diff --git a/GPT_SoVITS/TTS_infer_pack/TTS.py b/GPT_SoVITS/TTS_infer_pack/TTS.py
index 690be18..c5f227c 100644
--- a/GPT_SoVITS/TTS_infer_pack/TTS.py
+++ b/GPT_SoVITS/TTS_infer_pack/TTS.py
@@ -844,6 +844,7 @@ class TTS:
             self.vits_model = None
             self.init_t2s_weights(self.configs.t2s_weights_path)
             self.init_vits_weights(self.configs.vits_weights_path)
+            raise e
         finally:
             self.empty_cache()
     
diff --git a/GPT_SoVITS/TTS_infer_pack/text_segmentation_method.py b/GPT_SoVITS/TTS_infer_pack/text_segmentation_method.py
index eb25610..2608f4c 100644
--- a/GPT_SoVITS/TTS_infer_pack/text_segmentation_method.py
+++ b/GPT_SoVITS/TTS_infer_pack/text_segmentation_method.py
@@ -16,6 +16,9 @@ def get_method(name:str)->Callable:
         raise ValueError(f"Method {name} not found")
     return method
 
+def get_method_names()->list:
+    return list(METHODS.keys())
+
 def register_method(name):
     def decorator(func):
         METHODS[name] = func
diff --git a/api_v2.py b/api_v2.py
new file mode 100644
index 0000000..5018059
--- /dev/null
+++ b/api_v2.py
@@ -0,0 +1,443 @@
+"""
+# WebAPI文档
+
+` python api_v2.py -a 127.0.0.1 -p 9880 -c GPT_SoVITS/configs/tts_infer.yaml `
+
+## 执行参数:
+    `-a` - `绑定地址, 默认"127.0.0.1"`
+    `-p` - `绑定端口, 默认9880`
+    `-c` - `TTS配置文件路径, 默认"GPT_SoVITS/configs/tts_infer.yaml"`
+
+## 调用:
+
+### 推理
+
+endpoint: `/tts`
+GET:
+```
+http://127.0.0.1:9880/tts?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_lang=zh&ref_audio_path=archive_jingyuan_1.wav&prompt_lang=zh&prompt_text=我是「罗浮」云骑将军景元。不必拘谨，「将军」只是一时的身份，你称呼我景元便可&text_split_method=cut5&batch_size=1&media_type=wav&streaming_mode=true
+```
+
+POST:
+```json
+{
+    "text": "",                   # str.(required) text to be synthesized
+    "text_lang": "",               # str.(required) language of the text to be synthesized
+    "ref_audio_path": "",         # str.(required) reference audio path.
+    "prompt_text": "",            # str.(optional) prompt text for the reference audio
+    "prompt_lang": "",            # str.(required) language of the prompt text for the reference audio
+    "top_k": 5,                   # int.(optional) top k sampling
+    "top_p": 1,                   # float.(optional) top p sampling
+    "temperature": 1,             # float.(optional) temperature for sampling
+    "text_split_method": "cut5",  # str.(optional) text split method, see text_segmentation_method.py for details.
+    "batch_size": 1,              # int.(optional) batch size for inference
+    "batch_threshold": 0.75,      # float.(optional) threshold for batch splitting.
+    "split_bucket": true,          # bool.(optional) whether to split the batch into multiple buckets.
+    "speed_factor":1.0,           # float.(optional) control the speed of the synthesized audio.
+    "fragment_interval":0.3,      # float.(optional) to control the interval of the audio fragment.
+    "seed": -1,                   # int.(optional) random seed for reproducibility.
+    "media_type": "wav",          # str.(optional) media type of the output audio, support "wav", "raw", "ogg", "aac".
+    "streaming_mode": false,      # bool.(optional) whether to return a streaming response.
+}
+```
+
+RESP:
+成功: 直接返回 wav 音频流， http code 200
+失败: 返回包含错误信息的 json, http code 400
+
+### 命令控制
+
+endpoint: `/control`
+
+command:
+"restart": 重新运行
+"exit": 结束运行
+
+GET:
+```
+http://127.0.0.1:9880/control?command=restart
+```
+POST:
+```json
+{
+    "command": "restart"
+}
+```
+
+RESP: 无
+
+
+### 切换GPT模型
+
+endpoint: `/set_gpt_weights`
+
+GET:
+```
+http://127.0.0.1:9880/set_gpt_weights?weights_path=GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt
+```
+RESP: 
+成功: 返回"success", http code 200
+失败: 返回包含错误信息的 json, http code 400
+
+
+### 切换Sovits模型
+
+endpoint: `/set_sovits_weights`
+
+GET:
+```
+http://127.0.0.1:9880/set_sovits_weights?weights_path=GPT_SoVITS/pretrained_models/s2G488k.pth
+```
+
+RESP: 
+成功: 返回"success", http code 200
+失败: 返回包含错误信息的 json, http code 400
+    
+"""
+import os
+import sys
+import traceback
+from typing import Generator
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+sys.path.append("%s/GPT_SoVITS" % (now_dir))
+
+import argparse
+import subprocess
+import wave
+import signal
+import numpy as np
+import soundfile as sf
+from fastapi import FastAPI, Request, HTTPException, Response
+from fastapi.responses import StreamingResponse, JSONResponse
+from fastapi import FastAPI, UploadFile, File
+import uvicorn
+from io import BytesIO
+from tools.i18n.i18n import I18nAuto
+from GPT_SoVITS.TTS_infer_pack.TTS import TTS, TTS_Config
+from GPT_SoVITS.TTS_infer_pack.text_segmentation_method import get_method_names as get_cut_method_names
+from fastapi.responses import StreamingResponse
+from pydantic import BaseModel
+# print(sys.path)
+i18n = I18nAuto()
+cut_method_names = get_cut_method_names()
+
+parser = argparse.ArgumentParser(description="GPT-SoVITS api")
+parser.add_argument("-c", "--tts_config", type=str, default="GPT_SoVITS/configs/tts_infer.yaml", help="tts_infer路径")
+parser.add_argument("-a", "--bind_addr", type=str, default="127.0.0.1", help="default: 127.0.0.1")
+parser.add_argument("-p", "--port", type=int, default="9880", help="default: 9880")
+args = parser.parse_args()
+config_path = args.tts_config
+# device = args.device
+port = args.port
+host = args.bind_addr
+argv = sys.argv
+
+if config_path in [None, ""]:
+    config_path = "GPT-SoVITS/configs/tts_infer.yaml"
+
+tts_config = TTS_Config(config_path)
+tts_pipeline = TTS(tts_config)
+
+APP = FastAPI()
+class TTS_Request(BaseModel):
+    text: str = None
+    text_lang: str = None
+    ref_audio_path: str = None
+    prompt_lang: str = None
+    prompt_text: str = ""
+    top_k:int = 5
+    top_p:float = 1
+    temperature:float = 1
+    text_split_method:str = "cut5"
+    batch_size:int = 1
+    batch_threshold:float = 0.75
+    split_bucket:bool = True
+    speed_factor:float = 1.0
+    fragment_interval:float = 0.3
+    seed:int = -1
+    media_type:str = "wav"
+    streaming_mode:bool = False
+
+### modify from https://github.com/RVC-Boss/GPT-SoVITS/pull/894/files
+def pack_ogg(io_buffer:BytesIO, data:np.ndarray, rate:int):
+    with sf.SoundFile(io_buffer, mode='w', samplerate=rate, channels=1, format='ogg') as audio_file:
+        audio_file.write(data)
+    return io_buffer
+
+
+def pack_raw(io_buffer:BytesIO, data:np.ndarray, rate:int):
+    io_buffer.write(data.tobytes())
+    return io_buffer
+
+
+def pack_wav(io_buffer:BytesIO, data:np.ndarray, rate:int):
+    io_buffer = BytesIO()
+    sf.write(io_buffer, data, rate, format='wav')
+    return io_buffer
+
+def pack_aac(io_buffer:BytesIO, data:np.ndarray, rate:int):
+    process = subprocess.Popen([
+        'ffmpeg',
+        '-f', 's16le',  # 输入16位有符号小端整数PCM
+        '-ar', str(rate),  # 设置采样率
+        '-ac', '1',  # 单声道
+        '-i', 'pipe:0',  # 从管道读取输入
+        '-c:a', 'aac',  # 音频编码器为AAC
+        '-b:a', '192k',  # 比特率
+        '-vn',  # 不包含视频
+        '-f', 'adts',  # 输出AAC数据流格式
+        'pipe:1'  # 将输出写入管道
+    ], stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    out, _ = process.communicate(input=data.tobytes())
+    io_buffer.write(out)
+    return io_buffer
+
+def pack_audio(io_buffer:BytesIO, data:np.ndarray, rate:int, media_type:str):
+    if media_type == "ogg":
+        io_buffer = pack_ogg(io_buffer, data, rate)
+    elif media_type == "aac":
+        io_buffer = pack_aac(io_buffer, data, rate)
+    elif media_type == "wav":
+        io_buffer = pack_wav(io_buffer, data, rate)
+    else:
+        io_buffer = pack_raw(io_buffer, data, rate)
+    io_buffer.seek(0)
+    return io_buffer
+
