Fixes: More detailed prompt & summary resolved (#22)

* fix: testing summary

* fix debug statement

* fix: summary prompting

* remove prints

* feat: more info on question and set

* feat: more question info prompt

Author: neagualexa

src/agents/base_agent/base_agent.py

@@ -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 = [SystemMessage(content=summary_message)] + state["messages"][:-1]
+        messages = state["messages"][:-1] + [HumanMessage(content=summary_message)]
         valid_messages = self.check_for_valid_messages(messages)
         summary_response = self.summarisation_llm.invoke(valid_messages)
 
         # STEP 2: Analyze the conversational style
-        messages = [SystemMessage(content=conversationalStyle_message)] + state["messages"][:-1]
+        messages = state["messages"][:-1] + [HumanMessage(content=conversationalStyle_message)]
         valid_messages = self.check_for_valid_messages(messages)
         conversationalStyle_response = self.summarisation_llm.invoke(valid_messages)
 

src/agents/base_agent/base_prompts.py

@@ -68,11 +68,13 @@
 Structured: Organize the summary into sections such as 'Topics Discussed' and 'Top 3 Key Detailed Ideas'.
 Neutral and Accurate: Avoid adding interpretations or opinions; focus only on the content shared.
 When summarizing: If the conversation is technical, highlight significant concepts, solutions, and terminology. If context involves problem-solving, detail the problem and the steps or solutions provided. If the user asks for creative input, briefly describe the ideas presented.
-Last messages: Include the most recent 4 messages to provide context for the summary.
+Last messages: Include the most recent 5 messages to provide context for the summary.
 
 Provide the summary in a bulleted format for clarity. Avoid redundant details while preserving the core intent of the discussion."""
 
-summary_prompt = f"""Summarize the conversation between a student and a tutor. Your summary should highlight the major topics discussed during the session, followed by a detailed recollection of the last five significant points or ideas. Ensure the summary flows smoothly to maintain the continuity of the discussion."""
+summary_prompt = f"""Summarize the conversation between a student and a tutor. Your summary should highlight the major topics discussed during the session, followed by a detailed recollection of the last five significant points or ideas. Ensure the summary flows smoothly to maintain the continuity of the discussion.
+
+{summary_guidelines}"""
 
 update_summary_prompt = f"""Update the summary by taking into account the new messages above.
 

src/agents/google_learnLM_agent/google_learnLM_agent.py

@@ -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 = [SystemMessage(content=summary_message)] + state["messages"][:-1]
+        messages = state["messages"][:-1] + [HumanMessage(content=summary_message)]
         valid_messages = self.check_for_valid_messages(messages)
         summary_response = self.summarisation_llm.invoke(valid_messages)
 
         # STEP 2: Analyze the conversational style
-        messages = [SystemMessage(content=conversationalStyle_message)] + state["messages"][:-1]
+        messages = state["messages"][:-1] + [HumanMessage(content=conversationalStyle_message)]
         valid_messages = self.check_for_valid_messages(messages)
         conversationalStyle_response = self.summarisation_llm.invoke(valid_messages)
 

src/agents/google_learnLM_agent/google_learnLM_prompts.py

@@ -68,11 +68,13 @@
 Structured: Organize the summary into sections such as 'Topics Discussed' and 'Top 3 Key Detailed Ideas'.
 Neutral and Accurate: Avoid adding interpretations or opinions; focus only on the content shared.
 When summarizing: If the conversation is technical, highlight significant concepts, solutions, and terminology. If context involves problem-solving, detail the problem and the steps or solutions provided. If the user asks for creative input, briefly describe the ideas presented.
-Last messages: Include the most recent 4 messages to provide context for the summary.
+Last messages: Include the most recent 5 messages to provide context for the summary.
 
 Provide the summary in a bulleted format for clarity. Avoid redundant details while preserving the core intent of the discussion."""
 
-summary_prompt = f"""Summarize the conversation between a student and a tutor. Your summary should highlight the major topics discussed during the session, followed by a detailed recollection of the last five significant points or ideas. Ensure the summary flows smoothly to maintain the continuity of the discussion."""
+summary_prompt = f"""Summarize the conversation between a student and a tutor. Your summary should highlight the major topics discussed during the session, followed by a detailed recollection of the last five significant points or ideas. Ensure the summary flows smoothly to maintain the continuity of the discussion.
+
+{summary_guidelines}"""
 
 update_summary_prompt = f"""Update the summary by taking into account the new messages above.
 

src/agents/informational_agent/informational_agent.py

@@ -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 = [SystemMessage(content=summary_message)] + state["messages"][:-1]
+        messages = state["messages"][:-1] + [HumanMessage(content=summary_message)]
         valid_messages = self.check_for_valid_messages(messages)
         summary_response = self.summarisation_llm.invoke(valid_messages)
 
         # STEP 2: Analyze the conversational style
-        messages = [SystemMessage(content=conversationalStyle_message)] + state["messages"][:-1]
+        messages = state["messages"][:-1] + [HumanMessage(content=conversationalStyle_message)]
         valid_messages = self.check_for_valid_messages(messages)
         conversationalStyle_response = self.summarisation_llm.invoke(valid_messages)
 

src/agents/informational_agent/informational_prompts.py

@@ -133,11 +133,13 @@
 Structured: Organize the summary into sections such as 'Topics Discussed' and 'Top 3 Key Detailed Ideas'.
 Neutral and Accurate: Avoid adding interpretations or opinions; focus only on the content shared.
 When summarizing: If the conversation is technical, highlight significant concepts, solutions, and terminology. If context involves problem-solving, detail the problem and the steps or solutions provided. If the user asks for creative input, briefly describe the ideas presented.
-Last messages: Include the most recent 4 messages to provide context for the summary.
+Last messages: Include the most recent 5 messages to provide context for the summary.
 
