adding price prediction with api using

app.py

@@ -3,6 +3,7 @@ import pandas as pd
 import numpy as np
 import plotly.express as px
 import plotly.graph_objects as go
+import requests
 
 
 #################################################################### PAGE CONFIGURATION ####################################################################
@@ -12,7 +13,7 @@ st.set_page_config(page_title="Getaround Project Dashboard", page_icon="🚦", l
 #################################################################### SIDEBAR MENU ####################################################################
 
 st.sidebar.title("Navigation")
-page = st.sidebar.radio("Go to", ["🏠 Home/Introduction", "📊 Delays Analysis", "🎉 The End & Thank You"])
+page = st.sidebar.radio("Go to", ["🏠 Home/Introduction", "📊 Delays Analysis", "💸 Price Prediction", "🎉 The End & Thank You"])
 
 e = st.sidebar.empty()
 e.write("")
@@ -571,6 +572,74 @@ elif page == "📊 Delays Analysis":
                 ✨ Thanks for reading all the way through! I hope you enjoyed it and found it interesting.
                 Go to the last page, `The End & Thank You`, for a little surprise and links to my other works‼️
                 """)
+#################################################################### Price prediction ####################################################################
+
+elif page == "💸 Price Prediction":
+    st.title("Price Prediction for a Rental 💸💶")
+    st.markdown("""
+    Here, you can choose the parameters of a car and with a connection to my API, you can have a day price prediction of the car.
+    
+    🟠 **What you'll find in this page**:
+    * 🏎️ Object to select your car's characteristics?
+    * 💸 A price prediction for one rental day.
+                """)
+    
+    st.write("Select the car parameters below and get an estimated rental price!")
+
+    # Define API URL
+    api_url = "https://hyraxuna-api-getaround.hf.space/predict"
+
+    # Define input fields for car parameters
+    car_model = st.selectbox("Car Brand:", ['Citroën','Peugeot','PGO','Renault','Audi','BMW','Mercedes','Opel','Volkswagen','Ferrari','Mitsubishi','Nissan','SEAT','Subaru','Toyota','other'])
+    mileage = st.slider("Mileage (km):", 0, 300000, 50000, step=1000)
+    engine_power = st.slider("Engine Power (HP):", 50, 500, 150, step=10)
+    fuel = st.selectbox("Fuel Type:", ['diesel','petrol','other'])
+    paint_color = st.selectbox("Paint Color:", ['black','grey','white','red','silver','blue','beige','brown','other'])
+    car_type = st.selectbox("Car Type:", ['convertible','coupe','estate','hatchback','sedan','subcompact','suv','van'])
+
+    # Boolean Features
+    private_parking_available = st.checkbox("Private Parking Available")
+    has_gps = st.checkbox("GPS Included")
+    has_air_conditioning = st.checkbox("Air Conditioning")
+    automatic_car = st.checkbox("Automatic Transmission")
+    has_getaround_connect = st.checkbox("Getaround Connect Available")
+    has_speed_regulator = st.checkbox("Speed Regulator Installed")
+    winter_tires = st.checkbox("Winter Tires Installed")
+
+    # Button to Predict
+    if st.button("🔍 Predict Rental Price"):
+        st.subheader("💶 Prediction Results")
+
+        # Prepare input data as JSON
+        input_data = {
+            "model_key": car_model,
+            "mileage": mileage,
+            "engine_power": engine_power,
+            "fuel": fuel,
+            "paint_color": paint_color,
+            "car_type": car_type,
+            "private_parking_available": private_parking_available,
+            "has_gps": has_gps,
+            "has_air_conditioning": has_air_conditioning,
+            "automatic_car": automatic_car,
+            "has_getaround_connect": has_getaround_connect,
+            "has_speed_regulator": has_speed_regulator,
+            "winter_tires": winter_tires
+        }
+
+        try:
+            # API Request
+            response = requests.post(api_url, json=input_data)
+            result = response.json()
+
+            if response.status_code == 200:
+                predicted_price = result.get("predicted_price", "Error")
+                st.success(f"💰 Estimated Rental Price: **{predicted_price} € per day**")
+            else:
+                st.error("⚠️ Error fetching prediction. Please check API or try again.")
+        
+        except Exception as e:
+            st.error(f"⚠️ API Request Failed: {e}")
 
 #################################################################### END & THANK YOU PAGE ####################################################################