word2vec get recommendations

recommend_next_purchase.py

def recommend_next_purchase(model: Word2Vec, df:pd.DataFrame, user_id:int)->pd.DataFrame:
    """
    Parameters
    ----------
    model : instance of Word2Vec
    df : dataframe with preprocessed data
    user_id : int
        unique user id for whom we make recommendations
    Returns
    -------
    dataframe with recommended products
    """
    try:
        # Find the products the user browsed
        viewed_products = df.loc[df['user_id']==user_id]['product_id'].unique()
        # Get recommendations for next purchase
        output_words = model.predict_output_word([str(product) for product in viewed_products])
   
        return df.loc[df['product_id'].isin([int(word[0]) 
                                             for word in output_words])][[
                                                     'category_code',
                                                     'brand',
                                                     'product_id']].drop_duplicates()
            
    except KeyError:
        return f"Cannot find the specified user with id {user_id}"