import pandas as pd
import pickle as pkl
import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
import streamlit as st
import base64


def set_light_background(image_file):
    with open(image_file, "rb") as image:
        encoded = base64.b64encode(image.read()).decode()
    ext = image_file.split('.')[-1]

    st.markdown(
        f"""
        <style>
        .stApp {{
            background: linear-gradient(
                rgba(255, 255, 255, 0.7), 
                rgba(255, 255, 255, 0.7)
            ),
            url("data:image/{ext};base64,{encoded}");
            background-size: cover;
            background-repeat: no-repeat;
            background-attachment: fixed;
        }}
        h1, h2, h3, h4, h5, h6 {{
            color: #1a1a1a;
        }}
        .stApp {{
            color: #202020;
        }}
        </style>
        """,
        unsafe_allow_html=True
    )

set_light_background("musicbg.jpg")



# 🎯 Add Image at the Top
st.image("inno.jpg", use_container_width=True,width=500) 
st.markdown(
    f"<h1 style='text-align: center;'>Subscription & Business Analytics</h1>", 
    unsafe_allow_html=True)
# 🎯 Add Image at the Top
st.image("music.png", use_container_width=True,width=500) 

st.header("Business and Data Understanding")
st.subheader("Business Statements")
st.write(""" 
- The business problem statement is **music streaming service** that offers"
" different subscription plans (Free, Premium, Family). The main goal is to analyze"
" user behavior and predict customer churn—whether a user will leave the platform .""")

st.subheader("Business Objective")
st.write("""
- Identify key factors contributing to customer churn (e.g., subscription type, engagement metrics, payment method).
- Improve customer retention strategies by targeting at-risk users with promotions, better recommendations, or engagement campaigns.
- Enhance user experience by understanding listening habits, subscription patterns, and customer service interactions.
- Optimize marketing efforts to encourage conversions from free users to premium plans.""")

st.subheader("Business Constraints")
st.write("""
- Business constraints are limitations or restrictions that affect decision-making, 
         operations, or strategic planning within a business. They can include:

- Financial Constraints:  Budget limitations, funding availability, or cost-cutting measures.
- Time Constraints: Project deadlines, time-to-market pressures, or regulatory timelines.
- Resource Constraints: Limited workforce, technology, or raw materials.
- Legal & Compliance Constraints: Industry regulations, data privacy laws (e.g., GDPR), or contractual obligations.
- Market Constraints: Customer demand, competition, or economic conditions.
- Technical Constraints: Software/hardware limitations, system integrations, or scalability issues.
- Operational Constraints:  Supply chain restrictions, production capabilities, or logistics limitations.""")

st.header("Data Understanding")
st.write("""
- *Dataset Size:* 125000 rows × 20 columns.
- *Data Types:*  float64(3), int64(11), object(4)
- *Data Features:*'age', 'location', 'subscription_type', 'payment_plan',
       'num_subscription_pauses', 'customer_service_inquiries', 'signup_date',
       'weekly_hours', 'average_session_length' 'song_skip_rate',
       'weekly_songs_played', 'weekly_unique_songs', 'num_favorite_artists',
       'num_platform_friends', 'num_playlists_created', 'num_shared_playlists',
       'notifications_clicked', 'churned'. """)



st.write(r"https://www.kaggle.com/competitions/streaming-subscription-churn-model/overview")
st.write("Demo data")
data = pd.read_csv("data.csv")
st.write(data)
dff = st.file_uploader("Upload File:")

with open("pipe.pkl","rb") as file:
    pipe = pkl.load(file)

with open("model.pkl","rb") as file:
    model = pkl.load(file)

if dff:
    df =pd.read_csv(dff)
    req = df
    test = pipe.transform(req)

    predicted = model.predict(test)
    df["churned"] = predicted

    st.table(df[["customer_id","churned"]])

    ans = {
        0: {
            "name": "name",
            "email": "email",
            "mail": {
                "subject": "🎶 Discover New Music You'll Love, name!",
                "body": "Hey name,\n\nWe noticed you have a fantastic taste for music, "
                "exploring tons of unique songs every week! To help you find even more tracks you'll love, "
                "we've put together some recommendations just for you.\n\nBased on your listening habits, "
                "we think you might enjoy:\n\n* **Daily Mixes:** Personalized playlists refreshed daily with music "
                "we think you'll be excited about.\n* **New Music Friday:** Stay up-to-date with the freshest releases "
                "from your favorite genres and artists.\n* **Genre Playlists:** Dive deeper into genres you love or explore "
                "something completely new.\n\nReady to discover your next favorite song? Click here to explore: [Link to App/Music Platform]\n\nHappy listening,\nYour Music Team"
            }
        },
        1: {
            "name": "name",
            "email": "email",
            "mail": {
                "subject": "We Miss You, Moon! Come Back for More Music & Family Fun!",
                "body": "Hi name,\n\nWe've noticed you've been away from our music platform, "
                "and we wanted to reach out and see if everything is alright."
                " We truly value you as a Family plan subscriber and want to ensure you and your family are getting the most out of our service.\n\nTo welcome you back, "
                "we'd like to offer you a special **30-day free trial** to re-engage with all the latest music, podcasts, "
                "and features you might have missed. Rediscover millions of songs, create new playlists, "
                "and share the joy of music with your family again.\n\nClick here to reactivate your free trial and start listening: [Link to Reactivation Page]\n\nWe hope to see you back soon!\n\nBest regards,\nYour Music Team"
            }
        }
    }

    st.bar_chart(df["churned"].value_counts())

    mails_data = pd.DataFrame(ans).T

    if st.button('Send Mail'):
        for i in df.index:
            cust_id = df.iloc[i]["customer_id"]
            name = df.iloc[i]["name"]
            email_id = df.iloc[i]["email"]
            pred = df.iloc[i]["churned"]
            
            sender_email = "moon24012407@gmail.com"
            receiver_email = email_id
            password = "rjig xxky lwfc xkcb"
            
            # Email content
            subject = mails_data.iloc[pred]['mail']['subject'].replace('name',name)
            
            body = mails_data.iloc[pred]['mail']['body'].replace('name',name)
            
            
            # Create the email
            message = MIMEMultipart()
            message["From"] = sender_email
            message["To"] = receiver_email
            message["Subject"] = subject
            message.attach(MIMEText(body, "plain"))
            
            # Set up the SMTP server and send the email
            try:
                server = smtplib.SMTP("smtp.gmail.com", 587)
                server.starttls()  # Secure the connection
                server.login(sender_email, password)
                server.sendmail(sender_email, receiver_email, message.as_string())
                server.quit()
                st.write(f"{cust_id} : Email sent successfully!")
            except Exception as e:
                st.write(f"{cust_id} : Failed to send email: {e}")
st.write("Accurace : 0.82328")