Logging prints

index.py

@@ -9,7 +9,16 @@ def handler(event, context):
     Lambda handler function
     """
     # Log the input event for debugging purposes
-    print("Received event:", json.dumps(event, indent=2))
+    # print("Received event:", " ".join(json.dumps(event, indent=2).splitlines()))
+
+    if "body" in event:
+        try:
+            event = json.loads(event["body"])
+        except json.JSONDecodeError:
+            return {
+                "statusCode": 400,
+                "body": "Invalid JSON format in the body. Please check the input."
+            }
 
     if "message" not in event:
         return {
@@ -40,6 +49,6 @@ def handler(event, context):
     }
 
     # Log the response for debugging purposes
-    print("Returning response:", json.dumps(response, indent=2))
+    print("Returning response:", " ".join(json.dumps(response, indent=2).splitlines()))
 
     return response

src/agents/informational_agent/informational_agent.py

@@ -79,7 +79,9 @@ def call_model(self, state: State, config: RunnableConfig) -> str:
         messages = [SystemMessage(content=system_message)] + state['messages']
 
         valid_messages = self.check_for_valid_messages(messages)
+        print("Informational agent valid messages, ready for LLM call...")
         response = self.llm.invoke(valid_messages)
+        print("Informational agent response successfully received.")
 
         # Save summary for fetching outside the class
         self.summary = summary
@@ -131,6 +133,7 @@ def summarize_conversation(self, state: State, config: RunnableConfig) -> dict:
         valid_messages = self.check_for_valid_messages(messages)
         conversationalStyle_response = self.summarisation_llm.invoke(valid_messages)
 
+        print("Informational agent summary and conversational style responses successfully received.")
         # Delete messages that are no longer wanted, except the last ones
         delete_messages: list[AllMessageTypes] = [RemoveMessage(id=m.id) for m in state["messages"][:-3]]
 
@@ -153,6 +156,7 @@ def should_summarize(self, state: State) -> str:
 
         # always pairs of (sent, response) + 1 latest message
         if nr_messages > self.max_messages_to_summarize:
+            print("Informational agent: summarizing conversation needed...")
             return "summarize_conversation"
         return "call_llm"    
 
@@ -185,7 +189,9 @@ def invoke_informational_agent(query: str, conversation_history: list, summary:
     print(f'in invoke_informational_agent(), thread_id = {session_id}')
 
     config = {"configurable": {"thread_id": session_id, "summary": summary, "conversational_style": conversationalStyle, "question_response_details": question_response_details}}
+    print("Informational agent invoking...")
     response_events = agent.app.invoke({"messages": conversation_history, "summary": summary, "conversational_style": conversationalStyle}, config=config, stream_mode="values") #updates
+    print("Informational agent response received.")
     pretty_printed_response = agent.pretty_response_value(response_events) # get last event/ai answer in the response
 
     # Gather Metadata from the agent

src/module.py

@@ -63,9 +63,9 @@ def chat_module(message: Any, params: Params) -> Result:
                 question_information,
                 question_access_information
             )
-            print("INFO:: ", question_response_details_prompt)
+            print("INFO:: ", " ".join(question_response_details_prompt.splitlines()))
         except Exception as e:
-            print("ERROR:: ", e)
+            print("ERROR on parsing the JSON event to prompt:: ", e)
             raise Exception("Internal Error: The question response details could not be parsed.")
     if "agent_type" in params:
         agent_type = params["agent_type"]