diff --git a/server/website/website/tasks/async_tasks.py b/server/website/website/tasks/async_tasks.py
index 7153151..c7a2583 100644
--- a/server/website/website/tasks/async_tasks.py
+++ b/server/website/website/tasks/async_tasks.py
@@ -25,8 +25,7 @@ from analysis.gpr import ucb
 from analysis.gpr.optimize import tf_optimize
 from analysis.preprocessing import Bin, DummyEncoder
 from analysis.constraints import ParamConstraintHelper
-from website.models import (PipelineData, PipelineRun, Result, Workload, KnobCatalog, SessionKnob,
-                            MetricCatalog)
+from website.models import PipelineData, PipelineRun, Result, Workload, SessionKnob, MetricCatalog
 from website import db
 from website.types import PipelineTaskType, AlgorithmType, VarType
 from website.utils import DataUtil, JSONUtil
@@ -336,7 +335,7 @@ def train_ddpg(result_id):
         prev_result_id = result_id
     else:
         base_result_id = session_results[0].pk
-        prev_result_id = session_results[len(session_results)-1].pk
+        prev_result_id = session_results[len(session_results) - 1].pk
     base_result = Result.objects.filter(pk=base_result_id)
     prev_result = Result.objects.filter(pk=prev_result_id)
 
@@ -381,7 +380,7 @@ def train_ddpg(result_id):
         result.session.dbms.pk, result.session.target_objective)
 
     # Calculate the reward
-    if DDPG_SIMPLE_REWARD:
+    if params['DDPG_SIMPLE_REWARD']:
         objective = objective / base_objective
         if metric_meta[target_objective].improvement == '(less is better)':
             reward = -objective
@@ -505,7 +504,7 @@ def combine_workload(target_data):
     rowlabels_workload = np.array(workload_metric_data['rowlabels'])
 
     # Target workload data
-    newest_result = Result.objects.get(pk=target_data['newest_result_id']) 
+    newest_result = Result.objects.get(pk=target_data['newest_result_id'])
     X_target = target_data['X_matrix']
     y_target = target_data['y_matrix']
     rowlabels_target = np.array(target_data['rowlabels'])
@@ -652,7 +651,8 @@ def combine_workload(target_data):
         X_min[i] = col_min
         X_max[i] = col_max
 
-    return X_columnlabels, X_scaler, X_scaled, y_scaled, X_max, X_min
+    return X_columnlabels, X_scaler, X_scaled, y_scaled, X_max, X_min,\
+        dummy_encoder, constraint_helper
 
 
 @task(base=ConfigurationRecommendation, name='configuration_recommendation')
@@ -661,7 +661,7 @@ def configuration_recommendation(recommendation_input):
     LOG.info('configuration_recommendation called')
     newest_result = Result.objects.get(pk=target_data['newest_result_id'])
     session = newest_result.session
-    params = session.hyper_parameters
+    params = JSONUtil.loads(session.hyper_parameters)
 
     if target_data['bad'] is True:
         target_data_res = create_and_save_recommendation(
@@ -672,9 +672,8 @@ def configuration_recommendation(recommendation_input):
                   AlgorithmType.name(algorithm), JSONUtil.dumps(target_data, pprint=True))
         return target_data_res
 
-    latest_pipeline_run = PipelineRun.objects.get(pk=target_data['pipeline_run'])
-
-    X_columnlabels, X_scaler, X_scaled, y_scaled, X_max, X_min = combine_workload(target_data)
+    X_columnlabels, X_scaler, X_scaled, y_scaled, X_max, X_min,\
+        dummy_encoder, constraint_helper = combine_workload(target_data)
 
     # FIXME: we should generate more samples and use a smarter sampling
     # technique
@@ -698,9 +697,9 @@ def configuration_recommendation(recommendation_input):
             # make sure it is within the range.
             dist = sum(np.square(X_max - X_scaled[item[1]]))
             if dist < 0.001:
-                X_samples = np.vstack((X_samples, X_scaled[item[1]] - abs(GPR_EPS)))
+                X_samples = np.vstack((X_samples, X_scaled[item[1]] - abs(params['GPR_EPS'])))
             else:
-                X_samples = np.vstack((X_samples, X_scaled[item[1]] + abs(GPR_EPS)))
+                X_samples = np.vstack((X_samples, X_scaled[item[1]] + abs(params['GPR_EPS'])))
             i = i + 1
         except queue.Empty:
             break