Update app.py

app.py

@@ -2,17 +2,25 @@
 import gradio as gr
 from transformers import pipeline
 
-classifier = pipeline("audio-classification", model="superb/wav2vec2-base-superb-ks")
+# Pretrained model for audio classification
+MODEL = "superb/wav2vec2-base-superb-ks"  # keyword spotting (yes, no, up, down...)
+
+classifier = pipeline("audio-classification", model=MODEL)
 
 def classify_audio(audio_file):
-    return classifier(audio_file)
+    # audio_file is a tuple: (sample_rate, numpy_array) if "numpy", or path if "filepath"
+    if isinstance(audio_file, str):  # filepath
+        return classifier(audio_file)
+    else:  # (sr, data)
+        sr, data = audio_file
+        return classifier({"array": data, "sampling_rate": sr})
 
 demo = gr.Interface(
     fn=classify_audio,
-    inputs=gr.Audio(type="filepath"),
-    outputs=gr.Label(num_top_classes=5),
-    title="Audio Classification",
-    description="Upload or record audio to classify (keywords dataset model)."
+    inputs=gr.Audio(sources=["microphone", "upload"], type="filepath"),
+    outputs=gr.Label(),
+    title="🎵 Audio Classification",
+    description="Upload or record audio. Model: wav2vec2-base-superb-ks"
 )
 
 if __name__ == "__main__":