feat: fully implemented visual emotion recognition agent in pipeline

ref: N25B-393

src/control_backend/agents/bdi/bdi_core_agent.py

@@ -158,6 +158,9 @@ class BDICoreAgent(BaseAgent):
         for belief in beliefs:
             if belief.replace:
                 self._remove_all_with_name(belief.name)
+            elif belief.remove:
+                self._remove_belief(belief.name, belief.arguments)
+                continue
             self._add_belief(belief.name, belief.arguments)
 
     def _add_belief(self, name: str, args: Iterable[str] = []):

src/control_backend/agents/communication/ri_communication_agent.py

@@ -7,6 +7,9 @@ from zmq.asyncio import Context
 
 from control_backend.agents import BaseAgent
 from control_backend.agents.actuation.robot_gesture_agent import RobotGestureAgent
+from control_backend.agents.perception.visual_emotion_detection_agent.visual_emotion_recognition_agent import (
+    VisualEmotionRecognitionAgent,
+)
 from control_backend.core.config import settings
 
 from ..actuation.robot_speech_agent import RobotSpeechAgent
@@ -201,6 +204,13 @@ class RICommunicationAgent(BaseAgent):
                 case "audio":
                     vad_agent = VADAgent(audio_in_address=addr, audio_in_bind=bind)
                     await vad_agent.start()
+                case "video":
+                    visual_emotion_agent = VisualEmotionRecognitionAgent(
+                        settings.agent_settings.visual_emotion_recognition_name,
+                        socket_address=addr,
+                        bind=bind,
+                    )
+                    await visual_emotion_agent.start()
                 case _:
                     self.logger.warning("Unhandled negotiation id: %s", id)
 

src/control_backend/agents/perception/visual_emotion_detection_agent/visual_emotion_recognition_agent.py

@@ -1,23 +1,28 @@
-import asyncio
+import json
+import time
+from collections import Counter, defaultdict
+
+import cv2
+import numpy as np
+from pydantic_core import ValidationError
 import zmq
 import zmq.asyncio as azmq
-import numpy as np
-import cv2
-from collections import defaultdict, Counter
-import time
 
 from control_backend.agents import BaseAgent
-from control_backend.agents.perception.visual_emotion_detection_agent.visual_emotion_recognizer import DeepFaceEmotionRecognizer
+from control_backend.agents.perception.visual_emotion_detection_agent.visual_emotion_recognizer import (
+    DeepFaceEmotionRecognizer,
+)
 from control_backend.core.agent_system import InternalMessage
 from control_backend.core.config import settings
+from control_backend.schemas.belief_message import Belief
 
 # START FROM RI COMMUNICATION AGENT?
 
 class VisualEmotionRecognitionAgent(BaseAgent):
-    def __init__(self, socket_address: str, socket_bind: bool = False, timeout_ms: int = 1000):
-        super().__init__(settings.agent_settings.visual_emotion_recognition_name)
+    def __init__(self, name, socket_address: str, bind: bool = False, timeout_ms: int = 1000):
+        super().__init__(name)
         self.socket_address = socket_address
-        self.socket_bind = socket_bind
+        self.socket_bind = bind
         self.timeout_ms = timeout_ms
 
     async def setup(self):
@@ -41,8 +46,6 @@ class VisualEmotionRecognitionAgent(BaseAgent):
     async def emotion_update_loop(self):
         """
         Retrieve a video frame from the input socket.
-
-        :return: The received video frame, or None if timeout occurs.
         """
         window_duration = 1  # seconds
         next_window_time = time.time() + window_duration
@@ -70,7 +73,7 @@ class VisualEmotionRecognitionAgent(BaseAgent):
                 if frame_image is None:
                     # Could not decode image, skip this frame
                     continue
-
+                
                 # Get the dominant emotion from each face
                 current_emotions = self.emotion_recognizer.sorted_dominant_emotions(frame_image)
                 # Update emotion counts for each detected face
@@ -90,7 +93,6 @@ class VisualEmotionRecognitionAgent(BaseAgent):
                             window_dominant_emotions.add(dominant_emotion)
                     
                     await self.update_emotions(prev_dominant_emotions, window_dominant_emotions)
-
                     prev_dominant_emotions = window_dominant_emotions
                     face_stats.clear()
                     next_window_time = time.time() + window_duration
@@ -98,14 +100,40 @@ class VisualEmotionRecognitionAgent(BaseAgent):
             except zmq.Again:
                 self.logger.warning("No video frame received within timeout.")
 
