import streamlit as st
import numpy as np
import joblib

html_temp = """
    <div style="background-color:black;padding:10px">
    <h2 style="color:white;text-align:center;">Customer Clustering App </h2>
    </div>
    """
st.markdown(html_temp, unsafe_allow_html=True)

image_url="https://tse4.mm.bing.net/th?id=OIP.Sri9wahqIBdLwFTc85-tvgHaEK&pid=Api&P=0&h=180"

st.image(image_url, use_container_width=True)
st.markdown(f"""
    <style>
        /* Set the background image for the entire app */
        .stApp {{
            background-color: #a27250;
            background-size: 100px;
            background-repeat:no;
            background-attachment: auto;
            background-position:full;
        }}
    </style>
    """, unsafe_allow_html=True)

km_model=joblib.load("coffe_customer_prediction_model.joblib")

def clustering(monetary, frequency):
    new_customer = np.array([[monetary, frequency]])
    predicted_cluster = km_model.predict(new_customer)
    
    if predicted_cluster[0]==1:
        return "Daily"
    else:
        return "Weekely"
    
monetary=float(st.slider("Slide Size of the monetary",min_value=1,max_value=459,value=1))

frequency=float(st.slider("Slide Size of the frequency",min_value=1,max_value=25,value=1))

if st.button("Submit"):
    predicted_cluster = clustering(monetary, frequency)
    st.text_area("",f'New Customer assigned to Cluster: {predicted_cluster}')
    st.write("")