From 45b8597f158f000e041f820ed15740d6e75daa56 Mon Sep 17 00:00:00 2001
From: "Luijkx,S.O.H. (Storm)" <s.o.h.luijkx@students.uu.nl>
Date: Fri, 30 Jan 2026 16:53:15 +0000
Subject: [PATCH] feat: visual emotion recognition agent

---
 pyproject.toml                                |   4 +
 .../agents/bdi/agentspeak_generator.py        |   5 +
 .../communication/ri_communication_agent.py   |  27 +-
 .../visual_emotion_recognition_agent.py       | 207 ++++
 .../visual_emotion_recognizer.py              |  53 ++
 .../user_interrupt/user_interrupt_agent.py    |  30 +-
 src/control_backend/core/config.py            |   8 +
 src/control_backend/schemas/program.py        |  19 +-
 .../test_ri_communication_agent.py            |  37 -
 .../test_visual_emotion_detection.py          | 338 +++++++
 .../user_interrupt/test_user_interrupt.py     |  30 +-
 uv.lock                                       | 887 +++++++++++++++++-
 12 files changed, 1533 insertions(+), 112 deletions(-)
 create mode 100644 src/control_backend/agents/perception/visual_emotion_recognition_agent/visual_emotion_recognition_agent.py
 create mode 100644 src/control_backend/agents/perception/visual_emotion_recognition_agent/visual_emotion_recognizer.py
 create mode 100644 test/unit/agents/perception/visual_emotion_detection/test_visual_emotion_detection.py

diff --git a/pyproject.toml b/pyproject.toml
index 5de7daa..4ab5859 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -7,6 +7,7 @@ requires-python = ">=3.13"
 dependencies = [
   "agentspeak>=0.2.2",
   "colorlog>=6.10.1",
+  "deepface>=0.0.96",
   "fastapi[all]>=0.115.6",
   "mlx-whisper>=0.4.3 ; sys_platform == 'darwin'",
   "numpy>=2.3.3",
@@ -21,6 +22,7 @@ dependencies = [
   "silero-vad>=6.0.0",
   "sphinx>=7.3.7",
   "sphinx-rtd-theme>=3.0.2",
+  "tf-keras>=2.20.1",
   "torch>=2.8.0",
   "uvicorn>=0.37.0",
 ]
@@ -38,6 +40,7 @@ dev = [
 ]
 test = [
   "agentspeak>=0.2.2",
+  "deepface>=0.0.97",
   "fastapi>=0.115.6",
   "httpx>=0.28.1",
   "mlx-whisper>=0.4.3 ; sys_platform == 'darwin'",
@@ -52,6 +55,7 @@ test = [
   "pyyaml>=6.0.3",
   "pyzmq>=27.1.0",
   "soundfile>=0.13.1",
+  "tf-keras>=2.20.1",
 ]
 
 [tool.pytest.ini_options]
diff --git a/src/control_backend/agents/bdi/agentspeak_generator.py b/src/control_backend/agents/bdi/agentspeak_generator.py
index 042fad7..ea390f4 100644
--- a/src/control_backend/agents/bdi/agentspeak_generator.py
+++ b/src/control_backend/agents/bdi/agentspeak_generator.py
@@ -29,6 +29,7 @@ from control_backend.schemas.program import (
     BaseGoal,
     BasicNorm,
     ConditionalNorm,
+    EmotionBelief,
     GestureAction,
     Goal,
     InferredBelief,
@@ -681,6 +682,10 @@ class AgentSpeakGenerator:
         :return: An AstLiteral representing the semantic belief.
         """
         return AstLiteral(self.slugify(sb))
+    
+    @_astify.register
+    def _(self, eb: EmotionBelief) -> AstExpression:
+        return AstLiteral("emotion_detected", [AstAtom(eb.emotion)])
 
     @_astify.register
     def _(self, ib: InferredBelief) -> AstExpression:
diff --git a/src/control_backend/agents/communication/ri_communication_agent.py b/src/control_backend/agents/communication/ri_communication_agent.py
index 9460510..570d64e 100644
--- a/src/control_backend/agents/communication/ri_communication_agent.py
+++ b/src/control_backend/agents/communication/ri_communication_agent.py
@@ -9,14 +9,14 @@ import json
 
 import zmq
 import zmq.asyncio as azmq
-from pydantic import ValidationError
 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_recognition_agent.visual_emotion_recognition_agent import (  # noqa
+    VisualEmotionRecognitionAgent,
+)
 from control_backend.core.config import settings
-from control_backend.schemas.internal_message import InternalMessage
-from control_backend.schemas.ri_message import PauseCommand
 
 from ..actuation.robot_speech_agent import RobotSpeechAgent
 from ..perception import VADAgent
@@ -58,6 +58,7 @@ class RICommunicationAgent(BaseAgent):
         self.connected = False
         self.gesture_agent: RobotGestureAgent | None = None
         self.speech_agent: RobotSpeechAgent | None = None
+        self.visual_emotion_recognition_agent: VisualEmotionRecognitionAgent | None = None
 
     async def setup(self):
         """
@@ -215,6 +216,14 @@ 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,
+                    )
+                    self.visual_emotion_recognition_agent = visual_emotion_agent
+                    await visual_emotion_agent.start()
                 case _:
                     self.logger.warning("Unhandled negotiation id: %s", id)
 
