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import sys
from anime_recommender.exception.exception import AnimeRecommendorException
from anime_recommender.loggers.logging import logging
from anime_recommender.utils.main_utils.utils import load_csv_data
from anime_recommender.entity.artifact_entity import DataIngestionArtifact
from anime_recommender.model_trainer.top_anime_filtering import PopularityBasedFiltering
class PopularityBasedRecommendor:
"""
A class that provides anime recommendations based on different popularity criteria.
"""
def __init__(self,data_ingestion_artifact = DataIngestionArtifact):
"""
Initializes the PopularityBasedRecommendor with the ingested anime dataset.
Args:
data_ingestion_artifact (DataIngestionArtifact): An artifact containing the feature store file paths.
"""
try:
self.data_ingestion_artifact = data_ingestion_artifact
except Exception as e:
raise AnimeRecommendorException(e,sys)
def initiate_model_trainer(self,filter_type:str):
"""
Trains the popularity-based recommender model and logs the top anime recommendations
based on the specified filter type.
Args:
filter_type (str): The type of filtering to apply.
Options include:
- 'popular_animes': Most popular anime based on user engagement.
- 'top_ranked_animes': Highest ranked anime.
- 'overall_top_rated_animes': Overall top-rated anime.
- 'favorite_animes': Most favorited anime.
- 'top_animes_members': Anime with the highest number of members.
- 'popular_anime_among_members': Most popular anime among members.
- 'top_avg_rated': Anime with the highest average ratings.
"""
try:
logging.info("Loading transformed data...")
df = load_csv_data(self.data_ingestion_artifact.feature_store_anime_file_path)
recommender = PopularityBasedFiltering(df)
if filter_type == 'popular_animes':
popular_animes = recommender.popular_animes(n =10)
logging.info(f"Popular Anime recommendations: {popular_animes}")
elif filter_type == 'top_ranked_animes':
top_ranked_animes = recommender.top_ranked_animes(n =10)
logging.info(f"top_ranked_animes recommendations: {top_ranked_animes}")
elif filter_type == 'overall_top_rated_animes':
overall_top_rated_animes = recommender.overall_top_rated_animes(n =10)
logging.info(f"overall_top_rated_animes recommendations: {overall_top_rated_animes}")
elif filter_type == 'favorite_animes':
favorite_animes = recommender.favorite_animes(n =10)
logging.info(f"favorite_animes recommendations: {favorite_animes}")
elif filter_type == 'top_animes_members':
top_animes_members = recommender.top_animes_members(n = 10)
logging.info(f"top_animes_members recommendations: {top_animes_members}")
elif filter_type == 'popular_anime_among_members':
popular_anime_among_members = recommender.popular_anime_among_members(n =10)
logging.info(f"popular_anime_among_members recommendations: {popular_anime_among_members}")
elif filter_type == 'top_avg_rated':
top_avg_rated = recommender.top_avg_rated(n =10)
logging.info(f"top_avg_rated recommendations: {top_avg_rated}")
except Exception as e:
raise AnimeRecommendorException(e,sys) |