# Streamlit Web App for Extraa_Learn prediction
import streamlit as st
import requests
import numpy as np

# App Title
st.title("Extraa Learn Lead Conversion Prediction")

# User Inputs                              
Age = st.number_input("Age", min_value=18, max_value=100, value=35)
current_occupation = st.selectbox("Current Occupation", ["Professional", "Unemployed", "Student"])
first_interaction = st.selectbox("First Interaction", ["Website", "Mobile App"])
profile_completed = st.selectbox("Profile Completed", ["High", "Medium", "Low"])
website_visits = st.number_input("Website Visits", min_value=0, value=3)
time_spent_on_website = st.number_input("Time Spent on Website (seconds)", min_value=0, value=500)
page_views_per_visit = st.number_input("Page Views Per Visit", min_value=0.0, value=3.0)
last_activity = st.selectbox("Last Activity", ["Email Activity", "Phone Activity", "Website Activity"])
print_media_type1 = st.selectbox("Seen Ad in Newspaper?", ["Yes", "No"])
print_media_type2 = st.selectbox("Seen Ad in Magazine?", ["Yes", "No"])
digital_media = st.selectbox("Seen Ad on Digital Platforms?", ["Yes", "No"])
educational_channels = st.selectbox("Heard via Educational Channels?", ["Yes", "No"])
referral = st.selectbox("Heard via Referral?", ["Yes", "No"])


# Prepare JSON payload for the backend
product_data = {
   "age": int(Age),
    "current_occupation": current_occupation.strip(),
    "first_interaction": first_interaction.strip(),
    "profile_completed": profile_completed.strip(),
    "website_visits": int(website_visits),
    "time_spent_on_website": float(time_spent_on_website),
    "page_views_per_visit": float(page_views_per_visit),
    "last_activity": last_activity.strip(),
    "print_media_type1": print_media_type1,
    "print_media_type2": print_media_type2,
    "digital_media": digital_media,
    "educational_channels": educational_channels,
    "referral": referral
}
  
  # Trigger Prediction API Call
if st.button("Predict Status", type='primary'):
    try:
        # This is level 1 indentation (4 spaces)
        response = requests.post(
            "https://HSSHETTY01-Extraa_Learn-backend2.hf.space/v1/Status",
            json=product_data
        )
        
        # This must stay at level 1 indentation (4 spaces)
        if response.status_code == 200:
            # This is level 2 indentation (8 spaces)
            result = response.json()
            status_pred = result.get("Status", result.get("prediction", 0))
            
            if status_pred == 1:
                st.success("📈 **Status:** Lead is likely to convert!")
            else:
                st.warning("📉 **Status:** Lead is not likely to convert.")
        else:
            st.error(f"❌ API Error {response.status_code}: {response.text}")
            
    except Exception as e:
        # Aligns perfectly with the 'try:' statement
        st.error(f"⚠️ Connection error: {e}")