docs: update existing docstrings and add new docs
ref: N25B-453
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@@ -25,11 +25,12 @@ class BDIProgramManager(BaseAgent):
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BDI Program Manager Agent.
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This agent is responsible for receiving high-level programs (sequences of instructions/goals)
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from the external HTTP API (via ZMQ) and translating them into core beliefs (norms and goals)
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for the BDI Core Agent. In the future, it will be responsible for determining when goals are
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met, and passing on new norms and goals accordingly.
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from the external HTTP API (via ZMQ), transforming it into an AgentSpeak program, sharing the
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program and its components to other agents, and keeping agents informed of the current state.
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:ivar sub_socket: The ZMQ SUB socket used to receive program updates.
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:ivar _program: The current Program.
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:ivar _phase: The current Phase.
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"""
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_program: Program
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@@ -40,6 +41,12 @@ class BDIProgramManager(BaseAgent):
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self.sub_socket = None
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def _initialize_internal_state(self, program: Program):
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"""
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Initialize the state of the program manager given a new Program. Reset the tracking of the
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current phase to the first phase, make a mapping of goal IDs to goals, used during the life
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of the program.
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:param program: The new program.
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"""
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self._program = program
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self._phase = program.phases[0] # start in first phase
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self._goal_mapping: dict[str, Goal] = {}
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@@ -48,6 +55,11 @@ class BDIProgramManager(BaseAgent):
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self._populate_goal_mapping_with_goal(goal)
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def _populate_goal_mapping_with_goal(self, goal: Goal):
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"""
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Recurse through the given goal and its subgoals and add all goals found to the
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``self._goal_mapping``.
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:param goal: The goal to add to the ``self._goal_mapping``, including subgoals.
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"""
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self._goal_mapping[str(goal.id)] = goal
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for step in goal.plan.steps:
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if isinstance(step, Goal):
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@@ -88,6 +100,13 @@ class BDIProgramManager(BaseAgent):
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await self._send_achieved_goal_to_semantic_belief_extractor(goal_id)
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async def _transition_phase(self, old: str, new: str):
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"""
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When receiving a signal from the BDI core that the phase has changed, apply this change to
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the current state and inform other agents about the change.
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:param old: The ID of the old phase.
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:param new: The ID of the new phase.
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"""
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if old != str(self._phase.id):
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self.logger.warning(
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f"Phase transition desync detected! ASL requested move from '{old}', "
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@@ -126,6 +145,7 @@ class BDIProgramManager(BaseAgent):
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self.add_behavior(self.send(msg))
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def _extract_current_beliefs(self) -> list[Belief]:
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"""Extract beliefs from the current phase."""
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beliefs: list[Belief] = []
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for norm in self._phase.norms:
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@@ -139,6 +159,7 @@ class BDIProgramManager(BaseAgent):
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@staticmethod
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def _extract_beliefs_from_belief(belief: Belief) -> list[Belief]:
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"""Recursively extract beliefs from the given belief."""
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if isinstance(belief, InferredBelief):
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return BDIProgramManager._extract_beliefs_from_belief(
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belief.left
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@@ -146,9 +167,7 @@ class BDIProgramManager(BaseAgent):
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return [belief]
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async def _send_beliefs_to_semantic_belief_extractor(self):
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"""
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Extract beliefs from the program and send them to the Semantic Belief Extractor Agent.
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"""
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"""Extract beliefs from the program and send them to the Semantic Belief Extractor Agent."""
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beliefs = BeliefList(beliefs=self._extract_current_beliefs())
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message = InternalMessage(
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@@ -134,6 +134,10 @@ class TextBeliefExtractorAgent(BaseAgent):
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self.logger.warning("Received unexpected message from %s", msg.sender)
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def _reset_phase(self):
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"""
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Delete all state about the current phase, such as what beliefs exist and which ones are
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true.
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"""
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self.conversation = ChatHistory(messages=[])
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self.belief_inferrer.available_beliefs.clear()
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self._current_beliefs = BeliefState()
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@@ -141,6 +145,11 @@ class TextBeliefExtractorAgent(BaseAgent):
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self._current_goal_completions = {}
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def _handle_beliefs_message(self, msg: InternalMessage):
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"""
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Handle the message from the Program Manager agent containing the beliefs that exist for this
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phase.
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:param msg: A list of beliefs.
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"""
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try:
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belief_list = BeliefList.model_validate_json(msg.body)
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except ValidationError:
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@@ -158,6 +167,11 @@ class TextBeliefExtractorAgent(BaseAgent):
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)
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def _handle_goals_message(self, msg: InternalMessage):
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"""
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Handle the message from the Program Manager agent containing the goals that exist for this
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phase.
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:param msg: A list of goals.
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"""
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try:
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goals_list = GoalList.model_validate_json(msg.body)
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except ValidationError:
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@@ -177,6 +191,11 @@ class TextBeliefExtractorAgent(BaseAgent):
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)
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def _handle_goal_achieved_message(self, msg: InternalMessage):
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"""
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Handle message that gets sent when goals are marked achieved from a user interrupt. This
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goal should then not be changed by this agent anymore.
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:param msg: List of goals that are marked achieved.
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"""
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# NOTE: When goals can be marked unachieved, remember to re-add them to the goal_inferrer
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try:
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goals_list = GoalList.model_validate_json(msg.body)
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@@ -210,6 +229,10 @@ class TextBeliefExtractorAgent(BaseAgent):
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await self.send(belief_msg)
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async def _infer_new_beliefs(self):
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"""
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Determine which beliefs hold and do not hold for the current conversation state. When
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beliefs change, a message is sent to the BDI core.
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"""
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conversation_beliefs = await self.belief_inferrer.infer_from_conversation(self.conversation)
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new_beliefs = conversation_beliefs - self._current_beliefs
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@@ -233,6 +256,10 @@ class TextBeliefExtractorAgent(BaseAgent):
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await self.send(message)
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async def _infer_goal_completions(self):
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"""
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Determine which goals have been achieved given the current conversation state. When
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a goal's achieved state changes, a message is sent to the BDI core.
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"""
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goal_completions = await self.goal_inferrer.infer_from_conversation(self.conversation)
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new_achieved = [
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@@ -374,19 +401,22 @@ class SemanticBeliefInferrer:
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for beliefs in self._split_into_chunks(self.available_beliefs, n_parallel)
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]
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)
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retval = BeliefState()
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new_beliefs = BeliefState()
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# Collect beliefs from all parallel calls
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for beliefs in all_beliefs:
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if beliefs is None:
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continue
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# For each, convert them to InternalBeliefs
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for belief_name, belief_holds in beliefs.items():
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# Skip beliefs that were marked not possible to determine
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if belief_holds is None:
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continue
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belief = InternalBelief(name=belief_name, arguments=None)
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if belief_holds:
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retval.true.add(belief)
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new_beliefs.true.add(belief)
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else:
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retval.false.add(belief)
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return retval
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new_beliefs.false.add(belief)
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return new_beliefs
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@staticmethod
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def _split_into_chunks[T](items: list[T], n: int) -> list[list[T]]:
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