import streamlit as st import pandas as pd import pickle import requests def fetch_poster(movie_id): url = "https://api.themoviedb.org/3/movie/{}?api_key=8265bd1679663a7ea12ac168da84d2e8&language=en-US".format(movie_id) data = requests.get(url) data = data.json() poster_path = data['poster_path'] full_path = "https://image.tmdb.org/t/p/w500/" + poster_path return full_path def recommend(movie): movie_index = movies[movies['title'] == movie].index[0] distances = similarity[movie_index] movies_list = sorted(list(enumerate(distances)), reverse =True,key=lambda x: x[1])[1:6] recommended_movies = [] recommended_movies_posters = [] for i in movies_list: movie_id = movies.iloc[i[0]].movie_id # Help to fetch poster from api recommended_movies.append(movies.iloc[i[0]]['title']) recommended_movies_posters.append(fetch_poster(movie_id)) return recommended_movies, recommended_movies_posters movies = pickle.load(open('movies.pkl','rb')) similarity = pickle.load(open('similarity.pkl', 'rb')) st.title('Movie Recommendation App') selected_movie = st.selectbox( 'Select a movie to get recommendations', movies['title'].values) if st.button('Get Recommendations'): names,posters = recommend(selected_movie) col1, col2, col3,col4,col5 = st.columns(5) with col1: st.text(names[0]) st.image(posters[0]) with col2: st.text(names[1]) st.image(posters[1]) with col3: st.text(names[2]) st.image(posters[2]) with col4: st.text(names[3]) st.image(posters[3]) with col5: st.text(names[4]) st.image(posters[4]) hide_streamlit_style = """ """ st.markdown(hide_streamlit_style, unsafe_allow_html=True) footer=""" """ st.markdown(footer,unsafe_allow_html=True)