Update handler.py

handler.py

@@ -1,26 +1,14 @@
+
 from typing import Dict, List, Any
 import pickle
-import numpy as np
-import pandas as pd
 import os
-import dill
-
-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=k, replace=False) if len(recommended_books) >= k else recommended_books
+from model import ContentBasedRecommender
 
 class EndpointHandler:
     def __init__(self, path=""):
         model_path = os.path.join(path, "model.pkl")
         with open(model_path, 'rb') as f:
-            self.model = dill.load(f)
+            self.model = pickle.load(f)
 
     def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
         user_id = data.pop("user_id", None)
@@ -31,7 +19,7 @@ class EndpointHandler:
 
         try:
             recommended_books = self.model.predict(user_id, k=k)
-            return [{"recommended_books": recommended_books.tolist()}]
+            return [{"recommended_books": recommended_books}]
         except Exception as e:
             return [{"error": str(e)}]