app.py

import pickle
import streamlit as st

st.set_page_config(layout="wide")

from streamlit_modal import Modal

import numpy as np
import bookdb

import ai_services

st.header("My Book Buddy 🐛")

if "clicked_book" not in st.session_state:
    st.session_state["clicked_book"] = {}

if "closestReadBook" not in st.session_state:
    st.session_state["closestReadBook"] = None

if "suggestedBookText" not in st.session_state:
    st.session_state["suggestedBookText"] = ""

if "upvoted_book_ids" not in st.session_state:
    st.session_state["upvoted_book_ids"] = []

if "downvoted_book_ids" not in st.session_state:
    st.session_state["downvoted_book_ids"] = []

if "recommendedBooksData" not in st.session_state:
    st.session_state["recommendedBooksData"] = None

if "topCorrelatedReadersData" not in st.session_state:
    st.session_state["topCorrelatedReadersData"] = None

if "numSimilarUsers" not in st.session_state:
    st.session_state["numSimilarUsers"] = 0

def update_display(displayData):
    st.session_state["upvoted_book_ids"] = displayData["upvotedBookIds"]
    st.session_state["downvoted_book_ids"] = displayData["downvotedBookIds"]
    
    st.session_state["numSimilarUsers"] = displayData["numSimilarUsers"]
    st.session_state["recommendedBooksData"] = displayData["recommendedBooksData"]
    st.session_state["topCorrelatedReadersData"] = displayData["topCorrelatedReadersData"]

    st.session_state["bookByRatingData"] = displayData["bookByRatingData"]

def on_reset_votes():
    st.session_state["upvoted_book_ids"] = []
    st.session_state["downvoted_book_ids"] = []
    st.session_state["numSimilarUsers"] = 0
    st.session_state["recommendedBooksData"] = None
    st.session_state["topCorrelatedReadersData"] = None
    st.session_state["bookByRatingData"] = None

def on_test_submit_votes():
    upvotedBookIds =  [104, 103, 102, 110, 113, 124, 129, 135, 141, 142, 155, 161, 165, 176, 181, 974, 4443, 1496, 1003, 2600] # TODO REMOVE
    downvotedBookIds =  [126, 179, 183, 184, 187, 9076, 960, 5895, 777, 6902, 2084, 584] # TODO REMOVE

    update_display(bookdb.update_user_ratings(upvotedBookIds, downvotedBookIds))

def on_submit_votes():
    upvoteBookTitles = st.session_state["multiselect_upvote"]
    downvoteBookTitles = st.session_state["multiselect_downvote"]

    if len(upvoteBookTitles) == 0 and len(downvoteBookTitles) == 0:
        st.warning("Please select at least one book to upvote or downvote")
        return
    
    booksToUpvote = bookdb.get_book_ids_by_title(upvoteBookTitles)
    booksToDownvote = bookdb.get_book_ids_by_title(downvoteBookTitles)
    
    # get the currently voted book ids
    upvotedBookIds = st.session_state["upvoted_book_ids"]
    downvotedBookIds = st.session_state["downvoted_book_ids"]

    if (len(upvotedBookIds) + len(booksToUpvote)) == 0 or (len(downvotedBookIds) + len(booksToDownvote)) == 0:
        st.warning("You must select at least one book to upvote and one book to downvote")
        return

    # append booksToUpvote to upvotedBookIds
    upvotedBookIds.extend(booksToUpvote)
    # append booksToDownvote to downvotedBookIds
    downvotedBookIds.extend(booksToDownvote)

    # remove any upvoted books from downvotedBookIds if they are in there
    downvotedBookIds = [x for x in downvotedBookIds if x not in upvotedBookIds]
    
