Update pipeline.py

pipeline.py

@@ -15,6 +15,7 @@ from typing import List, Optional
 
 import torch
 import whisper
+from huggingface_hub import login
 from pyannote.audio import Pipeline as PyannotePipeline
 
 logging.basicConfig(level=logging.INFO)
@@ -24,6 +25,10 @@ DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 HF_TOKEN = os.environ.get("HF_TOKEN", "")
 WHISPER_MODEL = os.environ.get("WHISPER_MODEL", "base")
 
+# Login once at import time — works with all pyannote/huggingface_hub versions
+if HF_TOKEN:
+    login(token=HF_TOKEN)
+
 
 @dataclass
 class AnnotationSegment:
@@ -75,19 +80,10 @@ class SpeechAnnotationPipeline:
                     "HF_TOKEN not set. Add it in Space Settings > Variables and secrets."
                 )
             logger.info("Loading pyannote diarization pipeline...")
-
-            # Try both parameter names for compatibility
-            try:
-                self._diarization_pipeline = PyannotePipeline.from_pretrained(
-                    "pyannote/speaker-diarization-3.1",
-                    use_auth_token=HF_TOKEN,
-                )
-            except TypeError:
-                self._diarization_pipeline = PyannotePipeline.from_pretrained(
-                    "pyannote/speaker-diarization-3.1",
-                    token=HF_TOKEN,
-                )
-
+            # No token param needed — login() at top handles auth
+            self._diarization_pipeline = PyannotePipeline.from_pretrained(
+                "pyannote/speaker-diarization-3.1"
+            )
             if DEVICE == "cuda":
                 self._diarization_pipeline = self._diarization_pipeline.to(torch.device("cuda"))
         return self._diarization_pipeline