@@ -319,6 +328,9 @@ class RICommunicationAgent(BaseAgent):
 
         if self.speech_agent is not None:
             await self.speech_agent.stop()
+        
+        if self.visual_emotion_recognition_agent is not None:
+            await self.visual_emotion_recognition_agent.stop()
 
         if self.pub_socket is not None:
             self.pub_socket.close()
@@ -326,11 +338,4 @@ class RICommunicationAgent(BaseAgent):
         self.logger.debug("Restarting communication negotiation.")
         if await self._negotiate_connection(max_retries=2):
             self.connected = True
-
-    async def handle_message(self, msg: InternalMessage):
-        try:
-            pause_command = PauseCommand.model_validate_json(msg.body)
-            await self._req_socket.send_json(pause_command.model_dump())
-            self.logger.debug(await self._req_socket.recv_json())
-        except ValidationError:
-            self.logger.warning("Incorrect message format for PauseCommand.")
+            
\ No newline at end of file
diff --git a/src/control_backend/agents/perception/visual_emotion_recognition_agent/visual_emotion_recognition_agent.py b/src/control_backend/agents/perception/visual_emotion_recognition_agent/visual_emotion_recognition_agent.py
new file mode 100644
index 0000000..9793f2d
--- /dev/null
+++ b/src/control_backend/agents/perception/visual_emotion_recognition_agent/visual_emotion_recognition_agent.py
@@ -0,0 +1,207 @@
+import asyncio
+import json
+import time
+from collections import Counter, defaultdict
+
+import numpy as np
+import zmq
+import zmq.asyncio as azmq
+from pydantic_core import ValidationError
+
+from control_backend.agents import BaseAgent
+from control_backend.agents.perception.visual_emotion_recognition_agent.visual_emotion_recognizer import (  # noqa
+    DeepFaceEmotionRecognizer,
+)
+from control_backend.core.agent_system import InternalMessage
+from control_backend.core.config import settings
+from control_backend.schemas.belief_message import Belief
+
+
+class VisualEmotionRecognitionAgent(BaseAgent):
+    def __init__(
+        self,
+        name: str,
+        socket_address: str,
+        bind: bool = False,
+        timeout_ms: int = 1000,
+        window_duration: int = settings.behaviour_settings.visual_emotion_recognition_window_duration_s,  # noqa
+        min_frames_required: int = settings.behaviour_settings.visual_emotion_recognition_min_frames_per_face,  # noqa
+    ):
+        """
+        Initialize the Visual Emotion Recognition Agent.
+
+        :param name: Name of the agent
+        :param socket_address: Address of the socket to connect or bind to
+        :param bind: Whether to bind to the socket address (True) or connect (False)
+        :param timeout_ms: Timeout for socket receive operations in milliseconds
+        :param window_duration: Duration in seconds over which to aggregate emotions
+        :param min_frames_required: Minimum number of frames per face required to consider a face
+        valid
+        """
+        super().__init__(name)
+        self.socket_address = socket_address
+        self.socket_bind = bind
+        self.timeout_ms = timeout_ms
+        self.window_duration = window_duration
+        self.min_frames_required = min_frames_required
+
+        # Pause functionality
+        # NOTE: flag is set when running, cleared when paused
+        self._paused = asyncio.Event()
+        self._paused.set()
+
+    async def setup(self):
+        """
+        Initialize the agent resources.
+        1. Initializes the :class:`VisualEmotionRecognizer`.
+        2. Connects to the video input ZMQ socket.
+        3. Starts the background emotion recognition loop.
+        """
+        self.logger.info("Setting up %s.", self.name)
+
+        self.emotion_recognizer = DeepFaceEmotionRecognizer()
+
+        self.video_in_socket = azmq.Context.instance().socket(zmq.SUB)
+
+        self.video_in_socket.setsockopt(zmq.RCVHWM, 3)
+
+        if self.socket_bind:
+            self.video_in_socket.bind(self.socket_address)
+        else:
+            self.video_in_socket.connect(self.socket_address)
+
+        self.video_in_socket.setsockopt_string(zmq.SUBSCRIBE, "")
+        self.video_in_socket.setsockopt(zmq.RCVTIMEO, self.timeout_ms)
+
+        self.add_behavior(self.emotion_update_loop())
+
+    async def emotion_update_loop(self):
+        """
+        Background loop to receive video frames, recognize emotions, and update beliefs.
+        1. Receives video frames from the ZMQ socket.
+        2. Uses the :class:`VisualEmotionRecognizer` to detect emotions.
+        3. Aggregates emotions over a time window.
+        4. Sends updates to the BDI Core Agent about detected emotions.
+        """
+        # Next time to process the window and update emotions
+        next_window_time = time.time() + self.window_duration
+
+        # Tracks counts of detected emotions per face index
+        face_stats = defaultdict(Counter)
+
+        prev_dominant_emotions = set()
+
+        while self._running:
+            try:
+                await self._paused.wait()
+
+                width, height, image_bytes = await self.video_in_socket.recv_multipart()
+
+                width = int.from_bytes(width, 'little')
+                height = int.from_bytes(height, 'little')
+
+                # Convert bytes to a numpy buffer
+                image_array = np.frombuffer(image_bytes, np.uint8)
+
+                frame = image_array.reshape((height, width, 3))
+
+                # Get the dominant emotion from each face
+                current_emotions = self.emotion_recognizer.sorted_dominant_emotions(frame)
+                # Update emotion counts for each detected face
+                for i, emotion in enumerate(current_emotions):
+                    face_stats[i][emotion] += 1
+
+                # If window duration has passed, process the collected stats
+                if time.time() >= next_window_time:
+                    window_dominant_emotions = set()
+                    # Determine dominant emotion for each face in the window
+                    for _, counter in face_stats.items():
+                        total_detections = sum(counter.values())
+
+                        if total_detections >= self.min_frames_required:
+                            dominant_emotion = counter.most_common(1)[0][0]
+                            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() + self.window_duration
+
+            except zmq.Again:
+                self.logger.warning("No video frame received within timeout.")
+
+            except Exception as e:
+                self.logger.error(f"Error in emotion recognition loop: {e}")
+
+    
+    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.
+        """
+        emotions_to_remove = prev_emotions - emotions
+        emotions_to_add = emotions - prev_emotions
+
+        if not emotions_to_add and not emotions_to_remove:
+            return
+
+        emotion_beliefs_remove = []
+        for emotion in emotions_to_remove:
+            self.logger.info(f"Emotion '{emotion}' has disappeared.")
+            try:
+                emotion_beliefs_remove.append(
+                    Belief(name="emotion_detected", arguments=[emotion], remove=True)
+                )
+            except ValidationError:
+                self.logger.warning("Invalid belief for emotion removal: %s", emotion)
+
+        emotion_beliefs_add = []
+        for emotion in emotions_to_add:
+            self.logger.info(f"New emotion detected: '{emotion}'")
+            try:
+                emotion_beliefs_add.append(Belief(name="emotion_detected", arguments=[emotion]))
+            except ValidationError:
+                self.logger.warning("Invalid belief for new emotion: %s", emotion)
+
+        beliefs_list_add = [b.model_dump() for b in emotion_beliefs_add]
+        beliefs_list_remove = [b.model_dump() for b in emotion_beliefs_remove]
+        payload = {"create": beliefs_list_add, "delete": beliefs_list_remove}
+
+        message = InternalMessage(
+            to=settings.agent_settings.bdi_core_name,
+            sender=self.name,
+            body=json.dumps(payload),
+            thread="beliefs",
+        )
+        await self.send(message)
+
+    async def handle_message(self, msg: InternalMessage):
+        """
+        Handle incoming messages.
+
+        Expects messages to pause or resume the Visual Emotion Recognition 
+        processing from User Interrupt Agent.
+
+        :param msg: The received internal message.
+        """
+        sender = msg.sender
+
+        if sender == settings.agent_settings.user_interrupt_name:
+            if msg.body == "PAUSE":
+                self.logger.info("Pausing Visual Emotion Recognition processing.")
+                self._paused.clear()
+            elif msg.body == "RESUME":
+                self.logger.info("Resuming Visual Emotion Recognition processing.")
+                self._paused.set()
+            else:
+                self.logger.warning(f"Unknown command from User Interrupt Agent: {msg.body}")
+        else:
+            self.logger.debug(f"Ignoring message from unknown sender: {sender}")
+
+    async def stop(self):
+        """
+        Clean up resources used by the agent.
+        """
+        self.video_in_socket.close()
+        await super().stop()
+        
\ No newline at end of file
diff --git a/src/control_backend/agents/perception/visual_emotion_recognition_agent/visual_emotion_recognizer.py b/src/control_backend/agents/perception/visual_emotion_recognition_agent/visual_emotion_recognizer.py
new file mode 100644
index 0000000..0ff4b31
--- /dev/null
+++ b/src/control_backend/agents/perception/visual_emotion_recognition_agent/visual_emotion_recognizer.py
@@ -0,0 +1,53 @@
+import abc
+
+import numpy as np
+from deepface import DeepFace
+
+
+class VisualEmotionRecognizer(abc.ABC):
+    @abc.abstractmethod
+    def load_model(self):
+        """Load the visual emotion recognition model into memory."""
+        pass
+
+    @abc.abstractmethod
+    def sorted_dominant_emotions(self, image) -> list[str]:
+        """
+        Recognize dominant emotions from faces in the given image.
+        Emotions can be one of ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'].
+        To minimize false positives, consider filtering faces with low confidence.
+
+        :param image: The input image for emotion recognition.
+        :return: List of dominant emotion detected for each face in the image, 
+        sorted per face.
+        """
+        pass
+
+class DeepFaceEmotionRecognizer(VisualEmotionRecognizer):
+    """
+    DeepFace-based implementation of VisualEmotionRecognizer.
+    DeepFape has proven to be quite a pessimistic model, so expect sad, fear and neutral 
+    emotions to be over-represented.
+    """
+    def __init__(self):
+        self.load_model()
+    
+    def load_model(self):
+        dummy_img = np.zeros((224, 224, 3), dtype=np.uint8)
+        # analyze does not take a model as an argument, calling it once on a dummy image to load 
+        # the model
+        DeepFace.analyze(dummy_img, actions=['emotion'], enforce_detection=False)
+
+    def sorted_dominant_emotions(self, image) -> list[str]:
+        analysis = DeepFace.analyze(image, 
+                                    actions=['emotion'], 
+                                    enforce_detection=False
+                                    )
+        
+        # Sort faces by x coordinate to maintain left-to-right order
+        analysis.sort(key=lambda face: face['region']['x'])
+
+        analysis = [face for face in analysis if face['face_confidence'] >= 0.90]
+        
+        dominant_emotions = [face['dominant_emotion'] for face in analysis]
+        return dominant_emotions
diff --git a/src/control_backend/agents/user_interrupt/user_interrupt_agent.py b/src/control_backend/agents/user_interrupt/user_interrupt_agent.py
index ed38e8b..5553fe8 100644
--- a/src/control_backend/agents/user_interrupt/user_interrupt_agent.py
+++ b/src/control_backend/agents/user_interrupt/user_interrupt_agent.py
@@ -18,7 +18,6 @@ from control_backend.schemas.belief_message import Belief, BeliefMessage
 from control_backend.schemas.program import ConditionalNorm, Goal, Program
 from control_backend.schemas.ri_message import (
     GestureCommand,
-    PauseCommand,
     RIEndpoint,
     SpeechCommand,
 )
@@ -398,34 +397,29 @@ class UserInterruptAgent(BaseAgent):
         self.logger.debug("Sending experiment control '%s' to BDI Core.", thread)
         await self.send(out_msg)
 
