update

modules/config.py

@@ -5,8 +5,11 @@ from modules.utils.JsonObject import JsonObject
 
 from modules.utils import git
 
+# TODO impl RuntimeEnvVars() class
 runtime_env_vars = JsonObject({})
 
+auto_gc = True
+
 api = None
 
 versions = JsonObject(

modules/denoise.py

@@ -0,0 +1,7 @@
+from audio_denoiser.AudioDenoiser import AudioDenoiser
+import torch
+import torchaudio
+
+
+class TTSAudioDenoiser:
+    pass

modules/devices/devices.py

@@ -120,12 +120,14 @@ dtype_decoder: torch.dtype = torch.float32
 
 
 def reset_device():
+    global device
+    global dtype
+    global dtype_dvae
+    global dtype_vocos
+    global dtype_gpt
+    global dtype_decoder
+
     if config.runtime_env_vars.half:
-        global dtype
-        global dtype_dvae
-        global dtype_vocos
-        global dtype_gpt
-        global dtype_decoder
         dtype = torch.float16
         dtype_dvae = torch.float16
         dtype_vocos = torch.float16
@@ -133,15 +135,21 @@ def reset_device():
         dtype_decoder = torch.float16
 
         logger.info("Using half precision: torch.float16")
+    else:
+        dtype = torch.float32
+        dtype_dvae = torch.float32
+        dtype_vocos = torch.float32
+        dtype_gpt = torch.float32
+        dtype_decoder = torch.float32
+
+        logger.info("Using full precision: torch.float32")
 
-    if (
-        config.runtime_env_vars.device_id is not None
-        or config.runtime_env_vars.use_cpu is not None
-    ):
-        global device
+    if config.runtime_env_vars.use_cpu == "all":
+        device = cpu
+    else:
         device = get_optimal_device()
 
-        logger.info(f"Using device: {device}")
+    logger.info(f"Using device: {device}")
 
 
 @lru_cache

modules/generate_audio.py

@@ -7,6 +7,7 @@ from modules.utils.SeedContext import SeedContext
 from modules import models, config
 
 import logging
+import gc
 
 from modules.devices import devices
 from typing import Union
@@ -100,7 +101,9 @@ def generate_audio_batch(
 
     sample_rate = 24000
 
-    devices.torch_gc()
+    if config.auto_gc:
+        devices.torch_gc()
+        gc.collect()
 
     return [(sample_rate, np.array(wav).flatten().astype(np.float32)) for wav in wavs]
 

modules/hf.py

@@ -0,0 +1,14 @@
+# 给huggingface space写的兼容代码
+
+try:
+    import spaces
+except:
+
+    class NoneSpaces:
+        def __init__(self):
+            pass
+
+        def GPU(self, fn):
+            return fn
+
+    spaces = NoneSpaces()

modules/models.py

@@ -51,7 +51,8 @@ def initialize_chat_tts():
 def load_chat_tts():
     if chat_tts is None:
         initialize_chat_tts().join()
-    load_event.wait()
+    if chat_tts is None:
+        raise Exception("Failed to load ChatTTS models")
     return chat_tts
 
 

modules/utils/SeedContext.py

@@ -2,6 +2,9 @@ import torch
 import random
 import numpy as np
 from modules.utils import rng
+import logging
+
+logger = logging.getLogger(__name__)
 
 
 def deterministic(seed=0):
@@ -59,8 +62,11 @@ class SeedContext:
         try:
             deterministic(self.seed)
         except Exception as e:
-            raise ValueError(
-                f"Seed must be an integer, but: <{type(self.seed)}> {self.seed}"
+            # raise ValueError(
+            #     f"Seed must be an integer, but: <{type(self.seed)}> {self.seed}"
+            # )
+            logger.warning(
+                f"Deterministic field, with: <{type(self.seed)}> {self.seed}"
             )
 
     def __exit__(self, exc_type, exc_value, traceback):

modules/webui/app.py

@@ -0,0 +1,110 @@
+import logging
+import os
+
+import torch
+import gradio as gr
+
+from modules import config
+
+from modules.webui.tts_tab import create_tts_interface
+from modules.webui.ssml_tab import create_ssml_interface
+from modules.webui.spliter_tab import create_spliter_tab
+from modules.webui.speaker_tab import create_speaker_panel
+from modules.webui.readme_tab import create_readme_tab
+
+logger = logging.getLogger(__name__)
+
+logging.basicConfig(
+    level=os.getenv("LOG_LEVEL", "INFO"),
+    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
+)
+
+
+def webui_init():
+    # fix: If the system proxy is enabled in the Windows system, you need to skip these
+    os.environ["NO_PROXY"] = "localhost,127.0.0.1,0.0.0.0"
+
+    torch._dynamo.config.cache_size_limit = 64
+    torch._dynamo.config.suppress_errors = True
+    torch.set_float32_matmul_precision("high")
+
+    logger.info("WebUI module initialized")
+
+
+def create_app_footer():
+    gradio_version = gr.__version__
+    git_tag = config.versions.git_tag
+    git_commit = config.versions.git_commit
+    git_branch = config.versions.git_branch
+    python_version = config.versions.python_version
+    torch_version = config.versions.torch_version
+
+    config.versions.gradio_version = gradio_version
+
+    gr.Markdown(
+        f"""
+🍦 [ChatTTS-Forge](https://github.com/lenML/ChatTTS-Forge)
+version: [{git_tag}](https://github.com/lenML/ChatTTS-Forge/commit/{git_commit}) | branch: `{git_branch}` | python: `{python_version}` | torch: `{torch_version}`
+        """
+    )
+
+
+def create_interface():
+
+    js_func = """
+    function refresh() {
+        const url = new URL(window.location);
+
+        if (url.searchParams.get('__theme') !== 'dark') {
+            url.searchParams.set('__theme', 'dark');
+            window.location.href = url.href;
+        }
+    }
+    """
+
+    head_js = """
+    <script>
+    </script>
+    """
+
+    with gr.Blocks(js=js_func, head=head_js, title="ChatTTS Forge WebUI") as demo:
+        css = """
+        <style>
+        .big-button {
+            height: 80px;
+        }
+        #input_title div.eta-bar {
+            display: none !important; transform: none !important;
+        }
+        footer {
+            display: none !important;
+        }
+        </style>
+        """
+
+        gr.HTML(css)
+        with gr.Tabs() as tabs:
+            with gr.TabItem("TTS"):
+                create_tts_interface()
+
+            with gr.TabItem("SSML", id="ssml"):
+                ssml_input = create_ssml_interface()
+
+            with gr.TabItem("Spilter"):
+                create_spliter_tab(ssml_input, tabs=tabs)
+
+            if config.runtime_env_vars.webui_experimental:
+                with gr.TabItem("Speaker"):
+                    create_speaker_panel()
+                with gr.TabItem("Denoise"):
+                    gr.Markdown("🚧 Under construction")
+                with gr.TabItem("Inpainting"):
+                    gr.Markdown("🚧 Under construction")
+                with gr.TabItem("ASR"):
+                    gr.Markdown("🚧 Under construction")
+
+            with gr.TabItem("README"):
+                create_readme_tab()
+
+        create_app_footer()
+    return demo

