Update app.py

app.py

@@ -2,7 +2,7 @@ import pandas as pd,numpy as np
 import pickle
 import streamlit as st
 
-st.title("Mobile Data User Behaviour")
+# st.title("Mobile Data User Behaviour")
 
 # st.title("User Behavior Using Mobile Prediction")
 # model_2 = pickle.load(open(r"\rfc.pkl","rb")) #pickle file path
@@ -10,6 +10,46 @@ st.title("Mobile Data User Behaviour")
 # if st.button("Submit"):
 #     result = model_2.predict([[]])
 #     st.write(f"The predicted price of the rental house is {result}")
+
+import joblib
+import streamlit as st
+
+st.title("User Behavior Using Mobile Prediction")
+
+# Inputs
+Device_Model = st.selectbox("Enter Device Model Type", ['Xiaomi Mi 11', 'iPhone 12', 'Google Pixel 5', 'OnePlus 9', 'Samsung Galaxy S21'])
+age = st.number_input("Enter age", min_value=0, max_value=100, step=1, format="%d")
+gender = st.radio("Enter gender", ['Male', 'Female'])
+Operating_System = st.selectbox("Enter Operating System Type", ['Android', 'iOS'])
+App_Usage_Time = st.number_input("Enter the App Usage Time")
+Screen_On_Time = st.number_input("Enter the Screen On Time")
+Battery_Drain = st.number_input("Enter the Battery Drain")
+Number_of_Apps_Installed = st.number_input("Enter the Number of Apps Installed")
+Data_Usage = st.number_input("Enter the Data Usage")
+
+# Load the model
+model_path = "./rfc.pkl"  # Adjust if in a subdirectory
+try:
+    model_2 = joblib.load(model_path)
+
+    # Encode categorical variables
+    mapping_device = {'Xiaomi Mi 11': 0, 'iPhone 12': 1, 'Google Pixel 5': 2, 'OnePlus 9': 3, 'Samsung Galaxy S21': 4}
+    mapping_os = {'Android': 0, 'iOS': 1}
+    mapping_gender = {'Male': 0, 'Female': 1}
+
+    device_model_encoded = mapping_device[Device_Model]
+    operating_system_encoded = mapping_os[Operating_System]
+    gender_encoded = mapping_gender[gender]
+
+    if st.button("Submit"):
+        result = model_2.predict([[device_model_encoded, operating_system_encoded, App_Usage_Time, Screen_On_Time, Battery_Drain, Number_of_Apps_Installed, Data_Usage, age, gender_encoded]])
+        st.write(f"The predicted behavior is: {result}")
+except FileNotFoundError:
+    st.error(f"Model file not found at: {model_path}")
+except Exception as e:
+    st.error(f"An error occurred: {e}")
+
+
     
 
 # age = st.number_input("Enter age",min_value=0,max_value=1000,step=1,format="%d" )