Create app.py

app.py

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+import gradio as gr
+
+def predict_voice(audio_path):
+    # Load the Hugging Face model directly through gr.Interface.load
+    model = gr.Interface.load("models/Kabatubare/ast_celeb_spoof")
+    
+    # Since we're loading the model directly inside the prediction function,
+    # we use it immediately to make a prediction on the provided audio file.
+    predictions = model(audio_path)
+    
+    # Format predictions for display
+    formatted_predictions = [f"Label: {prediction['label']}, Confidence: {prediction['score']:.4f}" for prediction in predictions]
+    return formatted_predictions
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=predict_voice,
+    inputs=gr.Audio(label="Upload Audio File", type="filepath"),
+    outputs=gr.Text(label="Model Predictions"),
+    title="Voice Authenticity Detection with AST Celeb Spoof",
+    description="This model detects whether a voice is real or AI-generated. Upload an audio file to get started.",
+    allow_flagging="never",
+    theme="huggingface"
+)
+
+# Launch the Gradio app
+iface.launch()