-    async def _send_pause_command(self, pause):
+    async def _send_pause_command(self, pause: str):
         """
-        Send a pause command to the Robot Interface via the RI Communication Agent.
-        Send a pause command to the other internal agents; for now just VAD agent.
+        Send a pause command to the other internal agents; for now just VAD and VED agent.
         """
-        cmd = PauseCommand(data=pause)
-        message = InternalMessage(
-            to=settings.agent_settings.ri_communication_name,
-            sender=self.name,
-            body=cmd.model_dump_json(),
-        )
-        await self.send(message)
-
         if pause == "true":
-            # Send pause to VAD agent
+            # Send pause to VAD and VED agent
             vad_message = InternalMessage(
-                to=settings.agent_settings.vad_name,
+                to=[settings.agent_settings.vad_name, 
+                    settings.agent_settings.visual_emotion_recognition_name],
                 sender=self.name,
                 body="PAUSE",
             )
             await self.send(vad_message)
-            self.logger.info("Sent pause command to VAD Agent and RI Communication Agent.")
+            # Voice Activity Detection and Visual Emotion Recognition agents
+            self.logger.info("Sent pause command to VAD and VED agents.")
         else:
-            # Send resume to VAD agent
+            # Send resume to VAD and VED agents
             vad_message = InternalMessage(
-                to=settings.agent_settings.vad_name,
+                to=[settings.agent_settings.vad_name, 
+                    settings.agent_settings.visual_emotion_recognition_name],
                 sender=self.name,
                 body="RESUME",
             )
             await self.send(vad_message)
-            self.logger.info("Sent resume command to VAD Agent and RI Communication Agent.")
+            # Voice Activity Detection and Visual Emotion Recognition agents
+            self.logger.info("Sent resume command to VAD and VED agents.")
\ No newline at end of file
diff --git a/src/control_backend/core/config.py b/src/control_backend/core/config.py
index 5165e65..adb4c69 100644
--- a/src/control_backend/core/config.py
+++ b/src/control_backend/core/config.py
@@ -54,6 +54,7 @@ class AgentSettings(BaseModel):
     # agent names
     bdi_core_name: str = "bdi_core_agent"
     bdi_program_manager_name: str = "bdi_program_manager_agent"
+    visual_emotion_recognition_name: str = "visual_emotion_recognition_agent"
     text_belief_extractor_name: str = "text_belief_extractor_agent"
     vad_name: str = "vad_agent"
     llm_name: str = "llm_agent"
@@ -81,6 +82,10 @@ class BehaviourSettings(BaseModel):
     :ivar transcription_words_per_token: Estimated words per token for transcription timing.
     :ivar transcription_token_buffer: Buffer for transcription tokens.
     :ivar conversation_history_length_limit: The maximum amount of messages to extract beliefs from.
+    :ivar visual_emotion_recognition_window_duration_s: Duration in seconds over which to aggregate 
+    emotions and update emotion beliefs.
+    :ivar visual_emotion_recognition_min_frames_per_face: Minimum number of frames per face required
+    to consider a face valid.
     :ivar trigger_time_to_wait: Amount of milliseconds to wait before informing the UI about trigger
      completion.
     """
@@ -106,6 +111,9 @@ class BehaviourSettings(BaseModel):
     # Text belief extractor settings
     conversation_history_length_limit: int = 10
 
+    # Visual Emotion Recognition settings
+    visual_emotion_recognition_window_duration_s: int = 5
+    visual_emotion_recognition_min_frames_per_face: int = 3
     # AgentSpeak related settings
     trigger_time_to_wait: int = 2000
     agentspeak_file: str = "src/control_backend/agents/bdi/agentspeak.asl"
diff --git a/src/control_backend/schemas/program.py b/src/control_backend/schemas/program.py
index f3d102a..8f23cb9 100644
--- a/src/control_backend/schemas/program.py
+++ b/src/control_backend/schemas/program.py
@@ -41,8 +41,8 @@ class LogicalOperator(Enum):
     OR = "OR"
 
 
-type Belief = KeywordBelief | SemanticBelief | InferredBelief
-type BasicBelief = KeywordBelief | SemanticBelief
+type Belief = KeywordBelief | SemanticBelief | InferredBelief | EmotionBelief
+type BasicBelief = KeywordBelief | SemanticBelief | EmotionBelief
 
 
 class KeywordBelief(ProgramElement):
@@ -105,6 +105,15 @@ class InferredBelief(ProgramElement):
     left: Belief
     right: Belief
 
+class EmotionBelief(ProgramElement):
+    """
+    Represents a belief that is set when a certain emotion is detected.
+
+    :ivar emotion: The emotion on which this belief gets set.
+    """
+
+    name: str = ""
+    emotion: str
 
 class Norm(ProgramElement):
     """
@@ -315,3 +324,9 @@ class Program(BaseModel):
     """
 
     phases: list[Phase]
+
+
+if __name__ == "__main__":
+    input = input("Enter program JSON: ")
+    program = Program.model_validate_json(input)
+    print(program)
\ No newline at end of file
diff --git a/test/unit/agents/communication/test_ri_communication_agent.py b/test/unit/agents/communication/test_ri_communication_agent.py
index 989cbd6..f9d57d5 100644
--- a/test/unit/agents/communication/test_ri_communication_agent.py
+++ b/test/unit/agents/communication/test_ri_communication_agent.py
@@ -10,8 +10,6 @@ from unittest.mock import ANY, AsyncMock, MagicMock, patch
 import pytest
 
 from control_backend.agents.communication.ri_communication_agent import RICommunicationAgent
-from control_backend.core.agent_system import InternalMessage
-from control_backend.schemas.ri_message import PauseCommand, RIEndpoint
 
 
 def speech_agent_path():
@@ -402,38 +400,3 @@ async def test_negotiate_req_socket_none_causes_retry(zmq_context):
     result = await agent._negotiate_connection(max_retries=1)
 
     assert result is False
-
-
-@pytest.mark.asyncio
-async def test_handle_message_pause_command(zmq_context):
-    """Test handle_message with a valid PauseCommand."""
-    agent = RICommunicationAgent("ri_comm")
-    agent._req_socket = AsyncMock()
-    agent.logger = MagicMock()
-
-    agent._req_socket.recv_json.return_value = {"status": "ok"}
-
-    pause_cmd = PauseCommand(data=True)
-    msg = InternalMessage(to="ri_comm", sender="user_int", body=pause_cmd.model_dump_json())
-
-    await agent.handle_message(msg)
-
-    agent._req_socket.send_json.assert_awaited_once()
-    args = agent._req_socket.send_json.await_args[0][0]
-    assert args["endpoint"] == RIEndpoint.PAUSE.value
-    assert args["data"] is True
-
-
-@pytest.mark.asyncio
-async def test_handle_message_invalid_pause_command(zmq_context):
-    """Test handle_message with invalid JSON."""
-    agent = RICommunicationAgent("ri_comm")
-    agent._req_socket = AsyncMock()
-    agent.logger = MagicMock()
-
-    msg = InternalMessage(to="ri_comm", sender="user_int", body="invalid json")
-
-    await agent.handle_message(msg)
-
-    agent.logger.warning.assert_called_with("Incorrect message format for PauseCommand.")
-    agent._req_socket.send_json.assert_not_called()
diff --git a/test/unit/agents/perception/visual_emotion_detection/test_visual_emotion_detection.py b/test/unit/agents/perception/visual_emotion_detection/test_visual_emotion_detection.py
new file mode 100644
index 0000000..4b2b7c9
--- /dev/null
+++ b/test/unit/agents/perception/visual_emotion_detection/test_visual_emotion_detection.py
@@ -0,0 +1,338 @@
+import asyncio
+import json
+import time
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import numpy as np
+import pytest
+import zmq
+from pydantic_core import ValidationError
+
+# Adjust the import path to match your project structure
+from control_backend.agents.perception.visual_emotion_recognition_agent.visual_emotion_recognition_agent import (  # noqa
+    VisualEmotionRecognitionAgent,
+)
+from control_backend.core.agent_system import InternalMessage
+
+# -----------------------------------------------------------------------------
+# Fixtures
+# -----------------------------------------------------------------------------
+
+@pytest.fixture
+def mock_settings():
+    with patch("control_backend.agents.perception.visual_emotion_recognition_agent.visual_emotion_recognition_agent.settings") as mock: # noqa
+        # Set default values required by the agent
+        mock.behaviour_settings.visual_emotion_recognition_window_duration_s = 5
+        mock.behaviour_settings.visual_emotion_recognition_min_frames_per_face = 3
+        mock.agent_settings.bdi_core_name = "bdi_core_agent"
+        mock.agent_settings.user_interrupt_name = "user_interrupt_agent"
+        yield mock
+
+@pytest.fixture
+def mock_deepface():
+    with patch("control_backend.agents.perception.visual_emotion_recognition_agent.visual_emotion_recognition_agent.DeepFaceEmotionRecognizer") as mock: # noqa
+        instance = mock.return_value
+        instance.sorted_dominant_emotions.return_value = []
+        yield instance
+
+@pytest.fixture
+def mock_zmq_context():
+    with patch("zmq.asyncio.Context.instance") as mock_ctx:
+        mock_socket = MagicMock()
+        # Mock socket methods to return None or AsyncMock for async methods
+        mock_socket.bind = MagicMock()
+        mock_socket.connect = MagicMock()
+        mock_socket.setsockopt = MagicMock()
+        mock_socket.setsockopt_string = MagicMock()
+        mock_socket.recv_multipart = AsyncMock()
+        mock_socket.close = MagicMock()
+        
+        mock_ctx.return_value.socket.return_value = mock_socket
+        yield mock_ctx
+
+@pytest.fixture
+def agent(mock_settings, mock_deepface, mock_zmq_context):
+    # Initialize agent with specific params to control testing
+    agent = VisualEmotionRecognitionAgent(
+        name="test_agent",
+        socket_address="tcp://localhost:5555",
+        bind=False,
+        timeout_ms=100,
+        window_duration=2,
+        min_frames_required=2
+    )
+    # Mock the internal send method from BaseAgent
+    agent.send = AsyncMock()
+    # Mock the add_behavior method from BaseAgent
+    agent.add_behavior = MagicMock()
+    # Mock the logger
+    agent.logger = MagicMock()
+    
+    return agent
+
+# -----------------------------------------------------------------------------
+# Tests
+# -----------------------------------------------------------------------------
+
+@pytest.mark.asyncio
+async def test_initialization(agent):
+    """Test that the agent initializes with correct attributes."""
+    assert agent.name == "test_agent"
+    assert agent.socket_address == "tcp://localhost:5555"
+    assert agent.socket_bind is False
+    assert agent.timeout_ms == 100
+    assert agent._paused.is_set()
+
+@pytest.mark.asyncio
+async def test_setup_connect(agent, mock_zmq_context, mock_deepface):
+    """Test setup routine when binding is False (connect)."""
+    agent.socket_bind = False
+    await agent.setup()
+
+    socket = agent.video_in_socket
+    socket.connect.assert_called_with("tcp://localhost:5555")
+    socket.bind.assert_not_called()
+    socket.setsockopt.assert_any_call(zmq.RCVHWM, 3)
+    socket.setsockopt.assert_any_call(zmq.RCVTIMEO, 100)
+    agent.add_behavior.assert_called_once()
+    assert agent.emotion_recognizer == mock_deepface
+
+@pytest.mark.asyncio
+async def test_setup_bind(agent, mock_zmq_context):
+    """Test setup routine when binding is True."""
+    agent.socket_bind = True
+    await agent.setup()
+
+    socket = agent.video_in_socket
+    socket.bind.assert_called_with("tcp://localhost:5555")
+    socket.connect.assert_not_called()
+
+@pytest.mark.asyncio
+async def test_emotion_update_loop_normal_flow(agent, mock_deepface):
+    """
+    Test the main loop logic:
+    1. Receive frames
+    2. Aggregate stats
+    3. Trigger window update
+    4. Call update_emotions
+    """
+    # Setup dependencies
+    await agent.setup()
+    agent._running = True
+    
+    # Create fake image data (10x10 pixels)
+    width, height = 10, 10
+    image_bytes = np.zeros((10, 10, 3), dtype=np.uint8).tobytes()
+    w_bytes = width.to_bytes(4, 'little')
+    h_bytes = height.to_bytes(4, 'little')
+    
+    # Mock ZMQ receive to return data 3 times, then stop the loop
+    # We use a side_effect on recv_multipart to simulate frames and then stop the loop
+    async def recv_side_effect():
+        if agent._running:
+            return w_bytes, h_bytes, image_bytes
+        raise asyncio.CancelledError()
+
+    agent.video_in_socket.recv_multipart.side_effect = recv_side_effect
+
+    # Mock DeepFace to return emotions
+    # Frame 1: Happy
+    # Frame 2: Happy
+    # Frame 3: Happy (Trigger window)
+    mock_deepface.sorted_dominant_emotions.side_effect = [
+        ["happy"], 
+        ["happy"], 
+        ["happy"]
+    ]
+    
+    # Mock update_emotions to verify it's called
+    agent.update_emotions = AsyncMock()
+
+    # Mock time.time to simulate window passage
+    # We need time to advance significantly after the frames are collected
+    start_time = time.time()
+    
+    with patch("time.time") as mock_time:
+        # Sequence of time calls:
+        # 1. Init next_window_time calculation
+        # 2. Loop 1 check
+        # 3. Loop 2 check
+        # 4. Loop 3 check (Make this one pass the window threshold)
+        mock_time.side_effect = [
+            start_time,          # init
+            start_time + 0.1,    # frame 1 check
+            start_time + 0.2,    # frame 2 check
+            start_time + 10.0,   # frame 3 check (triggers window reset)
+            start_time + 10.1,   # next init
+            start_time + 10.2    # break loop
+        ]
+        
+        # We need to manually break the infinite loop after the update
+        # We can do this by wrapping update_emotions to set _running = False
+        async def stop_loop(*args, **kwargs):
+            agent._running = False
+        
+        agent.update_emotions.side_effect = stop_loop
+
+        # Run the loop
+        await agent.emotion_update_loop()
+
+    # Verifications
+    assert agent.update_emotions.called
+    # Check that it detected 'happy' as dominant (2 required, 3 found)
+    call_args = agent.update_emotions.call_args
+    assert call_args is not None
+    # args: (prev_emotions, window_dominant_emotions)
+    assert call_args[0][1] == {"happy"} 
+
+@pytest.mark.asyncio
+async def test_emotion_update_loop_insufficient_frames(agent, mock_deepface):
+    """Test that emotions are NOT updated if min_frames_required is not met."""
+    await agent.setup()
+    agent._running = True
+    agent.min_frames_required = 5  # Set high requirement
+
+    width, height = 10, 10
+    image_bytes = np.zeros((10, 10, 3), dtype=np.uint8).tobytes()
+    w_bytes = width.to_bytes(4, 'little')
+    h_bytes = height.to_bytes(4, 'little')
+
+    agent.video_in_socket.recv_multipart.return_value = (w_bytes, h_bytes, image_bytes)
+    mock_deepface.sorted_dominant_emotions.return_value = ["sad"]
+    
+    agent.update_emotions = AsyncMock()
+
+    with patch("time.time") as mock_time:
+        # Time setup to trigger window processing immediately
+        mock_time.side_effect = [0, 100, 101] 
+        
+        # Stop loop after first pass
+        async def stop_loop(*args, **kwargs):
+            agent._running = False
+        agent.update_emotions.side_effect = stop_loop
+
+        await agent.emotion_update_loop()
+
+    # It should call update_emotions with EMPTY set because min frames (5) > detected (1)
+    call_args = agent.update_emotions.call_args
+    assert call_args[0][1] == set()
+
+@pytest.mark.asyncio
+async def test_emotion_update_loop_zmq_again_and_exception(agent):
+    """Test that the loop handles ZMQ timeouts (Again) and generic exceptions."""
+    await agent.setup()
+    agent._running = True
+
+    # Side effect: 
+    # 1. Raise ZMQ Again (Timeout) -> should log warning
+    # 2. Raise Generic Exception -> should log error
+    # 3. Raise CancelledError -> stop loop (simulating stop)
+    agent.video_in_socket.recv_multipart.side_effect = [
+        zmq.Again(),
+        RuntimeError("Random Failure"),
+        asyncio.CancelledError() # To break loop cleanly
+    ]
+
+    # We need to ensure the loop doesn't block on _paused
+    agent._paused.set()
+
+    # Run loop
+    try:
+        await agent.emotion_update_loop()
+    except asyncio.CancelledError:
+        pass
+
+@pytest.mark.asyncio
+async def test_update_emotions_logic(agent, mock_settings):
+    """Test the logic for calculating diffs and sending messages."""
+    agent.name = "viz_agent"
+    
+    # Case 1: No change
+    await agent.update_emotions({"happy"}, {"happy"})
+    agent.send.assert_not_called()
+
+    # Case 2: Remove 'happy', Add 'sad'
+    await agent.update_emotions({"happy"}, {"sad"})
+    
+    assert agent.send.called
+    call_args = agent.send.call_args
+    msg = call_args[0][0] # InternalMessage object
+    
+    assert msg.to == mock_settings.agent_settings.bdi_core_name
+    assert msg.sender == "viz_agent"
+    assert msg.thread == "beliefs"
+    
+    payload = json.loads(msg.body)
+    
+    # Check Created Beliefs
+    assert len(payload["create"]) == 1
+    assert payload["create"][0]["name"] == "emotion_detected"
+    assert payload["create"][0]["arguments"] == ["sad"]
+    
+    # Check Deleted Beliefs
+    assert len(payload["delete"]) == 1
+    assert payload["delete"][0]["name"] == "emotion_detected"
+    assert payload["delete"][0]["arguments"] == ["happy"]
+
+@pytest.mark.asyncio
+async def test_update_emotions_validation_error(agent):
+    """Test that ValidationErrors during Belief creation are caught."""
+    
+    # We patch Belief to raise ValidationError
+    with patch("control_backend.agents.perception.visual_emotion_recognition_agent.visual_emotion_recognition_agent.Belief") as MockBelief: # noqa
+        MockBelief.side_effect = ValidationError.from_exception_data("Simulated Error", [])
+        
+        # Try to update emotions
+        await agent.update_emotions(prev_emotions={"happy"}, emotions={"sad"})
+        
+        # Verify empty payload is sent (or payload with valid ones if mixed)
+        # In this case both failed, so payload lists should be empty
+        assert agent.send.called
+        msg = agent.send.call_args[0][0]
+        payload = json.loads(msg.body)
+        assert payload["create"] == []
+        assert payload["delete"] == []
+
+@pytest.mark.asyncio
+async def test_handle_message(agent, mock_settings):
+    """Test message handling for Pause/Resume."""
+    
+    # Setup
+    ui_name = mock_settings.agent_settings.user_interrupt_name
+    
+    # 1. PAUSE message
+    msg_pause = InternalMessage(to="me", sender=ui_name, body="PAUSE")
+    await agent.handle_message(msg_pause)
+    assert not agent._paused.is_set() # Should be cleared (paused)
+    agent.logger.info.assert_called_with("Pausing Visual Emotion Recognition processing.")
+
+    # 2. RESUME message
+    msg_resume = InternalMessage(to="me", sender=ui_name, body="RESUME")
+    await agent.handle_message(msg_resume)
+    assert agent._paused.is_set() # Should be set (running)
+
+    # 3. Unknown command
+    msg_unknown = InternalMessage(to="me", sender=ui_name, body="DANCE")
+    await agent.handle_message(msg_unknown)
+
+    # 4. Unknown sender
+    msg_random = InternalMessage(to="me", sender="random_guy", body="PAUSE")
+    await agent.handle_message(msg_random)
+
+@pytest.mark.asyncio
+async def test_stop(agent, mock_zmq_context):
+    """Test the stop method cleans up resources."""
+    # We need to mock super().stop(). Since we can't easily patch super(),
+    # and the provided BaseAgent code shows stop() just sets _running and cancels tasks,
+    # we can rely on the fact that VisualEmotionRecognitionAgent calls it.
+    
+    # However, since we provided a 'agent' fixture that mocks things, we should verify specific cleanups. # noqa
+    await agent.setup()
+    
+    with patch("control_backend.agents.BaseAgent.stop", new_callable=AsyncMock) as mock_super_stop:
+        await agent.stop()
+        
+        # Verify socket closed
+        agent.video_in_socket.close.assert_called_once()
+        # Verify parent stop called
+        mock_super_stop.assert_called_once()
\ No newline at end of file
diff --git a/test/unit/agents/user_interrupt/test_user_interrupt.py b/test/unit/agents/user_interrupt/test_user_interrupt.py
index c678607..1d7fda9 100644
--- a/test/unit/agents/user_interrupt/test_user_interrupt.py
+++ b/test/unit/agents/user_interrupt/test_user_interrupt.py
@@ -305,26 +305,30 @@ async def test_send_experiment_control(agent):
 
