app.py

import gradio as gr
import xgboost as xgb
import numpy as np

# Load the XGBoost model
model = xgb.Booster()
model.load_model("xgboost_model.json")

# Define a prediction function
def predict(inputs):
    dmatrix = xgb.DMatrix(np.array(inputs))
    prediction = model.predict(dmatrix)
    return prediction.tolist()

# Create the Gradio interface
input_features = gr.Dataframe(headers=["temperature", "humidity", "vibration_amplitude", "vibration_frequency", "sound_amplitude", "sound_frequency"])
output_label = gr.Textbox()

gr.Interface(fn=predict, inputs=input_features, outputs=output_label, title="Fiber Optic Intrusion Detection").launch()