-    async def update_emotions(self, prev_emotions, emotions):
+    async def update_emotions(self, prev_emotions: set[str], emotions: set[str]):
+        """
+        Compare emotions from previous window and current emotions, 
+        send updates to BDI Core Agent.
+        """
         # Remove emotions that are no longer present
         emotions_to_remove = prev_emotions - emotions
+        new_emotions = emotions - prev_emotions
+
+        if not new_emotions and not emotions_to_remove:
+            return  
+        
+        emotion_beliefs = []
+        # Remove emotions that have disappeared
         for emotion in emotions_to_remove:
             self.logger.info(f"Emotion '{emotion}' has disappeared.")
-
+            try:
+                emotion_beliefs.append(Belief(name="emotion", arguments=[emotion], remove=True))
+            except ValidationError:
+                self.logger.warning("Invalid belief for emotion removal: %s", emotion)
+        
         # Add new emotions that have appeared
-        new_emotions = emotions - prev_emotions
         for emotion in new_emotions:
             self.logger.info(f"New emotion detected: '{emotion}'")
-                
+            try:
+                emotion_beliefs.append(Belief(name="emotion", arguments=[emotion]))
+            except ValidationError:
+                self.logger.warning("Invalid belief for new emotion: %s", emotion)
+        
+        message = InternalMessage(
+            to=settings.agent_settings.bdi_core_name,
+            sender=self.name,
+            body=json.dumps(emotion_beliefs),
+            thread="beliefs",
+        )
+        self.logger.debug("Sending emotion beliefs update: %s", emotion_beliefs)
+        await self.send(message)

src/control_backend/agents/perception/visual_emotion_detection_agent/visual_emotion_recognizer.py

@@ -1,7 +1,8 @@
-import abc 
-from deepface import DeepFace
+import abc
+
 import numpy as np
-from collections import Counter
+from deepface import DeepFace
+
 
 class VisualEmotionRecognizer(abc.ABC):
     @abc.abstractmethod
@@ -42,7 +43,6 @@ class DeepFaceEmotionRecognizer(VisualEmotionRecognizer):
 
         analysis = [face for face in analysis if face['face_confidence'] >= 0.90]
         
-        # Return list of (dominant_emotion, face_confidence) tuples
         dominant_emotions = [face['dominant_emotion'] for face in analysis]
         return dominant_emotions
         

src/control_backend/main.py

@@ -40,7 +40,9 @@ from control_backend.agents.communication import RICommunicationAgent
 from control_backend.agents.llm import LLMAgent
 
 # User Interrupt Agent
-from control_backend.agents.perception.visual_emotion_detection_agent.visual_emotion_recognition_agent import VisualEmotionRecognitionAgent
+from control_backend.agents.perception.visual_emotion_detection_agent.visual_emotion_recognition_agent import (
+    VisualEmotionRecognitionAgent,
+)
 from control_backend.agents.user_interrupt.user_interrupt_agent import UserInterruptAgent
 
 # Other backend imports
@@ -148,13 +150,6 @@ async def lifespan(app: FastAPI):
                 "name": settings.agent_settings.user_interrupt_name,
             },
         ),
-        # TODO: Spawn agent from RI Communication Agent
-        "VisualEmotionRecognitionAgent": ( 
-            VisualEmotionRecognitionAgent,
-            {
-                "socket_address": "tcp://localhost:5556", # TODO: move to settings
-            },
-        ),
     }
 
     agents = []

src/control_backend/schemas/belief_message.py

@@ -8,11 +8,13 @@ class Belief(BaseModel):
     :ivar name: The functor or name of the belief (e.g., 'user_said').
     :ivar arguments: A list of string arguments for the belief.
     :ivar replace: If True, existing beliefs with this name should be replaced by this one.
+    :ivar remove: If True, this belief should be removed from the belief base.
     """
 
     name: str
     arguments: list[str]
     replace: bool = False
+    remove: bool = False
 
 
 class BeliefMessage(BaseModel):