new features

cpv3/modules/transcription/service.py

@@ -240,11 +240,15 @@ def _make_document_from_segments(
     return Document(segments=result_segments)
 
 
+ProgressCallback = Callable[[float], None]
+
+
 def _whisper_transcribe_sync(
     *,
     local_file_path: str,
     model_name: str,
     language: str | None,
+    on_progress: ProgressCallback | None = None,
 ) -> Document:
     import whisper  # type: ignore[import-untyped]
 
@@ -267,14 +271,35 @@ def _whisper_transcribe_sync(
         probs = cast(dict[str, float], probs_raw)
         language = max(probs, key=lambda k: probs[k])
 
-    result = whisper.transcribe(
-        audio=whisper.load_audio(local_file_path),
-        model=model,
-        word_timestamps=True,
-        temperature=0.2,
-        language=language,
-        verbose=False,
-    )
+    if on_progress is not None:
+        from unittest.mock import patch
+        from tqdm import tqdm as _orig_tqdm
+
+        class _ProgressTqdm(_orig_tqdm):
+            def update(self, n=1):
+                super().update(n)
+                if self.total:
+                    on_progress(min(self.n / self.total * 100.0, 100.0))
+
+        with patch("whisper.transcribe.tqdm.tqdm", _ProgressTqdm):
+            result = whisper.transcribe(
+                audio=whisper.load_audio(local_file_path),
+                model=model,
+                word_timestamps=True,
+                temperature=0.2,
+                language=language,
+                verbose=False,
+            )
+        on_progress(100.0)
+    else:
+        result = whisper.transcribe(
+            audio=whisper.load_audio(local_file_path),
+            model=model,
+            word_timestamps=True,
+            temperature=0.2,
+            language=language,
+            verbose=None,
+        )
 
     parsed = WhisperResult.model_validate(result)
 
@@ -296,6 +321,7 @@ async def transcribe_with_whisper(
     file_key: str,
     model_name: str = "tiny",
     language: str | None = None,
+    on_progress: ProgressCallback | None = None,
 ) -> Document:
     tmp = await storage.download_to_temp(file_key)
     try:
@@ -304,6 +330,7 @@ async def transcribe_with_whisper(
                 local_file_path=tmp.path,
                 model_name=model_name,
                 language=language,
+                on_progress=on_progress,
             )
         )
     finally: