| 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))) |