diff --git a/GPT_SoVITS/api_simple.py b/GPT_SoVITS/api_simple.py
new file mode 100644
index 00000000..fa5f3c86
--- /dev/null
+++ b/GPT_SoVITS/api_simple.py
@@ -0,0 +1,363 @@
+"""
+# api.py usage
+
+` python api.py -dr "123.wav" -dt "一二三。" -dl "zh" `
+
+## 执行参数:
+
+`-s` - `SoVITS模型路径, 可在 config.py 中指定`
+`-g` - `GPT模型路径, 可在 config.py 中指定`
+
+调用请求缺少参考音频时使用
+`-dr` - `默认参考音频路径`
+`-dt` - `默认参考音频文本`
+`-dl` - `默认参考音频语种, "中文","英文","日文","zh","en","ja"`
+
+`-d` - `推理设备, "cuda","cpu"`
+`-a` - `绑定地址, 默认"127.0.0.1"`
+`-p` - `绑定端口, 默认9880, 可在 config.py 中指定`
+`-fp` - `覆盖 config.py 使用全精度`
+`-hp` - `覆盖 config.py 使用半精度`
+
+`-hb` - `cnhubert路径`
+`-b` - `bert路径`
+
+## 调用:
+
+### 推理
+
+endpoint: `/`
+
+使用执行参数指定的参考音频:
+GET:
+    `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`
+POST:
+```json
+{
+    "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"
+}
+```
+
+手动指定当次推理所使用的参考音频:
+GET:
+    `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`
+POST:
+```json
+{
+    "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"
+}
+```
+
+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
+
+
+### 更换默认参考音频
+
+endpoint: `/change_refer`
+
+key与推理端一样
+
+GET:
+    `http://127.0.0.1:9880/change_refer?refer_wav_path=123.wav&prompt_text=一二三。&prompt_language=zh`
+POST:
+```json
+{
+    "refer_wav_path": "123.wav",
+    "prompt_text": "一二三。",
+    "prompt_language": "zh"
+}
+```
+
+RESP:
+成功: json, http code 200
+失败: json, 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
+
+"""
+
+
+import argparse
+import os
+import sys
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+sys.path.append("%s/GPT_SoVITS" % (now_dir))
+
+import soundfile as sf
+from fastapi import FastAPI, Request, HTTPException
+from fastapi.responses import StreamingResponse, JSONResponse
+import uvicorn
+from io import BytesIO
+import inference_webui
+from inference_webui import inference as get_tts_wav
+import signal
+import config as global_config
+g_config = global_config.Config()
+# AVAILABLE_COMPUTE = "cuda" if torch.cuda.is_available() else "cpu"
+
+parser = argparse.ArgumentParser(description="GPT-SoVITS api")
+
+parser.add_argument("-s", "--sovits_path", type=str, default=g_config.sovits_path, help="SoVITS模型路径")
+parser.add_argument("-g", "--gpt_path", type=str, default=g_config.gpt_path, help="GPT模型路径")
+
+parser.add_argument("-dr", "--default_refer_path", type=str, default="", help="默认参考音频路径")
+parser.add_argument("-dt", "--default_refer_text", type=str, default="", help="默认参考音频文本")
+parser.add_argument("-dl", "--default_refer_language", type=str, default="", help="默认参考音频语种")
+
+parser.add_argument("-d", "--device", type=str, default=g_config.infer_device, help="cuda / cpu")
+parser.add_argument("-a", "--bind_addr", type=str, default="0.0.0.0", help="default: 0.0.0.0")
+parser.add_argument("-p", "--port", type=int, default=g_config.api_port, help="default: 9880")
+#parser.add_argument("-fp", "--full_precision", action="store_true", default=False, help="覆盖config.is_half为False, 使用全精度")
+#parser.add_argument("-hp", "--half_precision", action="store_true", default=False, help="覆盖config.is_half为True, 使用半精度")
+# bool值的用法为 `python ./api.py -fp ...`
+# 此时 full_precision==True, half_precision==False
+
+parser.add_argument("-hb", "--hubert_path", type=str, default=g_config.cnhubert_path, help="覆盖config.cnhubert_path")
+parser.add_argument("-b", "--bert_path", type=str, default=g_config.bert_path, help="覆盖config.bert_path")
+
+args = parser.parse_args()
+
+sovits_path = args.sovits_path
+gpt_path = args.gpt_path
+
+
+def change_sovits_weights(sovits_path):
