mirror of
https://github.com/RVC-Boss/GPT-SoVITS.git
synced 2025-10-08 16:00:01 +08:00
364 lines
11 KiB
Python
364 lines
11 KiB
Python
"""
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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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## 执行参数:
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`-s` - `SoVITS模型路径, 可在 config.py 中指定`
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`-g` - `GPT模型路径, 可在 config.py 中指定`
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调用请求缺少参考音频时使用
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`-dr` - `默认参考音频路径`
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`-dt` - `默认参考音频文本`
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`-dl` - `默认参考音频语种, "中文","英文","日文","zh","en","ja"`
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`-d` - `推理设备, "cuda","cpu"`
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`-a` - `绑定地址, 默认"127.0.0.1"`
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`-p` - `绑定端口, 默认9880, 可在 config.py 中指定`
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`-fp` - `覆盖 config.py 使用全精度`
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`-hp` - `覆盖 config.py 使用半精度`
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`-hb` - `cnhubert路径`
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`-b` - `bert路径`
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## 调用:
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### 推理
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endpoint: `/`
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使用执行参数指定的参考音频:
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GET:
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`http://127.0.0.1:9880?text=先帝创业未半而中道崩殂，今天下三分，益州疲弊，此诚危急存亡之秋也。&text_language=zh`
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POST:
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```json
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{
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"text": "先帝创业未半而中道崩殂，今天下三分，益州疲弊，此诚危急存亡之秋也。",
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"text_language": "zh"
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}
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```
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手动指定当次推理所使用的参考音频:
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GET:
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`http://127.0.0.1:9880?refer_wav_path=123.wav&prompt_text=一二三。&prompt_language=zh&text=先帝创业未半而中道崩殂，今天下三分，益州疲弊，此诚危急存亡之秋也。&text_language=zh`
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POST:
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```json
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{
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"refer_wav_path": "123.wav",
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"prompt_text": "一二三。",
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"prompt_language": "zh",
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"text": "先帝创业未半而中道崩殂，今天下三分，益州疲弊，此诚危急存亡之秋也。",
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"text_language": "zh"
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}
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```
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RESP:
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成功: 直接返回 wav 音频流， http code 200
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失败: 返回包含错误信息的 json, http code 400
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### 更换默认参考音频
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endpoint: `/change_refer`
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key与推理端一样
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GET:
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`http://127.0.0.1:9880/change_refer?refer_wav_path=123.wav&prompt_text=一二三。&prompt_language=zh`
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POST:
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```json
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{
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"refer_wav_path": "123.wav",
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"prompt_text": "一二三。",
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"prompt_language": "zh"
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}
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```
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RESP:
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成功: json, http code 200
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失败: json, 400
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### 命令控制
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endpoint: `/control`
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command:
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"restart": 重新运行
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"exit": 结束运行
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GET:
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`http://127.0.0.1:9880/control?command=restart`
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POST:
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```json
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{
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"command": "restart"
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}
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```
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RESP: 无
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"""
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import argparse
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import os
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import sys
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now_dir = os.getcwd()
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sys.path.append(now_dir)
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sys.path.append("%s/GPT_SoVITS" % (now_dir))
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import soundfile as sf
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from fastapi import FastAPI, Request, HTTPException
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from fastapi.responses import StreamingResponse, JSONResponse
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import uvicorn
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from io import BytesIO
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import inference_webui
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from inference_webui import inference as get_tts_wav
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import signal
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import config as global_config
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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("-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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parser.add_argument("-dr", "--default_refer_path", type=str, default="", help="默认参考音频路径")
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parser.add_argument("-dt", "--default_refer_text", type=str, default="", help="默认参考音频文本")
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parser.add_argument("-dl", "--default_refer_language", type=str, default="", help="默认参考音频语种")
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parser.add_argument("-d", "--device", type=str, default=g_config.infer_device, help="cuda / cpu")
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parser.add_argument("-a", "--bind_addr", type=str, default="0.0.0.0", help="default: 0.0.0.0")
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parser.add_argument("-p", "--port", type=int, default=g_config.api_port, help="default: 9880")
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#parser.add_argument("-fp", "--full_precision", action="store_true", default=False, help="覆盖config.is_half为False, 使用全精度")
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#parser.add_argument("-hp", "--half_precision", action="store_true", default=False, help="覆盖config.is_half为True, 使用半精度")
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# bool值的用法为 `python ./api.py -fp ...`
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# 此时 full_precision==True, half_precision==False
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parser.add_argument("-hb", "--hubert_path", type=str, default=g_config.cnhubert_path, help="覆盖config.cnhubert_path")
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parser.add_argument("-b", "--bert_path", type=str, default=g_config.bert_path, help="覆盖config.bert_path")
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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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def change_sovits_weights(sovits_path):
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if sovits_path is not None and sovits_path !="":
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inference_webui.tts_pipline.init_vits_weights(sovits_path)
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def change_gpt_weights(gpt_path):
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if gpt_path is not None and gpt_path !="":
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inference_webui.tts_pipline.init_t2s_weights(gpt_path)
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change_sovits_weights(sovits_path)
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change_gpt_weights(gpt_path)
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class DefaultRefer:
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def __init__(self, path, text, language):
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self.path = args.default_refer_path
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self.text = args.default_refer_text
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self.language = args.default_refer_language
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def is_ready(self) -> bool:
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return is_full(self.path, self.text, self.language)
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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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port = args.port
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host = args.bind_addr
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def is_empty(*items): # 任意一项不为空返回False
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for item in items:
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if item is not None and item != "":
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return False
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return True
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def is_full(*items): # 任意一项为空返回False
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for item in items:
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if item is None or item == "":
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return False
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return True
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dict_language = {
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"中文": "zh",
