recommender.py

import pickle
import requests

movies = pickle.load(open('movies.pkl', 'rb'))
similarity = pickle.load(open('similarity.pkl', 'rb'))

API_KEY = "YOUR-API-KEY"

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

def recommend(movie):
    movie_index = movies[movies['title'].str.lower() == movie.lower()].index[0]
    distances = similarity[movie_index]

    movies_list = sorted(
        list(enumerate(distances)),
        reverse=True,
        key=lambda x: x[1]
    )[1:6]

    names = []
    posters = []

    for i in movies_list:
        movie_id = movies.iloc[i[0]].movie_id
        names.append(movies.iloc[i[0]].title)
        posters.append(fetch_poster(movie_id))

    return names, posters