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import streamlit as st | |
import faiss | |
import pandas as pd | |
from functions.loader import data, index | |
from functions.logic import load_image, find_similar_shows | |
st.title('TV Show Recommender') | |
# User input for the show description | |
user_description = st.text_area("Describe the TV show you're looking for:") | |
# Slider for the number of recommendations | |
num_recommendations = st.slider('Number of recommendations:', min_value=1, max_value=10, value=5) | |
# Button to get recommendations | |
if st.button('Recommend') and user_description: | |
try: | |
recommended_shows = find_similar_shows(user_description, index, num_recommendations) | |
for idx in recommended_shows.index: | |
with st.container(): | |
link = data.loc[idx, 'url'] | |
poster_url = data.loc[idx, 'img'] | |
title = data.loc[idx, 'title'] | |
description = data.loc[idx, 'description'] | |
img = load_image(poster_url) # Use the load_image function | |
col1, col2 = st.columns([1, 2]) | |
with col1: | |
st.image(img, caption=title, use_column_width='always') | |
with col2: | |
st.write(description) | |
st.markdown(f"[More Info]({link})", unsafe_allow_html=True) | |
except Exception as e: | |
st.error(f"An error occurred: {e}") | |