diff --git a/ml/digest-score/app.py b/ml/digest-score/app.py
index f9c428100..0e83dab9d 100644
--- a/ml/digest-score/app.py
+++ b/ml/digest-score/app.py
@@ -2,6 +2,7 @@ import logging
 from flask import Flask, request, jsonify
 
 from typing import List
+from timeit import default_timer as timer
 
 import os
 import sys
@@ -24,6 +25,8 @@ logging.basicConfig(level=logging.INFO, stream=sys.stdout)
 USER_HISTORY_PATH = 'user_features.pkl'
 MODEL_PIPELINE_PATH = 'predict_read_pipeline-v002.pkl'
 
+pipeline = None
+user_features = None
 
 def download_from_gcs(bucket_name, gcs_path, destination_path):
   storage_client = storage.Client()
@@ -69,6 +72,21 @@ def merge_dicts(dict1, dict2):
       dict1[key] = value
   return dict1
 
+def refresh_data():
+  start = timer()
+  global pipeline
+  global user_features
+  if os.getenv('LOAD_LOCAL_MODEL') != None:
+    gcs_bucket_name = os.getenv('GCS_BUCKET')
+    download_from_gcs(gcs_bucket_name, f'data/features/user_features.pkl', USER_HISTORY_PATH)
+    download_from_gcs(gcs_bucket_name, f'data/models/predict_read_pipeline-v002.pkl', MODEL_PIPELINE_PATH)
+  pipeline = load_pipeline(MODEL_PIPELINE_PATH)
+  user_features = load_user_features(USER_HISTORY_PATH)
+  end = timer()
+  print('time to refresh data (in seconds):', end - start)
+  print('loaded pipeline:', pipeline)
+  print('loaded number of user_features:', len(user_features))
+
 
 def compute_score(user_id, item_features):
   interaction_score = compute_interaction_score(user_id, item_features)
@@ -132,6 +150,12 @@ def ready():
   return jsonify({'OK': 'yes'}), 200
 
 
+@app.route('/refresh', methods=['GET'])
+def refresh():
+  refresh_data()
+  return jsonify({'OK': 'yes'}), 200
+
+
 @app.route('/users/<user_id>/features', methods=['GET'])
 def get_user_features(user_id):
   result = {}
@@ -191,16 +215,6 @@ def batch():
     app.logger.error(f"exception in batch endpoint: {request.get_json()}\n{e}")
     return jsonify({'error': str(e)}), 500
 
-
-if os.getenv('LOAD_LOCAL_MODEL') != None:
-  gcs_bucket_name = os.getenv('GCS_BUCKET')
-  download_from_gcs(gcs_bucket_name, f'data/features/user_features.pkl', USER_HISTORY_PATH)
-  download_from_gcs(gcs_bucket_name, f'data/models/predict_read_pipeline-v002.pkl', MODEL_PIPELINE_PATH)
-
-
-pipeline = load_pipeline(MODEL_PIPELINE_PATH)
-user_features = load_user_features(USER_HISTORY_PATH)
-print('loaded pipeline and user_features', pipeline, user_features)
-
 if __name__ == '__main__':
+  refresh_data()
   app.run(debug=True, port=5000)
\ No newline at end of file