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36 lines
1.3 KiB
Python
36 lines
1.3 KiB
Python
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from django.core.management.base import BaseCommand
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from apps.recommendations.models import CollaborativelyFilteredRecommendation
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class Command(BaseCommand):
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help = "Generate recommendations based on Collaborative Filtering"
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def add_arguments(self, parser):
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parser.add_argument(
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"--user_id", type=int, required=True, help="ID of the user for whom to generate recommendations"
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)
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parser.add_argument(
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"--n", type=int, default=10, help="Number of recommendations to generate (default is 10)"
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)
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def handle(self, *args, **options):
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# Store user feed data to file
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file_name = "user_feed_data.csv"
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CollaborativelyFilteredRecommendation.store_user_feed_data_to_file(file_name)
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# Load data and get the trained model
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trainset, model = CollaborativelyFilteredRecommendation.load_surprise_data(file_name)
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user_id = options["user_id"]
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n = options["n"]
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# Get recommendations
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recommendations = CollaborativelyFilteredRecommendation.get_recommendations(
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trainset, user_id, model, n
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)
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# Print the recommendations
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self.stdout.write(self.style.SUCCESS(f"Recommendations for user {user_id}:"))
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for feed_id in recommendations:
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self.stdout.write(str(feed_id))
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