fix system message location

Author: neagualexa

src/agents/base_agent/base_agent.py

@@ -64,15 +64,15 @@ def call_model(self, state: State, config: RunnableConfig) -> str:
         # Adding external student progress and question context details from data queries
         question_response_details = config["configurable"].get("question_response_details", "")
         if question_response_details:
-            system_message += f"## Known Question Materials: {question_response_details} \n\n"
+            system_message += f"\n\n ## Known Question Materials: {question_response_details} \n\n"
 
         # Adding summary and conversational style to the system message
         summary = state.get("summary", "")
         conversationalStyle = state.get("conversationalStyle", "")
         if summary:
             system_message += summary_system_prompt.format(summary=summary)
         if conversationalStyle:
-            system_message += f"## Known conversational style and preferences of the student for this conversation: {conversationalStyle}. \n\nYour answer must be in line with this conversational style."
+            system_message += f"\n\n ## Known conversational style and preferences of the student for this conversation: {conversationalStyle}. \n\nYour answer must be in line with this conversational style."
 
         messages = [SystemMessage(content=system_message)] + state['messages']
 
@@ -120,12 +120,12 @@ def summarize_conversation(self, state: State, config: RunnableConfig) -> dict:
             conversationalStyle_message = self.conversation_preference_prompt
 
         # STEP 1: Summarize the conversation
-        messages = state["messages"][:-1] + [SystemMessage(content=summary_message)] 
+        messages = [SystemMessage(content=summary_message)] + state["messages"][:-1]
         valid_messages = self.check_for_valid_messages(messages)
         summary_response = self.summarisation_llm.invoke(valid_messages)
 
         # STEP 2: Analyze the conversational style
-        messages = state["messages"][:-1] + [SystemMessage(content=conversationalStyle_message)]
+        messages = [SystemMessage(content=conversationalStyle_message)] + state["messages"][:-1]
         valid_messages = self.check_for_valid_messages(messages)
         conversationalStyle_response = self.summarisation_llm.invoke(valid_messages)
 
@@ -184,7 +184,7 @@ def invoke_base_agent(query: str, conversation_history: list, summary: str, conv
     Call an agent that has no conversation memory and expects to receive all past messages in the params and the latest human request in the query.
     If conversation history longer than X, the agent will summarize the conversation and will provide a conversational style analysis.
     """
-    print(f'in invoke_base_agent(), query = {query}, thread_id = {session_id}')
+    print(f'in invoke_base_agent(), thread_id = {session_id}')
 
     config = {"configurable": {"thread_id": session_id, "summary": summary, "conversational_style": conversationalStyle, "question_response_details": question_response_details}}
     response_events = agent.app.invoke({"messages": conversation_history, "summary": summary, "conversational_style": conversationalStyle}, config=config, stream_mode="values") #updates

src/agents/google_learnLM_agent/google_learnLM_agent.py

@@ -68,15 +68,15 @@ def call_model(self, state: State, config: RunnableConfig) -> str:
         # Adding external student progress and question context details from data queries
         question_response_details = config["configurable"].get("question_response_details", "")
         if question_response_details:
-            system_message += f"## Known Question Materials: {question_response_details} \n\n"
+            system_message += f"\n\n ## Known Question Materials: {question_response_details} \n\n"
 
         # Adding summary and conversational style to the system message
         summary = state.get("summary", "")
         conversationalStyle = state.get("conversationalStyle", "")
         if summary:
             system_message += summary_system_prompt.format(summary=summary)
         if conversationalStyle:
-            system_message += f"## Known conversational style and preferences of the student for this conversation: {conversationalStyle}. \n\nYour answer must be in line with this conversational style."
+            system_message += f"\n\n ## Known conversational style and preferences of the student for this conversation: {conversationalStyle}. \n\nYour answer must be in line with this conversational style."
 
         messages = [SystemMessage(content=system_message)] + state['messages']
 
@@ -124,12 +124,12 @@ def summarize_conversation(self, state: State, config: RunnableConfig) -> dict:
             conversationalStyle_message = self.conversation_preference_prompt
 
