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