+    if sovits_path is not None and sovits_path !="":
+        inference_webui.tts_pipline.init_vits_weights(sovits_path)
+def change_gpt_weights(gpt_path):
+    if gpt_path is not None and gpt_path !="":
+        inference_webui.tts_pipline.init_t2s_weights(gpt_path)
+
+change_sovits_weights(sovits_path)
+change_gpt_weights(gpt_path)
+
+
+class DefaultRefer:
+    def __init__(self, path, text, language):
+        self.path = args.default_refer_path
+        self.text = args.default_refer_text
+        self.language = args.default_refer_language
+
+    def is_ready(self) -> bool:
+        return is_full(self.path, self.text, self.language)
+
+
+default_refer = DefaultRefer(args.default_refer_path, args.default_refer_text, args.default_refer_language)
+
+device = args.device
+port = args.port
+host = args.bind_addr
+
+
+
+def is_empty(*items):  # 任意一项不为空返回False
+    for item in items:
+        if item is not None and item != "":
+            return False
+    return True
+
+
+def is_full(*items):  # 任意一项为空返回False
+    for item in items:
+        if item is None or item == "":
+            return False
+    return True
+
+
+
+dict_language = {
+    "中文": "zh",
+    "英文": "en",
+    "日文": "ja",
+    "ZH": "zh",
+    "EN": "en",
+    "JA": "ja",
+    "zh": "zh",
+    "en": "en",
+    "ja": "ja"
+}
+
+
+def handle_control(command):
+    if command == "restart":
+        os.execl(g_config.python_exec, g_config.python_exec, *sys.argv)
+    elif command == "exit":
+        os.kill(os.getpid(), signal.SIGTERM)
+        exit(0)
+
+
+def handle_change(path, text, language):
+    if is_empty(path, text, language):
+        return JSONResponse({"code": 400, "message": '缺少任意一项以下参数: "path", "text", "language"'}, status_code=400)
+
+    if path != "" or path is not None:
+        default_refer.path = path
+    if text != "" or text is not None:
+        default_refer.text = text
+    if language != "" or language is not None:
+        default_refer.language = language
+
+    print(f"[INFO] 当前默认参考音频路径: {default_refer.path}")
+    print(f"[INFO] 当前默认参考音频文本: {default_refer.text}")
+    print(f"[INFO] 当前默认参考音频语种: {default_refer.language}")
+    print(f"[INFO] is_ready: {default_refer.is_ready()}")
+
+    return JSONResponse({"code": 0, "message": "Success"}, status_code=200)
+
+
+def handle(text, text_language, 
+              refer_wav_path, prompt_text, 
+              prompt_language, top_k, 
+              top_p, temperature, 
+              text_split_method, batch_size, 
+              speed_factor, ref_text_free,
+              split_bucket,fragment_interval,
+              seed):
+    if (
+            refer_wav_path == "" or refer_wav_path is None
+            or prompt_text == "" or prompt_text is None
+            or prompt_language == "" or prompt_language is None
+    ):
+        refer_wav_path, prompt_text, prompt_language = (
+            default_refer.path,
+            default_refer.text,
+            default_refer.language,
+        )
+        if not default_refer.is_ready():
+            return JSONResponse({"code": 400, "message": "未指定参考音频且接口无预设"}, status_code=400)
+    prompt_text = prompt_text.strip("\n")
+    prompt_language, text = prompt_language, text.strip("\n")
+    gen = get_tts_wav(text, text_language, 
+              refer_wav_path, prompt_text, 
+              prompt_language, top_k, 
+              top_p, temperature, 
+              text_split_method, batch_size, 
+              speed_factor, ref_text_free,
+              split_bucket,fragment_interval,