         # STEP 1: Summarize the conversation
-        messages = state["messages"][:-1] + [SystemMessage(content=summary_message)] 
+        messages = [SystemMessage(content=summary_message)] + state["messages"][:-1]
         valid_messages = self.check_for_valid_messages(messages)
         summary_response = self.summarisation_llm.invoke(valid_messages)
 
         # STEP 2: Analyze the conversational style
-        messages = state["messages"][:-1] + [SystemMessage(content=conversationalStyle_message)]
+        messages = [SystemMessage(content=conversationalStyle_message)] + state["messages"][:-1]
         valid_messages = self.check_for_valid_messages(messages)
         conversationalStyle_response = self.summarisation_llm.invoke(valid_messages)
 

src/agents/informational_agent/informational_agent.py

@@ -74,7 +74,7 @@ def call_model(self, state: State, config: RunnableConfig) -> str:
         if summary:
             system_message += summary_system_prompt.format(summary=summary)
         # if conversationalStyle:
-        #     system_message += f"## Known conversational style and preferences of the student for this conversation: {conversationalStyle}. \n\nYour answer must be in line with this conversational style."
+        #     system_message += f"\n\n ## Known conversational style and preferences of the student for this conversation: {conversationalStyle}. \n\nYour answer must be in line with this conversational style."
 
         messages = [SystemMessage(content=system_message)] + state['messages']
 
@@ -183,7 +183,7 @@ def pretty_response_value(self, event: dict) -> str:
 
 agent = InformationalAgent()
 def invoke_informational_agent(query: str, conversation_history: list, summary: str, conversationalStyle: str, question_response_details: str, session_id: str) -> InvokeAgentResponseType:
-    print(f'in invoke_informational_agent(), query = {query}, thread_id = {session_id}')
+    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}}
     response_events = agent.app.invoke({"messages": conversation_history, "summary": summary, "conversational_style": conversationalStyle}, config=config, stream_mode="values") #updates

src/agents/socratic_agent/socratic_agent.py

@@ -66,15 +66,15 @@ def call_model(self, state: State, config: RunnableConfig) -> str:
         # Adding external student progress and question context details from data queries
         question_response_details = config["configurable"].get("question_response_details", "")
         if question_response_details:
-            system_message += f"## Known Learning Materials: {question_response_details} \n\n"
+            system_message += f"\n\n ## Known Learning Materials: {question_response_details} \n\n"
 
         # Adding summary and conversational style to the system message
         summary = state.get("summary", "")
         conversationalStyle = state.get("conversationalStyle", "")
         if summary:
             system_message += summary_system_prompt.format(summary=summary)
         # if conversationalStyle:
-        #     system_message += f"## Known conversational style and preferences of the student for this conversation: {conversationalStyle}. \n\nYour answer must be in line with this conversational style."
+        #     system_message += f"\n\n ## Known conversational style and preferences of the student for this conversation: {conversationalStyle}. \n\nYour answer must be in line with this conversational style."
 
         messages = [SystemMessage(content=system_message)] + state['messages']
 
@@ -122,12 +122,12 @@ def summarize_conversation(self, state: State, config: RunnableConfig) -> dict:
         #     conversationalStyle_message = self.conversation_preference_prompt
 
         # STEP 1: Summarize the conversation
-        messages = state["messages"][:-1] + [SystemMessage(content=summary_message)] 
+        messages = [SystemMessage(content=summary_message)] + state["messages"][:-1]
         valid_messages = self.check_for_valid_messages(messages)
         summary_response = self.summarisation_llm.invoke(valid_messages)
 
         # STEP 2: Analyze the conversational style
-        # messages = state["messages"][:-1] + [SystemMessage(content=conversationalStyle_message)]
+        # messages = [SystemMessage(content=conversationalStyle_message)] + state["messages"][:-1]
         # valid_messages = self.check_for_valid_messages(messages)
         # conversationalStyle_response = self.summarisation_llm.invoke(valid_messages)