feat: make the pipeline work with Program and AgentSpeak

ref: N25B-429

src/control_backend/agents/bdi/agentspeak_generator.py

@@ -42,9 +42,9 @@ class AgentSpeakGenerator:
     def generate(self, program: Program) -> str:
         self._asp = AstProgram()
 
-        self._asp.rules.append(AstRule(AstLiteral("phase", [AstString("start")])))
+        self._asp.rules.append(AstRule(self._astify(program.phases[0])))
         self._add_keyword_inference()
-        self._add_response_goal()
+        self._add_default_plans()
 
         self._process_phases(program.phases)
 
@@ -66,11 +66,16 @@ class AgentSpeakGenerator:
             )
         )
 
-    def _add_response_goal(self):
+    def _add_default_plans(self):
+        self._add_reply_with_goal_plan()
+        self._add_say_plan()
+        self._add_reply_plan()
+
+    def _add_reply_with_goal_plan(self):
         self._asp.plans.append(
             AstPlan(
                 TriggerType.ADDED_GOAL,
-                AstLiteral("generate_response_with_goal", [AstVar("Goal")]),
+                AstLiteral("reply_with_goal", [AstVar("Goal")]),
                 [AstLiteral("user_said", [AstVar("Message")])],
                 [
                     AstStatement(StatementType.ADD_BELIEF, AstLiteral("responded_this_turn")),
@@ -91,12 +96,59 @@ class AgentSpeakGenerator:
             )
         )
 
+    def _add_say_plan(self):
+        self._asp.plans.append(
+            AstPlan(
+                TriggerType.ADDED_GOAL,
+                AstLiteral("say", [AstVar("Text")]),
+                [],
+                [
+                    AstStatement(StatementType.ADD_BELIEF, AstLiteral("responded_this_turn")),
+                    AstStatement(StatementType.DO_ACTION, AstLiteral("say", [AstVar("Text")])),
+                ],
+            )
+        )
+
+    def _add_reply_plan(self):
+        self._asp.plans.append(
+            AstPlan(
+                TriggerType.ADDED_GOAL,
+                AstLiteral("reply"),
+                [AstLiteral("user_said", [AstVar("Message")])],
+                [
+                    AstStatement(StatementType.ADD_BELIEF, AstLiteral("responded_this_turn")),
+                    AstStatement(
+                        StatementType.DO_ACTION,
+                        AstLiteral(
+                            "findall",
+                            [AstVar("Norm"), AstLiteral("norm", [AstVar("Norm")]), AstVar("Norms")],
+                        ),
+                    ),
+                    AstStatement(
+                        StatementType.DO_ACTION,
+                        AstLiteral("reply", [AstVar("Message"), AstVar("Norms")]),
+                    ),
+                ],
+            )
+        )
+
     def _process_phases(self, phases: list[Phase]) -> None:
         for curr_phase, next_phase in zip([None] + phases, phases + [None], strict=True):
             if curr_phase:
                 self._process_phase(curr_phase)
             self._add_phase_transition(curr_phase, next_phase)
 
+        # End phase behavior
+        # When deleting this, the entire `reply` plan and action can be deleted
+        self._asp.plans.append(
+            AstPlan(
+                type=TriggerType.ADDED_BELIEF,
+                trigger_literal=AstLiteral("user_said", [AstVar("Message")]),
+                context=[AstLiteral("phase", [AstString("end")])],
+                body=[AstStatement(StatementType.ACHIEVE_GOAL, AstLiteral("reply"))],
+            )
+        )
+
     def _process_phase(self, phase: Phase) -> None:
         for norm in phase.norms:
             self._process_norm(norm, phase)
@@ -112,14 +164,14 @@ class AgentSpeakGenerator:
             self._process_trigger(trigger, phase)
 
     def _add_phase_transition(self, from_phase: Phase | None, to_phase: Phase | None) -> None:
-        from_phase_ast = (
-            self._astify(from_phase) if from_phase else AstLiteral("phase", [AstString("start")])
-        )
+        if from_phase is None:
+            return
+        from_phase_ast = self._astify(from_phase)
         to_phase_ast = (
             self._astify(to_phase) if to_phase else AstLiteral("phase", [AstString("end")])
         )
 
-        context = [from_phase_ast]
+        context = [from_phase_ast, ~AstLiteral("responded_this_turn")]
         if from_phase and from_phase.goals:
             context.append(self._astify(from_phase.goals[-1], achieved=True))
 
@@ -221,14 +273,10 @@ class AgentSpeakGenerator:
 
     def _step_to_statement(self, step: PlanElement) -> AstStatement:
         match step:
-            case Goal() as g:
-                return AstStatement(StatementType.ACHIEVE_GOAL, self._astify(g))
-            case SpeechAction() | GestureAction() as a:
+            case Goal() | SpeechAction() | LLMAction() as a:
+                return AstStatement(StatementType.ACHIEVE_GOAL, self._astify(a))
+            case GestureAction() as a:
                 return AstStatement(StatementType.DO_ACTION, self._astify(a))
-            case LLMAction() as la:
-                return AstStatement(
-                    StatementType.ACHIEVE_GOAL, self._astify(la)
-                )  # LLM action is a goal in ASL
 
     # TODO: separate handling of keyword and others
     def _process_trigger(self, trigger: Trigger, phase: Phase) -> None:
@@ -318,7 +366,7 @@ class AgentSpeakGenerator:
 