modules/webui/denoise_tab.py

@@ -0,0 +1,5 @@
+import gradio as gr
+
+
+def create_denoise_tab():
+    pass

modules/webui/examples.py

@@ -0,0 +1,164 @@
+example_texts = [
+    {
+        "text": "大🍌，一条大🍌，嘿，你的感觉真的很奇妙  [lbreak]",
+    },
+    {"text": "Big 🍌, a big 🍌, hey, your feeling is really wonderful [lbreak]"},
+    {
+        "text": """
+# 这是 markdown 标题
+
+```
+代码块将跳过
+```
+
+- **文本标准化**:
+  - **Markdown**: 自动检测处理 markdown 格式文本。
+  - **数字转写**: 自动将数字转为模型可识别的文本。
+  - **Emoji 适配**: 自动翻译 emoji 为可读文本。
+  - **基于分词器**: 基于 tokenizer 预处理文本，覆盖模型所有不支持字符范围。
+  - **中英文识别**: 适配英文环境。
+        """
+    },
+    {
+        "text": "天气预报显示，今天会有小雨，请大家出门时记得带伞。降温的天气也提醒我们要适时添衣保暖 [lbreak]",
+    },
+    {
+        "text": "公司的年度总结会议将在下周三举行，请各部门提前准备好相关材料，确保会议顺利进行 [lbreak]",
+    },
+    {
+        "text": "今天的午餐菜单包括烤鸡、沙拉和蔬菜汤，大家可以根据自己的口味选择适合的菜品 [lbreak]",
+    },
+    {
+        "text": "请注意，电梯将在下午两点进行例行维护，预计需要一个小时的时间，请大家在此期间使用楼梯 [lbreak]",
+    },
+    {
+        "text": "图书馆新到了一批书籍，涵盖了文学、科学和历史等多个领域，欢迎大家前来借阅 [lbreak]",
+    },
+    {
+        "text": "电影中梁朝伟扮演的陈永仁的编号27149 [lbreak]",
+    },
+    {
+        "text": "这块黄金重达324.75克 [lbreak]",
+    },
+    {
+        "text": "我们班的最高总分为583分 [lbreak]",
+    },
+    {
+        "text": "12~23 [lbreak]",
+    },
+    {
+        "text": "-1.5~2 [lbreak]",
+    },
+    {
+        "text": "她出生于86年8月18日，她弟弟出生于1995年3月1日 [lbreak]",
+    },
+    {
+        "text": "等会请在12:05请通知我 [lbreak]",
+    },
+    {
+        "text": "今天的最低气温达到-10°C [lbreak]",
+    },
+    {
+        "text": "现场有7/12的观众投出了赞成票 [lbreak]",
+    },
+    {
+        "text": "明天有62％的概率降雨 [lbreak]",
+    },
+    {
+        "text": "随便来几个价格12块5，34.5元，20.1万 [lbreak]",
+    },
+    {
+        "text": "这是固话0421-33441122 [lbreak]",
+    },
+    {
+        "text": "这是手机+86 18544139121 [lbreak]",
+    },
+]
+
+ssml_example1 = """
+<speak version="0.1">
+    <voice spk="Bob" seed="42" style="narration-relaxed">
+        下面是一个 ChatTTS 用于合成多角色多情感的有声书示例[lbreak]
+    </voice>
+    <voice spk="Bob" seed="42" style="narration-relaxed">
+        黛玉冷笑道：[lbreak]
+    </voice>
+    <voice spk="female2" seed="42" style="angry">
+        我说呢 [uv_break] ，亏了绊住，不然，早就飞起来了[lbreak]
+    </voice>
+    <voice spk="Bob" seed="42" style="narration-relaxed">
+        宝玉道：[lbreak]
+    </voice>
+    <voice spk="Alice" seed="42" style="unfriendly">
+        “只许和你玩 [uv_break] ，替你解闷。不过偶然到他那里，就说这些闲话。”[lbreak]
+    </voice>
+    <voice spk="female2" seed="42" style="angry">
+        “好没意思的话！[uv_break] 去不去，关我什么事儿？ 又没叫你替我解闷儿 [uv_break]，还许你不理我呢” [lbreak]
+    </voice>
+    <voice spk="Bob" seed="42" style="narration-relaxed">
+        说着，便赌气回房去了 [lbreak]
+    </voice>
+</speak>
+"""
+ssml_example2 = """
+<speak version="0.1">
+    <voice spk="Bob" seed="42" style="narration-relaxed">
+        使用 prosody 控制生成文本的语速语调和音量，示例如下 [lbreak]
+
+        <prosody>
+            无任何限制将会继承父级voice配置进行生成 [lbreak]
+        </prosody>
+        <prosody rate="1.5">
+            设置 rate 大于1表示加速，小于1为减速 [lbreak]
+        </prosody>
+        <prosody pitch="6">
+            设置 pitch 调整音调，设置为6表示提高6个半音 [lbreak]
+        </prosody>
+        <prosody volume="2">
+            设置 volume 调整音量，设置为2表示提高2个分贝 [lbreak]
+        </prosody>
+
+        在 voice 中无prosody包裹的文本即为默认生成状态下的语音 [lbreak]
+    </voice>
+</speak>
+"""
+ssml_example3 = """
+<speak version="0.1">
+    <voice spk="Bob" seed="42" style="narration-relaxed">
+        使用 break 标签将会简单的 [lbreak]
+        
+        <break time="500" />
+
+        插入一段空白到生成结果中 [lbreak]
+    </voice>
+</speak>
+"""
+
+ssml_example4 = """
+<speak version="0.1">
+    <voice spk="Bob" seed="42" style="excited">
+        temperature for sampling (may be overridden by style or speaker) [lbreak]
+        <break time="500" />
+        温度值用于采样，这个值有可能被 style 或者 speaker 覆盖  [lbreak]
+        <break time="500" />
+        temperature for sampling ，这个值有可能被 style 或者 speaker 覆盖  [lbreak]
+        <break time="500" />
+        温度值用于采样，(may be overridden by style or speaker) [lbreak]
+    </voice>
+</speak>
+"""
+
+ssml_examples = [
+    ssml_example1,
+    ssml_example2,
+    ssml_example3,
+    ssml_example4,
+]
+
+default_ssml = """
+<speak version="0.1">
+  <voice spk="Bob" seed="42" style="narration-relaxed">
+    这里是一个简单的 SSML 示例 [lbreak] 
+  </voice>
+</speak>
+"""

modules/webui/readme_tab.py

@@ -0,0 +1,13 @@
+import gradio as gr
+
+
+def read_local_readme():
+    with open("README.md", "r", encoding="utf-8") as file:
+        content = file.read()
+        content = content[content.index("# ") :]
+        return content
+
+
+def create_readme_tab():
+    readme_content = read_local_readme()
+    gr.Markdown(readme_content)

modules/webui/speaker_tab.py

@@ -0,0 +1,13 @@
+import gradio as gr
+
+from modules.webui.webui_utils import get_speakers
+
+
+# 显示 a b c d 四个选择框，选择一个或多个，然后可以试音，并导出
+def create_speaker_panel():
+    speakers = get_speakers()
+
+    def get_speaker_show_name(spk):
+        pass
+
+    gr.Markdown("🚧 Under construction")

