fix: cache pyannote diarization pipeline to stop memory leak / OOM

The meeting pipeline created a fresh Diarizer per recording, each loading
the multi-GB pyannote speaker-diarization model anew (api/pipeline.py).
Whisper and Ollama run remotely in this deployment, so pyannote was the
only heavy in-process consumer. Reloading it per recording leaked CPU
memory (torch reference cycles + glibc arena fragmentation) that was
never returned to the OS, climbing to a 37 GB peak over a multi-day run
until the kernel OOM-killed the service.

Cache the loaded pipeline on the class and reuse it across Diarizer
instances, mirroring TranscriptionEngine._model. RSS now stays flat.

diarization.py

@@ -2,19 +2,29 @@ import asyncio
 
 
 class Diarizer:
+    # The pyannote pipeline holds multi-GB torch models. A fresh instance is
+    # created per recording (see api/pipeline.py), so cache the loaded pipeline
+    # on the class and reuse it — reloading per recording leaks CPU memory
+    # (torch reference cycles + glibc arena fragmentation) and eventually OOMs
+    # the long-running service. Mirrors TranscriptionEngine._model.
+    _shared_pipeline = None
+
     def __init__(self, hf_token: str):
         if not hf_token:
             raise ValueError("hf_token is required for diarization")
         self._hf_token = hf_token
-        self._pipeline = None
+        self._pipeline = None  # per-instance override (used by tests)
 
     def _load_pipeline(self):
-        if self._pipeline is None:
+        if self._pipeline is not None:
+            return self._pipeline
+        if Diarizer._shared_pipeline is None:
             from pyannote.audio import Pipeline
-            self._pipeline = Pipeline.from_pretrained(
+            Diarizer._shared_pipeline = Pipeline.from_pretrained(
                 "pyannote/speaker-diarization-3.1",
                 token=self._hf_token,
             )
+        self._pipeline = Diarizer._shared_pipeline
         return self._pipeline
 
     async def diarize(self, wav_path: str) -> list[tuple[float, float, str]]: