Merge branch 'main' into feat/face-recognition

This reverts commit 53ba8bb16b

.gitignore

@@ -222,6 +222,9 @@ __marimo__/
 docs/*
 !docs/conf.py
 
+# Generated files
+*.asl
+experiment-*.log
 
 
 

.gitlab-ci.yml

@@ -22,4 +22,5 @@ test:
   tags:
     - test
   script:
+    - apt-get update && apt-get install ffmpeg libsm6 libxext6 -y
     - uv run --only-group test pytest test

.logging_config.yaml

@@ -1,36 +1,57 @@
 version: 1
 
 custom_levels:
-  OBSERVATION: 25
-  ACTION: 26
+  OBSERVATION: 24
+  ACTION: 25
+  CHAT: 26
   LLM: 9
 
 formatters:
   # Console output
   colored:
-    (): "colorlog.ColoredFormatter"
+    class: colorlog.ColoredFormatter
     format: "{log_color}{asctime}.{msecs:03.0f} | {levelname:11} | {name:70} | {message}"
     style: "{"
     datefmt: "%H:%M:%S"
 
   # User-facing UI (structured JSON)
-  json_experiment:
-    (): "pythonjsonlogger.jsonlogger.JsonFormatter"
+  json:
+    class: pythonjsonlogger.jsonlogger.JsonFormatter
     format: "{name} {levelname} {levelno} {message} {created} {relativeCreated}"
     style: "{"
 
+  # Experiment stream for console and file output, with optional `role` field
+  experiment:
+    class: control_backend.logging.OptionalFieldFormatter
+    format: "%(asctime)s %(levelname)s %(role?)s %(message)s"
+    defaults:
+      role: "-"
+
+filters:
+  # Filter out any log records that have the extra field "partial" set to True, indicating that they
+  #  will be replaced later.
+  partial:
+    (): control_backend.logging.PartialFilter
+
 handlers:
   console:
     class: logging.StreamHandler
     level: DEBUG
     formatter: colored
+    filters: [partial]
     stream: ext://sys.stdout
   ui:
     class: zmq.log.handlers.PUBHandler
     level: LLM
-    formatter: json_experiment
+    formatter: json
+  file:
+    class: control_backend.logging.DatedFileHandler
+    formatter: experiment
+    filters: [partial]
+    # Directory must match config.logging_settings.experiment_log_directory
+    file_prefix: experiment_logs/experiment
 
-# Level of external libraries
+# Level for external libraries
 root:
   level: WARN
   handlers: [console]
@@ -39,3 +60,6 @@ loggers:
   control_backend:
     level: LLM
     handlers: [ui]
+  experiment:  # This name must match config.logging_settings.experiment_logger_name
+    level: DEBUG
+    handlers: [ui, file]

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",
 ]
@@ -48,6 +50,7 @@ test = [
   "pytest-asyncio>=1.2.0",
   "pytest-cov>=7.0.0",
   "pytest-mock>=3.15.1",
+  "python-slugify>=8.0.4",
   "pyyaml>=6.0.3",
   "pyzmq>=27.1.0",
   "soundfile>=0.13.1",

src/control_backend/__init__.py

@@ -0,0 +1,5 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""

src/control_backend/agents/__init__.py

@@ -1 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+-------------------------------------------------------------------------------
+This package contains all agent implementations for the PepperPlus Control Backend.
+"""
+
 from .base import BaseAgent as BaseAgent

src/control_backend/agents/actuation/__init__.py

@@ -1,2 +1,10 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+--------------------------------------------------------------------------------
+Agents responsible for controlling the robot's physical actions, such as speech and gestures.
+"""
+
 from .robot_gesture_agent import RobotGestureAgent as RobotGestureAgent
 from .robot_speech_agent import RobotSpeechAgent as RobotSpeechAgent

src/control_backend/agents/actuation/robot_gesture_agent.py

@@ -1,4 +1,11 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import json
+import logging
 
 import zmq
 import zmq.asyncio as azmq
@@ -8,6 +15,8 @@ from control_backend.core.agent_system import InternalMessage
 from control_backend.core.config import settings
 from control_backend.schemas.ri_message import GestureCommand, RIEndpoint
 
+experiment_logger = logging.getLogger(settings.logging_settings.experiment_logger_name)
+
 
 class RobotGestureAgent(BaseAgent):
     """
@@ -83,6 +92,8 @@ class RobotGestureAgent(BaseAgent):
             self.subsocket.close()
         if self.pubsocket:
             self.pubsocket.close()
+        if self.repsocket:
+            self.repsocket.close()
         await super().stop()
 
     async def handle_message(self, msg: InternalMessage):
@@ -109,6 +120,7 @@ class RobotGestureAgent(BaseAgent):
                         gesture_command.data,
                     )
                     return
+            experiment_logger.action("Gesture: %s", gesture_command.data)
             await self.pubsocket.send_json(gesture_command.model_dump())
         except Exception:
             self.logger.exception("Error processing internal message.")

src/control_backend/agents/actuation/robot_speech_agent.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import json
 
 import zmq

src/control_backend/agents/base.py

@@ -1,9 +1,16 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import logging
+from abc import ABC
 
 from control_backend.core.agent_system import BaseAgent as CoreBaseAgent
 
 
-class BaseAgent(CoreBaseAgent):
+class BaseAgent(CoreBaseAgent, ABC):
     """
     The primary base class for all implementation agents.
 

