diff --git a/agentune_simulate/agentune/simulate/outcome_detection/rag/prompt.py b/agentune_simulate/agentune/simulate/outcome_detection/rag/prompt.py
index d2835afc..b081ed04 100644
--- a/agentune_simulate/agentune/simulate/outcome_detection/rag/prompt.py
+++ b/agentune_simulate/agentune/simulate/outcome_detection/rag/prompt.py
@@ -108,7 +108,7 @@ def format_examples(examples: list[tuple[Document, float]]) -> str:
     
     for i, (doc, _) in enumerate(examples):
         messages_data = doc.metadata.get('full_conversation', '')
-        messages = converter.structure(messages_data, list[Message])
+        messages = converter.loads(messages_data, list[Message])
         conversation_text = indexing_and_retrieval.format_conversation(messages)
 
         outcome_info = doc.metadata.get('outcome', 'No outcome information available')
diff --git a/agentune_simulate/agentune/simulate/rag/indexing_and_retrieval.py b/agentune_simulate/agentune/simulate/rag/indexing_and_retrieval.py
index ff9ebaa8..17aec66e 100644
--- a/agentune_simulate/agentune/simulate/rag/indexing_and_retrieval.py
+++ b/agentune_simulate/agentune/simulate/rag/indexing_and_retrieval.py
@@ -152,6 +152,12 @@ async def get_similar_finished_conversations(
     # Sort by similarity score (highest first)
     retrieved_docs.sort(key=lambda x: x[1], reverse=True)
 
+    # If there is an exact match between the current conversation and one of the examples, remove it
+    retrieved_docs = [
+        (doc, score) for doc, score in retrieved_docs
+        if doc.metadata.get('conversation_hash') != hash(conversation.messages)
+    ]
+
     return retrieved_docs
 
 
diff --git a/agentune_simulate/streamlit/pages/Agentune_Simulate_Runner.py b/agentune_simulate/streamlit/pages/Agentune_Simulate_Runner.py
index 8ed0920c..22f63b54 100644
--- a/agentune_simulate/streamlit/pages/Agentune_Simulate_Runner.py
+++ b/agentune_simulate/streamlit/pages/Agentune_Simulate_Runner.py
@@ -337,7 +337,7 @@ async def run_simulation(
     """Run the conversation simulation."""
     
     # Get logging callback tracer
-    callbacks = get_llm_callbacks(config['session_name'])
+    callbacks = get_llm_callbacks()
     
     # Initialize models with logging callbacks
     agent_model = ChatOpenAI(**config['agent_model_kwargs'], callbacks=callbacks)