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https://github.com/RVC-Boss/GPT-SoVITS.git
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Merge d2cf5193486219ca4c571e6440e4203a525df12e into 53817b983c3c2f66206bbe214a46fb35714aa22b
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CMDHL
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248
api.py
248
api.py
@ -1,4 +1,60 @@
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"""
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# 1.28.2024 在原api.py基础上做出的一些改动
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## 简介
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- 原接口不变，仿照silero-api-server格式添加了一些endpoint，可接入傻酒馆sillytavern。
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- 运行api.py直至显示http://127.0.0.1:9880
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- 在staging版本的sillytavern>Extensions>TTS>Select TTS Provider选择silero
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- 将http://127.0.0.1:9880填入Provider Endpoint后点击reload
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- Select TTS Provider上方显示TTS Provider Loaded则连接成功，之后照常设置即可。
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- 支持运行中根据讲话人名称自动更换声音模型或参考音频。
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- 如果运行api.py时使用-vd提供了声音模型根目录，可以根据讲话人名称（子文件夹名称或"default"）自动更换模型和参考音频。例如：
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python api.py -vd "D:/Voices"
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- 原有方式导入的声音被命名为“default”，可以使用原有方式更改其参考音频。也可以通过POST至 /set_default_models 更改default声音的模型，例如使用powershell新窗口运行：
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Invoke-RestMethod -Uri "http://127.0.0.1:9880/set_default_models" -Method Post -ContentType "application/json" -Body (@{gpt_path="D:\Voices\ZB\ZB.ckpt"; sovits_path="D:\Voices\ZB\ZB.pth"} | ConvertTo-Json)
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- 默认输出语言是中文。可以在运行api.py时使用-ol指定其他输出语言，或后续POST至 /language 进行更改。
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- 例如要将输出语言改为英文，可以在新的powershell窗口运行：
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Invoke-RestMethod -Uri "http://127.0.0.1:9880/language" -Method Post -Body '{"language": "en"}' -ContentType "application/json"
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## 声音模型根目录格式
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Voices
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├─XXX
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├ ├───XXX.ckpt
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├ ├───XXX.pth
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├ ├───XXX.wav
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├ └───XXX.txt
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├─YYY
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├ ├───YYY.wav
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├ └───YYY.txt
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├─...
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├
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└─ZZZ
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├───ZZZ.ckpt
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├───ZZZ.pth
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├───ZZZ.wav
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└───ZZZ.txt
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- 没有提供GPT和SoVITS模型文件的声音(例如上图的YYY)将使用原有方式指定的default声音模型。
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- 每个文件夹中的txt文件是参考音频文本，目前仅支持单语言，内容格式为{语言}|{参考音频文本}，例如：
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zh|这是一段参考文本
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## 新增的执行参数
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`-vd`- `声音模型根目录，子文件夹以讲话人名称命名`
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`-ol` - `输出音频语言, "中文","英文","日文","zh","en","ja"`
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# api.py usage
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` python api.py -dr "123.wav" -dt "一二三。" -dl "zh" `
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@ -125,12 +181,18 @@ from module.mel_processing import spectrogram_torch
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from my_utils import load_audio
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import config as global_config
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.responses import FileResponse
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g_config = global_config.Config()
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# AVAILABLE_COMPUTE = "cuda" if torch.cuda.is_available() else "cpu"
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parser = argparse.ArgumentParser(description="GPT-SoVITS api")
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parser.add_argument("-vd", "--voices_dir", type=str, default="", help="声音模型根目录，子文件夹以讲话人名称命名")
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parser.add_argument("-ol", "--output_language", type=str, default="zh", help="输出音频语言")
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parser.add_argument("-s", "--sovits_path", type=str, default=g_config.sovits_path, help="SoVITS模型路径")
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parser.add_argument("-g", "--gpt_path", type=str, default=g_config.gpt_path, help="GPT模型路径")
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@ -151,6 +213,11 @@ parser.add_argument("-b", "--bert_path", type=str, default=g_config.bert_path, h
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args = parser.parse_args()
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voices_dir = args.voices_dir
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current_language=args.output_language
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current_gpt_path=args.gpt_path
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current_sovits_path=args.sovits_path
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sovits_path = args.sovits_path
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gpt_path = args.gpt_path
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@ -165,6 +232,47 @@ class DefaultRefer:
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return is_full(self.path, self.text, self.language)
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class Voice:
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def __init__(self, folder):
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try:
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self.refer_wav_path = os.path.join(voices_dir, folder, f"{folder}.wav")
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if not os.path.isfile(self.refer_wav_path):
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raise ValueError("找不到参考音频 {refer_wav_path}")
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refer_txt_path = os.path.join(voices_dir, folder, f"{folder}.txt")
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if not os.path.isfile(refer_txt_path):
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raise ValueError("找不到参考文本 {refer_txt_path}")
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with open(refer_txt_path, 'r', encoding='utf-8') as file:
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content = file.read()
