Update app.py

app.py

@@ -1,5 +1,18 @@
 import gradio as gr
 from transformers import pipeline
+import os
+
+# --- Performance Improvement ---
+# 1. Determine the number of available CPU cores.
+num_cpu_cores = os.cpu_count()
+
+# 2. Configure PyTorch to use all available CPU cores for its operations.
+# This is crucial for speeding up model inference on a CPU.
+if num_cpu_cores is not None:
+    torch.set_num_threads(num_cpu_cores)
+    print(f"✅ PyTorch is configured to use {num_cpu_cores} CPU cores.")
+else:
+    print("Could not determine the number of CPU cores. Using default settings.")
 
 # Initialize the audio classification pipeline with the MIT model
 pipe = pipeline("audio-classification", model="MIT/ast-finetuned-audioset-10-10-0.4593")