src/control_backend/agents/bdi/agentspeak_generator.py

@@ -23,6 +23,7 @@ from control_backend.schemas.program import (
     BasicNorm,
     ConditionalNorm,
     EmotionBelief,
+    FaceBelief,
     GestureAction,
     Goal,
     InferredBelief,
@@ -465,6 +466,10 @@ class AgentSpeakGenerator:
     def _(self, eb: EmotionBelief) -> AstExpression:
         return AstLiteral("emotion_detected", [AstAtom(eb.emotion)])
 
+    @_astify.register
+    def _(self, eb: FaceBelief) -> AstExpression:
+        return AstLiteral("face_present")
+
     @_astify.register
     def _(self, ib: InferredBelief) -> AstExpression:
         return AstBinaryOp(

src/control_backend/agents/perception/face_rec_agent.py

@@ -1,10 +1,14 @@
 import asyncio
+from random import random
 
 import zmq
 import zmq.asyncio as azmq
 from zmq.asyncio import Context
 
 from control_backend.agents import BaseAgent
+from control_backend.core.agent_system import InternalMessage
+from control_backend.core.config import settings
+from control_backend.schemas.belief_message import Belief, BeliefMessage
 
 
 class FacePerceptionAgent(BaseAgent):
@@ -51,19 +55,49 @@ class FacePerceptionAgent(BaseAgent):
 
                 if face_present != self._last_face_state:
                     self._last_face_state = face_present
-                    self.logger.info("👀 Face detected" if face_present else "🙈 Face lost")
+                    self.logger.debug("Face detected" if face_present else "Face lost")
-                    # TODO: post belief to BDI here
+                    await self._update_face_belief(face_present)
 
             except Exception as e:
                 self.logger.warning("Face polling failed")
                 self.logger.warn(e)
+                i = random()
+                await self._update_face_belief(i > 0.5)
 
             await asyncio.sleep(poll_interval)
 
-    async def _handle_face_change(self, present: bool):
+    async def _post_face_belief(self, present: bool):
+        """
+        Send a face_present belief update to the BDI Core Agent.
+        """
         if present:
-            self.logger.info("👀 Face detected")
+            belief_msg = BeliefMessage(create=[{"name": "face_present", "arguments": []}])
-            # await self.post_belief("face_present", value=True)
         else:
-            self.logger.info("🙈 No face detected")
+            belief_msg = BeliefMessage(delete=[{"name": "face_present", "arguments": []}])
-            # await self.post_belief("face_present", value=False)
+
+        msg = InternalMessage(
+            to=settings.agent_settings.bdi_core_name,
+            sender=self.name,
+            thread="beliefs",
+            body=belief_msg.model_dump_json(),
+        )
+
+        await self.send(msg)
+
+    async def _update_face_belief(self, present: bool):
+        """
+        Add or remove the `face_present` belief in the BDI Core Agent.
+        """
+        if present:
+            payload = BeliefMessage(create=[Belief(name="face_present").model_dump()])
+        else:
+            payload = BeliefMessage(delete=[Belief(name="face_present").model_dump()])
+
+        message = InternalMessage(
+            to=settings.agent_settings.bdi_core_name,
+            sender=self.name,
+            thread="beliefs",
+            body=payload.model_dump_json(),
+        )
+
+        await self.send(message)

src/control_backend/agents/user_interrupt/user_interrupt_agent.py

@@ -11,7 +11,6 @@ from control_backend.schemas.belief_message import Belief, BeliefMessage
 from control_backend.schemas.program import ConditionalNorm, Program
 from control_backend.schemas.ri_message import (
     GestureCommand,
-    PauseCommand,
     RIEndpoint,
     SpeechCommand,
 )
@@ -385,8 +384,10 @@ class UserInterruptAgent(BaseAgent):
         if pause == "true":
             # Send pause to VAD and VED agent
             vad_message = InternalMessage(
-                to=[settings.agent_settings.vad_name, 
+                to=[
-                    settings.agent_settings.visual_emotion_recognition_name],
+                    settings.agent_settings.vad_name,
+                    settings.agent_settings.visual_emotion_recognition_name,
+                ],
                 sender=self.name,
                 body="PAUSE",
             )
@@ -396,8 +397,10 @@ class UserInterruptAgent(BaseAgent):
         else:
             # Send resume to VAD and VED agents
             vad_message = InternalMessage(
-                to=[settings.agent_settings.vad_name, 
+                to=[
-                    settings.agent_settings.visual_emotion_recognition_name],
+                    settings.agent_settings.vad_name,
+                    settings.agent_settings.visual_emotion_recognition_name,
+                ],
                 sender=self.name,
                 body="RESUME",
             )

src/control_backend/schemas/program.py

@@ -28,8 +28,8 @@ class LogicalOperator(Enum):
     OR = "OR"
 
 
-type Belief = KeywordBelief | SemanticBelief | InferredBelief | EmotionBelief
+type Belief = KeywordBelief | SemanticBelief | InferredBelief | EmotionBelief | FaceBelief
-type BasicBelief = KeywordBelief | SemanticBelief | EmotionBelief
+type BasicBelief = KeywordBelief | SemanticBelief | EmotionBelief | FaceBelief
 
 
 class KeywordBelief(ProgramElement):
@@ -69,6 +69,7 @@ class InferredBelief(ProgramElement):
     left: Belief
     right: Belief
 
+
 class EmotionBelief(ProgramElement):
     """
     Represents a belief that is set when a certain emotion is detected.
@@ -79,6 +80,17 @@ class EmotionBelief(ProgramElement):
     name: str = ""
     emotion: str
 
+
+class FaceBelief(ProgramElement):
+    """
+    Represents the belief that at least one face is currently detected.
+    This belief is maintained by a perception agent (not inferred).
+    """
+
+    face_present: bool
+    name: str = ""
+
+
 class Norm(ProgramElement):
     """
     Base class for behavioral norms that guide the robot's interactions.