+              seed
+        )
+    audio,_ = next(gen)
+    sampling_rate,audio_data=audio
+
+    wav = BytesIO()
+    sf.write(wav, audio_data, sampling_rate, format="wav")
+    wav.seek(0)
+    return StreamingResponse(wav, media_type="audio/wav")
+
+
+app = FastAPI()
+
+#clark新增-----2024-02-21
+#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
+@app.post("/set_model")
+async def set_model(request: Request):
+    json_post_raw = await request.json()
+    global gpt_path
+    gpt_path=json_post_raw.get("gpt_model_path")
+    global sovits_path
+    sovits_path=json_post_raw.get("sovits_model_path")
+    print("gptpath"+gpt_path+";vitspath"+sovits_path)
+    change_sovits_weights(sovits_path)
+    change_gpt_weights(gpt_path)
+    return "ok"
+# 新增-----end------
+
+@app.post("/control")
+async def control(request: Request):
+    json_post_raw = await request.json()
+    return handle_control(json_post_raw.get("command"))
+
+
+@app.get("/control")
+async def control(command: str = None):
+    return handle_control(command)
+
+
+@app.post("/change_refer")
+async def change_refer(request: Request):
+    json_post_raw = await request.json()
+    return handle_change(
+        json_post_raw.get("refer_wav_path"),
+        json_post_raw.get("prompt_text"),
+        json_post_raw.get("prompt_language")
+    )
+
+
+@app.get("/change_refer")
+async def change_refer(
+        refer_wav_path: str = None,
+        prompt_text: str = None,
+        prompt_language: str = None
+):
+    return handle_change(refer_wav_path, prompt_text, prompt_language)
+
+'''
+@app.post("/")
+async def tts_endpoint(request: Request):
+    json_post_raw = await request.json()
+    return handle(
+        json_post_raw.get("refer_wav_path"),
+        json_post_raw.get("prompt_text"),
+        json_post_raw.get("prompt_language"),
+        json_post_raw.get("text"),
+        json_post_raw.get("text_language"),
+    )
+'''
+
+@app.get("/")
+async def tts_endpoint(
+        refer_wav_path: str = None,
+        prompt_text: str = None,
+        prompt_language: str = None,
+        text: str = None,
+        text_language: str = None,
+        top_k:int =5, 
+        top_p:float =1,
+        temperature:float=1,
+        text_split_method:str="凑四句一切",
+        batch_size:int=20, 
+        speed_factor:float=1,
+        ref_text_free:bool=False,
+        split_bucket:bool=True,
+        fragment_interval:float=0.3,
+        seed:int=-1,
+):
+    return handle(text, text_language, 
+              refer_wav_path, prompt_text, 
+              prompt_language, top_k, 
+              top_p, temperature, 
+              text_split_method, batch_size, 
+              speed_factor, ref_text_free,
+              split_bucket,fragment_interval,
+              seed)
+
+
+if __name__ == "__main__":
+    uvicorn.run(app, host=host, port=port, workers=1)
diff --git a/GPT_SoVITS/inference_webui.py b/GPT_SoVITS/inference_webui.py
index 199948c6..378ca287 100644
--- a/GPT_SoVITS/inference_webui.py
+++ b/GPT_SoVITS/inference_webui.py
@@ -1,17 +1,20 @@
-'''
+"""
 按中英混合识别
 按日英混合识别
 多语种启动切分识别语种
 全部按中文识别
 全部按英文识别
 全部按日文识别
-'''
+"""
+
 import random
 import os, sys
+
 now_dir = os.getcwd()
 sys.path.append(now_dir)
 
 import os, re, logging
+
 logging.getLogger("markdown_it").setLevel(logging.ERROR)
 logging.getLogger("urllib3").setLevel(logging.ERROR)
 logging.getLogger("httpcore").setLevel(logging.ERROR)
@@ -34,7 +37,7 @@ gpt_path = os.environ.get("gpt_path", None)
 sovits_path = os.environ.get("sovits_path", None)
 cnhubert_base_path = os.environ.get("cnhubert_base_path", None)
 bert_path = os.environ.get("bert_path", None)
-        
+
 import gradio as gr
 from TTS_infer_pack.TTS import TTS, TTS_Config
 from TTS_infer_pack.text_segmentation_method import get_method
@@ -50,18 +53,18 @@ if torch.cuda.is_available():
 #     device = "mps"
 else:
     device = "cpu"
-    
+
 dict_language = {
-    i18n("中文"): "all_zh",#全部按中文识别
-    i18n("英文"): "en",#全部按英文识别#######不变
-    i18n("日文"): "all_ja",#全部按日文识别
-    i18n("中英混合"): "zh",#按中英混合识别####不变
-    i18n("日英混合"): "ja",#按日英混合识别####不变
-    i18n("多语种混合"): "auto",#多语种启动切分识别语种
+    i18n("中文"): "all_zh",  # 全部按中文识别
+    i18n("英文"): "en",  # 全部按英文识别#######不变
+    i18n("日文"): "all_ja",  # 全部按日文识别
+    i18n("中英混合"): "zh",  # 按中英混合识别####不变
+    i18n("日英混合"): "ja",  # 按日英混合识别####不变
+    i18n("多语种混合"): "auto",  # 多语种启动切分识别语种
 }
 
 cut_method = {
-    i18n("不切"):"cut0",
+    i18n("不切"): "cut0",
     i18n("凑四句一切"): "cut1",
     i18n("凑50字一切"): "cut2",
     i18n("按中文句号。切"): "cut3",
@@ -80,23 +83,32 @@ if cnhubert_base_path is not None:
     tts_config.cnhuhbert_base_path = cnhubert_base_path
 if bert_path is not None:
     tts_config.bert_base_path = bert_path
-    
+
 print(tts_config)
 tts_pipline = TTS(tts_config)
 gpt_path = tts_config.t2s_weights_path
 sovits_path = tts_config.vits_weights_path
 
-def inference(text, text_lang, 
-              ref_audio_path, prompt_text, 
-              prompt_lang, top_k, 
-              top_p, temperature, 
-              text_split_method, batch_size, 
-              speed_factor, ref_text_free,
-              split_bucket,fragment_interval,
-              seed,
-              ):
+
+def inference(
+    text,
+    text_lang,
+    ref_audio_path,
+    prompt_text,
+    prompt_lang,
+    top_k,
+    top_p,
+    temperature,
+    text_split_method,
+    batch_size,
+    speed_factor,
+    ref_text_free,
+    split_bucket,
+    fragment_interval,
+    seed,
+):
     actual_seed = seed if seed not in [-1, "", None] else random.randrange(1 << 32)
-    inputs={
+    inputs = {
         "text": text,
         "text_lang": dict_language[text_lang],
         "ref_audio_path": ref_audio_path,
@@ -106,19 +118,20 @@ def inference(text, text_lang,
         "top_p": top_p,
         "temperature": temperature,
         "text_split_method": cut_method[text_split_method],
-        "batch_size":int(batch_size),
-        "speed_factor":float(speed_factor),
-        "split_bucket":split_bucket,
-        "return_fragment":False,
-        "fragment_interval":fragment_interval,
-        "seed":actual_seed,
+        "batch_size": int(batch_size),
+        "speed_factor": float(speed_factor),
+        "split_bucket": split_bucket,
+        "return_fragment": False,
+        "fragment_interval": fragment_interval,
+        "seed": actual_seed,
     }
     for item in tts_pipline.run(inputs):
         yield item, actual_seed
-        
+
+
 def custom_sort_key(s):
     # 使用正则表达式提取字符串中的数字部分和非数字部分
-    parts = re.split('(\d+)', s)
+    parts = re.split("(\d+)", s)
     # 将数字部分转换为整数，非数字部分保持不变
     parts = [int(part) if part.isdigit() else part for part in parts]
     return parts
@@ -126,11 +139,16 @@ def custom_sort_key(s):
 
 def change_choices():
     SoVITS_names, GPT_names = get_weights_names()
-    return {"choices": sorted(SoVITS_names, key=custom_sort_key), "__type__": "update"}, {"choices": sorted(GPT_names, key=custom_sort_key), "__type__": "update"}
+    return {
+        "choices": sorted(SoVITS_names, key=custom_sort_key),
+        "__type__": "update",
