Support headless voice download

src/calibre/gui2/tts/download.py

@@ -162,6 +162,24 @@ class DownloadResources(QDialog):
         super().reject()
 
 
+def download_resources(
+    title: str, message: str, urls: dict[str, tuple[str, str]], parent: QWidget | None = None, headless: bool = False
+) -> bool:
+    if not headless:
+        d = DownloadResources(title, message, urls, parent=parent)
+        return d.exec() == QDialog.DialogCode.Accepted
+    from calibre import browser
+    print(title)
+    print(message)
+    for url, (path, name) in urls.items():
+        print(_('Downloading {}...').format(name))
+        br = browser()
+        data = br.open_novisit(url).read()
+        with open(path, 'wb') as f:
+            f.write(data)
+    return True
+
+
 def develop():
     from calibre.gui2 import Application
     app = Application([])

src/calibre/gui2/tts/piper.py

@@ -13,11 +13,11 @@ from itertools import count
 from time import monotonic
 
 from qt.core import (
+    QApplication,
     QAudio,
     QAudioFormat,
     QAudioSink,
     QByteArray,
-    QDialog,
     QIODevice,
     QIODeviceBase,
     QMediaDevices,
@@ -469,14 +469,13 @@ class Piper(TTSBackend):
             if not download_even_if_exists:
                 return model_path, config_path
         os.makedirs(os.path.dirname(model_path), exist_ok=True)
-        from calibre.gui2.tts.download import DownloadResources
-        d = DownloadResources(_('Downloading voice for Read aloud'), _('Downloading neural network for the {} voice').format(voice.human_name), {
-            voice.engine_data['model_url']: (model_path, _('Neural network data')),
-            voice.engine_data['config_url']: (config_path, _('Neural network metadata')),
-        }, parent=widget_parent(self))
-        if d.exec() == QDialog.DialogCode.Accepted:
-            return model_path, config_path
-        return '', ''
+        from calibre.gui2.tts.download import download_resources
+        ok = download_resources(_('Downloading voice for Read aloud'), _('Downloading neural network for the {} voice').format(voice.human_name), {
+                voice.engine_data['model_url']: (model_path, _('Neural network data')),
+                voice.engine_data['config_url']: (config_path, _('Neural network metadata')),
+            }, parent=widget_parent(self), headless=getattr(QApplication.instance(), 'headless', False)
+        )
+        return (model_path, config_path) if ok else ('', '')
 
     def download_voice(self, v: Voice) -> None:
         if not v.name: