from PIL import Image
import requests
from io import BytesIO
from functions.loader import model, data



def load_image(url):
    try:
        response = requests.get(url)
        img = Image.open(BytesIO(response.content))
    except Exception:
        img = Image.open("data/cat.jpg")
    return img


def vectorize(descriptions):
    embeddings = model.encode(descriptions)
    return embeddings


def find_similar_shows(user_description, index, k=5):
    query_vector = vectorize([user_description])
    _, indices = index.search(query_vector, k)
    return data.iloc[indices.flatten()]