extract select_device to domain/device.py; fix bug where conversion_runner didn't check torch availability

abogen/domain/device.py

@@ -0,0 +1,31 @@
+from __future__ import annotations
+
+import platform as _platform
+
+
+def select_device() -> str:
+    """Return the best available compute device (``"mps"``, ``"cuda"``, or ``"cpu"``).
+
+    Checks ``torch`` availability at runtime so this can be called from
+    any context without requiring torch at import time.
+    """
+    try:
+        import torch  # type: ignore[import-not-found]
+    except Exception:
+        return "cpu"
+
+    system = _platform.system()
+    if system == "Darwin" and _platform.processor() == "arm":
+        try:
+            if torch.backends.mps.is_available():  # type: ignore[union-attr]
+                return "mps"
+        except Exception:
+            pass
+        return "cpu"
+
+    try:
+        if torch.cuda.is_available():  # type: ignore[union-attr]
+            return "cuda"
+    except Exception:
+        pass
+    return "cpu"

abogen/pyqt/gui.py

@@ -7,6 +7,7 @@ import base64
 import re
 from abogen.pyqt.queue_manager_gui import QueueManager
 from abogen.pyqt.queued_item import QueuedItem
+from abogen.domain.device import select_device as _select_device
 import abogen.hf_tracker as hf_tracker
 import hashlib  # Added for cache path generation
 from PyQt6.QtWidgets import (
@@ -2428,10 +2429,7 @@ class abogen(QWidget):
 
             # Determine device based on GPU availability
             if gpu_ok:
-                if platform.system() == "Darwin" and platform.processor() == "arm":
-                    device = "mps"
-                else:
-                    device = "cuda"
+                device = _select_device()
             else:
                 device = "cpu"
 
@@ -2877,10 +2875,7 @@ class abogen(QWidget):
 
         # Determine device based on GPU availability
         if self.gpu_ok:
-            if platform.system() == "Darwin" and platform.processor() == "arm":
-                device = "mps"
-            else:
-                device = "cuda"
+            device = _select_device()
         else:
             device = "cpu"
 

abogen/webui/conversion_runner.py

@@ -109,6 +109,7 @@ from abogen.domain.output_paths import (
     resolve_output_directory as _resolve_output_directory,
     resolve_project_layout as _resolve_project_layout,
 )
+from abogen.domain.device import select_device as _select_device
 from abogen.domain.audio_helpers import (
     build_ffmpeg_command as _build_ffmpeg_command,
     to_float32 as _to_float32,
@@ -1188,15 +1189,6 @@ def _load_pipeline(job: Job):
     return create_pipeline("kokoro", lang_code=job.language, device=device)
 
 
-def _select_device() -> str:
-    import platform
-
-    system = platform.system()
-    if system == "Darwin" and platform.processor() == "arm":
-        return "mps"
-    return "cuda"
-
-
 def _prepare_output_dir(job: Job) -> Path:
     from platformdirs import user_desktop_dir  # type: ignore[import-not-found]
 

abogen/webui/routes/utils/preview.py

@@ -6,6 +6,8 @@ import soundfile as sf
 from flask import current_app, send_file
 from flask.typing import ResponseReturnValue
 
+from abogen.domain.device import select_device as _select_device
+
 
 SPLIT_PATTERN = r"\n+"
 SAMPLE_RATE = 24000
@@ -25,31 +27,6 @@ def clear_preview_pipelines() -> None:
         _preview_pipelines.clear()
 
 
-def _select_device() -> str:
-    import platform
-
-    try:
-        import torch  # type: ignore[import-not-found]
-    except Exception:
-        return "cpu"
-
-    system = platform.system()
-    if system == "Darwin" and platform.processor() == "arm":
-        try:
-            if torch.backends.mps.is_available():
-                return "mps"
-        except Exception:
-            pass
-        return "cpu"
-
-    try:
-        if torch.cuda.is_available():
-            return "cuda"
-    except Exception:
-        pass
-    return "cpu"
-
-
 def _resolve_pipeline(language: str, use_gpu: bool) -> Tuple[Any, bool]:
     devices: List[str] = ["cpu"]
     if use_gpu: