adjusted prompts; bug fix: logger file handling encoding; improved logging

alfred.py

@@ -44,20 +44,28 @@ class GraphBuilder:
         """
         Assistant agent that evaluates the query and decides whether to give a final answer
         or continue the conversation with the Manager.
-        
+
         Uses the existing Assistant implementation.
         """
+        if Args.LOGGER is None:
+            raise RuntimeError("LOGGER must be defined before running the assistant_node.")
+
+        Args.LOGGER.log(logging.INFO, "********** assistant_node **********")
+
         if state["current_message"] is None:
             # First time, just forward the query to the manager
             response = state["initial_query"]
         else:
-            response = await self.assistant_agent.query(state["current_message"])
-        
+            assistent_input = f"This is the initial user query:\n\n{state["initial_query"]}\n\nThe manager provided the following answer:\n\n{state["current_message"]}\n"
+            response = await self.assistant_agent.query(assistent_input)
+
         # Check if this is a final answer
         if self.final_answer_hint in response:
             # Extract the text after final answer hint
-            state["final_response"] = response.split(self.final_answer_hint, 1)[1].strip()
-        
+            final_response = response.split(self.final_answer_hint)[-1]
+            final_response = final_response.strip()
+            state["final_response"] = final_response
+
         state["current_message"] = response
         state["nr_interactions"] += 1
 
@@ -69,6 +77,11 @@ class GraphBuilder:
         
         Uses the existing Manager implementation.
         """
+        if Args.LOGGER is None:
+            raise RuntimeError("LOGGER must be defined before running the manager_node.")
+
+        Args.LOGGER.log(logging.INFO, "********** manager_node **********")
+
         if state["current_message"] is None:
             raise ValueError("manager_node called with no current_message in state")
 
@@ -85,27 +98,32 @@ class GraphBuilder:
         If there's already a final answer in the state, it uses that.
         Otherwise, it asks the assistant to formulate a final answer.
         """
-        print("========== final_answer_node ==========")
+        if Args.LOGGER is None:
+            raise RuntimeError("LOGGER must be defined before running the final_answer_node.")
+
+        Args.LOGGER.log(logging.INFO, "********** final_answer_node **********")
+
         # If we already have a final answer, use it
         final_response = state.get("final_response")
         if final_response is not None:
-            print(f"====================\nFinal response:\n{final_response}\n====================")
+            Args.LOGGER.log(logging.INFO, f"==========\nFinal response:\n{final_response}\n==========")
             return state
         
         # Otherwise, have the assistant formulate a final answer
         prompt = f"Based on the conversation so far, provide a final answer to the original query:\n\n{state['initial_query']}"
         state["current_message"] = prompt
-        response = await self.assistant_agent.query(state["current_message"])
+        response = await self.assistant_agent.query(prompt)
         
         # Format the response
         if self.final_answer_hint not in response:
-            print(f"WARNING: final_answer_hint '{self.final_answer_hint}' not in response !")
+            Args.LOGGER.log(logging.WARNING, f"Final_answer_hint '{self.final_answer_hint}' not in response !")
             response = f"{self.final_answer_hint}{response}"
         
         # Extract the text after final answer hint
-        state["final_response"] = response.split(self.final_answer_hint, 1)[1].strip()
-        final_response = state.get("final_response")
-        print(f"====================\nFinal response:\n{final_response}\n====================")
+        final_response = response.split(self.final_answer_hint)[-1]
+        final_response = final_response.strip()
+        state["final_response"] = final_response
+        Args.LOGGER.log(logging.INFO, f"==========\nFinal response:\n{final_response}\n==========")
         
         return state
 
@@ -117,15 +135,21 @@ class GraphBuilder:
             "manager": If the Assistant has decided to continue the conversation
             "final_answer": If the Assistant has decided to provide a final answer
         """
+        if Args.LOGGER is None:
+            raise RuntimeError("LOGGER must be defined before running the should_continue edge.")
+
+        Args.LOGGER.log(logging.INFO, "++++++++++ should_continue edge ++++++++++")
+
         if state["current_message"] is None:
             raise ValueError("should_continue conditional edge was reached with no current_message in state")
 
         message = state["current_message"]
         
         if state["nr_interactions"] >= MAX_INTERACTIONS or self.final_answer_hint in message:
+            Args.LOGGER.log(logging.INFO, "++++++++++ should_continue edge decision: final_answer ++++++++++")
             return "final_answer"
-        else:
-            return "manager"
+        Args.LOGGER.log(logging.INFO, "++++++++++ should_continue edge decision: manager ++++++++++")
+        return "manager"
 
     def build_agent_graph(self) -> CompiledStateGraph:
         """Build and return the agent graph."""
@@ -217,8 +241,8 @@ class Alfred:
         log_filename = f"{current_time}.txt"
         log_filepath = logs_dir / log_filename
         
-        # Create file handler
-        file_handler = logging.FileHandler(log_filepath)
+        # Create file handler with UTF-8 encoding to handle all Unicode characters
+        file_handler = logging.FileHandler(log_filepath, encoding='utf-8')
         file_handler.setLevel(logging.INFO)
         file_handler.setFormatter(formatter)
         

itf_agent.py

@@ -13,7 +13,6 @@ from llama_index.core.agent.workflow import AgentWorkflow
 
 class IAgent():
     def __init__(self, temperature, max_tokens, sys_prompt_filename, llm_itf: LLMInterface):
-        print(f"Agent initialized using {sys_prompt_filename} prompt file.")
         self.name = self._format_name(sys_prompt_filename)
         self.temperature, self.max_tokens = temperature, max_tokens
         # Load the system prompt from a file
@@ -125,7 +124,8 @@ class IAgent():
         Clears the current context of the agent, resetting any conversation history.
         This is useful when starting a new conversation or when the context needs to be refreshed.
         """
-        self.ctx = Context(self.agent)
+        if self.ctx is not None:
+            self.ctx = Context(self.agent)
 