modules/webui/spliter_tab.py

@@ -0,0 +1,168 @@
+import gradio as gr
+import torch
+from modules.normalization import text_normalize
+from modules.webui.webui_utils import (
+    get_speakers,
+    get_styles,
+    split_long_text,
+    synthesize_ssml,
+)
+from modules.webui import webui_config
+from modules.webui.examples import ssml_examples, default_ssml
+
+
+def merge_dataframe_to_ssml(dataframe, spk, style, seed):
+    if style == "*auto":
+        style = None
+    if spk == "-1" or spk == -1:
+        spk = None
+    if seed == -1 or seed == "-1":
+        seed = None
+
+    ssml = ""
+    indent = " " * 2
+
+    for i, row in dataframe.iterrows():
+        ssml += f"{indent}<voice"
+        if spk:
+            ssml += f' spk="{spk}"'
+        if style:
+            ssml += f' style="{style}"'
+        if seed:
+            ssml += f' seed="{seed}"'
+        ssml += ">\n"
+        ssml += f"{indent}{indent}{text_normalize(row[1])}\n"
+        ssml += f"{indent}</voice>\n"
+    return f"<speak version='0.1'>\n{ssml}</speak>"
+
+
+# 长文本处理
+# 可以输入长文本，并选择切割方法，切割之后可以将拼接的SSML发送到SSML tab
+# 根据 。 句号切割，切割之后显示到 data table
+def create_spliter_tab(ssml_input, tabs):
+    speakers = get_speakers()
+
+    def get_speaker_show_name(spk):
+        if spk.gender == "*" or spk.gender == "":
+            return spk.name
+        return f"{spk.gender} : {spk.name}"
+
+    speaker_names = ["*random"] + [
+        get_speaker_show_name(speaker) for speaker in speakers
+    ]
+
+    styles = ["*auto"] + [s.get("name") for s in get_styles()]
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            # 选择说话人 选择风格 选择seed
+            with gr.Group():
+                gr.Markdown("🗣️Speaker")
+                spk_input_text = gr.Textbox(
+                    label="Speaker (Text or Seed)",
+                    value="female2",
+                    show_label=False,
+                )
+                spk_input_dropdown = gr.Dropdown(
+                    choices=speaker_names,
+                    interactive=True,
+                    value="female : female2",
+                    show_label=False,
+                )
+                spk_rand_button = gr.Button(
+                    value="🎲",
+                    variant="secondary",
+                )
+            with gr.Group():
+                gr.Markdown("🎭Style")
+                style_input_dropdown = gr.Dropdown(
+                    choices=styles,
+                    interactive=True,
+                    show_label=False,
+                    value="*auto",
+                )
+            with gr.Group():
+                gr.Markdown("🗣️Seed")
+                infer_seed_input = gr.Number(
+                    value=42,
+                    label="Inference Seed",
+                    show_label=False,
+                    minimum=-1,
+                    maximum=2**32 - 1,
+                )
+                infer_seed_rand_button = gr.Button(
+                    value="🎲",
+                    variant="secondary",
+                )
+
+            send_btn = gr.Button("📩Send to SSML", variant="primary")
+
+        with gr.Column(scale=3):
+            with gr.Group():
+                gr.Markdown("📝Long Text Input")
+                gr.Markdown("- 此页面用于处理超长文本")
+                gr.Markdown("- 切割后，可以选择说话人、风格、seed，然后发送到SSML")
+                long_text_input = gr.Textbox(
+                    label="Long Text Input",
+                    lines=10,
+                    placeholder="输入长文本",
+                    elem_id="long-text-input",
+                    show_label=False,
+                )
+                long_text_split_button = gr.Button("🔪Split Text")
+
+    with gr.Row():
+        with gr.Column(scale=3):
+            with gr.Group():
+                gr.Markdown("🎨Output")
+                long_text_output = gr.DataFrame(
+                    headers=["index", "text", "length"],
+                    datatype=["number", "str", "number"],
+                    elem_id="long-text-output",
+                    interactive=False,
+                    wrap=True,
+                    value=[],
+                )
+
+    spk_input_dropdown.change(
+        fn=lambda x: x.startswith("*") and "-1" or x.split(":")[-1].strip(),
+        inputs=[spk_input_dropdown],
+        outputs=[spk_input_text],
+    )
+    spk_rand_button.click(
+        lambda x: int(torch.randint(0, 2**32 - 1, (1,)).item()),
+        inputs=[spk_input_text],
+        outputs=[spk_input_text],
+    )
+    infer_seed_rand_button.click(
+        lambda x: int(torch.randint(0, 2**32 - 1, (1,)).item()),
+        inputs=[infer_seed_input],
+        outputs=[infer_seed_input],
+    )
+    long_text_split_button.click(
+        split_long_text,
+        inputs=[long_text_input],
+        outputs=[long_text_output],
+    )
+
+    infer_seed_rand_button.click(
+        lambda x: int(torch.randint(0, 2**32 - 1, (1,)).item()),
+        inputs=[infer_seed_input],
+        outputs=[infer_seed_input],
+    )
+
+    send_btn.click(
+        merge_dataframe_to_ssml,
+        inputs=[
+            long_text_output,
+            spk_input_text,
+            style_input_dropdown,
+            infer_seed_input,
+        ],
+        outputs=[ssml_input],
+    )
+
+    def change_tab():
+        return gr.Tabs(selected="ssml")
+
+    send_btn.click(change_tab, inputs=[], outputs=[tabs])

modules/webui/ssml_tab.py

@@ -0,0 +1,55 @@
+import gradio as gr
+from modules.webui.webui_utils import (
+    synthesize_ssml,
+)
+from modules.webui import webui_config
+from modules.webui.examples import ssml_examples, default_ssml
+
+
+def create_ssml_interface():
+    with gr.Row():
+        with gr.Column(scale=3):
+            with gr.Group():
+                gr.Markdown("📝SSML Input")
+                gr.Markdown(f"- 最长{webui_config.ssml_max:,}字符，超过会被截断")
+                gr.Markdown("- 尽量保证使用相同的 seed")
+                gr.Markdown(
+                    "- 关于SSML可以看这个 [文档](https://github.com/lenML/ChatTTS-Forge/blob/main/docs/SSML.md)"
+                )
+                ssml_input = gr.Textbox(
+                    label="SSML Input",
+                    lines=10,
+                    value=default_ssml,
+                    placeholder="输入 SSML 或选择示例",
+                    elem_id="ssml_input",
+                    show_label=False,
+                )
+                ssml_button = gr.Button("🔊Synthesize SSML", variant="primary")
+        with gr.Column(scale=1):
+            with gr.Group():
+                # 参数
+                gr.Markdown("🎛️Parameters")
+                # batch size
+                batch_size_input = gr.Slider(
+                    label="Batch Size",
+                    value=4,
+                    minimum=1,
+                    maximum=webui_config.max_batch_size,
+                    step=1,
+                )
+            with gr.Group():
+                gr.Markdown("🎄Examples")
+                gr.Examples(
+                    examples=ssml_examples,
+                    inputs=[ssml_input],
+                )
+
+    ssml_output = gr.Audio(label="Generated Audio")
+
+    ssml_button.click(
+        synthesize_ssml,
+        inputs=[ssml_input, batch_size_input],
+        outputs=ssml_output,
+    )
+
+    return ssml_input

modules/webui/tts_tab.py

@@ -0,0 +1,248 @@
+import gradio as gr
+import torch
+from modules.webui.webui_utils import (
+    get_speakers,
+    get_styles,
+    refine_text,
+    tts_generate,
+)
+from modules.webui import webui_config
+from modules.webui.examples import example_texts
+from modules import config
+
+
+def create_tts_interface():
+    speakers = get_speakers()
+
+    def get_speaker_show_name(spk):
+        if spk.gender == "*" or spk.gender == "":
+            return spk.name
+        return f"{spk.gender} : {spk.name}"
+
+    speaker_names = ["*random"] + [
+        get_speaker_show_name(speaker) for speaker in speakers
+    ]
+
+    styles = ["*auto"] + [s.get("name") for s in get_styles()]
+
+    history = []
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            with gr.Group():
+                gr.Markdown("🎛️Sampling")
+                temperature_input = gr.Slider(
+                    0.01, 2.0, value=0.3, step=0.01, label="Temperature"
+                )
+                top_p_input = gr.Slider(0.1, 1.0, value=0.7, step=0.1, label="Top P")
+                top_k_input = gr.Slider(1, 50, value=20, step=1, label="Top K")
+                batch_size_input = gr.Slider(
+                    1,
+                    webui_config.max_batch_size,
+                    value=4,
+                    step=1,
+                    label="Batch Size",
+                )
+
+            with gr.Row():
+                with gr.Group():
+                    gr.Markdown("🎭Style")
+                    gr.Markdown("- 后缀为 `_p` 表示带prompt，效果更强但是影响质量")
+                    style_input_dropdown = gr.Dropdown(
+                        choices=styles,
+                        # label="Choose Style",
+                        interactive=True,
+                        show_label=False,
+                        value="*auto",
+                    )
+            with gr.Row():
+                with gr.Group():
+                    gr.Markdown("🗣️Speaker")
+                    with gr.Tabs():
+                        with gr.Tab(label="Pick"):
+                            spk_input_text = gr.Textbox(
+                                label="Speaker (Text or Seed)",
+                                value="female2",
+                                show_label=False,
+                            )
+                            spk_input_dropdown = gr.Dropdown(
+                                choices=speaker_names,
+                                # label="Choose Speaker",
+                                interactive=True,
+                                value="female : female2",
+                                show_label=False,
+                            )
+                            spk_rand_button = gr.Button(
+                                value="🎲",
+                                # tooltip="Random Seed",
+                                variant="secondary",
+                            )
+                            spk_input_dropdown.change(
+                                fn=lambda x: x.startswith("*")
+                                and "-1"
+                                or x.split(":")[-1].strip(),
+                                inputs=[spk_input_dropdown],
+                                outputs=[spk_input_text],
+                            )
+                            spk_rand_button.click(
+                                lambda x: str(torch.randint(0, 2**32 - 1, (1,)).item()),
+                                inputs=[spk_input_text],
+                                outputs=[spk_input_text],
+                            )
+
+                        if config.runtime_env_vars.webui_experimental:
+                            with gr.Tab(label="Upload"):
+                                spk_input_upload = gr.File(label="Speaker (Upload)")
+                                # TODO 读取 speaker
+                                # spk_input_upload.change(
+                                #     fn=lambda x: x.read().decode("utf-8"),
+                                #     inputs=[spk_input_upload],
+                                #     outputs=[spk_input_text],
+                                # )
+            with gr.Group():
+                gr.Markdown("💃Inference Seed")
+                infer_seed_input = gr.Number(
+                    value=42,
+                    label="Inference Seed",
+                    show_label=False,
+                    minimum=-1,
+                    maximum=2**32 - 1,
+                )
+                infer_seed_rand_button = gr.Button(
+                    value="🎲",
+                    # tooltip="Random Seed",
+                    variant="secondary",
+                )
+            use_decoder_input = gr.Checkbox(
+                value=True, label="Use Decoder", visible=False
+            )
+            with gr.Group():
+                gr.Markdown("🔧Prompt engineering")
+                prompt1_input = gr.Textbox(label="Prompt 1")
+                prompt2_input = gr.Textbox(label="Prompt 2")
+                prefix_input = gr.Textbox(label="Prefix")
+
+                if config.runtime_env_vars.webui_experimental:
+                    prompt_audio = gr.File(label="prompt_audio")
+
+            infer_seed_rand_button.click(
+                lambda x: int(torch.randint(0, 2**32 - 1, (1,)).item()),
+                inputs=[infer_seed_input],
+                outputs=[infer_seed_input],
+            )
+        with gr.Column(scale=3):
+            with gr.Row():
+                with gr.Column(scale=4):
+                    with gr.Group():
+                        input_title = gr.Markdown(
+                            "📝Text Input",
+                            elem_id="input-title",
+                        )
+                        gr.Markdown(
+                            f"- 字数限制{webui_config.tts_max:,}字，超过部分截断"
+                        )
+                        gr.Markdown("- 如果尾字吞字不读，可以试试结尾加上 `[lbreak]`")
+                        gr.Markdown(
+                            "- If the input text is all in English, it is recommended to check disable_normalize"
+                        )
+                        text_input = gr.Textbox(
+                            show_label=False,
+                            label="Text to Speech",
+                            lines=10,
+                            placeholder="输入文本或选择示例",
+                            elem_id="text-input",
+                        )
+                        # TODO 字数统计，其实实现很好写，但是就是会触发loading...并且还要和后端交互...
+                        # text_input.change(
+                        #     fn=lambda x: (
+                        #         f"📝Text Input ({len(x)} char)"
+                        #         if x
+                        #         else (
+                        #             "📝Text Input (0 char)"
+                        #             if not x
+                        #             else "📝Text Input (0 char)"
+                        #         )
+                        #     ),
+                        #     inputs=[text_input],
+                        #     outputs=[input_title],
+                        # )
+                        with gr.Row():
+                            contorl_tokens = [
+                                "[laugh]",
+                                "[uv_break]",
+                                "[v_break]",
+                                "[lbreak]",
+                            ]
+
+                            for tk in contorl_tokens:
+                                t_btn = gr.Button(tk)
+                                t_btn.click(
+                                    lambda text, tk=tk: text + " " + tk,
+                                    inputs=[text_input],
+                                    outputs=[text_input],
+                                )
+                with gr.Column(scale=1):
+                    with gr.Group():
+                        gr.Markdown("🎶Refiner")
+                        refine_prompt_input = gr.Textbox(
+                            label="Refine Prompt",
+                            value="[oral_2][laugh_0][break_6]",
+                        )
+                        refine_button = gr.Button("✍️Refine Text")
+                        # TODO 分割句子，使用当前配置拼接为SSML，然后发送到SSML tab
+                        # send_button = gr.Button("📩Split and send to SSML")
+
+                    with gr.Group():
+                        gr.Markdown("🔊Generate")
+                        disable_normalize_input = gr.Checkbox(
+                            value=False, label="Disable Normalize"
+                        )
+                        tts_button = gr.Button(
+                            "🔊Generate Audio",
+                            variant="primary",
+                            elem_classes="big-button",
+                        )
+
+            with gr.Group():
+                gr.Markdown("🎄Examples")
+                sample_dropdown = gr.Dropdown(
+                    choices=[sample["text"] for sample in example_texts],
+                    show_label=False,
+                    value=None,
+                    interactive=True,
+                )
+                sample_dropdown.change(
+                    fn=lambda x: x,
+                    inputs=[sample_dropdown],
+                    outputs=[text_input],
+                )
+
+            with gr.Group():
+                gr.Markdown("🎨Output")
+                tts_output = gr.Audio(label="Generated Audio")
+
+    refine_button.click(
+        refine_text,
+        inputs=[text_input, refine_prompt_input],
+        outputs=[text_input],
+    )
+
+    tts_button.click(
+        tts_generate,
+        inputs=[
+            text_input,
+            temperature_input,
+            top_p_input,
+            top_k_input,
+            spk_input_text,
+            infer_seed_input,
+            use_decoder_input,
+            prompt1_input,
+            prompt2_input,
+            prefix_input,
+            style_input_dropdown,
+            disable_normalize_input,
+            batch_size_input,
+        ],
+        outputs=tts_output,
+    )

modules/webui/webui_config.py

@@ -0,0 +1,4 @@
+tts_max = 1000
+ssml_max = 1000
+spliter_threshold = 100
+max_batch_size = 8

