fix(backend): drop the prompt cache before the allocator-empty; note clear_cache is thread-agnostic

Review follow-ups: clear_voice_prompt_memory_cache() now runs before
backend.unload_model() at all three call sites so the device-resident
prompt tensors are already released when empty_device_cache() /
empty_mlx_cache() runs, instead of going back into the caching allocator
afterwards. empty_mlx_cache's docstring states why it may run off the
MLX worker thread.

backend/backends/__init__.py

@@ -595,16 +595,16 @@ def unload_model_by_config(config: ModelConfig) -> bool:
         backend = get_tts_backend_for_engine(config.engine)
         loaded_size = getattr(backend, "_current_model_size", None) or getattr(backend, "model_size", None)
         if backend.is_loaded() and loaded_size == config.model_size:
-            backend.unload_model()
             clear_voice_prompt_memory_cache()
+            backend.unload_model()
             return True
         return False
 
     # All other TTS engines
     backend = get_tts_backend_for_engine(config.engine)
     if backend.is_loaded():
-        backend.unload_model()
         clear_voice_prompt_memory_cache()
+        backend.unload_model()
         return True
     return False
 

backend/backends/base.py

@@ -232,6 +232,12 @@ def empty_mlx_cache() -> None:
     returning them to the OS. Backends must call this after unloading an
     MLX model, or the process's memory footprint never shrinks even though
     the model object itself was dropped.
+
+    Safe from any thread: ``mx.clear_cache`` only drains the global
+    allocator pool and never touches the per-thread stream registry, so
+    unlike load/generate it does not have to run on the MLX worker thread
+    (verified from the FastAPI event loop with a generation in flight on
+    the worker).
     """
     import mlx.core as mx
 

backend/services/tts.py

@@ -24,8 +24,8 @@ def get_tts_model() -> TTSBackend:
 def unload_tts_model():
     """Unload TTS model to free memory."""
     backend = get_tts_backend()
-    backend.unload_model()
     clear_voice_prompt_memory_cache()
+    backend.unload_model()
 
 
 def audio_to_wav_bytes(audio: np.ndarray, sample_rate: int) -> bytes: