fix(backend): prevent unbounded memory accumulation over consecutive TTS generations (#923)

backend/backends/base.py

@@ -205,17 +205,23 @@ def check_cuda_compatibility() -> tuple[bool, str | None]:
 
 def empty_device_cache(device: str) -> None:
     """
-    Free cached memory on the given device (CUDA or XPU).
+    Free cached memory and unreferenced tensors on the given device (CUDA, XPU, MPS, CPU).
 
-    Backends should call this after unloading models so VRAM is returned
-    to the OS.
+    Backends call this after model unloading and post-generation cleanup to return
+    memory to the OS and prevent process heap accumulation.
     """
+    import gc
     import torch
 
+    gc.collect()
+
     if device == "cuda" and torch.cuda.is_available():
         torch.cuda.empty_cache()
     elif device == "xpu" and hasattr(torch, "xpu"):
         torch.xpu.empty_cache()
+    elif device == "mps" and hasattr(torch.backends, "mps") and torch.backends.mps.is_available():
+        if hasattr(torch.mps, "empty_cache"):
+            torch.mps.empty_cache()
 
 
 def manual_seed(seed: int, device: str) -> None:

backend/backends/chatterbox_backend.py

@@ -203,6 +203,7 @@ class ChatterboxTTSBackend:
 
             logger.info(f"[Chatterbox] Generating: lang={language}")
 
+            with torch.inference_mode():
                 wav = self.model.generate(
                     text,
                     language_id=language,

backend/backends/chatterbox_turbo_backend.py

@@ -184,6 +184,7 @@ class ChatterboxTurboTTSBackend:
 
             logger.info("[Chatterbox Turbo] Generating (English)")
 
+            with torch.inference_mode():
                 wav = self.model.generate(
                     text,
                     audio_prompt_path=ref_audio,

backend/backends/kokoro_backend.py

@@ -276,6 +276,7 @@ class KokoroTTSBackend:
 
             # Generate all chunks and concatenate
             audio_chunks = []
+            with torch.inference_mode():
                 for result in pipeline(text, voice=voice_name, speed=1.0):
                     if result.audio is not None:
                         chunk = result.audio

backend/backends/luxtts_backend.py

@@ -167,6 +167,9 @@ class LuxTTSBackend:
             if seed is not None:
                 manual_seed(seed, self.device)
 
+            import torch
+
+            with torch.inference_mode():
                 wav = self.model.generate_speech(
                     text=text,
                     encode_dict=voice_prompt,

backend/backends/pytorch_backend.py

@@ -231,6 +231,7 @@ class PyTorchTTSBackend:
 
             # See _create_prompt_sync comment — inference runs with the
             # process's default HF_HUB_OFFLINE state (issue #462).
+            with torch.inference_mode():
                 wavs, sample_rate = self.model.generate_voice_clone(
                     text=text,
                     voice_clone_prompt=voice_prompt,

backend/backends/qwen_custom_voice_backend.py

@@ -207,6 +207,7 @@ class QwenCustomVoiceBackend:
             # state. Forcing offline here (issue #462) regressed online
             # users whose libraries issue legitimate metadata lookups
             # during generation.
+            with torch.inference_mode():
                 wavs, sample_rate = self.model.generate_custom_voice(**kwargs)
             return wavs[0], sample_rate
 

backend/services/generation.py

@@ -156,6 +156,12 @@ async def run_generation(
     finally:
         task_manager.complete_generation(generation_id)
         bg_db.close()
+        try:
+            from ..backends.base import empty_device_cache
+            device = getattr(tts_model, "device", "cpu") if "tts_model" in locals() else "cpu"
+            empty_device_cache(device)
+        except Exception:
+            pass
 
 
 def _notify_speak_end(generation_id: str, *, status: str) -> None:
@@ -313,6 +319,7 @@ async def generate_audio_sync(
     if crossfade_ms is not None:
         gen_kwargs["crossfade_ms"] = crossfade_ms
 
+    try:
         audio, sample_rate = await generate_chunked(
             tts_model, text, voice_prompt, **gen_kwargs
         )
@@ -321,6 +328,13 @@ async def generate_audio_sync(
             audio = normalize_audio(audio)
 
         return tts.audio_to_wav_bytes(audio, sample_rate)
+    finally:
+        try:
+            from ..backends.base import empty_device_cache
+            device = getattr(tts_model, "device", "cpu") if "tts_model" in locals() else "cpu"
+            empty_device_cache(device)
+        except Exception:
+            pass
 
 
 def _save_regenerate(