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https://github.com/RVC-Boss/GPT-SoVITS.git
synced 2025-08-07 15:33:29 +08:00
add allc
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samiabat
parent
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commit
39e77a61ac
@ -3,7 +3,7 @@ import os
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import soundfile as sf
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from tools.i18n.i18n import I18nAuto
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from GPT_SoVITS.inference_webui import change_gpt_weights, change_sovits_weights, get_tts_wav
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from GPT_SoVITS.inference_webui import change_gpt_weights, change_sovits_weights, get_tts_wav, test
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i18n = I18nAuto()
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@ -11,9 +11,13 @@ def synthesize(GPT_model_path, SoVITS_model_path, ref_audio_path, ref_text, ref_
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energy_scale=1.0, volume_scale=1.0, strain_effect=0.0):
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# Change model weights
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print("Changing model weights about to be called...")
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test()
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change_gpt_weights(gpt_path=GPT_model_path)
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change_sovits_weights(sovits_path=SoVITS_model_path)
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print("Model weights changed successfully.")
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# Synthesize audio
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synthesis_result = get_tts_wav(ref_wav_path=ref_audio_path,
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prompt_text=ref_text,
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@ -41,6 +41,8 @@ for i in range(3):
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if os.path.exists(pretrained_sovits_name[i]):_[-1].append(pretrained_sovits_name[i])
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pretrained_gpt_name,pretrained_sovits_name = _
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def test():
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print("GPT_SoVITS/inference_cli.py is running")
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if os.path.exists(f"./weight.json"):
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pass
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@ -327,7 +329,7 @@ def change_gpt_weights(gpt_path):
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change_gpt_weights(gpt_path)
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os.environ["HF_ENDPOINT"] = "https://hf-mirror.com"
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os.environ["HF_ENDPOINT"] = "https://hf-mirror.com"
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import torch,soundfile
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now_dir = os.getcwd()
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import soundfile
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246
api.py
246
api.py
@ -1,146 +1,3 @@
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"""
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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","韩文","粤语,"zh","en","ja","ko","yue"`
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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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`-sm` - `流式返回模式, 默认不启用, "close","c", "normal","n", "keepalive","k"`
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·-mt` - `返回的音频编码格式, 流式默认ogg, 非流式默认wav, "wav", "ogg", "aac"`
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·-st` - `返回的音频数据类型, 默认int16, "int16", "int32"`
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·-cp` - `文本切分符号设定, 默认为空, 以",.，。"字符串的方式传入`
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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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使用执行参数指定的参考音频并设定分割符号:
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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&cut_punc=，。`
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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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"cut_punc": "，。",
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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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手动指定当次推理所使用的参考音频，并提供参数:
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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&top_k=20&top_p=0.6&temperature=0.6&speed=1&inp_refs="456.wav"&inp_refs="789.wav"`
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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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"top_k": 20,
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"top_p": 0.6,
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"temperature": 0.6,
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"speed": 1,
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"inp_refs": ["456.wav","789.wav"]
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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,re
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import sys
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@ -279,7 +136,7 @@ def get_sovits_weights(sovits_path):
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is_exist_s2gv3=os.path.exists(path_sovits_v3)
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version, model_version, if_lora_v3=get_sovits_version_from_path_fast(sovits_path)
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logger.info(f"the version of version: {version}, model version: {model_version}, if lora v3: {if_lora_v3}")
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logger.info(f"the version is: {version}, model version: {model_version}, if lora v3: {if_lora_v3}")
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if if_lora_v3==True and is_exist_s2gv3==False:
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logger.info("SoVITS V3 底模缺失，无法加载相应 LoRA 权重")
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@ -1021,53 +878,6 @@ change_gpt_sovits_weights(gpt_path = gpt_path, sovits_path = sovits_path)
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# --------------------------------
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app = FastAPI()
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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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return change_gpt_sovits_weights(
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gpt_path = json_post_raw.get("gpt_model_path"),
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sovits_path = json_post_raw.get("sovits_model_path")
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)
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@app.get("/set_model")
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async def set_model(
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gpt_model_path: str = None,
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sovits_model_path: str = None,
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):
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return change_gpt_sovits_weights(gpt_path = gpt_model_path, sovits_path = sovits_model_path)
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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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@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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@ -1092,60 +902,6 @@ import soundfile as sf
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import io
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from fastapi.responses import StreamingResponse
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@app.get("/version-4")
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async def version_4(
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GPT_model_path = "GPT_SoVITS/pretrained_models/kurari-e40.ckpt",
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SoVITS_model_path = "GPT_SoVITS/pretrained_models/kurari_e20_s1800_l32.pth",
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ref_text: str = "おはよう〜。今日はどんな1日過ごすー？くらりはね〜いつでもあなたの味方だよ",
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ref_language: str = "日文",
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target_text: str = None,
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text_language: str = "日文",
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output_path: str = None,
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character_name: str = "Kurari",
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model_id: int = 14,
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):
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# Create a temporary buffer to store the audio
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audio_buffer = io.BytesIO()
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# GPT_model_path, SoVITS_model_path, ref_audio_path, ref_text, ref_language, target_text, text_language, output_path
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# Synthesize audio and get the result
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path = "idols/kurari/kurari.wav"
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if character_name == "saotome":
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path = "idols/saotome/saotome.wav"
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GPT_model_path = "GPT_SoVITS/pretrained_models/saotome-e30.ckpt"
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SoVITS_model_path = "GPT_SoVITS/pretrained_models/saotome_e9_s522_l32.pth"
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ref_text = "今日は友達と一緒に映画を見に行く予定ですが、天気が悪くて少し心配です。"
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ref_language = "日文"
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synthesis_result = synthesize(
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GPT_model_path = GPT_model_path,
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SoVITS_model_path = SoVITS_model_path,
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ref_audio_path = path,
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ref_text = ref_text,
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ref_language = ref_language,
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target_text = target_text,
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text_language = text_language,
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output_path = output_path # Don't save to file
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)
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# Get the last audio data and sample rate from synthesis result
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result_list = list(synthesis_result)
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if result_list:
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last_sampling_rate, last_audio_data = result_list[-1]
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# Write audio data to buffer
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# sf.write(audio_buffer, last_audio_data, last_sampling_rate, )
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sf.write(audio_buffer, last_audio_data, last_sampling_rate, format="wav")
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audio_buffer.seek(0)
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# Return audio as streaming response
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return StreamingResponse(
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audio_buffer,
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media_type="audio/wav",
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headers={"Content-Disposition": "attachment; filename=output.wav"}
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)
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return JSONResponse({"error": "Failed to generate audio"}, status_code=400)
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def version_4_cli(
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GPT_model_path = "GPT_SoVITS/pretrained_models/kurari-e40.ckpt",
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