diff --git a/examples/llm_complex/llm_main_example.py b/examples/llm_complex/llm_main_example.py
index 46253d0b..f0916f7d 100644
--- a/examples/llm_complex/llm_main_example.py
+++ b/examples/llm_complex/llm_main_example.py
@@ -12,8 +12,6 @@
 
 from examples.llm_complex.llm_dataprep import dataprep_workflow
 from examples.llm_complex.llm_model import model_train, TransformerModel
-from flowcept.commons.daos.docdb_dao.mongodb_dao import MongoDBDAO
-from flowcept.commons.flowcept_logger import FlowceptLogger
 
 from flowcept.configs import MONGO_ENABLED, INSTRUMENTATION
 from flowcept import Flowcept
@@ -237,7 +235,7 @@ def run_asserts_and_exports(campaign_id, model_search_wf_id):
     return n_workflows_expected, n_tasks_expected
 
 
-def save_files(campaign_id, model_search_wf_id, output_dir="output_data"):
+def save_files(mongo_dao, campaign_id, model_search_wf_id, output_dir="output_data"):
     os.makedirs(output_dir, exist_ok=True)
     best_task = Flowcept.db.query({"workflow_id": model_search_wf_id, "activity_id": "model_train"}, limit=1,
                                   sort=[("generated.test_loss", Flowcept.db.ASCENDING)])[0]
@@ -258,8 +256,7 @@ def save_files(campaign_id, model_search_wf_id, output_dir="output_data"):
                f"{output_dir}/wf_{model_search_wf_id}_transformer_wikitext2.pth")
 
     print("Deleting best model from the database.")
-    dao = MongoDBDAO(create_indices=False)
-    dao.delete_object_keys("object_id", [doc["object_id"]])
+    mongo_dao.delete_object_keys("object_id", [doc["object_id"]])
 
     workflows_file = f"{output_dir}/workflows_{uuid.uuid4()}.json"
     print(f"workflows_file = '{workflows_file}'")
@@ -311,7 +308,7 @@ def run_campaign():
     return _campaign_id, _dataprep_wf_id, _search_wf_id, epochs, max_runs, dataprep_generated["train_n_batches"], dataprep_generated["val_n_batches"]
 
 
-def asserts_on_saved_dfs(workflows_file, tasks_file, n_workflows_expected, n_tasks_expected, epoch_iterations, max_runs, n_batches_train, n_batches_eval, n_modules):
+def asserts_on_saved_dfs(mongo_dao, workflows_file, tasks_file, n_workflows_expected, n_tasks_expected, epoch_iterations, max_runs, n_batches_train, n_batches_eval, n_modules):
     workflows_df = pd.read_json(workflows_file)
     # Assert workflows dump
     assert len(workflows_df) == n_workflows_expected
@@ -365,16 +362,14 @@ def asserts_on_saved_dfs(workflows_file, tasks_file, n_workflows_expected, n_tas
     task_ids = list(tasks_df["task_id"].unique())
     workflow_ids = list(workflows_df["workflow_id"].unique())
     print("Deleting generated data in MongoDB")
-    dao = MongoDBDAO(create_indices=False)
-    dao.delete_task_keys("task_id", task_ids)
-    dao.delete_workflow_keys("workflow_id", workflow_ids)
+    mongo_dao.delete_task_keys("task_id", task_ids)
+    mongo_dao.delete_workflow_keys("workflow_id", workflow_ids)
 
 
-def verify_number_docs_in_db(n_tasks=None, n_wfs=None, n_objects=None):
-    dao = MongoDBDAO(create_indices=False)
-    _n_tasks = dao.count_tasks()
-    _n_wfs = dao.count_workflows()
-    _n_objects = dao.count_objects()
+def verify_number_docs_in_db(mongo_dao, n_tasks=None, n_wfs=None, n_objects=None):
+    _n_tasks = mongo_dao.count_tasks()
+    _n_wfs = mongo_dao.count_workflows()
+    _n_objects = mongo_dao.count_objects()
 
     if n_tasks:
         if n_tasks != _n_tasks:
@@ -400,25 +395,29 @@ def verify_number_docs_in_db(n_tasks=None, n_wfs=None, n_objects=None):
 
 def main():
 
-    if not MONGO_ENABLED:
-        print("This test is only available if Mongo is enabled.")
-        sys.exit(0)
-
     print("TORCH SETTINGS: " + str(INSTRUMENTATION.get("torch")))
 
-    n_tasks, n_wfs, n_objects = verify_number_docs_in_db()
+    from flowcept.commons.daos.docdb_dao.mongodb_dao import MongoDBDAO
+    mongo_dao = MongoDBDAO(create_indices=False)
+
+    n_tasks, n_wfs, n_objects = verify_number_docs_in_db(mongo_dao)
 
     campaign_id, dataprep_wf_id, model_search_wf_id, epochs, max_runs, n_batches_train, n_batches_eval = run_campaign()
 
     n_workflows_expected, n_tasks_expected = run_asserts_and_exports(campaign_id, model_search_wf_id)
-    workflows_file, tasks_file = save_files(campaign_id, model_search_wf_id)
-    asserts_on_saved_dfs(workflows_file, tasks_file, n_workflows_expected, n_tasks_expected,
+    workflows_file, tasks_file = save_files(mongo_dao, campaign_id, model_search_wf_id)
+    asserts_on_saved_dfs(mongo_dao, workflows_file, tasks_file, n_workflows_expected, n_tasks_expected,
                          epochs, max_runs, n_batches_train, n_batches_eval, n_modules=4)
-    verify_number_docs_in_db(n_tasks, n_wfs, n_objects)
+    verify_number_docs_in_db(mongo_dao, n_tasks, n_wfs, n_objects)
     print("Alright! Congrats.")
 
 
 if __name__ == "__main__":
+
+    if not MONGO_ENABLED:
+        print("This test is only available if Mongo is enabled.")
+        sys.exit(0)
+
     main()
     sys.exit(0)