.

app.py

@@ -1,6 +1,10 @@
 import requests
 import gradio as gr
 import os
+import torch
+
+# Check if CUDA is available and set the device accordingly
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 
 API_URL = "https://api-inference.huggingface.co/models/MIT/ast-finetuned-audioset-10-10-0.4593"
 headers = {"Authorization": f"Bearer {os.environ.get('HF_TOKEN')}"}
@@ -12,12 +16,17 @@ def classify_audio(audio_file):
     if audio_file is None:
         return "Please upload an audio file."
     
-    with open(audio_file.name, "rb") as f:
-        data = f.read()
-    response = requests.post(API_URL, headers=headers, data=data)
     try:
-        results = response.json()
-        return results
+        with open(audio_file.name, "rb") as f:
+            data = f.read()
+        response = requests.post(API_URL, headers=headers, data=data)
+        
+        if response.status_code == 200:
+            results = response.json()
+            return results
+        else:
+            return f"Error: API returned status code {response.status_code}"
+            
     except Exception as e:
         return f"Error processing audio: {str(e)}"
 
@@ -32,7 +41,5 @@ iface = gr.Interface(
 )
 
 # Launch the interface
-iface.launch()
-
-
-
+if __name__ == "__main__":
+    iface.launch(server_name="0.0.0.0", server_port=7860)