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parts = content.split('|', 1)
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if len(parts) == 2:
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self.refer_lang, self.refer_text = parts
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else:
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raise ValueError("参考文本格式错误。请使用'|'标注文本语言。目前仅支持单语言文本。例如:\nzh|这是一段参考文本。")
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self.sovits_path =os.path.join(voices_dir, folder, f"{folder}.pth")
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if not os.path.isfile(self.sovits_path):
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self.sovits_path=None
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print(f"[WARNING] 找不到 {folder} 专属SoVITS模型。此声音将使用默认SoVITS模型。")
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self.gpt_path = os.path.join(voices_dir, folder, f"{folder}.ckpt")
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if not os.path.isfile(self.gpt_path):
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self.gpt_path=None
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print(f"[WARNING] 找不到 {folder} 专属GPT模型。此声音将使用默认GPT模型。")
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self.name=folder
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except Exception as e:
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raise e
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voices = {}
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if voices_dir!="":
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print(f"[INFO] 声音模型根目录: {voices_dir}")
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for folder in os.listdir(voices_dir):
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if os.path.isdir(os.path.join(voices_dir, folder)):
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try:
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voices[folder]=Voice(folder)
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print(f"[INFO] 根目录下发现声音: {folder}")
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except Exception as e:
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print(f"[WARNING] {folder} 声音模型文件夹格式错误: {e}")
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pass
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default_refer = DefaultRefer(args.default_refer_path, args.default_refer_text, args.default_refer_language)
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device = args.device
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@ -414,6 +522,54 @@ def handle_change(path, text, language):
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return JSONResponse({"code": 0, "message": "Success"}, status_code=200)
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def handle_load(new_gpt_path, new_sovits_path):
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global gpt_path,sovits_path,current_gpt_path,current_sovits_path
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if(new_gpt_path=="" or new_gpt_path is None):
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new_gpt_path = gpt_path
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if(gpt_path=="" or gpt_path is None):
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print("[ERROR] 未设置默认GPT模型地址")
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raise ValueError("未设置默认GPT模型地址")
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if(new_sovits_path=="" or new_sovits_path is None):
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new_sovits_path = sovits_path
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if(sovits_path=="" or sovits_path is None):
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print("[ERROR] 未设置默认SoVITS模型地址")
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raise ValueError("未设置默认SoVITS模型地址")
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if(os.path.normpath(os.path.abspath(current_gpt_path))==os.path.normpath(os.path.abspath(new_gpt_path))
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and os.path.normpath(os.path.abspath(current_sovits_path)) == os.path.normpath(os.path.abspath(new_sovits_path))):
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return
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print(f"current models: {current_gpt_path}, {current_sovits_path}")
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print(f"loading new models: {new_gpt_path}, {new_sovits_path}")
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current_gpt_path=new_gpt_path
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current_sovits_path=new_sovits_path
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global dict_s2, hps, dict_s1, config, vq_model, max_sec, t2s_model
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dict_s2 = torch.load(new_sovits_path, map_location="cpu") # Corrected the variable name here
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hps = dict_s2["config"]
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hps = DictToAttrRecursive(hps)
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hps.model.semantic_frame_rate = "25hz"
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dict_s1 = torch.load(new_gpt_path, map_location="cpu")
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config = dict_s1["config"]
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vq_model = SynthesizerTrn(
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hps.data.filter_length // 2 + 1,
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hps.train.segment_size // hps.data.hop_length,
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n_speakers=hps.data.n_speakers,
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**hps.model)
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if is_half:
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vq_model = vq_model.half().to(device)
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else:
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vq_model = vq_model.to(device)
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vq_model.eval()
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print(vq_model.load_state_dict(dict_s2["weight"], strict=False))
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max_sec = config['data']['max_sec']
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t2s_model = Text2SemanticLightningModule(config, "****", is_train=False)
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t2s_model.load_state_dict(dict_s1["weight"])
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if is_half:
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t2s_model = t2s_model.half()
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t2s_model = t2s_model.to(device)
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t2s_model.eval()
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def handle(refer_wav_path, prompt_text, prompt_language, text, text_language):
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if (
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refer_wav_path == "" or refer_wav_path is None