modules/webui/webui_utils.py

@@ -0,0 +1,169 @@
+import os
+import logging
+import sys
+
+import numpy as np
+
+from modules.devices import devices
+from modules.synthesize_audio import synthesize_audio
+from modules.hf import spaces
+from modules.webui import webui_config
+
+logging.basicConfig(
+    level=os.getenv("LOG_LEVEL", "INFO"),
+    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
+)
+
+
+import gradio as gr
+
+import torch
+
+from modules.ssml import parse_ssml
+from modules.SynthesizeSegments import SynthesizeSegments, combine_audio_segments
+
+from modules.speaker import speaker_mgr
+from modules.data import styles_mgr
+
+from modules.api.utils import calc_spk_style
+import modules.generate_audio as generate
+
+from modules.normalization import text_normalize
+from modules import refiner, config
+
+from modules.utils import env, audio
+from modules.SentenceSplitter import SentenceSplitter
+
+
+def get_speakers():
+    return speaker_mgr.list_speakers()
+
+
+def get_styles():
+    return styles_mgr.list_items()
+
+
+def segments_length_limit(segments, total_max: int):
+    ret_segments = []
+    total_len = 0
+    for seg in segments:
+        if "text" not in seg:
+            continue
+        total_len += len(seg["text"])
+        if total_len > total_max:
+            break
+        ret_segments.append(seg)
+    return ret_segments
+
+
+@torch.inference_mode()
+@spaces.GPU
+def synthesize_ssml(ssml: str, batch_size=4):
+    try:
+        batch_size = int(batch_size)
+    except Exception:
+        batch_size = 8
+
+    ssml = ssml.strip()
+
+    if ssml == "":
+        return None
+
+    segments = parse_ssml(ssml)
+    max_len = webui_config.ssml_max
+    segments = segments_length_limit(segments, max_len)
+
+    if len(segments) == 0:
+        return None
+
+    synthesize = SynthesizeSegments(batch_size=batch_size)
+    audio_segments = synthesize.synthesize_segments(segments)
+    combined_audio = combine_audio_segments(audio_segments)
+
+    return audio.pydub_to_np(combined_audio)
+
+
+@torch.inference_mode()
+@spaces.GPU
+def tts_generate(
+    text,
+    temperature,
+    top_p,
+    top_k,
+    spk,
+    infer_seed,
+    use_decoder,
+    prompt1,
+    prompt2,
+    prefix,
+    style,
+    disable_normalize=False,
+    batch_size=4,
+):
+    try:
+        batch_size = int(batch_size)
+    except Exception:
+        batch_size = 4
+
+    max_len = webui_config.tts_max
+    text = text.strip()[0:max_len]
+
+    if text == "":
+        return None
+
+    if style == "*auto":
+        style = None
+
+    if isinstance(top_k, float):
+        top_k = int(top_k)
+
+    params = calc_spk_style(spk=spk, style=style)
+    spk = params.get("spk", spk)
+
+    infer_seed = infer_seed or params.get("seed", infer_seed)
+    temperature = temperature or params.get("temperature", temperature)
+    prefix = prefix or params.get("prefix", prefix)
+    prompt1 = prompt1 or params.get("prompt1", "")
+    prompt2 = prompt2 or params.get("prompt2", "")
+
+    infer_seed = np.clip(infer_seed, -1, 2**32 - 1, out=None, dtype=np.int64)
+    infer_seed = int(infer_seed)
+
+    if not disable_normalize:
+        text = text_normalize(text)
+
+    sample_rate, audio_data = synthesize_audio(
+        text=text,
+        temperature=temperature,
+        top_P=top_p,
+        top_K=top_k,
+        spk=spk,
+        infer_seed=infer_seed,
+        use_decoder=use_decoder,
+        prompt1=prompt1,
+        prompt2=prompt2,
+        prefix=prefix,
+        batch_size=batch_size,
+    )
+
+    audio_data = audio.audio_to_int16(audio_data)
+    return sample_rate, audio_data
+
+
+@torch.inference_mode()
+@spaces.GPU
+def refine_text(text: str, prompt: str):
+    text = text_normalize(text)
+    return refiner.refine_text(text, prompt=prompt)
+
+
+@torch.inference_mode()
+@spaces.GPU
+def split_long_text(long_text_input):
+    spliter = SentenceSplitter(webui_config.spliter_threshold)
+    sentences = spliter.parse(long_text_input)
+    sentences = [text_normalize(s) for s in sentences]
+    data = []
+    for i, text in enumerate(sentences):
+        data.append([i, text, len(text)])
+    return data