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"英文": "en",
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"日文": "ja",
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"ZH": "zh",
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"EN": "en",
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"JA": "ja",
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"zh": "zh",
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"en": "en",
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"ja": "ja"
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}
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def handle_control(command):
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if command == "restart":
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os.execl(g_config.python_exec, g_config.python_exec, *sys.argv)
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elif command == "exit":
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os.kill(os.getpid(), signal.SIGTERM)
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exit(0)
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def handle_change(path, text, language):
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if is_empty(path, text, language):
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return JSONResponse({"code": 400, "message": '缺少任意一项以下参数: "path", "text", "language"'}, status_code=400)
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if path != "" or path is not None:
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default_refer.path = path
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if text != "" or text is not None:
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default_refer.text = text
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if language != "" or language is not None:
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default_refer.language = language
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print(f"[INFO] 当前默认参考音频路径: {default_refer.path}")
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print(f"[INFO] 当前默认参考音频文本: {default_refer.text}")
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print(f"[INFO] 当前默认参考音频语种: {default_refer.language}")
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print(f"[INFO] is_ready: {default_refer.is_ready()}")
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return JSONResponse({"code": 0, "message": "Success"}, status_code=200)
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def handle(text, text_language,
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refer_wav_path, prompt_text,
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prompt_language, top_k,
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top_p, temperature,
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text_split_method, batch_size,
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speed_factor, ref_text_free,
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split_bucket,fragment_interval,
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seed):
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if (
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refer_wav_path == "" or refer_wav_path is None
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or prompt_text == "" or prompt_text is None
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or prompt_language == "" or prompt_language is None
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):
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refer_wav_path, prompt_text, prompt_language = (
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default_refer.path,
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default_refer.text,
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default_refer.language,
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)
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if not default_refer.is_ready():
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return JSONResponse({"code": 400, "message": "未指定参考音频且接口无预设"}, status_code=400)
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prompt_text = prompt_text.strip("\n")
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prompt_language, text = prompt_language, text.strip("\n")
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gen = get_tts_wav(text, text_language,
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refer_wav_path, prompt_text,
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prompt_language, top_k,
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top_p, temperature,
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text_split_method, batch_size,
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speed_factor, ref_text_free,
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split_bucket,fragment_interval,
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seed
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)
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audio,_ = next(gen)
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sampling_rate,audio_data=audio
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wav = BytesIO()
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sf.write(wav, audio_data, sampling_rate, format="wav")
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wav.seek(0)
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return StreamingResponse(wav, media_type="audio/wav")
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app = FastAPI()
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#clark新增-----2024-02-21
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#可在启动后动态修改模型，以此满足同一个api不同的朗读者请求
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@app.post("/set_model")
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async def set_model(request: Request):
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json_post_raw = await request.json()
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global gpt_path
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gpt_path=json_post_raw.get("gpt_model_path")
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global sovits_path
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sovits_path=json_post_raw.get("sovits_model_path")
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print("gptpath"+gpt_path+";vitspath"+sovits_path)
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change_sovits_weights(sovits_path)
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change_gpt_weights(gpt_path)
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return "ok"
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# 新增-----end------
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@app.post("/control")
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async def control(request: Request):
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json_post_raw = await request.json()
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return handle_control(json_post_raw.get("command"))
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@app.get("/control")
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async def control(command: str = None):
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return handle_control(command)
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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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return handle_change(
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json_post_raw.get("refer_wav_path"),
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json_post_raw.get("prompt_text"),
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json_post_raw.get("prompt_language")
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)
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@app.get("/change_refer")
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async def change_refer(
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refer_wav_path: str = None,
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prompt_text: str = None,
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prompt_language: str = None
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):
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return handle_change(refer_wav_path, prompt_text, prompt_language)
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'''
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@app.post("/")
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async def tts_endpoint(request: Request):
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json_post_raw = await request.json()
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return handle(
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json_post_raw.get("refer_wav_path"),
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json_post_raw.get("prompt_text"),
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json_post_raw.get("prompt_language"),
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json_post_raw.get("text"),
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json_post_raw.get("text_language"),
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)
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'''
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@app.get("/")
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async def tts_endpoint(
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refer_wav_path: str = None,
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prompt_text: str = None,
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prompt_language: str = None,
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text: str = None,
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text_language: str = None,
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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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text_split_method:str="凑四句一切",
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batch_size:int=20,
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speed_factor:float=1,
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ref_text_free:bool=False,
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split_bucket:bool=True,
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fragment_interval:float=0.3,
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seed:int=-1,
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):
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return handle(text, text_language,
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refer_wav_path, prompt_text,
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prompt_language, top_k,
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top_p, temperature,
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text_split_method, batch_size,
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speed_factor, ref_text_free,
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split_bucket,fragment_interval,
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seed)
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if __name__ == "__main__":
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uvicorn.run(app, host=host, port=port, workers=1)
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