Update app.py

app.py

@@ -4,18 +4,17 @@ from transformers import pipeline
 # Initialize the audio classification pipeline with the MIT model
 pipe = pipeline("audio-classification", model="MIT/ast-finetuned-audioset-10-10-0.4593")
 
-# Define a function to classify an audio file
+# Define the function to classify an audio file
 def classify_audio(audio):
-    # The input audio is passed to the model for classification
     result = pipe(audio)
     return {label['label']: label['score'] for label in result}
 
 # Set up the Gradio interface
 app = gr.Interface(
     fn=classify_audio,                  # Function to classify audio
-    inputs=gr.Audio(source="upload", type="filepath"),  # Input field for uploading an audio file
-    outputs=gr.Label(num_top_classes=3),              # Output with top 3 classification results
-    title="Audio Classification",                     # App title
+    inputs=gr.Audio(),                  # Input for uploading an audio file (no 'source' or 'type' needed)
+    outputs=gr.Label(num_top_classes=3), # Output with top 3 classification results
+    title="Audio Classification",        # App title
     description="Upload an audio file to classify it using MIT's fine-tuned AudioSet model."
 )