+    }, {"choices": sorted(GPT_names, key=custom_sort_key), "__type__": "update"}
 
 
 pretrained_sovits_name = "GPT_SoVITS/pretrained_models/s2G488k.pth"
-pretrained_gpt_name = "GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt"
+pretrained_gpt_name = (
+    "GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt"
+)
 SoVITS_weight_root = "SoVITS_weights"
 GPT_weight_root = "GPT_weights"
 os.makedirs(SoVITS_weight_root, exist_ok=True)
@@ -140,122 +158,255 @@ os.makedirs(GPT_weight_root, exist_ok=True)
 def get_weights_names():
     SoVITS_names = [pretrained_sovits_name]
     for name in os.listdir(SoVITS_weight_root):
-        if name.endswith(".pth"): SoVITS_names.append("%s/%s" % (SoVITS_weight_root, name))
+        if name.endswith(".pth"):
+            SoVITS_names.append("%s/%s" % (SoVITS_weight_root, name))
     GPT_names = [pretrained_gpt_name]
     for name in os.listdir(GPT_weight_root):
-        if name.endswith(".ckpt"): GPT_names.append("%s/%s" % (GPT_weight_root, name))
+        if name.endswith(".ckpt"):
+            GPT_names.append("%s/%s" % (GPT_weight_root, name))
     return SoVITS_names, GPT_names
 
 
 SoVITS_names, GPT_names = get_weights_names()
 
-with gr.Blocks(title="GPT-SoVITS WebUI") as app:
-    gr.Markdown(
-        value=i18n("本软件以MIT协议开源, 作者不对软件具备任何控制力, 使用软件者、传播软件导出的声音者自负全责. <br>如不认可该条款, 则不能使用或引用软件包内任何代码和文件. 详见根目录<b>LICENSE</b>.")
-    )
-    
-    with gr.Column():
-        # with gr.Group():
-        gr.Markdown(value=i18n("模型切换"))
-        with gr.Row():
-            GPT_dropdown = gr.Dropdown(label=i18n("GPT模型列表"), choices=sorted(GPT_names, key=custom_sort_key), value=gpt_path, interactive=True)
-            SoVITS_dropdown = gr.Dropdown(label=i18n("SoVITS模型列表"), choices=sorted(SoVITS_names, key=custom_sort_key), value=sovits_path, interactive=True)
-            refresh_button = gr.Button(i18n("刷新模型路径"), variant="primary")
-            refresh_button.click(fn=change_choices, inputs=[], outputs=[SoVITS_dropdown, GPT_dropdown])
-            SoVITS_dropdown.change(tts_pipline.init_vits_weights, [SoVITS_dropdown], [])
-            GPT_dropdown.change(tts_pipline.init_t2s_weights, [GPT_dropdown], [])
-    
-    with gr.Row():
-        with gr.Column():
-            gr.Markdown(value=i18n("*请上传并填写参考信息"))
-            inp_ref = gr.Audio(label=i18n("请上传3~10秒内参考音频，超过会报错！"), type="filepath")
-            prompt_text = gr.Textbox(label=i18n("参考音频的文本"), value="", lines=2)
-            with gr.Row():
-                prompt_language = gr.Dropdown(
-                    label=i18n("参考音频的语种"), choices=[i18n("中文"), i18n("英文"), i18n("日文"), i18n("中英混合"), i18n("日英混合"), i18n("多语种混合")], value=i18n("中文")
-                )
-                with gr.Column():
-                    ref_text_free = gr.Checkbox(label=i18n("开启无参考文本模式。不填参考文本亦相当于开启。"), value=False, interactive=True, show_label=True)
-                    gr.Markdown(i18n("使用无参考文本模式时建议使用微调的GPT，听不清参考音频说的啥(不晓得写啥)可以开，开启后无视填写的参考文本。"))
-    
-        with gr.Column():
-            gr.Markdown(value=i18n("*请填写需要合成的目标文本和语种模式"))
-            text = gr.Textbox(label=i18n("需要合成的文本"), value="", lines=16, max_lines=16)
-            text_language = gr.Dropdown(
-                label=i18n("需要合成的语种"), choices=[i18n("中文"), i18n("英文"), i18n("日文"), i18n("中英混合"), i18n("日英混合"), i18n("多语种混合")], value=i18n("中文")
+if __name__ == "__main__":
+    with gr.Blocks(title="GPT-SoVITS WebUI") as app:
+        gr.Markdown(
+            value=i18n(
+                "本软件以MIT协议开源, 作者不对软件具备任何控制力, 使用软件者、传播软件导出的声音者自负全责. <br>如不认可该条款, 则不能使用或引用软件包内任何代码和文件. 详见根目录<b>LICENSE</b>."
