Update handler.py

handler.py

@@ -1,23 +1,16 @@
 from typing import Dict
 from pyannote.audio import Pipeline
-from pyannote.audio import Audio
-import io
 import torch
-import os
+import io
+from pyannote.audio import Audio
 
 SAMPLE_RATE = 16000
 
-# Set the PYANNOTE_CACHE environment variable
-os.environ["PYANNOTE_CACHE"] = "/repository/.cache"
-
 class EndpointHandler():
     def __init__(self, path=""):
-        # Construct the full path to the model directory
-        model_path = os.path.join("/repository", "")  # Add trailing slash
-
-        # Load the pipeline from the model repository using the full path
-        self.pipeline = Pipeline.from_pretrained(model_path)
-        self.audio = Audio(sample_rate=SAMPLE_RATE, mono="downmix")  # Set mono="downmix"
+        # Load the pipeline from the model repository (using config.yaml)
+        self.pipeline = Pipeline.from_pretrained(path)
+        self.audio = Audio(sample_rate=SAMPLE_RATE, mono="downmix")
 
     def __call__(self, data: Dict[str, bytes]) -> Dict[str, str]:
         """
@@ -31,7 +24,7 @@ class EndpointHandler():
         inputs = data.pop("inputs", data)
         parameters = data.pop("parameters", None)
 
-        # Load the audio using pyannote.audio (downmixing to mono)
+        # Load the audio using pyannote.audio
         waveform, sample_rate = self.audio(io.BytesIO(inputs))
 
         # prepare pyannote input