mirror of
https://github.com/RVC-Boss/GPT-SoVITS.git
synced 2025-10-08 16:00:01 +08:00
384 lines
15 KiB
Python
384 lines
15 KiB
Python
import tempfile, io, wave
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import gradio as gr
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import uvicorn
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import argparse
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from fastapi import FastAPI
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from fastapi.responses import StreamingResponse
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from pydub import AudioSegment
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from tools.i18n.i18n import I18nAuto
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from GPT_SoVITS.inference_webui import (
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get_weights_names,
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custom_sort_key,
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change_choices,
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change_gpt_weights,
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change_sovits_weights,
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get_tts_wav,
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)
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api_app = FastAPI()
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i18n = I18nAuto()
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# API mode Usage: python GPT_SoVITS/inference_stream.py --api
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parser = argparse.ArgumentParser(description="GPT-SoVITS Streaming API")
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parser.add_argument(
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"-api",
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"--api",
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action="store_true",
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default=False,
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help="是否开启API模式(不开启则是WebUI模式)",
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)
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parser.add_argument(
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"-s",
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"--sovits_path",
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type=str,
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default="GPT_SoVITS/pretrained_models/s2G488k.pth",
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help="SoVITS模型路径",
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)
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parser.add_argument(
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"-g",
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"--gpt_path",
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type=str,
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default="GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt",
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help="GPT模型路径",
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)
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parser.add_argument(
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"-rw",
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"--ref_wav",
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type=str,
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default="./example/archive_ruanmei_8.wav",
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help="参考音频路径",
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)
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parser.add_argument(
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"-rt",
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"--prompt_text",
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type=str,
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default="我听不惯现代乐，听戏却极易入迷，琴弦拨动，时间便流往过去。",
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help="参考音频文本",
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)
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parser.add_argument(
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"-rl",
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"--prompt_language",
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type=str,
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default=i18n("中文"),
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help="参考音频语种",
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)
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args = parser.parse_args()
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sovits_path = args.sovits_path
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gpt_path = args.gpt_path
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SoVITS_names, GPT_names = get_weights_names()
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EXAMPLES = [
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[
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i18n("中文"),
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"根据过年的传说，远古时代有一隻凶残年兽，每到岁末就会从海底跑出来吃人。"
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+ "人们为了不被年兽吃掉，家家户户都会祭拜祖先祈求平安，也会聚在一起吃一顿丰盛的晚餐。"
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+ "后来人们发现年兽害怕红色、噪音与火光，便开始在当天穿上红衣、门上贴上红纸、燃烧爆竹声，藉此把年兽赶走。"
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+ "而这些之后也成为过年吃团圆饭、穿红衣、放鞭炮、贴春联的过年习俗。",
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],
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[
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i18n("中文"),
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"在父母的葬礼上，她穿一身全黑的丧服。她依旧把头发束得很好，如墨的发丝遮掩着她的神情。她没有掉一滴眼泪。"
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+ "直到夜色降临，在实验室的屏幕上，数据螺旋制成的层层几何花纹在戏声中变换、舒展、流动，而将那花纹层层剥去后，是她万般呵护、小心制作的秘密。"
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+ "阖眼的父亲与母亲，二者冰冷如沉睡般的面容。是辜负。他们没能遵守和外婆的约定。我也没能履行保护父母的承诺，同样辜负了他们。"
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+ "唯有科学…不会辜负。她说。少女希望父母平等，便将自己从前的昵称抹去，将名字从二人姓氏中各取一。"
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+ "自那以后，每当有人问及家，她的眼中总是闪过一丝迷茫，她似乎把一切都忘了。在这样的状态中，她开始了忽视时间规律的演算。"
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+ "由于沉迷科研，她的进食毫不规律，兴致起来便研究几日几夜，到了极限便昏昏睡去。很快，她只借着火萤微弱的光，在每个夜晚收获研究的进展。"
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+ "她愈对已有的生命法则置若罔闻，她的前进就愈加迅速；她完全不在乎公式，接着她漠视了生命的意义。"
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+ "她只去观察、用双手揣摩，将数据握在手里感受，接着就编纂出新的物种规律。于是，在她的实验室中，那些蕨类植物与花愈发生长地茂盛，"
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+ "它们以肉眼可见的速度长高，接着充斥了所有空间。在那花叶开合的缝隙中——笼罩着父母清冷而素净的、由数据汇聚而成的面庞。"
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+ "在沉睡的父母将要睁开双眼的时刻——她几乎摧毁了整个星球原本的物种衍变规律，但她仍然在向着自己的目标前进。"
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+ "直到她从研究中抬起头，猛烈地望向天空：智识的瞥视降临到了她的身上。",
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],
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[
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i18n("中文"),
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"神霄折戟录其二"
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+"「嗯，好吃。」被附体的未央变得温柔了许多，也冷淡了很多。"
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+ "她拿起弥耳做的馅饼，小口小口吃了起来。第一口被烫到了,还很可爱地吐着舌头吸气。"
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+ "「我一下子有点接受不了, 需要消化消化。」用一只眼睛作为代价维持降灵的弥耳自己也拿了一个馅饼，「你再说一 遍?」"
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+ "「当年所谓的陨铁其实是神戟。它被凡人折断，铸成魔剑九柄。这一把是雾海魔剑。 加上他们之前已经收集了两柄。「然后你是?」"
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+ "「我是曾经的天帝之女，名字已经忘了。我司掌审判与断罪，用你们的话说，就是刑律。」"
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+ "因为光禄寺执掌祭祀典礼的事情，所以仪式、祝词什么的，弥耳被老爹逼得倒是能倒背如流。同时因为尽是接触怪力乱神，弥耳也是知道一些小]道的。 神明要是被知道了真正的秘密名讳，就只能任人驱使了。眼前这位未必是忘了。"
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+ "「所以朝廷是想重铸神霄之戟吗?」弥耳说服自己接受了这个设定，追问道。"
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+ "「我不知道。这具身体的主人并不知道别的事。她只是很愤怒,想要证明自己。」未央把手放在了胸口上。"
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+"「那接下来,我是应该弄个什么送神仪式把你送走吗?」弥耳摸了摸绷带下已经失去功能的眼睛，「然后我的眼睛也会回来?」"
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],
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]
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# from https://huggingface.co/spaces/coqui/voice-chat-with-mistral/blob/main/app.py
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def wave_header_chunk(frame_input=b"", channels=1, sample_width=2, sample_rate=32000):
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# This will create a wave header then append the frame input
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# It should be first on a streaming wav file
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# Other frames better should not have it (else you will hear some artifacts each chunk start)
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wav_buf = io.BytesIO()
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with wave.open(wav_buf, "wb") as vfout:
