app.py

import gradio as gr
from transformers import pipeline

# Initialize the pipeline for audio classification
# Ensure you have the transformers library installed
model_pipeline = pipeline("audio-classification", model="Kabatubare/ast_celeb_spoof")

def predict_voice(audio_file):
    predictions = model_pipeline(audio_file.name)
    # Format the predictions for display
    formatted_predictions = [f"Label: {prediction['label']}, Confidence: {prediction['score']:.4f}" for prediction in predictions]
    return "\n".join(formatted_predictions)

# Define the Gradio interface
iface = gr.Interface(
    fn=predict_voice,
    inputs=gr.Audio(source="upload", type="file", label="Upload Audio File"),
    outputs=gr.Text(label="Predictions"),
    title="Voice Authenticity Detection",
    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()