import streamlit as st
import requests

st.set_page_config(
    page_title="ExtraaLearn Lead Conversion Predictor",
    layout="centered"
)

st.title("🎓 ExtraaLearn Lead Conversion Prediction")

st.write("Fill in the lead details below to predict conversion likelihood.")

# ---------------- INPUT FIELDS ---------------- #

age = st.number_input("Age", min_value=18, max_value=80, value=57)

current_occupation = st.selectbox(
    "Current Occupation",
    ["Student", "Working Professional", "Unemployed"]
)

first_interaction = st.selectbox(
    "First Interaction",
    ["Website", "Email", "Referral", "Social Media"]
)

profile_completed = st.selectbox(
    "Profile Completion Level",
    ["Low", "Medium", "High"]
)

website_visits = st.number_input(
    "Website Visits", min_value=0, max_value=100, value=7
)

time_spent_on_website = st.number_input(
    "Time Spent on Website (seconds)", min_value=0, value=1639
)

page_views_per_visit = st.number_input(
    "Page Views per Visit", min_value=0.0, value=1.861
)

last_activity = st.selectbox(
    "Last Activity",
    ["Website Activity", "Email Opened", "SMS Clicked", "Form Submitted"]
)

print_media_type1 = st.selectbox(
    "Print Media Type 1",
    ["Yes", "No"]
)

print_media_type2 = st.selectbox(
    "Print Media Type 2",
    ["Yes", "No"]
)

digital_media = st.selectbox(
    "Digital Media",
    ["Yes", "No"]
)

educational_channels = st.selectbox(
    "Educational Channels",
    ["Yes", "No"]
)

referral = st.selectbox(
    "Referral",
    ["Yes", "No"]
)

# ---------------- PREDICT ---------------- #

if st.button("Predict Conversion"):
    payload = {
        "inputs": [
            {
                "age": age,
                "current_occupation": current_occupation,
                "first_interaction": first_interaction,
                "profile_completed": profile_completed,
                "website_visits": website_visits,
                "time_spent_on_website": time_spent_on_website,
                "page_views_per_visit": page_views_per_visit,
                "last_activity": last_activity,
                "print_media_type1": 1 if print_media_type1 == "Yes" else 0,
                "print_media_type2": 1 if print_media_type2 == "Yes" else 0,
                "digital_media": 1 if digital_media == "Yes" else 0,
                "educational_channels": 1 if educational_channels == "Yes" else 0,
                "referral": 1 if referral == "Yes" else 0
            }
        ]
    }

    BACKEND_URL = "https://rohitmv-extra-learn-be.hf.space/predict"

    try:
        response = requests.post(BACKEND_URL, json=payload, timeout=15)

        if response.status_code == 200:
            result = response.json()

            st.success("Prediction Successful")

            st.metric(
                "Conversion Probability",
                f"{int(result['conversion_probability'] * 100)}%"
            )

            st.write(
                "### ✅ Likely to Convert"
                if result["prediction"] == 1
                else "### ❌ Unlikely to Convert"
            )

            st.write(f"**Lead Category:** {result['lead_category']}")

        else:
            st.error("Backend error")
            st.json(response.json())

    except Exception as e:
        st.error("Could not connect to backend")
        st.write(str(e))