def get_reco(title, cs_matrix, indices_dict, df):
    """
    Given a movie title and a pre-trained similarity matrix, return the top 10 most simililar movies
    Input:
        1. title in string
        2. cosine similarity matrix (Fitted)
        3. dictionary of mapping of title to index
        4. dataframe to retrieve title given index
    Output:
        1. list of top 10 movie titles
    """
    if title == None:
        return ["Generating results..."]
    # Get the index of the movie that matches the title
    idx = indices_dict[title]

    # Get the similarity scores of all 10K movies that are related to this movie & sort it & return top 10
    sim_scores = sorted(
        list(enumerate(cs_matrix[idx])), key=lambda x: x[1], reverse=True
    )[1:11]

    # top 10 movie indices
    movie_indices = [i[0] for i in sim_scores]

    # top 10 movie titles
    return df["title"].iloc[movie_indices]