webui.py

@@ -1,859 +1,10 @@
-try:
-    import spaces
-except:
-
-    class NoneSpaces:
-        def __init__(self):
-            pass
-
-        def GPU(self, fn):
-            return fn
-
-    spaces = NoneSpaces()
-
 import os
-import logging
-import sys
-
-import numpy as np
-
 from modules.devices import devices
-from modules.synthesize_audio import synthesize_audio
-
-logging.basicConfig(
-    level=os.getenv("LOG_LEVEL", "INFO"),
-    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
-)
-
-
-import gradio as gr
-
-import torch
-
-from modules.ssml import parse_ssml
-from modules.SynthesizeSegments import SynthesizeSegments, combine_audio_segments
-
-from modules.speaker import speaker_mgr
-from modules.data import styles_mgr
-
-from modules.api.utils import calc_spk_style
-import modules.generate_audio as generate
-
-from modules.normalization import text_normalize
-from modules import refiner, config, models
-
-from modules.utils import env, audio
-from modules.SentenceSplitter import SentenceSplitter
-
-# fix: If the system proxy is enabled in the Windows system, you need to skip these
-os.environ["NO_PROXY"] = "localhost,127.0.0.1,0.0.0.0"
-
-torch._dynamo.config.cache_size_limit = 64
-torch._dynamo.config.suppress_errors = True
-torch.set_float32_matmul_precision("high")
-
-webui_config = {
-    "tts_max": 1000,
-    "ssml_max": 5000,
-    "spliter_threshold": 100,
-    "max_batch_size": 8,
-}
-
-
-def get_speakers():
-    return speaker_mgr.list_speakers()
-
-
-def get_styles():
-    return styles_mgr.list_items()
-
-
-def segments_length_limit(segments, total_max: int):
-    ret_segments = []
-    total_len = 0
-    for seg in segments:
-        if "text" not in seg:
-            continue
-        total_len += len(seg["text"])
-        if total_len > total_max:
-            break
-        ret_segments.append(seg)
-    return ret_segments
-
-
-@torch.inference_mode()
-@spaces.GPU
-def synthesize_ssml(ssml: str, batch_size=4):
-    try:
-        batch_size = int(batch_size)
-    except Exception:
-        batch_size = 8
-
-    ssml = ssml.strip()
-
-    if ssml == "":
-        return None
-
-    segments = parse_ssml(ssml)
-    max_len = webui_config["ssml_max"]
-    segments = segments_length_limit(segments, max_len)
-
-    if len(segments) == 0:
-        return None
-
-    models.load_chat_tts()
-    synthesize = SynthesizeSegments(batch_size=batch_size)
-    audio_segments = synthesize.synthesize_segments(segments)
-    combined_audio = combine_audio_segments(audio_segments)
-
-    return audio.pydub_to_np(combined_audio)
-
-
-@torch.inference_mode()
-@spaces.GPU
-def tts_generate(
-    text,
-    temperature,
-    top_p,
-    top_k,
-    spk,
-    infer_seed,
-    use_decoder,
-    prompt1,
-    prompt2,
-    prefix,
-    style,
-    disable_normalize=False,
-    batch_size=4,
-):
-    try:
-        batch_size = int(batch_size)
-    except Exception:
-        batch_size = 4
-
-    max_len = webui_config["tts_max"]
-    text = text.strip()[0:max_len]
-
-    if text == "":
-        return None
-
-    if style == "*auto":
-        style = None
-
-    if isinstance(top_k, float):
-        top_k = int(top_k)
-
-    params = calc_spk_style(spk=spk, style=style)
-    spk = params.get("spk", spk)
-
-    infer_seed = infer_seed or params.get("seed", infer_seed)
-    temperature = temperature or params.get("temperature", temperature)
-    prefix = prefix or params.get("prefix", prefix)
-    prompt1 = prompt1 or params.get("prompt1", "")
-    prompt2 = prompt2 or params.get("prompt2", "")
-
-    infer_seed = np.clip(infer_seed, -1, 2**32 - 1, out=None, dtype=np.int64)
-    infer_seed = int(infer_seed)
-
-    if not disable_normalize:
-        text = text_normalize(text)
-
-    models.load_chat_tts()
-    sample_rate, audio_data = synthesize_audio(
-        text=text,
-        temperature=temperature,
-        top_P=top_p,
-        top_K=top_k,
-        spk=spk,
-        infer_seed=infer_seed,
-        use_decoder=use_decoder,
-        prompt1=prompt1,
-        prompt2=prompt2,
-        prefix=prefix,
-        batch_size=batch_size,
-    )
-
-    audio_data = audio.audio_to_int16(audio_data)
-    return sample_rate, audio_data
-
-
-@torch.inference_mode()
-@spaces.GPU
-def refine_text(text: str, prompt: str):
-    text = text_normalize(text)
-    return refiner.refine_text(text, prompt=prompt)
-
-
-def read_local_readme():
-    with open("README.md", "r", encoding="utf-8") as file:
-        content = file.read()
-        content = content[content.index("# ") :]
-        return content
-
-
-# 演示示例文本
-sample_texts = [
-    {
-        "text": "大🍌，一条大🍌，嘿，你的感觉真的很奇妙  [lbreak]",
-    },
-    {
-        "text": "天气预报显示，今天会有小雨，请大家出门时记得带伞。降温的天气也提醒我们要适时添衣保暖 [lbreak]",
-    },
-    {
-        "text": "公司的年度总结会议将在下周三举行，请各部门提前准备好相关材料，确保会议顺利进行 [lbreak]",
-    },
-    {
-        "text": "今天的午餐菜单包括烤鸡、���拉和蔬菜汤，大家可以根据自己的口味选择适合的菜品 [lbreak]",
-    },
-    {
-        "text": "请注意，电梯将在下午两点进行例行维护，预计需要一个小时的时间，请大家在此期间使用楼梯 [lbreak]",
-    },
-    {
-        "text": "图书馆新到了一批书籍，涵盖了文学、科学和历史等多个领域，欢迎大家前来借阅 [lbreak]",
-    },
-    {
-        "text": "电影中梁朝伟扮演的陈永仁的编号27149 [lbreak]",
-    },
-    {
-        "text": "这块黄金重达324.75克 [lbreak]",
-    },
-    {
-        "text": "我们班的最高总分为583分 [lbreak]",
-    },
-    {
-        "text": "12~23 [lbreak]",
-    },
-    {
-        "text": "-1.5~2 [lbreak]",
-    },
-    {
-        "text": "她出生于86年8月18日，她弟弟出生于1995年3月1日 [lbreak]",
-    },
-    {
-        "text": "等会请在12:05请通知我 [lbreak]",
-    },
-    {
-        "text": "今天的最低气温达到-10°C [lbreak]",
-    },
-    {
-        "text": "现场有7/12的观众投出了赞成票 [lbreak]",
-    },
-    {
-        "text": "明天有62％的概率降雨 [lbreak]",
-    },
-    {
-        "text": "随便来几个价格12块5，34.5元，20.1万 [lbreak]",
-    },
-    {
-        "text": "这是固话0421-33441122 [lbreak]",
-    },
-    {
-        "text": "这是手机+86 18544139121 [lbreak]",
-    },
-]
-
-ssml_example1 = """
-<speak version="0.1">
-    <voice spk="Bob" seed="42" style="narration-relaxed">
-        下面是一个 ChatTTS 用于合成多角色多情感的有声书示例[lbreak]
-    </voice>
-    <voice spk="Bob" seed="42" style="narration-relaxed">
-        黛玉冷笑道：[lbreak]
-    </voice>
-    <voice spk="female2" seed="42" style="angry">
-        我说呢 [uv_break] ，亏了绊住，不然，早就飞起来了[lbreak]
-    </voice>
-    <voice spk="Bob" seed="42" style="narration-relaxed">
-        宝玉道：[lbreak]
-    </voice>
-    <voice spk="Alice" seed="42" style="unfriendly">
-        “只许和你玩 [uv_break] ，替你解闷。不过偶然到他那里，就说这些闲话。”[lbreak]
-    </voice>
-    <voice spk="female2" seed="42" style="angry">
-        “好没意思的话！[uv_break] 去不去，关我什么事儿？ 又没叫你替我解闷儿 [uv_break]，还许你不理我呢” [lbreak]
-    </voice>
-    <voice spk="Bob" seed="42" style="narration-relaxed">
-        说着，便赌气回房去了 [lbreak]
-    </voice>
-</speak>
-"""
-ssml_example2 = """
-<speak version="0.1">
-    <voice spk="Bob" seed="42" style="narration-relaxed">
-        使用 prosody 控制生成文本的语速语调和音量，示例如下 [lbreak]
-
-        <prosody>
-            无任何限制将会继承父级voice配置进行生成 [lbreak]
-        </prosody>
-        <prosody rate="1.5">
-            设置 rate 大于1表示加速，小于1为减速 [lbreak]
-        </prosody>
-        <prosody pitch="6">
-            设置 pitch 调整音调，设置为6表示提高6个半音 [lbreak]
-        </prosody>
-        <prosody volume="2">
-            设置 volume 调整音量，设置为2表示提高2个分贝 [lbreak]
-        </prosody>
-
-        在 voice 中无prosody包裹的文本即为默认生成状态下的语音 [lbreak]
-    </voice>
-</speak>
-"""
-ssml_example3 = """
-<speak version="0.1">
-    <voice spk="Bob" seed="42" style="narration-relaxed">
-        使用 break 标签将会简单的 [lbreak]
-        
-        <break time="500" />
-
-        插入一段空白到生成结果中 [lbreak]
-    </voice>
-</speak>
-"""
-
-ssml_example4 = """
-<speak version="0.1">
-    <voice spk="Bob" seed="42" style="excited">
-        temperature for sampling (may be overridden by style or speaker) [lbreak]
-        <break time="500" />
-        温度值用于采样，这个值有可能被 style 或者 speaker 覆盖  [lbreak]
-        <break time="500" />
-        temperature for sampling ，这个值有可能被 style 或者 speaker 覆盖  [lbreak]
-        <break time="500" />
-        温度值用于采样，(may be overridden by style or speaker) [lbreak]
-    </voice>
-</speak>
-"""
-
-default_ssml = """
-<speak version="0.1">
-  <voice spk="Bob" seed="42" style="narration-relaxed">
-    这里是一个简单的 SSML 示例 [lbreak] 
-  </voice>
-</speak>
-"""
-
-
-def create_tts_interface():
-    speakers = get_speakers()
-
-    def get_speaker_show_name(spk):
-        if spk.gender == "*" or spk.gender == "":
-            return spk.name
-        return f"{spk.gender} : {spk.name}"
-
-    speaker_names = ["*random"] + [
-        get_speaker_show_name(speaker) for speaker in speakers
-    ]
-
-    styles = ["*auto"] + [s.get("name") for s in get_styles()]
-
-    history = []
-
-    with gr.Row():
-        with gr.Column(scale=1):
-            with gr.Group():
-                gr.Markdown("🎛️Sampling")
-                temperature_input = gr.Slider(
-                    0.01, 2.0, value=0.3, step=0.01, label="Temperature"
-                )
-                top_p_input = gr.Slider(0.1, 1.0, value=0.7, step=0.1, label="Top P")
-                top_k_input = gr.Slider(1, 50, value=20, step=1, label="Top K")
-                batch_size_input = gr.Slider(
-                    1,
-                    webui_config["max_batch_size"],
-                    value=4,
-                    step=1,
-                    label="Batch Size",
-                )
-
-            with gr.Row():
-                with gr.Group():
-                    gr.Markdown("🎭Style")
-                    gr.Markdown("- 后缀为 `_p` 表示带prompt，效果更强但是影响质量")
-                    style_input_dropdown = gr.Dropdown(
-                        choices=styles,
-                        # label="Choose Style",
-                        interactive=True,
-                        show_label=False,
-                        value="*auto",
-                    )
-            with gr.Row():
-                with gr.Group():
-                    gr.Markdown("🗣️Speaker (Name or Seed)")
-                    spk_input_text = gr.Textbox(
-                        label="Speaker (Text or Seed)",
-                        value="female2",
-                        show_label=False,
-                    )
-                    spk_input_dropdown = gr.Dropdown(
-                        choices=speaker_names,
-                        # label="Choose Speaker",
-                        interactive=True,
-                        value="female : female2",
-                        show_label=False,
-                    )
-                    spk_rand_button = gr.Button(
-                        value="🎲",
-                        # tooltip="Random Seed",
-                        variant="secondary",
-                    )
-                    spk_input_dropdown.change(
-                        fn=lambda x: x.startswith("*")
-                        and "-1"
-                        or x.split(":")[-1].strip(),
-                        inputs=[spk_input_dropdown],
-                        outputs=[spk_input_text],
-                    )
-                    spk_rand_button.click(
-                        lambda x: str(torch.randint(0, 2**32 - 1, (1,)).item()),
-                        inputs=[spk_input_text],
-                        outputs=[spk_input_text],
-                    )
-            with gr.Group():
-                gr.Markdown("💃Inference Seed")
-                infer_seed_input = gr.Number(
-                    value=42,
-                    label="Inference Seed",
-                    show_label=False,
-                    minimum=-1,
-                    maximum=2**32 - 1,
-                )
-                infer_seed_rand_button = gr.Button(
-                    value="🎲",
-                    # tooltip="Random Seed",
-                    variant="secondary",
-                )
-            use_decoder_input = gr.Checkbox(
-                value=True, label="Use Decoder", visible=False
-            )
-            with gr.Group():
-                gr.Markdown("🔧Prompt engineering")
-                prompt1_input = gr.Textbox(label="Prompt 1")
-                prompt2_input = gr.Textbox(label="Prompt 2")
-                prefix_input = gr.Textbox(label="Prefix")
-
-            infer_seed_rand_button.click(
-                lambda x: int(torch.randint(0, 2**32 - 1, (1,)).item()),
-                inputs=[infer_seed_input],
-                outputs=[infer_seed_input],
-            )
-        with gr.Column(scale=3):
-            with gr.Row():
-                with gr.Column(scale=4):
-                    with gr.Group():
-                        input_title = gr.Markdown(
-                            "📝Text Input",
-                            elem_id="input-title",
-                        )
-                        gr.Markdown(
-                            f"- 字数限制{webui_config['tts_max']:,}字，超过部分截断"
-                        )
-                        gr.Markdown("- 如果尾字吞字不读，可以试试结尾加上 `[lbreak]`")
-                        gr.Markdown(
-                            "- If the input text is all in English, it is recommended to check disable_normalize"
-                        )
-                        text_input = gr.Textbox(
-                            show_label=False,
-                            label="Text to Speech",
-                            lines=10,
-                            placeholder="输入文本或选择示例",
-                            elem_id="text-input",
-                        )
-                        # TODO 字数统计，其实实现很好写，但是就是会触发loading...并且还要和后端交互...
-                        # text_input.change(
-                        #     fn=lambda x: (
-                        #         f"📝Text Input ({len(x)} char)"
-                        #         if x
-                        #         else (
-                        #             "📝Text Input (0 char)"
-                        #             if not x
-                        #             else "📝Text Input (0 char)"
-                        #         )
-                        #     ),
-                        #     inputs=[text_input],
-                        #     outputs=[input_title],
-                        # )
-                        with gr.Row():
-                            contorl_tokens = [
-                                "[laugh]",
-                                "[uv_break]",
-                                "[v_break]",
-                                "[lbreak]",
-                            ]
-
-                            for tk in contorl_tokens:
-                                t_btn = gr.Button(tk)
-                                t_btn.click(
-                                    lambda text, tk=tk: text + " " + tk,
-                                    inputs=[text_input],
-                                    outputs=[text_input],
-                                )
-                with gr.Column(scale=1):
-                    with gr.Group():
-                        gr.Markdown("🎶Refiner")
-                        refine_prompt_input = gr.Textbox(
-                            label="Refine Prompt",
-                            value="[oral_2][laugh_0][break_6]",
-                        )
-                        refine_button = gr.Button("✍️Refine Text")
-                        # TODO 分割句子，使用当前配置拼接为SSML，然后发送到SSML tab
-                        # send_button = gr.Button("📩Split and send to SSML")
-
-                    with gr.Group():
-                        gr.Markdown("🔊Generate")
-                        disable_normalize_input = gr.Checkbox(
-                            value=False, label="Disable Normalize"
-                        )
-                        tts_button = gr.Button(
-                            "🔊Generate Audio",
-                            variant="primary",
-                            elem_classes="big-button",
-                        )
-
-            with gr.Group():
-                gr.Markdown("🎄Examples")
-                sample_dropdown = gr.Dropdown(
-                    choices=[sample["text"] for sample in sample_texts],
-                    show_label=False,
-                    value=None,
-                    interactive=True,
-                )
-                sample_dropdown.change(
-                    fn=lambda x: x,
-                    inputs=[sample_dropdown],
-                    outputs=[text_input],
-                )
-
-            with gr.Group():
-                gr.Markdown("🎨Output")
-                tts_output = gr.Audio(label="Generated Audio")
-
-    refine_button.click(
-        refine_text,
-        inputs=[text_input, refine_prompt_input],
-        outputs=[text_input],
-    )
-
-    tts_button.click(
-        tts_generate,
-        inputs=[
-            text_input,
-            temperature_input,
-            top_p_input,
-            top_k_input,
-            spk_input_text,
-            infer_seed_input,
-            use_decoder_input,
-            prompt1_input,
-            prompt2_input,
-            prefix_input,
-            style_input_dropdown,
-            disable_normalize_input,
-            batch_size_input,
-        ],
-        outputs=tts_output,
-    )
-
-
-def create_ssml_interface():
-    examples = [
-        ssml_example1,
-        ssml_example2,
-        ssml_example3,
-        ssml_example4,
-    ]
-
-    with gr.Row():
-        with gr.Column(scale=3):
-            with gr.Group():
-                gr.Markdown("📝SSML Input")
-                gr.Markdown(f"- 最长{webui_config['ssml_max']:,}字符，超过会被截断")
-                gr.Markdown("- 尽量保证使用相同的 seed")
-                gr.Markdown(
-                    "- 关于SSML可以看这个 [文档](https://github.com/lenML/ChatTTS-Forge/blob/main/docs/SSML.md)"
-                )
-                ssml_input = gr.Textbox(
-                    label="SSML Input",
-                    lines=10,
-                    value=default_ssml,
-                    placeholder="输入 SSML 或选择示例",
-                    elem_id="ssml_input",
-                    show_label=False,
-                )
-                ssml_button = gr.Button("🔊Synthesize SSML", variant="primary")
-        with gr.Column(scale=1):
-            with gr.Group():
-                # 参数
-                gr.Markdown("🎛️Parameters")
-                # batch size
-                batch_size_input = gr.Slider(
-                    label="Batch Size",
-                    value=4,
-                    minimum=1,
-                    maximum=webui_config["max_batch_size"],
-                    step=1,
-                )
-            with gr.Group():
-                gr.Markdown("🎄Examples")
-                gr.Examples(
-                    examples=examples,
-                    inputs=[ssml_input],
-                )
-
-    ssml_output = gr.Audio(label="Generated Audio")
-
-    ssml_button.click(
-        synthesize_ssml,
-        inputs=[ssml_input, batch_size_input],
-        outputs=ssml_output,
-    )
-
-    return ssml_input
-
-
-# NOTE: 这个其实是需要GPU的...但是spaces会自动卸载，所以不太好使，具体处理在text_normalize中兼容
-# @spaces.GPU
-def split_long_text(long_text_input):
-    spliter = SentenceSplitter(webui_config["spliter_threshold"])
-    sentences = spliter.parse(long_text_input)
-    sentences = [text_normalize(s) for s in sentences]
-    data = []
-    for i, text in enumerate(sentences):
-        data.append([i, text, len(text)])
-    return data
-
-
-def merge_dataframe_to_ssml(dataframe, spk, style, seed):
-    if style == "*auto":
-        style = None
-    if spk == "-1" or spk == -1:
-        spk = None
-    if seed == -1 or seed == "-1":
-        seed = None
-
-    ssml = ""
-    indent = " " * 2
-
-    for i, row in dataframe.iterrows():
-        ssml += f"{indent}<voice"
-        if spk:
-            ssml += f' spk="{spk}"'
-        if style:
-            ssml += f' style="{style}"'
-        if seed:
-            ssml += f' seed="{seed}"'
-        ssml += ">\n"
-        ssml += f"{indent}{indent}{text_normalize(row[1])}\n"
-        ssml += f"{indent}</voice>\n"
-    return f"<speak version='0.1'>\n{ssml}</speak>"
-
-
-# 长文本处理
-# 可以输入长文本，并选择切割方法，切割之后可以将拼接的SSML发送到SSML tab
-# 根据 。 句号切割，切割之后显示到 data table
-def create_long_content_tab(ssml_input, tabs):
-    speakers = get_speakers()
-
-    def get_speaker_show_name(spk):
-        if spk.gender == "*" or spk.gender == "":
-            return spk.name
-        return f"{spk.gender} : {spk.name}"
-
-    speaker_names = ["*random"] + [
-        get_speaker_show_name(speaker) for speaker in speakers
-    ]
-
-    styles = ["*auto"] + [s.get("name") for s in get_styles()]
-
-    with gr.Row():
-        with gr.Column(scale=1):
-            # 选择说话人 选择风格 选择seed
-            with gr.Group():
-                gr.Markdown("🗣️Speaker")
-                spk_input_text = gr.Textbox(
-                    label="Speaker (Text or Seed)",
-                    value="female2",
-                    show_label=False,
-                )
-                spk_input_dropdown = gr.Dropdown(
-                    choices=speaker_names,
-                    interactive=True,
-                    value="female : female2",
-                    show_label=False,
-                )
-                spk_rand_button = gr.Button(
-                    value="🎲",
-                    variant="secondary",
-                )
-            with gr.Group():
-                gr.Markdown("🎭Style")
-                style_input_dropdown = gr.Dropdown(
-                    choices=styles,
-                    interactive=True,
-                    show_label=False,
-                    value="*auto",
-                )
-            with gr.Group():
-                gr.Markdown("🗣️Seed")
-                infer_seed_input = gr.Number(
-                    value=42,
-                    label="Inference Seed",
-                    show_label=False,
-                    minimum=-1,
-                    maximum=2**32 - 1,
-                )
-                infer_seed_rand_button = gr.Button(
-                    value="🎲",
-                    variant="secondary",
-                )
-
-            send_btn = gr.Button("📩Send to SSML", variant="primary")
-
-        with gr.Column(scale=3):
-            with gr.Group():
-                gr.Markdown("📝Long Text Input")
-                gr.Markdown("- 此页面用于处理超长文本")
-                gr.Markdown("- 切割后，可以选择说话人、风格、seed，然后发送到SSML")
-                long_text_input = gr.Textbox(
-                    label="Long Text Input",
-                    lines=10,
-                    placeholder="输入长文本",
-                    elem_id="long-text-input",
-                    show_label=False,
-                )
-                long_text_split_button = gr.Button("🔪Split Text")
-
-    with gr.Row():
-        with gr.Column(scale=3):
-            with gr.Group():
-                gr.Markdown("🎨Output")
-                long_text_output = gr.DataFrame(
-                    headers=["index", "text", "length"],
-                    datatype=["number", "str", "number"],
-                    elem_id="long-text-output",
-                    interactive=False,
-                    wrap=True,
-                    value=[],
-                )
-
-    spk_input_dropdown.change(
-        fn=lambda x: x.startswith("*") and "-1" or x.split(":")[-1].strip(),
-        inputs=[spk_input_dropdown],
-        outputs=[spk_input_text],
-    )
-    spk_rand_button.click(
-        lambda x: int(torch.randint(0, 2**32 - 1, (1,)).item()),
-        inputs=[spk_input_text],
-        outputs=[spk_input_text],
-    )
-    infer_seed_rand_button.click(
-        lambda x: int(torch.randint(0, 2**32 - 1, (1,)).item()),
-        inputs=[infer_seed_input],
-        outputs=[infer_seed_input],
-    )
-    long_text_split_button.click(
-        split_long_text,
-        inputs=[long_text_input],
-        outputs=[long_text_output],
-    )
-
-    infer_seed_rand_button.click(
-        lambda x: int(torch.randint(0, 2**32 - 1, (1,)).item()),
-        inputs=[infer_seed_input],
-        outputs=[infer_seed_input],
-    )
-
-    send_btn.click(
-        merge_dataframe_to_ssml,
-        inputs=[
-            long_text_output,
-            spk_input_text,
-            style_input_dropdown,
-            infer_seed_input,
-        ],
-        outputs=[ssml_input],
-    )
-
-    def change_tab():
-        return gr.Tabs(selected="ssml")
-
-    send_btn.click(change_tab, inputs=[], outputs=[tabs])
-
-
-def create_readme_tab():
-    readme_content = read_local_readme()
-    gr.Markdown(readme_content)
-
-
-def create_app_footer():
-    gradio_version = gr.__version__
-    git_tag = config.versions.git_tag
-    git_commit = config.versions.git_commit
-    git_branch = config.versions.git_branch
-    python_version = config.versions.python_version
-    torch_version = config.versions.torch_version
-
-    config.versions.gradio_version = gradio_version
-
-    gr.Markdown(
-        f"""
-🍦 [ChatTTS-Forge](https://github.com/lenML/ChatTTS-Forge)
-version: [{git_tag}](https://github.com/lenML/ChatTTS-Forge/commit/{git_commit}) | branch: `{git_branch}` | python: `{python_version}` | torch: `{torch_version}`
-        """
-    )
-
-
-def create_interface():
-
-    js_func = """
-    function refresh() {
-        const url = new URL(window.location);
-
-        if (url.searchParams.get('__theme') !== 'dark') {
-            url.searchParams.set('__theme', 'dark');
-            window.location.href = url.href;
-        }
-    }
-    """
-
-    head_js = """
-    <script>
-    </script>
-    """
-
-    with gr.Blocks(js=js_func, head=head_js, title="ChatTTS Forge WebUI") as demo:
-        css = """
-        <style>
-        .big-button {
-            height: 80px;
-        }
-        #input_title div.eta-bar {
-            display: none !important; transform: none !important;
-        }
-        footer {
-            display: none !important;
-        }
-        </style>
-        """
-
-        gr.HTML(css)
-        with gr.Tabs() as tabs:
-            with gr.TabItem("TTS"):
-                create_tts_interface()
-
-            with gr.TabItem("SSML", id="ssml"):
-                ssml_input = create_ssml_interface()
-
-            with gr.TabItem("Long Text"):
-                create_long_content_tab(ssml_input, tabs=tabs)
-
-            with gr.TabItem("README"):
-                create_readme_tab()
-
-        create_app_footer()
-    return demo
-
+from modules.utils import env
+from modules.webui import webui_config
+from modules.webui.app import webui_init, create_interface
+from modules import generate_audio
+from modules import config
 
