Fix Whisper model selection caching

backend/app/services/note.py

@@ -262,7 +262,10 @@ class NoteGenerator:
             raise Exception(f"不支持的转写器：{self.transcriber_type}")
 
         logger.info(f"使用转写器：{self.transcriber_type}")
-        return get_transcriber(transcriber_type=self.transcriber_type)
+        return get_transcriber(
+            transcriber_type=self.transcriber_type,
+            model_size=self.model_size,
+        )
 
     def _get_gpt(self, model_name: Optional[str], provider_id: Optional[str]) -> GPT:
         """

backend/app/transcriber/transcriber_provider.py

@@ -1,5 +1,6 @@
 import os
 import platform
+import threading
 from enum import Enum
 
 from app.transcriber.groq import GroqTranscriber
@@ -38,17 +39,29 @@ _transcribers = {
     TranscriberType.GROQ: None,
 }
 
+# Cache instances together with their constructor configuration. The
+# transcriber choice and Whisper model size can be changed from the frontend,
+# so caching by transcriber type alone would keep using the first loaded model.
+_transcriber_configs = {key: None for key in _transcribers}
+_transcriber_init_lock = threading.Lock()
+
 # 公共实例初始化函数
 def _init_transcriber(key: TranscriberType, cls, *args, **kwargs):
-    if _transcribers[key] is None:
-        logger.info(f'创建 {cls.__name__} 实例: {key}')
-        try:
-            _transcribers[key] = cls(*args, **kwargs)
+    init_config = (args, tuple(sorted(kwargs.items())))
+    with _transcriber_init_lock:
+        instance = _transcribers[key]
+        if instance is None or _transcriber_configs[key] != init_config:
+            action = "创建" if instance is None else "按新配置重新创建"
+            logger.info(f'{action} {cls.__name__} 实例: {key}')
+            try:
+                new_instance = cls(*args, **kwargs)
+            except Exception as e:
+                logger.error(f"{cls.__name__} 创建失败: {e}")
+                raise
+            _transcribers[key] = new_instance
+            _transcriber_configs[key] = init_config
             logger.info(f'{cls.__name__} 创建成功')
-        except Exception as e:
-            logger.error(f"{cls.__name__} 创建失败: {e}")
-            raise
-    return _transcribers[key]
+        return _transcribers[key]
 
 # 各类型获取方法
 def get_groq_transcriber():

backend/tests/test_whisper_config_forwarding.py

@@ -0,0 +1,82 @@
+import os
+import pathlib
+import subprocess
+import sys
+import textwrap
+
+
+ROOT = pathlib.Path(__file__).resolve().parents[1]
+
+
+def _run_isolated(script: str) -> None:
+    env = os.environ.copy()
+    env["PYTHONPATH"] = os.pathsep.join(
+        filter(None, [str(ROOT), env.get("PYTHONPATH")])
+    )
+    result = subprocess.run(
+        [sys.executable, "-c", textwrap.dedent(script)],
+        cwd=ROOT,
+        env=env,
+        capture_output=True,
+        text=True,
+    )
+    assert result.returncode == 0, result.stdout + result.stderr
+
+
+def test_note_generator_forwards_configured_whisper_model_size():
+    _run_isolated(
+        """
+        from app.services import note as note_service
+
+        calls = []
+
+        def fake_get_transcriber(**kwargs):
+            calls.append(kwargs)
+            return object()
+
+        note_service.get_transcriber = fake_get_transcriber
+
+        generator = note_service.NoteGenerator.__new__(note_service.NoteGenerator)
+        generator.transcriber_type = "fast-whisper"
+        generator.model_size = "large-v3-turbo"
+
+        generator._init_transcriber()
+
+        assert calls == [
+            {
+                "transcriber_type": "fast-whisper",
+                "model_size": "large-v3-turbo",
+            }
+        ]
+        """
+    )
+
+
+def test_whisper_cache_is_rebuilt_when_model_size_changes():
+    _run_isolated(
+        """
+        from app.transcriber import transcriber_provider as provider
+
+        class FakeWhisperTranscriber:
+            def __init__(self, model_size, device):
+                self.model_size = model_size
+                self.device = device
+
+        provider._transcribers = {key: None for key in provider._transcribers}
+        provider._transcriber_configs = {
+            key: None for key in provider._transcribers
+        }
+        provider.WhisperTranscriber = FakeWhisperTranscriber
+
+        base = provider.get_whisper_transcriber("base", device="cpu")
+        turbo = provider.get_whisper_transcriber("large-v3-turbo", device="cpu")
+        turbo_again = provider.get_whisper_transcriber(
+            "large-v3-turbo", device="cpu"
+        )
+
+        assert base.model_size == "base"
+        assert turbo.model_size == "large-v3-turbo"
+        assert turbo is not base
+        assert turbo_again is turbo
+        """
+    )