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@ -439,7 +595,8 @@ def handle(refer_wav_path, prompt_text, prompt_language, text, text_language):
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wav.seek(0)
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torch.cuda.empty_cache()
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torch.mps.empty_cache()
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if(device=="mps"): #added condition so it can run on my device for testing
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torch.mps.empty_cache()
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return StreamingResponse(wav, media_type="audio/wav")
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@ -457,6 +614,15 @@ async def control(command: str = None):
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return handle_control(command)
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@app.post("/set_default_models")
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async def set_default_models(request: Request):
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global gpt_path,sovits_path
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json_post_raw = await request.json()
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gpt_path = json_post_raw.get("gpt_path")
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sovits_path = json_post_raw.get("sovits_path")
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return JSONResponse({"gpt_path":gpt_path,"sovits_path":sovits_path},status_code=200)
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@app.post("/change_refer")
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async def change_refer(request: Request):
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json_post_raw = await request.json()
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@ -499,5 +665,85 @@ async def tts_endpoint(
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return handle(refer_wav_path, prompt_text, prompt_language, text, text_language)
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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@app.get("/speakers")
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async def speakers(request:Request):
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voices_info = [
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{
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"name":"default",
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"voice_id":"default",
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"preview_url": f"{str(request.base_url)}sample/default"
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}
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]
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if(len(voices)>0):
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for v in voices.values():
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voices_info.append(
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{
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"name":v.name,
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"voice_id":v.name,
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"preview_url": f"{str(request.base_url)}sample/{v.name}"
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}
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)
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return voices_info
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@app.post("/generate")
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async def generate(request:Request):
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json_post_raw=await request.json()
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speaker = json_post_raw.get("speaker")
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if(speaker=="default"):
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handle_load(gpt_path,sovits_path)
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handle_result=handle(
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None,
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None,
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None,
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json_post_raw.get("text"),
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current_language,
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)
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else:
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handle_load(voices[speaker].gpt_path,voices[speaker].sovits_path)
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return handle(
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voices[speaker].refer_wav_path,
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voices[speaker].refer_text,
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voices[speaker].refer_lang,
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json_post_raw.get("text"),
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current_language,
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)
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@app.get("/sample/{speaker}")
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async def play_sample(speaker: str = 'default'):
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if(speaker=='default'):
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return FileResponse(default_refer.path,status_code=200)
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print(f"sending {voices[speaker].refer_wav_path}")
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return FileResponse(voices[speaker].refer_wav_path,status_code=200)
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@app.post("/session") #just a placeholder
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async def session(request:Request):
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return JSONResponse({},status_code=200)
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@app.get("/language")
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async def get_languages():
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return JSONResponse(list(dict_language.keys()),headers={'Content-Type': 'text/plain; charset=utf-8'}, status_code=200)
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@app.post("/language")
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async def set_language(request: Request):
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global current_language
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json_post_raw=await request.json()
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current_language = json_post_raw.get("language")
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print(f"[INFO] output language is set to:{current_language}")
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return JSONResponse(f"current language: {current_language}",status_code=200)
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if __name__ == "__main__":
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uvicorn.run(app, host=host, port=port, workers=1)
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