Update app.py

app.py

@@ -4,30 +4,28 @@ import torch
 import io
 from pyannote.audio import Pipeline
 from pyannote.audio import Audio
-from pyannote.audio.pipelines.utils.hook import TimingHook
 from pyannote.core import Segment
 
 pipeline = Pipeline.from_pretrained(
   "pyannote/speaker-diarization-3.1",
   use_auth_token=os.environ['api'])
 
-def process_audio(audio_file):
+def process_audio(audio):
     # Save the uploaded audio file to a temporary location
-    temp_file = "temp_audio.wav"
-    with open(temp_file, "wb") as f:
-        f.write(audio_file.read())
+    with open("temp.wav", "wb") as f:
+        f.write(audio)
     
-    # Use the diarization pipeline to process the audio file
-    diarization = pipeline(temp_file)
+    # Use the diarization pipeline to process the audio
+    diarization = pipeline("temp.wav")
     
     # Remove the temporary file
-    os.remove(temp_file)
+    os.remove("temp.wav")
     
     # Return the diarization output
     return diarization
 
 with gr.Blocks() as demo:
-    audio_input = gr.File(label="Upload Audio", file_types=["audio"])
+    audio_input = gr.Audio(label="Upload Audio")  
     process_button = gr.Button("Process")
     diarization_output = gr.JSON(label="Diarization Output")