 Provide the summary in a bulleted format for clarity. Avoid redundant details while preserving the core intent of the discussion."""
 
-summary_prompt = f"""Summarize the conversation between a student and a tutor. Your summary should highlight the major topics discussed during the session, followed by a detailed recollection of the last five significant points or ideas. Ensure the summary flows smoothly to maintain the continuity of the discussion."""
+summary_prompt = f"""Summarize the conversation between a student and a tutor. Your summary should highlight the major topics discussed during the session, followed by a detailed recollection of the last five significant points or ideas. Ensure the summary flows smoothly to maintain the continuity of the discussion.
+
+{summary_guidelines}"""
 
 update_summary_prompt = f"""Update the summary by taking into account the new messages above.
 

src/agents/socratic_agent/socratic_agent.py

@@ -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 = [SystemMessage(content=summary_message)] + state["messages"][:-1]
+        messages = state["messages"][:-1] + [HumanMessage(content=summary_message)]
         valid_messages = self.check_for_valid_messages(messages)
         summary_response = self.summarisation_llm.invoke(valid_messages)
 
         # STEP 2: Analyze the conversational style
-        # messages = [SystemMessage(content=conversationalStyle_message)] + state["messages"][:-1]
+        # messages = state["messages"][:-1] + [HumanMessage(content=conversationalStyle_message)]
         # valid_messages = self.check_for_valid_messages(messages)
         # conversationalStyle_response = self.summarisation_llm.invoke(valid_messages)
 

src/agents/socratic_agent/socratic_prompts.py

@@ -92,11 +92,13 @@
 Structured: Organize the summary into sections such as 'Topics Discussed' and 'Top 3 Key Detailed Ideas'.
 Neutral and Accurate: Avoid adding interpretations or opinions; focus only on the content shared.
 When summarizing: If the conversation is technical, highlight significant concepts, solutions, and terminology. If context involves problem-solving, detail the problem and the steps or solutions provided. If the user asks for creative input, briefly describe the ideas presented.
-Last messages: Include the most recent 4 messages to provide context for the summary.
+Last messages: Include the most recent 5 messages to provide context for the summary.
 
 Provide the summary in a bulleted format for clarity. Avoid redundant details while preserving the core intent of the discussion."""
 
-summary_prompt = f"""Summarize the conversation between a student and a tutor. Your summary should highlight the major topics discussed during the session, followed by a detailed recollection of the last five significant points or ideas. Ensure the summary flows smoothly to maintain the continuity of the discussion."""
+summary_prompt = f"""Summarize the conversation between a student and a tutor. Your summary should highlight the major topics discussed during the session, followed by a detailed recollection of the last five significant points or ideas. Ensure the summary flows smoothly to maintain the continuity of the discussion.
+
+{summary_guidelines}"""
 
 update_summary_prompt = f"""Update the summary by taking into account the new messages above.
 

src/agents/utils/parse_json_to_prompt.py

@@ -83,13 +83,21 @@ def __init__(
 class QuestionDetails:
     def __init__(
         self,
+        setNumber: Optional[int] = None,
+        setName: Optional[str] = None,
+        setDescription: Optional[str] = None,
+        questionNumber: Optional[int] = None,
         questionTitle: Optional[str] = None,
         questionGuidance: Optional[str] = None,
         questionContent: Optional[str] = None,
         durationLowerBound: Optional[int] = None,
         durationUpperBound: Optional[int] = None,
         parts: Optional[List[PartDetails]] = [],
     ):
+        self.setNumber = setNumber
+        self.setName = setName
+        self.setDescription = setDescription
+        self.questionNumber = questionNumber
         self.questionTitle = questionTitle
         self.questionGuidance = questionGuidance
         self.questionContent = questionContent
@@ -186,8 +194,8 @@ def format_part_details(part: PartDetails, currentPart: CurrentPart, summary: Li
 
     questionDetails = f"""This is the question I am currently working on. I am currently working on Part ({convert_index_to_lowercase_letter(questionAccessInformation.currentPart.position)}). Below, you'll find its details, including the parts of the question, my responses for each response area, and the feedback I received. This information highlights my efforts and progress so far. Use this this information to inform your understanding about the question materials provided to me and my work on them.
     Maths equations are in KaTex format, preserve them the same. Use British English spellings.
-
-# Question: {questionInformation.questionTitle};
+{f'# Question Set {questionInformation.setNumber + 1}: {questionInformation.setName};' if questionInformation.setName and questionInformation.setNumber else ''}
+# Question{f' {questionInformation.setNumber + 1}.{questionInformation.questionNumber + 1}' if questionInformation.setNumber and questionInformation.questionNumber else ''}: {questionInformation.questionTitle};
     Guidance to Solve the Question: {questionInformation.questionGuidance or 'None'};
     Description of Question: {questionInformation.questionContent};
     Expected Time to Complete the Question: {f'{questionInformation.durationLowerBound} - {questionInformation.durationUpperBound} min;' if questionInformation.durationLowerBound and questionInformation.durationUpperBound else 'No specified duration.'}