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import pandas as pd
import joblib
import gradio as gr
# Load model artifact once
artifact = joblib.load("pue_artifact.joblib")
def predict_pue(
zone_id, hour, day_of_week, is_weekend,
weather_factor, event_factor, traffic_index,
distance_km, duration_min, base_fare,
avg_distance, avg_duration, avg_fare,
discount_usage_rate, total_rides
):
input_data = {
"zone_id": int(zone_id),
"hour": int(hour),
"day_of_week": int(day_of_week),
"is_weekend": int(is_weekend),
"weather_factor": float(weather_factor),
"event_factor": float(event_factor),
"traffic_index": float(traffic_index),
"distance_km": float(distance_km),
"duration_min": float(duration_min),
"base_fare": float(base_fare),
"avg_distance": float(avg_distance),
"avg_duration": float(avg_duration),
"avg_fare": float(avg_fare),
"discount_usage_rate": float(discount_usage_rate),
"total_rides": int(total_rides)
}
X = pd.DataFrame([input_data])
X = X.reindex(columns=artifact["features"], fill_value=0)
ride = artifact["ride_encoder"].inverse_transform(
artifact["ride_model"].predict(X)
)[0]
discount_prob = artifact["discount_model"].predict_proba(X)[0][1]
route = artifact["route_encoder"].inverse_transform(
artifact["route_model"].predict(X)
)[0]
return {
"Recommended Ride Type": ride,
"Discount Probability": round(float(discount_prob), 2),
"Preferred Route": route
}
# Gradio UI
app = gr.Interface(
fn=predict_pue,
inputs=[
gr.Number(label="Zone ID"),
gr.Slider(0,23,step=1,label="Hour"),
gr.Slider(0,6,step=1,label="Day of Week"),
gr.Radio([0,1],label="Weekend"),
gr.Slider(1,1.5,label="Weather Factor"),
gr.Slider(1,1.6,label="Event Factor"),
gr.Slider(0.5,2,label="Traffic Index"),
gr.Number(label="Distance (km)"),
gr.Number(label="Duration (min)"),
gr.Number(label="Base Fare"),
gr.Number(label="Avg Distance"),
gr.Number(label="Avg Duration"),
gr.Number(label="Avg Fare"),
gr.Slider(0,1,label="Discount Usage Rate"),
gr.Number(label="Total Rides")
],
outputs="json",
title="Personalized User Experience – Real-Time ML",
description="Real-time personalization for ride-hailing apps"
)
app.launch() |