             )
+        )
 
-        
-    with gr.Group():
-        gr.Markdown(value=i18n("推理设置"))
-        with gr.Row():
-
-            with gr.Column():
-                batch_size = gr.Slider(minimum=1,maximum=200,step=1,label=i18n("batch_size"),value=20,interactive=True)
-                fragment_interval = gr.Slider(minimum=0.01,maximum=1,step=0.01,label=i18n("分段间隔(秒)"),value=0.3,interactive=True)
-                speed_factor = gr.Slider(minimum=0.25,maximum=4,step=0.05,label="speed_factor",value=1.0,interactive=True)
-                top_k = gr.Slider(minimum=1,maximum=100,step=1,label=i18n("top_k"),value=5,interactive=True)
-                top_p = gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("top_p"),value=1,interactive=True)
-                temperature = gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("temperature"),value=1,interactive=True)
-            with gr.Column():
-                how_to_cut = gr.Radio(
-                    label=i18n("怎么切"),
-                    choices=[i18n("不切"), i18n("凑四句一切"), i18n("凑50字一切"), i18n("按中文句号。切"), i18n("按英文句号.切"), i18n("按标点符号切"), ],
-                    value=i18n("凑四句一切"),
+        with gr.Column():
+            # with gr.Group():
+            gr.Markdown(value=i18n("模型切换"))
+            with gr.Row():
+                GPT_dropdown = gr.Dropdown(
+                    label=i18n("GPT模型列表"),
+                    choices=sorted(GPT_names, key=custom_sort_key),
+                    value=gpt_path,
                     interactive=True,
                 )
-                with gr.Row():
-                    split_bucket = gr.Checkbox(label=i18n("数据分桶(可能会降低一点计算量，选就对了)"), value=True, interactive=True, show_label=True)
-                    seed = gr.Number(label=i18n("随机种子"),value=-1)
-            # with gr.Column():
-                output = gr.Audio(label=i18n("输出的语音"))
-                with gr.Row():
-                    inference_button = gr.Button(i18n("合成语音"), variant="primary")
-                    stop_infer = gr.Button(i18n("终止合成"), variant="primary")
-                
-        
-        inference_button.click(
-            inference,
-            [
-                text,text_language, inp_ref, 
-                prompt_text, prompt_language, 
-                top_k, top_p, temperature, 
-                how_to_cut, batch_size, 
-                speed_factor, ref_text_free,
-                split_bucket,fragment_interval,
-                seed
-             ],
-            [output, seed],
-        )
-        stop_infer.click(tts_pipline.stop, [], [])
+                SoVITS_dropdown = gr.Dropdown(
+                    label=i18n("SoVITS模型列表"),
+                    choices=sorted(SoVITS_names, key=custom_sort_key),
+                    value=sovits_path,
+                    interactive=True,
+                )
+                refresh_button = gr.Button(i18n("刷新模型路径"), variant="primary")
+                refresh_button.click(
+                    fn=change_choices,
+                    inputs=[],
+                    outputs=[SoVITS_dropdown, GPT_dropdown],
+                )
+                SoVITS_dropdown.change(
+                    tts_pipline.init_vits_weights, [SoVITS_dropdown], []
+                )
+                GPT_dropdown.change(tts_pipline.init_t2s_weights, [GPT_dropdown], [])
 
-    with gr.Group():
-        gr.Markdown(value=i18n("文本切分工具。太长的文本合成出来效果不一定好，所以太长建议先切。合成会根据文本的换行分开合成再拼起来。"))
         with gr.Row():
-            text_inp = gr.Textbox(label=i18n("需要合成的切分前文本"), value="", lines=4)
             with gr.Column():
-                _how_to_cut = gr.Radio(
-                            label=i18n("怎么切"),
-                            choices=[i18n("不切"), i18n("凑四句一切"), i18n("凑50字一切"), i18n("按中文句号。切"), i18n("按英文句号.切"), i18n("按标点符号切"), ],
-                            value=i18n("凑四句一切"),
+                gr.Markdown(value=i18n("*请上传并填写参考信息"))
+                inp_ref = gr.Audio(
+                    label=i18n("请上传3~10秒内参考音频，超过会报错！"), type="filepath"
+                )
+                prompt_text = gr.Textbox(
+                    label=i18n("参考音频的文本"), value="", lines=2
