Fix Whisper model selection caching

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
+        """
+    )