Create app.py

app.py

@@ -0,0 +1,71 @@
+import gradio as gr
+import pandas as pd
+import numpy as np
+import pickle
+
+# Load trained model safely
+with open("dynamic_pricing_model.pkl", "rb") as f:
+    model = pickle.load(f)
+
+def predict_dynamic_pricing(
+    zone_id, demand, supply, driver_availability,
+    weather_factor, event_factor, temperature, traffic_index,
+    distance_km, duration_min, base_fare,
+    hour, day_of_week, is_weekend, rate_per_km=6
+):
+
+    demand_supply_ratio = np.clip(demand / (supply + 1), 0, 3)
+
+    row = pd.DataFrame([{
+        "zone_id": zone_id,
+        "hour": hour,
+        "day_of_week": day_of_week,
+        "is_weekend": is_weekend,
+        "demand": demand,
+        "supply": supply,
+        "driver_availability": driver_availability,
+        "weather_factor": weather_factor,
+        "event_factor": event_factor,
+        "temperature": temperature,
+        "traffic_index": traffic_index,
+        "distance_km": distance_km,
+        "duration_min": duration_min,
+        "base_fare": base_fare,
+        "demand_supply_ratio": demand_supply_ratio
+    }])
+
+    surge = float(model.predict(row)[0])
+    base_price = base_fare + distance_km * rate_per_km
+    final_price = base_price * surge
+
+    return base_price, surge, final_price
+
+
+demo = gr.Interface(
+    fn=predict_dynamic_pricing,
+    inputs=[
+        gr.Number(label="Zone ID"),
+        gr.Number(label="Demand"),
+        gr.Number(label="Supply"),
+        gr.Number(label="Driver Availability"),
+        gr.Number(label="Weather Factor"),
+        gr.Number(label="Event Factor"),
+        gr.Number(label="Temperature"),
+        gr.Number(label="Traffic Index"),
+        gr.Number(label="Distance (km)"),
+        gr.Number(label="Duration (min)"),
+        gr.Number(label="Base Fare"),
+        gr.Number(label="Hour"),
+        gr.Number(label="Day of Week"),
+        gr.Number(label="Is Weekend")
+    ],
+    outputs=[
+        gr.Number(label="Base Price"),
+        gr.Number(label="Surge Factor"),
+        gr.Number(label="Final Dynamic Price")
+    ],
+    title="Dynamic Pricing Model",
+    description="AI-based real-time surge pricing."
+)
+
+demo.launch(server_name="0.0.0.0", server_port=7860)