import streamlit as st
import numpy as np
import pickle
import streamlit.components.v1 as components
from sklearn.preprocessing import LabelEncoder

# Load the pickled model
@st.cache_resource
def load_model():
    with open('online_payment_fraud_detection_randomforest.pkl', 'rb') as f:
        return pickle.load(f)

# Load the LabelEncoder
@st.cache_resource
def load_label_encoder():
    with open('label_encoder.pkl', 'rb') as f:
        return pickle.load(f)

# Function for model prediction
def model_prediction(model, features):
    predicted = str(model.predict(features)[0])
    return predicted

def transform(le, text):
    text = le.transform(text)
    return text[0]

def app_design(le):
    st.subheader("Enter the following values:")

    step = st.number_input("Step: represents a unit of time where 1 step equals 1 hour", min_value=0)
    typeup = st.selectbox('Type of online transaction', ('PAYMENT', 'TRANSFER', 'CASH_OUT', 'DEBIT', 'CASH_IN'))
    typeup = transform(le, [typeup])

    amount = st.number_input("The amount of the transaction", min_value=0.0)

    nameOrig = st.text_input("Transaction ID (any ID)").strip()
    nameOrig_transformed = transform(le, ['No'])  # Dummy fallback for ID field

    oldbalanceOrg = st.number_input("Balance before the transaction", min_value=0.0)
    newbalanceOrig = st.number_input("Balance after the transaction", min_value=0.0)

    nameDest = st.text_input("Recipient ID (any ID)").strip()
    nameDest_transformed = transform(le, ['No'])  # Dummy fallback for ID field

    oldbalanceDest = st.number_input("Initial balance of recipient before the transaction", min_value=0.0)
    newbalanceDest = st.number_input("The new balance of recipient after the transaction", min_value=0.0)

    isFlaggedFraud = st.selectbox('Is this transaction flagged as fraud?', ('Yes', 'No'))
    isFlaggedFraud = transform(le, [isFlaggedFraud])
    
    # Create a feature list from the user inputs
    features = np.array([[step, typeup, amount, nameOrig_transformed, oldbalanceOrg, newbalanceOrig, nameDest_transformed, oldbalanceDest, newbalanceDest, isFlaggedFraud]])

    # Load the model
    model = load_model()
    
    # Make a prediction when the user clicks the "Predict" button
    if st.button('Predict Online Payment Fraud'):
        predicted_value = model_prediction(model, features)
        if predicted_value == '1':
            st.success("🚨 Online payment fraud detected!")
        else:
            st.success("✅ No online payment fraud detected.")

def about_RamDevs():
    components.html("""
    <div>
        <h4>🚀 Unlock Your Easy Safety with RamDevs Community!</h4>
        <p class="subtitle">🔍 Seeking the perfect hassle-free safe online transactions? RamDevs Community is your gateway to easier and safer transactions. Explore free expert sessions, customer support, and password transformation tips.</p>
        <p class="subtitle">💼 We offer an upskill program in <b>CyberSecurity, Password management, Legal Terms and Services</b>, and assist customers in <b>security and safer online transactions</b> at minimal development costs.</p>
        <p class="subtitle">🆓 Best of all, everything we offer is <b>completely free</b>! We are dedicated to helping society.</p>
        <p class="subtitle">Book free of cost 1:1 mentorship on any topic of your choice — <a class="link" href="https://topmate.io/deepakchawla1307">topmate</a></p>
        <p class="subtitle">✨ We dedicate over 30 minutes to each applicant’s Password selection, Online profile, mock frauds, and upskill program. If you’d like our guidance, check out our services <a class="link" href="https://RamDevscommunity.wixsite.com/RamDevs">here</a></p>
        <p class="subtitle">💡 Join us now, and turbocharge your CyberSecurity!</p>
        <p class="subtitle">
            <a class="link" href="https://RamDevscommunity.wixsite.com/RamDevs" target="__blank">Website</a>
            <a class="link" href="https://www.youtube.com/@RamDevsCommunity1307/" target="__blank">YouTube</a>
            <a class="link" href="https://www.instagram.com/RamDevs_community/" target="__blank">Instagram</a>
            <a class="link" href="https://medium.com/@RamDevscommunity" target="__blank">Medium</a>
            <a class="link" href="https://www.linkedin.com/company/RamDevs-community/" target="__blank">LinkedIn</a>
            <a class="link" href="https://github.com/RamDevscommunity" target="__blank">GitHub</a>
        </p>
    </div>
    """, height=600)

def main():
    st.set_page_config(page_title="Online Payment Fraud Detection", page_icon=":chart_with_upwards_trend:")
    st.title("Welcome to our Online Payment Fraud Detection App! 🚀")

    le = load_label_encoder()
    app_design(le)
    st.header("About RamDevs Community")
    about_RamDevs()

if __name__ == '__main__':
    main()