Upload model.py

model.py

@@ -0,0 +1,13 @@
+import numpy as np
+import pandas as pd
+
+class ContentBasedRecommender:
+    def __init__(self, train_data):
+        self.train_data = train_data
+
+    def predict(self, user_id, k=10):
+        user_books = set(self.train_data[self.train_data['user_id'] == user_id]['book_id'])
+        similar_books = set().union(*(self.train_data[self.train_data['book_id'] == book_id]['similar_books'].iloc[0] for book_id in user_books))
+        recommended_books = list(similar_books - user_books)
+
+        return np.random.choice(recommended_books, size=min(k, len(recommended_books)), replace=False).tolist()