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3fa3306
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1 Parent(s): 1c8893a

Add initial app.py

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  1. app.py +80 -0
app.py ADDED
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+ import pickle
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+ import streamlit as st
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+ import numpy as np
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+
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+
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+ st.header("Book Recommender System")
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+
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+ # model = pickle.load(open("artifacts/model.pkl", "rb"))
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+ # book_names = pickle.load(open("artifacts/book_names.pkl", "rb"))
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+ # final_ratings = pickle.load(open("artifacts/final_ratings.pkl", "rb"))
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+ # book_pivot = pickle.load(open("artifacts/book_pivot.pkl", "rb"))
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+
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+ # def fetch_poster(suggestion):
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+ # bookNames = []
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+ # idsIndex = []
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+ # posterUrl = []
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+
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+ # for bookId in suggestion[0]:
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+ # name = book_pivot.index[bookId]
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+
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+ # bookNames.append(book_pivot.index[bookId])
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+
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+ # for name in bookNames:
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+ # ids = np.where(final_ratings['title'] == name)[0][0]
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+ # idsIndex.append(ids)
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+
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+ # for idx in idsIndex:
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+ # row = final_ratings.iloc[idx]
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+ # url = row['img_url']
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+ # posterUrl.append(url)
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+
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+ # return posterUrl
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+
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+ # def recommend_book(bookName):
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+ # bookList = []
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+
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+ # book_id = np.where(book_pivot.index == bookName)[0][0]
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+
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+ # distance, suggestion = model.kneighbors(book_pivot.iloc[book_id,:].values.reshape(1, -1), n_neighbors=5)
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+
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+ # poster_url = fetch_poster(suggestion)
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+
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+ # for i in range(len(suggestion)):
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+ # books = book_pivot.index[suggestion[i]]
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+
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+ # for j in books:
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+ # bookList.append(j)
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+
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+ # return bookList, poster_url
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+
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+ # selected_books = st.selectbox(
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+ # "Select a book",
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+ # book_names
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+ # )
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+
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+ # if st.button("Show Recommendations"):
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+ # recommendations, posterUrls = recommend_book(selected_books)
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+
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+ # st.subheader("Recommendations")
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+
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+ # col1, col2, col3, col4 = st.columns(4)
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+
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+ # for url in posterUrls:
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+ # print(url)
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+
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+ # with col1:
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+ # st.text(recommendations[1])
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+ # st.image(posterUrls[1])
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+
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+ # with col2:
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+ # st.text(recommendations[2])
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+ # st.image(posterUrls[2])
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+
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+ # with col3:
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+ # st.text(recommendations[3])
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+ # st.image(posterUrls[3])
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+
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+ # with col4:
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+ # st.text(recommendations[4])
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+ # st.image(posterUrls[4])