import requests

def fetch_poster(movie_id):
    url = f"https://api.themoviedb.org/3/movie/{movie_id}?api_key=f99f126bfd58ba9b4aa8a3e6db301b6e&language=en-US"
    data = requests.get(url).json()
    poster_path = data['poster_path']
    full_path = f"https://image.tmdb.org/t/p/w500/{poster_path}"
    return full_path

def recommend(movie, movies, similarity):
    index = movies[movies['title'] == movie].index[0]
    distances = sorted(list(enumerate(similarity[index])), reverse=True, key=lambda x: x[1])
    recommended_movies = []
    recommended_posters = []
    for i in distances[1:8]:  # Get top 5 recommendations
        movie_id = movies.iloc[i[0]].id
        recommended_movies.append(movies.iloc[i[0]].title)
        recommended_posters.append(fetch_poster(movie_id))
    return recommended_movies, recommended_posters