Update app.py

app.py

@@ -9,7 +9,6 @@ try:
     classifier = pipeline("audio-classification", model="superb/wav2vec2-base-superb-er")
 except Exception as e:
     # If there's an error during model loading, we can display it in the Gradio interface
-    # This helps in debugging issues directly on the Hugging Face Space.
     def error_fn(audio_file):
         return {"error": f"Failed to load the model. Please check the logs. Error: {str(e)}"}
     classifier = None
@@ -40,7 +39,6 @@ def predict_emotion(audio_file):
     elif isinstance(audio_file, tuple):
         # Handle microphone input (samplerate, numpy_array)
         sample_rate, audio_array = audio_file
-        # Save the numpy array to a temporary WAV file as the pipeline expects a file path or direct bytes
         temp_audio_path = "temp_audio_from_mic.wav"
         sf.write(temp_audio_path, audio_array, sample_rate)
         audio_path = temp_audio_path
@@ -49,7 +47,7 @@ def predict_emotion(audio_file):
 
     try:
         # Perform inference
-        results = classifier(audio_path, top_k=5) # top_k ensures we get all relevant emotion scores
+        results = classifier(audio_path, top_k=5)
 
         # Process results into a dictionary for better display
         emotion_scores = {item['label']: round(item['score'], 3) for item in results}
@@ -64,20 +62,14 @@ def predict_emotion(audio_file):
 
 
 # --- Gradio Interface ---
-# Define the Gradio interface
 iface = gr.Interface(
     fn=predict_emotion,
-    # THIS IS THE CORRECTED LINE:
     inputs=gr.Audio(sources=["microphone", "upload"], type="filepath", label="Upload Audio or Record with Microphone"),
-    outputs=gr.Label(num_top_classes=5, label="Emotion Probabilities"), # This model has 4 emotions + 'no-emotion'
+    outputs=gr.Label(num_top_classes=5, label="Emotion Probabilities"),
     title="AI Audio Emotion Detector",
     description="Upload an audio file or record your voice to detect emotions. This model is trained to recognize 'anger', 'happiness', 'neutral', 'sadness', and 'no-emotion'.",
-    examples=[
-        # You can add example audio files to your Hugging Face Space and reference them here.
-        # For now, we'll leave this empty.
-    ]
 )
 
-# Launch the Gradio app
+# Launch the Gradio app with the API queue enabled
 if __name__ == "__main__":
-    iface.launch()
+    iface.queue().launch() # <-- THE FIX IS HERE!