+                )
+                with gr.Row():
+                    prompt_language = gr.Dropdown(
+                        label=i18n("参考音频的语种"),
+                        choices=[
+                            i18n("中文"),
+                            i18n("英文"),
+                            i18n("日文"),
+                            i18n("中英混合"),
+                            i18n("日英混合"),
+                            i18n("多语种混合"),
+                        ],
+                        value=i18n("中文"),
+                    )
+                    with gr.Column():
+                        ref_text_free = gr.Checkbox(
+                            label=i18n(
+                                "开启无参考文本模式。不填参考文本亦相当于开启。"
+                            ),
+                            value=False,
                             interactive=True,
+                            show_label=True,
+                        )
+                        gr.Markdown(
+                            i18n(
+                                "使用无参考文本模式时建议使用微调的GPT，听不清参考音频说的啥(不晓得写啥)可以开，开启后无视填写的参考文本。"
+                            )
                         )
-                cut_text= gr.Button(i18n("切分"), variant="primary")
-            
-            def to_cut(text_inp, how_to_cut):
-                if len(text_inp.strip()) == 0 or text_inp==[]:
-                    return ""
-                method = get_method(cut_method[how_to_cut])
-                return method(text_inp)
-        
-            text_opt = gr.Textbox(label=i18n("切分后文本"), value="", lines=4)
-            cut_text.click(to_cut, [text_inp, _how_to_cut], [text_opt])
-        gr.Markdown(value=i18n("后续将支持转音素、手工修改音素、语音合成分步执行。"))
 
-app.queue(concurrency_count=511, max_size=1022).launch(
-    server_name="0.0.0.0",
-    inbrowser=True,
-    share=is_share,
-    server_port=infer_ttswebui,
-    quiet=True,
-)
+            with gr.Column():
+                gr.Markdown(value=i18n("*请填写需要合成的目标文本和语种模式"))
+                text = gr.Textbox(
+                    label=i18n("需要合成的文本"), value="", lines=16, max_lines=16
+                )
+                text_language = gr.Dropdown(
+                    label=i18n("需要合成的语种"),
+                    choices=[
+                        i18n("中文"),
+                        i18n("英文"),
+                        i18n("日文"),
+                        i18n("中英混合"),
+                        i18n("日英混合"),
+                        i18n("多语种混合"),
+                    ],
+                    value=i18n("中文"),
+                )
+
+        with gr.Group():
+            gr.Markdown(value=i18n("推理设置"))
+            with gr.Row():
+
+                with gr.Column():
+                    batch_size = gr.Slider(
+                        minimum=1,
+                        maximum=200,
+                        step=1,
+                        label=i18n("batch_size"),
+                        value=20,
+                        interactive=True,
+                    )
+                    fragment_interval = gr.Slider(
+                        minimum=0.01,
+                        maximum=1,
+                        step=0.01,
+                        label=i18n("分段间隔(秒)"),
+                        value=0.3,
+                        interactive=True,
+                    )
+                    speed_factor = gr.Slider(
+                        minimum=0.25,
+                        maximum=4,
+                        step=0.05,
+                        label="speed_factor",
+                        value=1.0,
+                        interactive=True,
+                    )
+                    top_k = gr.Slider(
+                        minimum=1,
+                        maximum=100,
+                        step=1,
+                        label=i18n("top_k"),
+                        value=5,
+                        interactive=True,
+                    )
+                    top_p = gr.Slider(
+                        minimum=0,
+                        maximum=1,
+                        step=0.05,
+                        label=i18n("top_p"),
+                        value=1,