 @pytest.mark.asyncio
 async def test_send_pause_command(agent):
+    # --- Test PAUSE ---
     await agent._send_pause_command("true")
-    # Sends to RI and VAD
-    assert agent.send.await_count == 2
-    msgs = [call.args[0] for call in agent.send.call_args_list]
 
-    ri_msg = next(m for m in msgs if m.to == settings.agent_settings.ri_communication_name)
-    assert json.loads(ri_msg.body)["endpoint"] == ""  # PAUSE endpoint
-    assert json.loads(ri_msg.body)["data"] is True
+    # Should send exactly 1 message
+    assert agent.send.await_count == 1
+    
+    # Extract the message object from the mock call
+    # call_args[0] are positional args, and [0] is the first arg (the message)
+    msg = agent.send.call_args[0][0]
 
-    vad_msg = next(m for m in msgs if m.to == settings.agent_settings.vad_name)
-    assert vad_msg.body == "PAUSE"
+    # Verify Body
+    assert msg.body == "PAUSE"
 
+    # --- Test RESUME ---
     agent.send.reset_mock()
     await agent._send_pause_command("false")
-    assert agent.send.await_count == 2
-    vad_msg = next(
-        m for m in agent.send.call_args_list if m.args[0].to == settings.agent_settings.vad_name
-    ).args[0]
-    assert vad_msg.body == "RESUME"
 
+    # Should send exactly 1 message
+    assert agent.send.await_count == 1
+    
+    msg = agent.send.call_args[0][0]
+
+    # Verify Body
+    assert msg.body == "RESUME"
 
 @pytest.mark.asyncio
 async def test_setup(agent):
diff --git a/uv.lock b/uv.lock
index ea39c17..b87cc0b 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,9 +1,22 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.13"
 resolution-markers = [
-    "python_full_version >= '3.14'",
-    "python_full_version < '3.14'",
+    "python_full_version >= '3.14' and sys_platform == 'darwin'",
+    "python_full_version >= '3.14' and platform_machine == 'aarch64' and sys_platform == 'linux'",
+    "(python_full_version >= '3.14' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.14' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version < '3.14' and sys_platform == 'darwin'",
+    "python_full_version < '3.14' and platform_machine == 'aarch64' and sys_platform == 'linux'",
+    "(python_full_version < '3.14' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version < '3.14' and sys_platform != 'darwin' and sys_platform != 'linux')",
+]
+
+[[package]]
+name = "absl-py"
+version = "2.3.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/10/2a/c93173ffa1b39c1d0395b7e842bbdc62e556ca9d8d3b5572926f3e4ca752/absl_py-2.3.1.tar.gz", hash = "sha256:a97820526f7fbfd2ec1bce83f3f25e3a14840dac0d8e02a0b71cd75db3f77fc9", size = 116588, upload-time = "2025-07-03T09:31:44.05Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/8f/aa/ba0014cc4659328dc818a28827be78e6d97312ab0cb98105a770924dc11e/absl_py-2.3.1-py3-none-any.whl", hash = "sha256:eeecf07f0c2a93ace0772c92e596ace6d3d3996c042b2128459aaae2a76de11d", size = 135811, upload-time = "2025-07-03T09:31:42.253Z" },
 ]
 
 [[package]]
@@ -49,6 +62,19 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/15/b3/9b1a8074496371342ec1e796a96f99c82c945a339cd81a8e73de28b4cf9e/anyio-4.11.0-py3-none-any.whl", hash = "sha256:0287e96f4d26d4149305414d4e3bc32f0dcd0862365a4bddea19d7a1ec38c4fc", size = 109097, upload-time = "2025-09-23T09:19:10.601Z" },
 ]
 