         if not self.slaves:
             return

management.py

@@ -97,8 +97,7 @@ class Manager(IAgent):
         observation = ""
         for task in tasks:
             solution = await self.solver.query(task)
-            response = f"For task:\n\n{task}\n\nThe Solver provided the solution:\n\n{solution}\n\n"
-            observation += response
+            observation += solution
 
         report = await self.summarizer.query(observation.strip())
         return report

system_prompts/01_assistant.txt

@@ -9,11 +9,13 @@ VERY IMPORTANT - QUERY RESOLUTION PROTOCOL:
 - Your final answer will be evaluated by exact comparison with the correct answer, therefore it must be precise, accurate, and contain no redundant words.
 - Include "Final answer:" string in your response only when you are confident you have the correct solution, or when you are prompted to wrap up an answer.
 
+
+When interacting with the Manager, be ruthlessly critical of any detected nonsense, hallucinations, or factual inaccuracies. Immediately call out such errors with direct, harsh corrections to put the conversation back on the right path. Do not tolerate imprecision or made-up information, as this would compromise the accuracy of your final answer.
+
+
 Response length:
     - **Keep It Brief, But Clear**: Provide direct and efficient responses with minimal explanation. 
     Offer slightly more detail than a single word but avoid unnecessary elaboration. 
     Only include additional context when strictly relevant.
     - For your final answer be extreme precision is paramount ! It will be evaluated by exact comparison with the correct answer, 
     therefore it must be precise, accurate, and contain no redundant words, otherwise it will be considered wrong, even if the information provided is correct.
-
-/no_think

system_prompts/02_manager.txt

@@ -61,6 +61,17 @@ NOTE 2: It is important to also try to break up the tasks yourself first.
     You should definitely request help in this matter but there must be a ballance between your effort on braking up tasks and the help you receive.
 
 
+When interacting with Solver / Team, be ruthlessly critical of any detected nonsense, hallucinations, or factual inaccuracies. Immediately call out such errors with direct, harsh corrections to put the conversation back on the right path. Do not tolerate imprecision or made-up information, as this would compromise the accuracy of your final answer.
+
+
+Response length:
+    - **Keep It Brief, But Clear**: Provide direct and efficient responses with minimal explanation. 
+    Offer slightly more detail than a single word but avoid unnecessary elaboration. 
+    Only include additional context when strictly relevant.
+    - For your final answer be extreme precision is paramount ! It will be evaluated by exact comparison with the correct answer, 
+    therefore it must be precise, accurate, and contain no redundant words, otherwise it will be considered wrong, even if the information provided is correct.
+
+
 Additional recommendations:
 - When managing complexity, employ systematic decomposition into manageable components with clear interdependencies.
 - Consistently focus on critical path activities that directly impact key deliverables and strategic objectives.

system_prompts/03_solver.txt

@@ -50,3 +50,11 @@ EDGE CASE MANAGEMENT:
 - VERIFY: Confirm solution robustness under varied conditions and stress factors
 
 Operate with intellectual honesty – acknowledge limitations, uncertainties, and tradeoffs explicitly. Structure all solutions for maximum clarity and actionability, with implementation pathways clearly delineated.
+When interacting with specialized agents, be ruthlessly critical of any detected nonsense, hallucinations, or factual inaccuracies. Immediately call out such errors with direct, harsh corrections to put the conversation back on the right path. Do not tolerate imprecision or made-up information, as this would compromise the accuracy of your final answer.
+
+Response length:
+    - **Keep It Brief, But Clear**: Provide direct and efficient responses with minimal explanation. 
+    Offer slightly more detail than a single word but avoid unnecessary elaboration. 
+    Only include additional context when strictly relevant.
+    - For your final answer be extreme precision is paramount ! It will be evaluated by exact comparison with the correct answer, 
+    therefore it must be precise, accurate, and contain no redundant words, otherwise it will be considered wrong, even if the information provided is correct.

system_prompts/04_summarizer.txt

@@ -28,4 +28,11 @@ PRESENTATION:
 - Utilize formatting (bullet points, headings) to enhance readability
 - Focus on substance over style
 
+Response length:
+    - **Keep It Brief, But Clear**: Provide direct and efficient responses with minimal explanation. 
+    Offer slightly more detail than a single word but avoid unnecessary elaboration. 
+    Only include additional context when strictly relevant.
+    - For your final answer be extreme precision is paramount ! It will be evaluated by exact comparison with the correct answer, 
+    therefore it must be precise, accurate, and contain no redundant words, otherwise it will be considered wrong, even if the information provided is correct.
+
 Your goal is to deliver maximum information value in minimum space while ensuring the summary faithfully represents the original content.

system_prompts/05_researcher.txt

@@ -31,4 +31,11 @@ When reformulating searches:
 - Add qualifiers like "latest," "recent," "explained," or "overview" as appropriate
 - Consider searching for specific time periods if date-sensitive information is needed
 
+Response length:
+    - **Keep It Brief, But Clear**: Provide direct and efficient responses with minimal explanation. 
+    Offer slightly more detail than a single word but avoid unnecessary elaboration. 
+    Only include additional context when strictly relevant.
+    - For your final answer be extreme precision is paramount ! It will be evaluated by exact comparison with the correct answer, 
+    therefore it must be precise, accurate, and contain no redundant words, otherwise it will be considered wrong, even if the information provided is correct.
+
 Be persistent in your search efforts. Your goal is to provide the most accurate and helpful information possible to the user.