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import streamlit as st
import numpy as np
import pickle
import random
import os
# Function to load the model
def load_model():
try:
# Get the absolute path to the .pkl file
model_path = os.path.join(os.getcwd(), "clfmodel.pkl")
model = pickle.load(open(model_path, 'rb'))
st.write("Model loaded successfully.")
return model
except Exception as e:
st.write("Something went wrong while loading the model.")
st.write(e)
return None
# Function to make prediction
@st.cache_data
def make_prediction(_model, features):
try:
predicted_label = _model.predict(features)
return predicted_label
except Exception as e:
st.write("Something went wrong while making prediction.")
st.write(e)
return None
# Main function to run the app
def main():
st.title("Custom Grocery App Predictor in Hungary")
st.write("This app predicts the preferable grocery app based on user characteristics.")
# Load the model
clf_model = load_model()
if clf_model:
# Sidebar inputs
st.sidebar.header('User Input Features')
gender = st.sidebar.radio('Gender', ('Male', 'Female'))
education = st.sidebar.selectbox('Education Level', ('Under Diploma and Diploma', 'Associate', 'Bachelor', 'Master', 'PhD'))
age = st.sidebar.slider('Age', 18, 100, 30)
exp_online = st.sidebar.slider('Years of Online Experience', 0, 50, 5)
exp_app = st.sidebar.slider('Years of App Experience', 0, 20, 1)
gender_code = 1 if gender == 'Male' else 2
education_code = ['Under Diploma and Diploma', 'Associate', 'Bachelor', 'Master', 'PhD'].index(education) + 1
# Make prediction
predicted_label = make_prediction(clf_model, np.array([[gender_code, education_code, age, exp_online, exp_app]]))
if predicted_label is not None:
class_App_names = ['FoodPanda', 'Wolt', 'Spar', 'Tesco online', 'myLidl']
predicted_App_class = class_App_names[predicted_label[0] - 1]
# Generate a random color
random_color = "#{:06x}".format(random.randint(0, 0xFFFFFF))
# Render the output with only the predicted_App_class colored and bigger font size
st.write(f"In Hungary, for a {gender}, with education level of {education}, age of {age}, with online experience of {exp_online} years, and shopping experience from online Apps {exp_app} years, It seems that the preferable Grocery App is: ", end="")
st.markdown(f"<span style='color: {random_color}; font-weight: bold; font-size: 50px'>{predicted_App_class}</span>.", unsafe_allow_html=True)
else:
st.write("Failed to load the model.")
if __name__ == '__main__':
main()
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