+[[package]]
+name = "astunparse"
+version = "1.6.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "six" },
+    { name = "wheel" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/f3/af/4182184d3c338792894f34a62672919db7ca008c89abee9b564dd34d8029/astunparse-1.6.3.tar.gz", hash = "sha256:5ad93a8456f0d084c3456d059fd9a92cce667963232cbf763eac3bc5b7940872", size = 18290, upload-time = "2019-12-22T18:12:13.129Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/2b/03/13dde6512ad7b4557eb792fbcf0c653af6076b81e5941d36ec61f7ce6028/astunparse-1.6.3-py2.py3-none-any.whl", hash = "sha256:c2652417f2c8b5bb325c885ae329bdf3f86424075c4fd1a128674bc6fba4b8e8", size = 12732, upload-time = "2019-12-22T18:12:11.297Z" },
+]
+
 [[package]]
 name = "babel"
 version = "2.17.0"
@@ -58,6 +84,28 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/b7/b8/3fe70c75fe32afc4bb507f75563d39bc5642255d1d94f1f23604725780bf/babel-2.17.0-py3-none-any.whl", hash = "sha256:4d0b53093fdfb4b21c92b5213dba5a1b23885afa8383709427046b21c366e5f2", size = 10182537, upload-time = "2025-02-01T15:17:37.39Z" },
 ]
 
+[[package]]
+name = "beautifulsoup4"
+version = "4.14.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "soupsieve" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/c3/b0/1c6a16426d389813b48d95e26898aff79abbde42ad353958ad95cc8c9b21/beautifulsoup4-4.14.3.tar.gz", hash = "sha256:6292b1c5186d356bba669ef9f7f051757099565ad9ada5dd630bd9de5fa7fb86", size = 627737, upload-time = "2025-11-30T15:08:26.084Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl", hash = "sha256:0918bfe44902e6ad8d57732ba310582e98da931428d231a5ecb9e7c703a735bb", size = 107721, upload-time = "2025-11-30T15:08:24.087Z" },
+]
+
+[[package]]
+name = "blinker"
+version = "1.9.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/21/28/9b3f50ce0e048515135495f198351908d99540d69bfdc8c1d15b73dc55ce/blinker-1.9.0.tar.gz", hash = "sha256:b4ce2265a7abece45e7cc896e98dbebe6cead56bcf805a3d23136d145f5445bf", size = 22460, upload-time = "2024-11-08T17:25:47.436Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/10/cb/f2ad4230dc2eb1a74edf38f1a38b9b52277f75bef262d8908e60d957e13c/blinker-1.9.0-py3-none-any.whl", hash = "sha256:ba0efaa9080b619ff2f3459d1d500c57bddea4a6b424b60a91141db6fd2f08bc", size = 8458, upload-time = "2024-11-08T17:25:46.184Z" },
+]
+
 [[package]]
 name = "certifi"
 version = "2025.10.5"
@@ -258,6 +306,34 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/5f/04/642c1d8a448ae5ea1369eac8495740a79eb4e581a9fb0cbdce56bbf56da1/coverage-7.11.0-py3-none-any.whl", hash = "sha256:4b7589765348d78fb4e5fb6ea35d07564e387da2fc5efff62e0222971f155f68", size = 207761, upload-time = "2025-10-15T15:15:06.439Z" },
 ]
 
+[[package]]
+name = "deepface"
+version = "0.0.97"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "fire" },
+    { name = "flask" },
+    { name = "flask-cors" },
+    { name = "gdown" },
+    { name = "gunicorn" },
+    { name = "keras" },
+    { name = "lightphe" },
+    { name = "mtcnn" },
+    { name = "numpy" },
+    { name = "opencv-python" },
+    { name = "pandas" },
+    { name = "pillow" },
+    { name = "python-dotenv" },
+    { name = "requests" },
+    { name = "retina-face" },
+    { name = "tensorflow" },
+    { name = "tqdm" },
+]
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 version = "0.1.0"
@@ -989,6 +1507,7 @@ source = { virtual = "." }
 dependencies = [
     { name = "agentspeak" },
     { name = "colorlog" },
+    { name = "deepface" },
     { name = "fastapi", extra = ["all"] },
     { name = "mlx-whisper", marker = "sys_platform == 'darwin'" },
     { name = "numpy" },
@@ -1003,6 +1522,7 @@ dependencies = [
     { name = "silero-vad" },
     { name = "sphinx" },
     { name = "sphinx-rtd-theme" },
+    { name = "tf-keras" },
     { name = "torch" },
     { name = "uvicorn" },
 ]
@@ -1020,6 +1540,7 @@ dev = [
 ]
 test = [
     { name = "agentspeak" },
+    { name = "deepface" },
     { name = "fastapi" },
     { name = "httpx" },
     { name = "mlx-whisper", marker = "sys_platform == 'darwin'" },
@@ -1034,12 +1555,14 @@ test = [
     { name = "pyyaml" },
     { name = "pyzmq" },
     { name = "soundfile" },
+    { name = "tf-keras" },
 ]
 
 [package.metadata]
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     { name = "sphinx", specifier = ">=7.3.7" },
     { name = "sphinx-rtd-theme", specifier = ">=3.0.2" },
+    { name = "tf-keras", specifier = ">=2.20.1" },
     { name = "torch", specifier = ">=2.8.0" },
     { name = "uvicorn", specifier = ">=0.37.0" },
 ]
@@ -1071,6 +1595,7 @@ dev = [
 ]
 test = [
     { name = "agentspeak", specifier = ">=0.2.2" },
+    { name = "deepface", specifier = ">=0.0.97" },
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     { name = "pyzmq", specifier = ">=27.1.0" },
     { name = "soundfile", specifier = ">=0.13.1" },
+    { name = "tf-keras", specifier = ">=2.20.1" },
+]
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