feat: 新增模型管理和供应商配置功能

### v1.1.0
- #### Added
  - 新增 AI 笔记风格选择
  - 新增 AI 笔记返回格式选择
  - 添加 AI 自定义笔记备注 Prompt
  - 添加任务失败重试
  - 添加全局设置页，可在设置页进行模型设置

- #### Optimize
  - 优化前端样式，优化用户体验
  - 增加生成中间产物，可用于失败后加快生成速度
- #### Fix
  - 修复视频截图视频过早删除错误

backend/app/transcriber/whisper.py

@@ -4,14 +4,19 @@ from app.decorators.timeit import timeit
 from app.models.transcriber_model import TranscriptSegment, TranscriptResult
 from app.transcriber.base import Transcriber
 from app.utils.env_checker import is_cuda_available, is_torch_installed
+from app.utils.logger import get_logger
 from app.utils.path_helper import get_model_dir
 
 from events import transcription_finished
+from pathlib import Path
+import os
+from tqdm import tqdm
+from huggingface_hub import snapshot_download
 
 '''
  Size of the model to use (tiny, tiny.en, base, base.en, small, small.en, distil-small.en, medium, medium.en, distil-medium.en, large-v1, large-v2, large-v3, large, distil-large-v2, distil-large-v3, large-v3-turbo, or turbo
 '''
-
+logger=get_logger(__name__)
 
 class WhisperTranscriber(Transcriber):
     # TODO:修改为可配置
@@ -31,15 +36,25 @@ class WhisperTranscriber(Transcriber):
 
         self.compute_type = compute_type or ("float16" if self.device == "cuda" else "int8")
 
-        model_path = get_model_dir("whisper")
+        model_dir = get_model_dir("whisper")
+        model_path = os.path.join(model_dir, f"whisper-{model_size}")
+        if not Path(model_path).exists():
+            logger.info(f"模型 whisper-{model_size} 不存在，开始下载...")
+            repo_id = f"guillaumekln/faster-whisper-{model_size}"
+            snapshot_download(
+                repo_id,
+                local_dir=model_path,
+                local_dir_use_symlinks=False,
+            )
+            logger.info("模型下载完成")
+
         self.model = WhisperModel(
             model_size,
             device=self.device,
-            # compute_type="int8",  # 或 "float16"
+            compute_type=self.compute_type,
             cpu_threads=cpu_threads,
-            download_root=model_path
+            download_root=model_dir
         )
-
     @staticmethod
     def is_torch_installed() -> bool:
         try:
@@ -88,7 +103,7 @@ class WhisperTranscriber(Transcriber):
                 segments=segments,
                 raw=info
             )
-            self.on_finish(file_path, result)
+            # self.on_finish(file_path, result)
             return result
         except Exception as e:
             print(f"转写失败：{e}")