fix: 性能优化、前端转写器配置、任务进度丢失及 MLX Whisper 回退问题修复

### 性能优化
- 后端任务执行从串行锁改为 ThreadPoolExecutor 并发执行（默认3线程）
- 添加 GZipMiddleware 响应压缩 + Nginx gzip 配置
- 数据库连接池参数优化（pool_size=10, max_overflow=20）
- 视频帧提取并行化（ThreadPoolExecutor）
- LLM 重试配置缓存到实例，避免每次请求读 env var
- 前端路由级代码拆分（React.lazy + Suspense）
- Vite manualChunks 拆分 markdown/markmap/vendor
- MarkdownViewer 用 React.memo + useMemo 减少不必要渲染
- NoteHistory Fuse.js 实例 useMemo 缓存
- useTaskPolling 无待处理任务时跳过轮询
- 移除 antd 依赖（NoteForm Alert、modelForm Tag），改用 shadcn/ui

### 前端转写器配置（新功能）
- 新增 TranscriberConfigManager（JSON 文件存储，替代环境变量）
- 新增 GET/POST /transcriber_config API 端点
- 新增 GET /transcriber_models_status 模型下载状态查询
- 新增 POST /transcriber_download 后台模型下载触发
- 前端转写器设置页面：引擎选择、模型大小选择、模型下载管理
- deploy_status 端点同步从配置文件读取

### Bug 修复
- 修复任务进行中切换页面后进度丢失：Home.tsx status 派生逻辑补全中间状态
- 修复 MLX Whisper 静默回退 fast-whisper：移除环境变量门控，macOS 下自动尝试导入
- MLX Whisper 不可用时抛出 RuntimeError 而非静默回退
- 前端展示 MLX Whisper 可用性状态，不可用时禁用保存

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/app/services/note.py

@@ -66,9 +66,11 @@ class NoteGenerator:
     """
 
     def __init__(self):
-        self.model_size: str = "base"
+        from app.services.transcriber_config_manager import TranscriberConfigManager
+        config_manager = TranscriberConfigManager()
+        self.model_size: str = config_manager.get_whisper_model_size()
         self.device: Optional[str] = None
-        self.transcriber_type: str = os.getenv("TRANSCRIBER_TYPE", "fast-whisper")
+        self.transcriber_type: str = config_manager.get_transcriber_type()
         self.transcriber: Transcriber = self._init_transcriber()
         self.video_path: Optional[Path] = None
         self.video_img_urls=[]

backend/app/services/task_serial_executor.py

@@ -1,14 +1,23 @@
-import threading
+import os
+from concurrent.futures import ThreadPoolExecutor, Future
 from typing import Any, Callable
 
 
-class SerialTaskExecutor:
-    def __init__(self):
-        self._lock = threading.Lock()
+class ConcurrentTaskExecutor:
+    """使用线程池并发执行任务，替代原来的串行锁。"""
+
+    def __init__(self, max_workers: int | None = None):
+        self._max_workers = max_workers or int(os.getenv("TASK_MAX_WORKERS", "3"))
+        self._pool = ThreadPoolExecutor(max_workers=self._max_workers)
 
     def run(self, fn: Callable[..., Any], *args: Any, **kwargs: Any) -> Any:
-        with self._lock:
-            return fn(*args, **kwargs)
+        future: Future = self._pool.submit(fn, *args, **kwargs)
+        return future.result()
+
+    def shutdown(self, wait: bool = True):
+        self._pool.shutdown(wait=wait)
 
 
-task_serial_executor = SerialTaskExecutor()
+# 保持向后兼容的导出名
+SerialTaskExecutor = ConcurrentTaskExecutor
+task_serial_executor = ConcurrentTaskExecutor()

backend/app/services/transcriber_config_manager.py

@@ -0,0 +1,58 @@
+import json
+import os
+from pathlib import Path
+from typing import Optional, Dict, Any
+
+
+class TranscriberConfigManager:
+    """管理转写器配置，存储在 JSON 文件中，支持前端动态修改。"""
+
+    def __init__(self, filepath: str = "config/transcriber.json"):
+        self.path = Path(filepath)
+        self.path.parent.mkdir(parents=True, exist_ok=True)
+
+    def _read(self) -> Dict[str, Any]:
+        if not self.path.exists():
+            return {}
+        try:
+            with self.path.open("r", encoding="utf-8") as f:
+                return json.load(f)
+        except Exception:
+            return {}
+
+    def _write(self, data: Dict[str, Any]):
+        with self.path.open("w", encoding="utf-8") as f:
+            json.dump(data, f, ensure_ascii=False, indent=2)
+
+    def get_config(self) -> Dict[str, Any]:
+        """获取当前转写器配置，fallback 到环境变量默认值。"""
+        data = self._read()
+        return {
+            "transcriber_type": data.get(
+                "transcriber_type",
+                os.getenv("TRANSCRIBER_TYPE", "fast-whisper"),
+            ),
+            "whisper_model_size": data.get(
+                "whisper_model_size",
+                os.getenv("WHISPER_MODEL_SIZE", "medium"),
+            ),
+        }
+
+    def update_config(
+        self,
+        transcriber_type: str,
+        whisper_model_size: Optional[str] = None,
+    ) -> Dict[str, Any]:
+        """更新转写器配置并持久化。"""
+        data = self._read()
+        data["transcriber_type"] = transcriber_type
+        if whisper_model_size is not None:
+            data["whisper_model_size"] = whisper_model_size
+        self._write(data)
+        return self.get_config()
+
+    def get_transcriber_type(self) -> str:
+        return self.get_config()["transcriber_type"]
+
+    def get_whisper_model_size(self) -> str:
+        return self.get_config()["whisper_model_size"]