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vfout.setnchannels(channels)
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vfout.setsampwidth(sample_width)
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vfout.setframerate(sample_rate)
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vfout.writeframes(frame_input)
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wav_buf.seek(0)
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return wav_buf.read()
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def get_streaming_tts_wav(
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ref_wav_path,
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prompt_text,
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prompt_language,
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text,
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text_language,
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how_to_cut,
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top_k,
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top_p,
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temperature,
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ref_free,
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byte_stream=True,
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):
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chunks = get_tts_wav(
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ref_wav_path=ref_wav_path,
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prompt_text=prompt_text,
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prompt_language=prompt_language,
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text=text,
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text_language=text_language,
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how_to_cut=how_to_cut,
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top_k=top_k,
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top_p=top_p,
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temperature=temperature,
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ref_free=ref_free,
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stream=True,
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)
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if byte_stream:
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yield wave_header_chunk()
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for chunk in chunks:
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yield chunk
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else:
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# Send chunk files
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i = 0
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format = "wav"
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for chunk in chunks:
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i += 1
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file = f"{tempfile.gettempdir()}/{i}.{format}"
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segment = AudioSegment(chunk, frame_rate=32000, sample_width=2, channels=1)
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segment.export(file, format=format)
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yield file
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def webui():
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with gr.Blocks(title="GPT-SoVITS Streaming Demo") as app:
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gr.Markdown(
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value=i18n(
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"流式输出演示，分句推理后推送到组件中。由于目前bytes模式的限制，采用<a href='https://github.com/gradio-app/gradio/blob/gradio%404.17.0/demo/stream_audio_out/run.py'>stream_audio_out</a>中临时文件的方案输出分句。这种方式相比bytes，会增加wav文件解析的延迟。"
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),
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)
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gr.Markdown(value=i18n("模型切换"))
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with gr.Row():
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GPT_dropdown = gr.Dropdown(
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label=i18n("GPT模型列表"),
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choices=sorted(GPT_names, key=custom_sort_key),
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value=gpt_path,
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interactive=True,
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)
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SoVITS_dropdown = gr.Dropdown(
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label=i18n("SoVITS模型列表"),
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choices=sorted(SoVITS_names, key=custom_sort_key),
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value=sovits_path,
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interactive=True,
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)
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refresh_button = gr.Button(i18n("刷新模型路径"), variant="primary")
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refresh_button.click(
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fn=change_choices, inputs=[], outputs=[SoVITS_dropdown, GPT_dropdown]
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)
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SoVITS_dropdown.change(change_sovits_weights, [SoVITS_dropdown], [])
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GPT_dropdown.change(change_gpt_weights, [GPT_dropdown], [])
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gr.Markdown(value=i18n("*请上传并填写参考信息"))
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with gr.Row():
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inp_ref = gr.Audio(
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label=i18n("请上传3~10秒内参考音频，超过会报错！"), value=args.ref_wav, type="filepath"
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)
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with gr.Column():
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ref_text_free = gr.Checkbox(
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label=i18n("开启无参考文本模式。不填参考文本亦相当于开启。"),
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value=False,
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interactive=True,
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show_label=True,
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)
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gr.Markdown(i18n("使用无参考文本模式时建议使用微调的GPT"))
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prompt_text = gr.Textbox(label=i18n("参考音频的文本"), value=args.prompt_text)
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prompt_language = gr.Dropdown(
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label=i18n("参考音频的语种"),
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choices=[
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i18n("中文"),
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i18n("英文"),
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i18n("日文"),
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i18n("中英混合"),
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i18n("日英混合"),
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i18n("多语种混合"),
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],
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value=args.prompt_language,
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)
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def load_text(file):
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with open(file.name, "r", encoding="utf-8") as file:
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return file.read()
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load_button = gr.UploadButton(i18n("加载参考文本"), variant="secondary")
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load_button.upload(load_text, load_button, prompt_text)
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gr.Markdown(
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value=i18n(
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"*请填写需要合成的目标文本。中英混合选中文，日英混合选日文，中日混合暂不支持，非目标语言文本自动遗弃。"
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)
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)
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with gr.Row():
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text = gr.Textbox(
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label=i18n("需要合成的文本"), value="", lines=5, interactive=True
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)
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text_language = gr.Dropdown(
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label=i18n("需要合成的语种"),
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choices=[
