init

app.py

@@ -3,6 +3,9 @@ import torch
 from pyannote.audio import Pipeline
 
 
+import spaces
+
+@spaces.GPU
 def analyze_audio(audio_path: str, hf_token: str) -> dict:
     if not audio_path:
         return {"message": "Please upload an audio file."}
@@ -72,11 +75,7 @@ with gr.Blocks(title="Speaker Diarization") as demo:
             summary = gr.Textbox(label="Summary", lines=10)
             details = gr.JSON(label="Details")
 
-    def _run(audio_path, token):
-        result = analyze_audio(audio_path, token)
-        return result.get("message", ""), result
-
-    submit_btn.click(_run, [audio_input, hf_token], [summary, details])
+    submit_btn.click(analyze_audio, [audio_input, hf_token], [summary, details])
 
 
 if __name__ == "__main__":

requirements.txt

@@ -5,4 +5,5 @@ pyannote.core>=5.0.0
 pyannote.metrics>=3.2.1
 librosa>=0.10.1
 soundfile>=0.12.1
+spaces