    # clear the multiselects
    st.session_state.multiselect_upvote = []
    st.session_state.multiselect_downvote = []    

    update_display(bookdb.update_user_ratings(upvotedBookIds, downvotedBookIds))

clickedBook = st.session_state["clicked_book"] if "clicked_book" in st.session_state else {}

modal = Modal(
    f"📖 {clickedBook['title'] if 'title' in clickedBook else ''}",
    key="book-modal"
)

def on_update_recommendations():
    # iterate through the number of recommendations and check the selected radio button

    recommendations = st.session_state["recommendedBooksData"]

    bookIdsToUpvote = []
    bookIdsToDownvote = []

    for counter in range(len(recommendations)):
        radioKey = f"update_recommendation_{counter}"

        radioValue = st.session_state[radioKey]

        if radioValue == "👍":
            bookIdsToUpvote.append(recommendations[counter]["book_id"])
        elif radioValue == "👎":
            bookIdsToDownvote.append(recommendations[counter]["book_id"])

        # reset the radio button
        st.session_state[radioKey] = None

    if len(bookIdsToUpvote) == 0 and len(bookIdsToDownvote) == 0:
        st.warning("Please select at least one book to upvote or downvote")
        return
    
    # append booksToUpvote to upvotedBookIds
    upvotedBookIds = st.session_state["upvoted_book_ids"]
    downvotedBookIds = st.session_state["downvoted_book_ids"]

    upvotedBookIds.extend(bookIdsToUpvote)
    downvotedBookIds.extend(bookIdsToDownvote)

    # remove any upvoted books from downvotedBookIds if they are in there
    downvotedBookIds = [x for x in downvotedBookIds if x not in upvotedBookIds]

    update_display(bookdb.update_user_ratings(upvotedBookIds, downvotedBookIds))

if st.session_state["recommendedBooksData"] is not None:
    recommendations = st.session_state["recommendedBooksData"]

    st.subheader("Recommendations")

    recommendationsCol1, recommendationsCol2, recommendationsCol3 = st.columns(3)

    for counter in range(len(recommendations)):
        bookData = recommendations[counter]

        bookMetadata = bookdb.get_book_metadata_by_id(bookData["book_id"])

        # print(bookMetadata)
    
        if counter % 3 == 0:
            container = recommendationsCol1.container(border=True)
        elif counter % 3 == 1:
            container = recommendationsCol2.container(border=True)
        else:
            container = recommendationsCol3.container(border=True)

        bookAuthor = bookData["authors"]
        bookTitle = bookData["title"]
        bookPubYear = bookData["original_publication_year"]

        containerCol1, containerCol2, containerCol3  = container.columns([5, 10, 2])

        containerCol1.html(f"<img width='100%' src='{bookMetadata['thumbnail']}'>")
    
        textContainer = containerCol2.container()

        titleClicked = textContainer.button(f"{bookTitle}", use_container_width=True)

        if titleClicked:
            bookByRatingData = st.session_state["bookByRatingData"] 
            upvotedBookIds = st.session_state["upvoted_book_ids"]
            targetBookId = bookData["book_id"]

            closestReadBookData = bookdb.find_closest_read_title(bookByRatingData, upvotedBookIds, targetBookId)

            targetBookData = bookdb.get_book_data_by_id(targetBookId)

            st.session_state["closestReadBook"] = closestReadBookData
            st.session_state["clicked_book"] = bookData

            st.session_state["suggestedBookText"] = ai_services.get_suggestion_text(closestReadBookData, targetBookData)

            modal.open()            
        
        textContainer.markdown(f"*{bookAuthor}*")

        textContainer.markdown(f"Published: {int(bookPubYear)}")
                             
        # containerCol2.markdown(textHTMLcontent, unsafe_allow_html=True)
        # containerCol2.markdown(f"[{bookTitle}](https://streamlit.io)\n\n*{bookAuthor}*\n\nPublished: {int(bookPubYear)}")
        # radioContainer = containerCol3.container()

        containerCol3.radio(label="Upvote/Downvote", label_visibility="hidden", options=["👍", "👎"], key=f"update_recommendation_{counter}", index=None)        