+                        interactive=True,
+                    )
+                    temperature = gr.Slider(
+                        minimum=0,
+                        maximum=1,
+                        step=0.05,
+                        label=i18n("temperature"),
+                        value=1,
+                        interactive=True,
+                    )
+                with gr.Column():
+                    how_to_cut = gr.Radio(
+                        label=i18n("怎么切"),
+                        choices=[
+                            i18n("不切"),
+                            i18n("凑四句一切"),
+                            i18n("凑50字一切"),
+                            i18n("按中文句号。切"),
+                            i18n("按英文句号.切"),
+                            i18n("按标点符号切"),
+                        ],
+                        value=i18n("凑四句一切"),
+                        interactive=True,
+                    )
+                    with gr.Row():
+                        split_bucket = gr.Checkbox(
+                            label=i18n("数据分桶(可能会降低一点计算量，选就对了)"),
+                            value=True,
+                            interactive=True,
+                            show_label=True,
+                        )
+                        seed = gr.Number(label=i18n("随机种子"), value=-1)
+                    # with gr.Column():
+                    output = gr.Audio(label=i18n("输出的语音"))
+                    with gr.Row():
+                        inference_button = gr.Button(
+                            i18n("合成语音"), variant="primary"
+                        )
+                        stop_infer = gr.Button(i18n("终止合成"), variant="primary")
+
+            inference_button.click(
+                inference,
+                [
+                    text,
+                    text_language,
+                    inp_ref,
+                    prompt_text,
+                    prompt_language,
+                    top_k,
+                    top_p,
+                    temperature,
+                    how_to_cut,
+                    batch_size,
+                    speed_factor,
+                    ref_text_free,
+                    split_bucket,
+                    fragment_interval,
+                    seed,
+                ],
+                [output, seed],
+            )
+            stop_infer.click(tts_pipline.stop, [], [])
+
+        with gr.Group():
+            gr.Markdown(
+                value=i18n(
+                    "文本切分工具。太长的文本合成出来效果不一定好，所以太长建议先切。合成会根据文本的换行分开合成再拼起来。"
+                )
+            )
+            with gr.Row():
+                text_inp = gr.Textbox(
+                    label=i18n("需要合成的切分前文本"), value="", lines=4
+                )
+                with gr.Column():
+                    _how_to_cut = gr.Radio(
+                        label=i18n("怎么切"),
+                        choices=[
+                            i18n("不切"),
+                            i18n("凑四句一切"),
+                            i18n("凑50字一切"),
+                            i18n("按中文句号。切"),
+                            i18n("按英文句号.切"),
+                            i18n("按标点符号切"),
+                        ],
+                        value=i18n("凑四句一切"),
+                        interactive=True,
+                    )
+                    cut_text = gr.Button(i18n("切分"), variant="primary")
+
+                def to_cut(text_inp, how_to_cut):
+                    if len(text_inp.strip()) == 0 or text_inp == []:
+                        return ""
+                    method = get_method(cut_method[how_to_cut])
+                    return method(text_inp)
+
+                text_opt = gr.Textbox(label=i18n("切分后文本"), value="", lines=4)
+                cut_text.click(to_cut, [text_inp, _how_to_cut], [text_opt])
+            gr.Markdown(
+                value=i18n("后续将支持转音素、手工修改音素、语音合成分步执行。")
+            )
+
+    app.queue(concurrency_count=511, max_size=1022).launch(
+        server_name="0.0.0.0",
+        inbrowser=True,
+        share=is_share,
+        server_port=infer_ttswebui,
+        quiet=True,
+    )