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| import streamlit as st | |
| import pandas as pd | |
| import numpy as np | |
| from PIL import Image | |
| from SVD_Model import Recommender_Model | |
| def load_model(): | |
| return Recommender_Model() | |
| model = load_model() | |
| def view_suggestions(movies_array: list, number_of_suggestions): | |
| movie1 = model.find_nearest_movie(movies_array[0])[0] | |
| movie2 = model.find_nearest_movie(movies_array[1])[0] | |
| movie3 = model.find_nearest_movie(movies_array[2])[0] | |
| suggestions = model.suggest([movie1, movie2, movie3], number_of_suggestions=number_of_suggestions) | |
| for movie in [movie1, movie2, movie3]: | |
| suggestions = suggestions[suggestions['title'] != movie] | |
| suggestions = suggestions.to_numpy() | |
| suggested_movies = [] | |
| for row in suggestions: | |
| name = row[0] | |
| suggested_movies.append(model.get_movie_info(name)) | |
| for idx, info in enumerate(suggested_movies): | |
| if idx >= number_of_suggestions: | |
| break | |
| st.subheader(info['title']) | |
| st.markdown(f"__Overview:__ {info['overview']}") | |
| st.markdown(f"__Genres:__") | |
| st.write(info['genres'], value='genre') | |
| st.markdown(f"__Language:__ {info['language']}") | |
| st.divider() | |
| with st.sidebar: | |
| logo = Image.open("MM Logo.jpeg") | |
| st.image(logo, caption='MM Movie Recommender') | |
| st.title("MM Movie Recommender") | |
| st.subheader("Development Team:") | |
| st.markdown("<a href='https://www.linkedin.com/in/mobin-nesari/'>Mobin Nesari</a>", unsafe_allow_html=True) | |
| st.markdown("<a href='https://www.linkedin.com/in/m0hsnn/'>Seyed Mohsen Sadeghi</a>", unsafe_allow_html=True) | |
| st.markdown("Huge shout-out to __Mohammad Reza Saheb__ & __Mirhossein Adnani Oskoui__ for reviewing and testing beta version!") | |
| st.title("MM Movie Recommender") | |
| st.header("Movie Names:") | |
| st.subheader("Please specify three movies which you like them") | |
| with st.form("input_form"): | |
| movie1 = st.text_input('Movie 1', placeholder="Like Ironman 1") | |
| movie2 = st.text_input('Movie 2', placeholder='Like Ironman 2') | |
| movie3 = st.text_input('Movie 3', placeholder="Like Ironman 3") | |
| number_of_suggestions = st.slider(label = 'How many movies do you want to be suggested?', min_value=1, max_value=10, step=1) | |
| submitted = st.form_submit_button("Submit") | |
| if submitted: | |
| view_suggestions([movie1, movie2, movie3], number_of_suggestions=number_of_suggestions) |