main.py

import streamlit as st
import pandas as pd
from loading_file import precomputed_df  # Import pre-fetched dataset

# Function to search for application numbers
def search_application(application_number):
    if precomputed_df is None:
        st.error("Data not available. Please reload the app.")
        return
    
    # Ensure input is numeric only
    if not application_number.isdigit():
        st.error("Invalid input! Please enter only numeric application numbers.")
        return

    application_number = str(application_number)
    
    result = precomputed_df[precomputed_df["Application Number"] == application_number]

    if not result.empty:
        st.success(f"Record found for Application Number: {application_number}")
        st.table(result)
    else:
        st.warning(f"No record found for Application Number: {application_number}")

        # Find nearest applications
        precomputed_df["Application Number"] = precomputed_df["Application Number"].astype(int)
        application_number = int(application_number)

        nearest_before = precomputed_df[precomputed_df["Application Number"] < application_number].max()
        nearest_after = precomputed_df[precomputed_df["Application Number"] > application_number].min()

        nearest_df = pd.DataFrame([
            {"Nearest Application": "Before", "Application Number": nearest_before["Application Number"], "Decision": nearest_before["Decision"], "Difference": abs(nearest_before["Application Number"] - application_number)},
            {"Nearest Application": "After", "Application Number": nearest_after["Application Number"], "Decision": nearest_after["Decision"], "Difference": abs(nearest_after["Application Number"] - application_number)}
        ])

        st.write("Nearest Application Numbers:")
        st.table(nearest_df)

# UI for searching application numbers
st.title("Visa Application Status Checker")
application_number = st.text_input("Enter Application Number:")
if st.button("Search"):
    search_application(application_number)