improve prompts and logs for the entity agent and its components.

PiperOrigin-RevId: 654688746
Change-Id: I48c3b249656e49f33cfcc047a88f2a1687533972

concordia/components/agent/v2/all_similar_memories.py

@@ -105,7 +105,7 @@ def _make_pre_act_value(self) -> str:
     result = new_prompt.open_question(
         f'{question}\nStatements:\n{mems}',
         max_tokens=2000,
-        terminators=(),
+        terminators=('\n\n',),
     )
 
     self._logging_channel({

concordia/components/agent/v2/concat_act_component.py

@@ -109,7 +109,7 @@ def get_action_attempt(
   ) -> str:
     prompt = interactive_document.InteractiveDocument(self._model)
     context = self._context_for_action(contexts)
-    prompt.statement(context)
+    prompt.statement(context + '\n')
 
     call_to_action = action_spec.call_to_action.format(
         name=self.get_entity().name,

concordia/components/agent/v2/constant.py

@@ -44,6 +44,9 @@ def __init__(
     """
     super().__init__(pre_act_key)
     self._state = state
+    self._logging_channel = logging_channel
 
   def _make_pre_act_value(self) -> str:
+    self._logging_channel(
+        {'Key': self.get_pre_act_key(), 'Value': self._state})
     return self._state

concordia/components/agent/v2/person_by_situation.py

@@ -108,7 +108,6 @@ def _make_pre_act_value(self) -> str:
     memory.add(f'[intent reflection] {result}', metadata={})
 
     self._logging_channel({
-        'Summary': question,
         'Key': self.get_pre_act_key(),
         'Value': result,
         'Chain of thought': prompt.view().text().splitlines(),

concordia/components/agent/v2/plan.py

@@ -129,7 +129,7 @@ def _make_pre_act_value(self) -> str:
       prompt.statement(
           f'Current goal: {goal_component.get_pre_act_value()}.')  # pylint: disable=undefined-variable
     prompt.statement(f'Current plan: {self._current_plan}')
-    prompt.statement(f'Current situation: {observation}')
+    prompt.statement(f'Current situation: {latest_observations}')
 
     time_now = self._clock_now().strftime('[%d %b %Y %H:%M:%S]')
     prompt.statement(f'The current time is: {time_now}\n')
@@ -155,10 +155,6 @@ def _make_pre_act_value(self) -> str:
     result = self._current_plan
 
     self._logging_channel({
-        'Summary': (
-            f'detailed plan of {agent_name} '
-            + f'for {self._horizon}'
-        ),
         'Key': self.get_pre_act_key(),
         'Value': result,
         'Chain of thought': prompt.view().text().splitlines(),

concordia/factory/agent/temporary_entity_agent__main_role.py

@@ -69,7 +69,7 @@ def build_agent(
   observation = agent_components.observation.Observation(
       clock_now=clock.now,
       timeframe=clock.get_step_size(),
-      pre_act_key='Observation',
+      pre_act_key='\nObservation',
       logging_channel=measurements.get_channel('Observation').on_next,
   )
 
@@ -83,12 +83,12 @@ def build_agent(
   )
   time_display = agent_components.report_function.ReportFunction(
       function=clock.current_time_interval_str,
-      pre_act_key='Current time',
+      pre_act_key='\nCurrent time',
       logging_channel=measurements.get_channel('TimeDisplay').on_next,
   )
   identity_characteristics = agent_components.identity.IdentityWithoutPreAct(
       model=model,
-      logging_channel=measurements.get_channel('Identity').on_next,
+      logging_channel=measurements.get_channel('IdentityWithoutPreAct').on_next,
   )
   self_perception_label = (
       f'\nQuestion: What kind of person is {agent_name}?\nAnswer')
@@ -129,7 +129,7 @@ def build_agent(
       pre_act_key=person_by_situation_label,
       logging_channel=measurements.get_channel('PersonBySituation').on_next,
   )
-  relevant_memories_label = 'Recalled memories and observations'
+  relevant_memories_label = '\nRecalled memories and observations'
   relevant_memories = agent_components.all_similar_memories.AllSimilarMemories(
       model=model,
       components={
@@ -143,11 +143,12 @@ def build_agent(
 
   plan_components = {}
   if config.goal:
-    goal_label = 'Overarching goal'
+    goal_label = '\nOverarching goal'
     overarching_goal = agent_components.constant.Constant(
         state=config.goal,
-        pre_act_key=goal_label)
-    plan_components[_get_class_name(overarching_goal)] = goal_label
+        pre_act_key=goal_label,
+        logging_channel=measurements.get_channel(goal_label).on_next)
+    plan_components[goal_label] = goal_label
   else:
     goal_label = None
     overarching_goal = None
@@ -165,7 +166,7 @@ def build_agent(
       clock_now=clock.now,
       goal_component_name=_get_class_name(person_by_situation),
       horizon=DEFAULT_PLANNING_HORIZON,
-      pre_act_key='Plan',
+      pre_act_key='\nPlan',
       logging_channel=measurements.get_channel('Plan').on_next,
   )
 
@@ -174,12 +175,12 @@ def build_agent(
       instructions,
       observation,
       observation_summary,
-      self_perception,
       relevant_memories,
+      self_perception,
       situation_perception,
       person_by_situation,
-      time_display,
       plan,
+      time_display,
 
       # Components that do not provide pre_act context.
       identity_characteristics,