Update app.py

app.py

@@ -6,10 +6,18 @@ from transformers import pipeline
 classifier = pipeline("audio-classification", model="superb/wav2vec2-base-superb-ks")
 
 def classify_audio(audio):
-    # audio is a tuple: (sample_rate, numpy array)
     if audio is None:
-        return "No audio provided"
-    return classifier(audio)
+        return {"error": "No audio provided"}
+    
+    # Gradio audio returns (sample_rate, data)
+    sr, data = audio
+    
+    # Convert to Hugging Face expected format
+    inputs = {"array": data, "sampling_rate": sr}
+    
+    # Run classification
+    results = classifier(inputs)
+    return results
 
 with gr.Blocks() as demo:
     gr.Markdown("## 🎵 Audio Classification (Keyword Spotting)")