        # radioContainer.button('Why This Book?', type="secondary", key=f"submit_{counter}")

    st.button('Update Recommendations', type="primary", on_click=on_update_recommendations)

    st.subheader("Your Ratings")

    displayCol1, displayCol2 = st.columns(2)

    if len(st.session_state["upvoted_book_ids"]) > 0:
        upvotedBookIds = st.session_state["upvoted_book_ids"]

        displayCol1.markdown(f"Upvoted: {len(upvotedBookIds)} book(s)")

        for bookId in upvotedBookIds:
            displayCol1.markdown(f'  - {bookId}-{bookdb.get_book_title(bookId)}')

    if len(st.session_state["downvoted_book_ids"]) > 0:
        downvotedBookIds = st.session_state["downvoted_book_ids"]

        displayCol2.markdown(f'Downvoted: {len(downvotedBookIds)} book(s)')

        for bookId in downvotedBookIds:
            displayCol2.markdown(f'  - {bookId}-{bookdb.get_book_title(bookId)}')

    st.button('Reset All Ratings', type="secondary", on_click=on_reset_votes)

    # st.write(f"Similar User Min Percent Shared Books = {round(bookdb.SIMILAR_USER_MIN_PERCENT_SHARED_BOOKS * 100)}%")
    # st.write(f"Similar User Min Correlation = {bookdb.SIMILAR_USER_MIN_CORRELATION}")
    
    # if "numSimilarUsers" in st.session_state:
        # st.write(f"{st.session_state['numSimilarUsers']} similar users")

with st.form(key='upvote_form'):
    col1, col2 = st.columns(2)

    allBookTitles = bookdb.get_all_book_titles()

    myRatedBookTitles = bookdb.get_book_titles(st.session_state["upvoted_book_ids"] + st.session_state["downvoted_book_ids"])

    # remove myRatedBookTitles from allBookTitles
    remainingBookTitles = [x for x in allBookTitles if x not in myRatedBookTitles]

    col1.multiselect(
        'Upvote Books 👍', 
        remainingBookTitles,
        key='multiselect_upvote'
    )
    col2.multiselect(
        'Downvote Books 👎', 
        remainingBookTitles,
        key='multiselect_downvote'
    )
    st.form_submit_button(label='Submit', type="primary", on_click=on_submit_votes)

    st.form_submit_button(label='Test', type="secondary", on_click=on_test_submit_votes)

if st.session_state["topCorrelatedReadersData"] is not None:
    df = st.session_state["topCorrelatedReadersData"]

    st.subheader("Top Correlated Readers")

    st.dataframe(df, use_container_width=True)

if modal.is_open():
    with modal.container():
        clickedBook = st.session_state["clicked_book"]

        clickedBookMetadata = bookdb.get_book_metadata_by_id(clickedBook["book_id"])

        clickedBookDescription = clickedBookMetadata["description"]

        st.html(f"{clickedBookDescription}")
        
        aiSuggestContainer = st.container(border=True)

        closestReadBook = st.session_state["closestReadBook"]

        suggestedBookText = st.session_state["suggestedBookText"]

        aiSuggestContainer.html(f"<p style=\"color:#DA70D6;\">💫 Because you liked <i><b>{closestReadBook['title']}</b></i> by <b>{closestReadBook['authors']}</b>...</p>")
        
        aiSuggestContainer.html(f"<p style=\"color:#DA70D6;\">{suggestedBookText}</p>")

        buttonCol1, buttonCol2, buttonCol3, buttonCol4  = st.columns(4)

        clickedBookTitle = clickedBook["title"]
        clickedBookAuthor = clickedBook["authors"]
        clickedBookISBN = clickedBook["isbn"]

        outboundLinkSuffix = f"{clickedBookTitle} {clickedBookAuthor}"

        buttonCol1.link_button('🛒 Bookshop', f'https://bookshop.org/search?keywords={outboundLinkSuffix}')
        buttonCol2.link_button('📚 Biblio', f'https://www.biblio.com/search.php?stage=1&title={outboundLinkSuffix}')
        buttonCol3.link_button('🎧 Libro', f'https://libro.fm/search?utf8=%E2%9C%93&q={outboundLinkSuffix}')
        buttonCol4.link_button('💬 Hardcover', f'https://hardcover.app/search?q={outboundLinkSuffix}')

st.write("Version 0.1.0")