import streamlit as st
import numpy as np
from joblib import load   

st.title("book recomandation")

model = load("model.pkl")
books_name = load("book_names.pkl")
final_rating = load("final_rating.pkl")
book_pivot_tale = load("book_pivot_tale.pkl")

select_book = st.selectbox("select book",options=books_name)

if st.button("recommend"):
    def recommended_book(book_name):
        book_id = np.where(book_pivot_tale.index==book_name)[0][0]
        distance,suggestion=model.kneighbors(book_pivot_tale.iloc[book_id,:].values.reshape(1,-1),n_neighbors=6)
        for i in suggestion:
            books = book_pivot_tale.index[i]
            return books
    st.success(list(recommended_book(select_book)))