.launch() |