     @_astify.register
     def _(self, la: LLMAction) -> AstExpression:
-        return AstLiteral("generate_response_with_goal", [AstString(la.goal)])
+        return AstLiteral("reply_with_goal", [AstString(la.goal)])
 
     @staticmethod
     def _slugify_str(text: str) -> str:

src/control_backend/agents/bdi/bdi_core_agent.py

@@ -48,6 +48,7 @@ class BDICoreAgent(BaseAgent):
         # Deep copy because we don't actually want to modify the standard actions globally
         self.actions = copy.deepcopy(agentspeak.stdlib.actions)
         self._wake_bdi_loop = asyncio.Event()
+        self._bdi_loop_task = None
 
     async def setup(self) -> None:
         """
@@ -64,7 +65,7 @@ class BDICoreAgent(BaseAgent):
         await self._load_asl()
 
         # Start the BDI cycle loop
-        self.add_behavior(self._bdi_loop())
+        self._bdi_loop_task = self.add_behavior(self._bdi_loop())
         self._wake_bdi_loop.set()
         self.logger.debug("Setup complete.")
 
@@ -72,7 +73,7 @@ class BDICoreAgent(BaseAgent):
         """
         Load and parse the AgentSpeak source file.
         """
-        file_name = file_name or "src/control_backend/agents/bdi/rules.asl"
+        file_name = file_name or "src/control_backend/agents/bdi/default_behavior.asl"
 
         try:
             with open(file_name) as source:
@@ -135,7 +136,10 @@ class BDICoreAgent(BaseAgent):
 
         # New agentspeak file
         if msg.thread == "new_program":
+            if self._bdi_loop_task:
+                self._bdi_loop_task.cancel()
             await self._load_asl(msg.body)
+            self.add_behavior(self._bdi_loop())
 
         # The message was not a belief, handle special cases based on sender
         match msg.sender:
@@ -246,20 +250,18 @@ class BDICoreAgent(BaseAgent):
         the function expects (which will be located in `term.args`).
         """
 
-        @self.actions.add(".reply", 3)
+        @self.actions.add(".reply", 2)
         def _reply(agent: "BDICoreAgent", term, intention):
             """
             Let the LLM generate a response to a user's utterance with the current norms and goals.
             """
             message_text = agentspeak.grounded(term.args[0], intention.scope)
             norms = agentspeak.grounded(term.args[1], intention.scope)
-            goals = agentspeak.grounded(term.args[2], intention.scope)
 
             self.logger.debug("Norms: %s", norms)
-            self.logger.debug("Goals: %s", goals)
             self.logger.debug("User text: %s", message_text)
 
-            asyncio.create_task(self._send_to_llm(str(message_text), str(norms), str(goals)))
+            self.add_behavior(self._send_to_llm(str(message_text), str(norms), ""))
             yield
 
         @self.actions.add(".reply_with_goal", 3)
@@ -278,7 +280,7 @@ class BDICoreAgent(BaseAgent):
                 norms,
                 goal,
             )
-            # asyncio.create_task(self._send_to_llm(str(message_text), norms, str(goal)))
+            self.add_behavior(self._send_to_llm(str(message_text), str(norms), str(goal)))
             yield
 
         @self.actions.add(".say", 1)
@@ -290,13 +292,14 @@ class BDICoreAgent(BaseAgent):
 
             self.logger.debug('"say" action called with text=%s', message_text)
 
-            # speech_command = SpeechCommand(data=message_text)
-            # speech_message = InternalMessage(
-            #     to=settings.agent_settings.robot_speech_name,
-            #     sender=settings.agent_settings.bdi_core_name,
-            #     body=speech_command.model_dump_json(),
-            # )
-            # asyncio.create_task(agent.send(speech_message))
+            speech_command = SpeechCommand(data=message_text)
+            speech_message = InternalMessage(
+                to=settings.agent_settings.robot_speech_name,
+                sender=settings.agent_settings.bdi_core_name,
+                body=speech_command.model_dump_json(),
+            )
+            # TODO: add to conversation history
+            self.add_behavior(self.send(speech_message))
             yield
 
         @self.actions.add(".gesture", 2)

src/control_backend/agents/bdi/belief_collector_agent.py

@@ -101,7 +101,7 @@ class BDIBeliefCollectorAgent(BaseAgent):
             :return: A Belief object if the input is valid or None.
             """
             try:
-                return Belief(name=name, arguments=arguments)
+                return Belief(name=name, arguments=arguments, replace=name == "user_said")
             except ValidationError:
                 return None
 

src/control_backend/agents/bdi/default_behavior.asl

@@ -0,0 +1,5 @@
+norms("").
+
++user_said(Message) : norms(Norms) <-
+  -user_said(Message);
+  .reply(Message, Norms).

src/control_backend/agents/bdi/rules.asl

@@ -1,6 +0,0 @@
-norms("").
-goals("").
-
-+user_said(Message) : norms(Norms) & goals(Goals) <-
-  -user_said(Message);
-  .reply(Message, Norms, Goals).

src/control_backend/schemas/program.py

@@ -194,7 +194,7 @@ class Phase(ProgramElement):
     """
 
     name: str = ""
-    norms: list[Norm]
+    norms: list[BasicNorm | ConditionalNorm]
     goals: list[Goal]
     triggers: list[Trigger]