+
+
+# from https://huggingface.co/spaces/coqui/voice-chat-with-mistral/blob/main/app.py
+def wave_header_chunk(frame_input=b"", channels=1, sample_width=2, sample_rate=32000):
+    # This will create a wave header then append the frame input
+    # It should be first on a streaming wav file
+    # Other frames better should not have it (else you will hear some artifacts each chunk start)
+    wav_buf = BytesIO()
+    with wave.open(wav_buf, "wb") as vfout:
+        vfout.setnchannels(channels)
+        vfout.setsampwidth(sample_width)
+        vfout.setframerate(sample_rate)
+        vfout.writeframes(frame_input)
+
+    wav_buf.seek(0)
+    return wav_buf.read()
+
+
+def handle_control(command:str):
+    if command == "restart":
+        os.execl(sys.executable, sys.executable, *argv)
+    elif command == "exit":
+        os.kill(os.getpid(), signal.SIGTERM)
+        exit(0)
+
+
+def check_params(req:dict):
+    text:str = req.get("text", "")
+    text_lang:str = req.get("text_lang", "")
+    ref_audio_path:str = req.get("ref_audio_path", "")
+    streaming_mode:bool = req.get("streaming_mode", False)
+    media_type:str = req.get("media_type", "wav")
+    prompt_lang:str = req.get("prompt_lang", "")
+    text_split_method:str = req.get("text_split_method", "cut5")
+
+    if ref_audio_path in [None, ""]:
+        return JSONResponse(status_code=400, content={"message": "ref_audio_path is required"})
+    if text in [None, ""]:
+        return JSONResponse(status_code=400, content={"message": "text is required"})
+    if (text_lang in [None, ""]) :
+        return JSONResponse(status_code=400, content={"message": "text_lang is required"})
+    elif text_lang.lower() not in tts_config.languages:
+        return JSONResponse(status_code=400, content={"message": "text_lang is not supported"})
+    if (prompt_lang in [None, ""]) :
+        return JSONResponse(status_code=400, content={"message": "prompt_lang is required"})
+    elif prompt_lang.lower() not in tts_config.languages:
+        return JSONResponse(status_code=400, content={"message": "prompt_lang is not supported"})
+    if media_type not in ["wav", "raw", "ogg", "aac"]:
+        return JSONResponse(status_code=400, content={"message": "media_type is not supported"})
+    elif media_type == "ogg" and  not streaming_mode:
+        return JSONResponse(status_code=400, content={"message": "ogg format is not supported in non-streaming mode"})
+    
+    if text_split_method not in cut_method_names:
+        return JSONResponse(status_code=400, content={"message": f"text_split_method:{text_split_method} is not supported"})
+
+    return None
+
+async def tts_handle(req:dict):
+    """
+    Text to speech handler.
+    
+    Args:
+        req (dict): 
+            {
+                "text": "",                   # str.(required) text to be synthesized
+                "text_lang: "",               # str.(required) language of the text to be synthesized
+                "ref_audio_path": "",         # str.(required) reference audio path
+                "prompt_text": "",            # str.(optional) prompt text for the reference audio
+                "prompt_lang": "",            # str.(required) language of the prompt text for the reference audio
+                "top_k": 5,                   # int. top k sampling
+                "top_p": 1,                   # float. top p sampling
+                "temperature": 1,             # float. temperature for sampling
+                "text_split_method": "cut5",  # str. text split method, see text_segmentation_method.py for details.
+                "batch_size": 1,              # int. batch size for inference
+                "batch_threshold": 0.75,      # float. threshold for batch splitting.
+                "split_bucket: True,          # bool. whether to split the batch into multiple buckets.
+                "speed_factor":1.0,           # float. control the speed of the synthesized audio.
+                "fragment_interval":0.3,      # float. to control the interval of the audio fragment.
+                "seed": -1,                   # int. random seed for reproducibility.
+                "media_type": "wav",          # str. media type of the output audio, support "wav", "raw", "ogg", "aac".
+                "streaming_mode": False,      # bool. whether to return a streaming response.
+            }
+    returns:
+        StreamingResponse: audio stream response.
