Update app.py

app.py

@@ -1,21 +1,20 @@
 import gradio as gr
 import os
-import torch
-import io
-import wavio
-import numpy as np
 from pyannote.audio import Pipeline
-from pyannote.audio import Audio
-from pyannote.core import Segment
 
+# instantiate the pipeline
 pipeline = Pipeline.from_pretrained(
   "pyannote/speaker-diarization-3.1",
-  use_auth_token=os.environ['api'])
+  use_auth_token="HUGGINGFACE_ACCESS_TOKEN_GOES_HERE")
 
 def process_audio(audio):
+    # Read the uploaded audio file
+    with open(audio, "rb") as f:
+        audio_data = f.read()
+
     # Save the uploaded audio file to a temporary location
     with open("temp.wav", "wb") as f:
-        f.write(audio)
+        f.write(audio_data)
 
     # Use the diarization pipeline to process the audio
     diarization = pipeline("temp.wav")
@@ -24,7 +23,7 @@ def process_audio(audio):
     os.remove("temp.wav")
 
     # Return the diarization output
-    return diarization
+    return str(diarization)
 
 with gr.Blocks() as demo:
     audio_input = gr.Audio(type="filepath", label="Upload Audio")