Update app.py

app.py

@@ -3,33 +3,15 @@
 @author:XuMing([email protected])
 @description: Re-train by TWMAN
 """
-
 import hashlib
 import os
 import ssl
 import subprocess
-
-import gradio as gr
 import torch
 from loguru import logger
 import nltk
-
-import torch.serialization
 from torch.serialization import add_safe_globals
 
-class DummyHParams:
-    pass
-
-# ➕ 加入允許的類別進入 PyTorch 的安全清單中
-add_safe_globals([DummyHParams])
-
-# ✅ 繼續 monkey patch torch.load
-_original_torch_load = torch.load
-def patched_torch_load(*args, **kwargs):
-    return _original_torch_load(*args, **kwargs)
-
-torch.load = patched_torch_load
-
 # 設定 HTTPS context 避免證書錯誤
 ssl._create_default_https_context = ssl._create_unverified_context
 
@@ -51,6 +33,20 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 logger.info(f"device: {device}")
 half = True if device == "cuda" else False
 
+# 允許全局類別 HParams
+class DummyHParams:
+    pass
+
+add_safe_globals([DummyHParams])
+
+# 啟用 patch，強制設置 weights_only=False
+_original_torch_load = torch.load
+def patched_torch_load(*args, **kwargs):
+    kwargs['weights_only'] = False  # 強制設置 weights_only=False
+    return _original_torch_load(*args, **kwargs)
+
+torch.load = patched_torch_load
+
 # 初始化 TTS 模型
 m = TextToSpeech(
     speaker_model_path="DeepLearning101/GPT-SoVITS_TWMAN",
@@ -98,24 +94,6 @@ with gr.Blocks(title="TTS WebUI") as app:
     - [基於機器閱讀理解和指令微調的統一信息抽取框架之診斷書醫囑資訊擷取分析](https://blog.twman.org/2023/07/HugIE.html)    
     """)
     
-    with gr.Group():
-        gr.Markdown("🔤 請輸入要進行語音合成的文字：")
-        with gr.Row():
-            text = gr.Textbox(
-                label="輸入文字（建議 100 字內）",
-                value="床前明月光，疑是地上霜。舉頭望明月，低頭思故鄉。",
-                placeholder="請輸入文字...",
-                lines=3
-            )
-            inference_button = gr.Button("🎤 語音合成", variant="primary")
-            output = gr.Audio(label="🔊 合成的語音")
-
-        inference_button.click(
-            do_tts_wav_predict,
-            [text],
-            [output],
-        )
-
 # 啟動 Gradio App
 app.queue(max_size=10)
 app.launch(share=True, inbrowser=True)