+    """
+    
+    streaming_mode = req.get("streaming_mode", False)
+    media_type = req.get("media_type", "wav")
+
+    check_res = check_params(req)
+    if check_res is not None:
+        return check_res
+
+    if streaming_mode:
+        req["return_fragment"] = True
+    
+    try:
+        tts_generator=tts_pipeline.run(req)
+        
+        if streaming_mode:
+            def streaming_generator(tts_generator:Generator, media_type:str):
+                if media_type == "wav":
+                    yield wave_header_chunk()
+                    media_type = "raw"
+                for sr, chunk in tts_generator:
+                    yield pack_audio(BytesIO(), chunk, sr, media_type).getvalue()
+            # _media_type = f"audio/{media_type}" if not (streaming_mode and media_type in ["wav", "raw"]) else f"audio/x-{media_type}"
+            return StreamingResponse(streaming_generator(tts_generator, media_type, ), media_type=f"audio/{media_type}")
+    
+        else:
+            sr, audio_data = next(tts_generator)
+            audio_data = pack_audio(BytesIO(), audio_data, sr, media_type).getvalue()
+            return Response(audio_data, media_type=f"audio/{media_type}")
+    except Exception as e:
+        return JSONResponse(status_code=400, content={"message": f"tts failed", "Exception": str(e)})
+    
+
+
+
+
+
+@APP.get("/control")
+async def control(command: str = None):
+    if command is None:
+        return JSONResponse(status_code=400, content={"message": "command is required"})
+    handle_control(command)
+
+
+
+@APP.get("/tts")
+async def tts_get_endpoint(
+                        text: str = None,
+                        text_lang: str = None,
+                        ref_audio_path: str = None,
+                        prompt_lang: str = None,
+                        prompt_text: str = "",
+                        top_k:int = 5,
+                        top_p:float = 1,
+                        temperature:float = 1,
+                        text_split_method:str = "cut0",
+                        batch_size:int = 1,
+                        batch_threshold:float = 0.75,
+                        split_bucket:bool = True,
+                        speed_factor:float = 1.0,
+                        fragment_interval:float = 0.3,
+                        seed:int = -1,
+                        media_type:str = "wav",
+                        streaming_mode:bool = False,
+                        ):
+    req = {
+        "text": text,
+        "text_lang": text_lang.lower(),
+        "ref_audio_path": ref_audio_path,
+        "prompt_text": prompt_text,
+        "prompt_lang": prompt_lang.lower(),
+        "top_k": top_k,
+        "top_p": top_p,
+        "temperature": temperature,
+        "text_split_method": text_split_method,
+        "batch_size":int(batch_size),
+        "batch_threshold":float(batch_threshold),
+        "speed_factor":float(speed_factor),
+        "split_bucket":split_bucket,
+        "fragment_interval":fragment_interval,
+        "seed":seed,
+        "media_type":media_type,
+        "streaming_mode":streaming_mode,
+    }
+    return await tts_handle(req)
+                
+
+@APP.post("/tts")
+async def tts_post_endpoint(request: TTS_Request):
+    req = request.dict()
+    return await tts_handle(req)
+
+
+@APP.get("/set_refer_audio")
+async def set_refer_aduio(refer_audio_path: str = None):
+    try:
+        tts_pipeline.set_ref_audio(refer_audio_path)
+    except Exception as e:
+        return JSONResponse(status_code=400, content={"message": f"set refer audio failed", "Exception": str(e)})
+    return JSONResponse(status_code=200, content={"message": "success"})
+
+
+# @APP.post("/set_refer_audio")
+# async def set_refer_aduio_post(audio_file: UploadFile = File(...)):
+#     try:
+#         # 检查文件类型，确保是音频文件
+#         if not audio_file.content_type.startswith("audio/"):
+#             return JSONResponse(status_code=400, content={"message": "file type is not supported"})
+        
+#         os.makedirs("uploaded_audio", exist_ok=True)
+#         save_path = os.path.join("uploaded_audio", audio_file.filename)
+#         # 保存音频文件到服务器上的一个目录
+#         with open(save_path , "wb") as buffer:
+#             buffer.write(await audio_file.read())
+            
+#         tts_pipeline.set_ref_audio(save_path)
+#     except Exception as e:
+#         return JSONResponse(status_code=400, content={"message": f"set refer audio failed", "Exception": str(e)})
+#     return JSONResponse(status_code=200, content={"message": "success"})
+
+@APP.get("/set_gpt_weights")
+async def set_gpt_weights(weights_path: str = None):
+    try:
+        if weights_path in ["", None]:
+            return JSONResponse(status_code=400, content={"message": "gpt weight path is required"})
+        tts_pipeline.init_t2s_weights(weights_path)
+    except Exception as e:
+        return JSONResponse(status_code=400, content={"message": f"change gpt weight failed", "Exception": str(e)})
+
+    return JSONResponse(status_code=200, content={"message": "success"})
+
+
+@APP.get("/set_sovits_weights")
+async def set_sovits_weights(weights_path: str = None):
+    try:
+        if weights_path in ["", None]:
+            return JSONResponse(status_code=400, content={"message": "sovits weight path is required"})
+        tts_pipeline.init_vits_weights(weights_path)
+    except Exception as e:
+        return JSONResponse(status_code=400, content={"message": f"change sovits weight failed", "Exception": str(e)})
+    return JSONResponse(status_code=200, content={"message": "success"})
+
+
+
+if __name__ == "__main__":
+    try:
+        uvicorn.run(APP, host=host, port=port, workers=1)
+    except Exception as e:
+        traceback.print_exc()
+        os.kill(os.getpid(), signal.SIGTERM)
+        exit(0)
\ No newline at end of file