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i18n("中文"),
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i18n("英文"),
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i18n("日文"),
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i18n("中英混合"),
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i18n("日英混合"),
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i18n("多语种混合"),
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],
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value=i18n("中文"),
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)
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how_to_cut = gr.Radio(
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label=i18n("怎么切"),
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choices=[
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i18n("不切"),
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i18n("凑四句一切"),
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i18n("凑50字一切"),
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i18n("按中文句号。切"),
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i18n("按英文句号.切"),
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i18n("按标点符号切"),
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],
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value=i18n("按标点符号切"),
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interactive=True,
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)
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gr.Markdown(value=i18n("* 参数设置"))
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with gr.Row():
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with gr.Column():
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top_k = gr.Slider(
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minimum=1,
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maximum=100,
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step=1,
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label=i18n("top_k"),
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value=5,
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interactive=True,
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)
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top_p = gr.Slider(
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minimum=0,
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maximum=1,
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step=0.05,
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label=i18n("top_p"),
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value=1,
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interactive=True,
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)
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temperature = gr.Slider(
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minimum=0,
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maximum=1,
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step=0.05,
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label=i18n("temperature"),
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value=1,
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interactive=True,
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)
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inference_button = gr.Button(i18n("合成语音"), variant="primary")
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gr.Markdown(value=i18n("* 结果输出(等待第2句推理结束后会自动播放)"))
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with gr.Row():
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audio_file = gr.Audio(
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value=None,
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label=i18n("输出的语音"),
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streaming=True,
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autoplay=True,
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interactive=False,
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show_label=True,
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)
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inference_button.click(
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get_streaming_tts_wav,
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[
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inp_ref,
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prompt_text,
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prompt_language,
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text,
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text_language,
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how_to_cut,
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top_k,
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top_p,
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temperature,
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ref_text_free,
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],
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[audio_file],
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).then(lambda: gr.update(interactive=True), None, [text], queue=False)
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with gr.Row():
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gr.Examples(
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EXAMPLES,
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[text_language, text],
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cache_examples=False,
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run_on_click=False, # Will not work , user should submit it
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)
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app.queue().launch(
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server_name="0.0.0.0",
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inbrowser=True,
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share=False,
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server_port=8080,
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quiet=True,
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)
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@api_app.get("/")
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async def tts(
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text: str, # 必选参数
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language: str = i18n("中文"),
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top_k: int = 5,
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top_p: float = 1,
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temperature: float = 1,
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):
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ref_wav_path = args.ref_wav
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prompt_text = args.prompt_text
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prompt_language = args.prompt_language
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how_to_cut = i18n("按标点符号切")
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return StreamingResponse(
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get_streaming_tts_wav(
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ref_wav_path=ref_wav_path,
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prompt_text=prompt_text,
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prompt_language=prompt_language,
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text=text,
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text_language=language,
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how_to_cut=how_to_cut,
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top_k=top_k,
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top_p=top_p,
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temperature=temperature,
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ref_free=False,
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byte_stream=True,
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),
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media_type="audio/x-wav",
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)
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def api():
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uvicorn.run(
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app="inference_stream:api_app", host="127.0.0.1", port=8080, reload=True
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)
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if __name__ == "__main__":
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# 模式选择，默认是webui模式
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if not args.api:
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webui()
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else:
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api()
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