 if __name__ == "__main__":
     import argparse
@@ -916,6 +67,12 @@ if __name__ == "__main__":
         type=str.lower,
     )
     parser.add_argument("--compile", action="store_true", help="Enable model compile")
+    # webui_Experimental
+    parser.add_argument(
+        "--webui_experimental",
+        action="store_true",
+        help="Enable webui_experimental features",
+    )
 
     args = parser.parse_args()
 
@@ -936,20 +93,23 @@ if __name__ == "__main__":
     device_id = get_and_update_env(args, "device_id", None, str)
     use_cpu = get_and_update_env(args, "use_cpu", [], list)
     compile = get_and_update_env(args, "compile", False, bool)
+    webui_experimental = get_and_update_env(args, "webui_experimental", False, bool)
 
-    webui_config["tts_max"] = get_and_update_env(args, "tts_max_len", 1000, int)
-    webui_config["ssml_max"] = get_and_update_env(args, "ssml_max_len", 5000, int)
-    webui_config["max_batch_size"] = get_and_update_env(args, "max_batch_size", 8, int)
+    webui_config.tts_max = get_and_update_env(args, "tts_max_len", 1000, int)
+    webui_config.ssml_max = get_and_update_env(args, "ssml_max_len", 5000, int)
+    webui_config.max_batch_size = get_and_update_env(args, "max_batch_size", 8, int)
 
     demo = create_interface()
 
     if auth:
         auth = tuple(auth.split(":"))
 
-    generate.setup_lru_cache()
+    generate_audio.setup_lru_cache()
     devices.reset_device()
     devices.first_time_calculation()
 
+    webui_init()
+
     demo.queue().launch(
         server_name=server_name,
         server_port=server_port,