src/control_backend/agents/bdi/__init__.py

@@ -1,8 +1,14 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+--------------------------------------------------------------------------------
+Agents and utilities for the BDI (Belief-Desire-Intention) reasoning system,
+implementing AgentSpeak(L) logic.
+"""
+
 from control_backend.agents.bdi.bdi_core_agent import BDICoreAgent as BDICoreAgent
 
-from .belief_collector_agent import (
-    BDIBeliefCollectorAgent as BDIBeliefCollectorAgent,
-)
 from .text_belief_extractor_agent import (
     TextBeliefExtractorAgent as TextBeliefExtractorAgent,
 )

src/control_backend/agents/bdi/agentspeak_ast.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
@@ -8,31 +14,78 @@ from enum import StrEnum
 class AstNode(ABC):
     """
     Abstract base class for all elements of an AgentSpeak program.
+
+    This class serves as the foundation for all AgentSpeak abstract syntax tree (AST) nodes.
+    It defines the core interface that all AST nodes must implement to generate AgentSpeak code.
     """
 
     @abstractmethod
     def _to_agentspeak(self) -> str:
         """
         Generates the AgentSpeak code string.
+
+        This method converts the AST node into its corresponding
+        AgentSpeak source code representation.
+
+        :return: The AgentSpeak code string representation of this node.
         """
         pass
 
     def __str__(self) -> str:
+        """
+        Returns the string representation of this AST node.
+
+        This method provides a convenient way to get the AgentSpeak code representation
+        by delegating to the _to_agentspeak method.
+
+        :return: The AgentSpeak code string representation of this node.
+        """
         return self._to_agentspeak()
 
 
 class AstExpression(AstNode, ABC):
     """
     Intermediate class for anything that can be used in a logical expression.
+
+    This class extends AstNode to provide common functionality for all expressions
+    that can be used in logical operations within AgentSpeak programs.
     """
 
     def __and__(self, other: ExprCoalescible) -> AstBinaryOp:
+        """
+        Creates a logical AND operation between this expression and another.
+
+        This method allows for operator overloading of the & operator to create
+        binary logical operations in a more intuitive syntax.
+
+        :param other: The right-hand side expression to combine with this one.
+        :return: A new AstBinaryOp representing the logical AND operation.
+        """
         return AstBinaryOp(self, BinaryOperatorType.AND, _coalesce_expr(other))
 
     def __or__(self, other: ExprCoalescible) -> AstBinaryOp:
+        """
+        Creates a logical OR operation between this expression and another.
+
+        This method allows for operator overloading of the | operator to create
+        binary logical operations in a more intuitive syntax.
+
+        :param other: The right-hand side expression to combine with this one.
+        :return: A new AstBinaryOp representing the logical OR operation.
+        """
         return AstBinaryOp(self, BinaryOperatorType.OR, _coalesce_expr(other))
 
     def __invert__(self) -> AstLogicalExpression:
+        """
+        Creates a logical negation of this expression.
+
+        This method allows for operator overloading of the ~ operator to create
+        negated expressions. If the expression is already a logical expression,
+        it toggles the negation flag. Otherwise, it wraps the expression in a
+        new AstLogicalExpression with negation set to True.
+
+        :return: An AstLogicalExpression representing the negated form of this expression.
+        """
         if isinstance(self, AstLogicalExpression):
             self.negated = not self.negated
             return self
@@ -77,52 +130,128 @@ class AstTerm(AstExpression, ABC):
         return AstBinaryOp(self, BinaryOperatorType.NOT_EQUALS, _coalesce_expr(other))
 
 
-@dataclass
+@dataclass(eq=False)
 class AstAtom(AstTerm):
     """
-    Grounded expression in all lowercase.
+    Represents a grounded atom in AgentSpeak (e.g., lowercase constants).
+
+    Atoms are the simplest form of terms in AgentSpeak, representing concrete,
+    unchanging values. They are typically used as constants in logical expressions.
+
+    :ivar value: The string value of this atom, which will be converted to lowercase
+                 in the AgentSpeak representation.
     """
 
     value: str
 
     def _to_agentspeak(self) -> str:
+        """
+        Converts this atom to its AgentSpeak string representation.
+
+        Atoms are represented in lowercase in AgentSpeak to distinguish them
+        from variables (which are capitalized).
+
+        :return: The lowercase string representation of this atom.
+        """
         return self.value.lower()
 
 
-@dataclass
+@dataclass(eq=False)
 class AstVar(AstTerm):
     """
-    Ungrounded variable expression. First letter capitalized.
+    Represents an ungrounded variable in AgentSpeak (e.g., capitalized names).
+
+    Variables in AgentSpeak are placeholders that can be bound to specific values
+    during execution. They are distinguished from atoms by their capitalization.
+
+    :ivar name: The name of this variable, which will be capitalized in the
+                AgentSpeak representation.
     """
 
     name: str
 
     def _to_agentspeak(self) -> str:
+        """
+        Converts this variable to its AgentSpeak string representation.
+
+        Variables are represented with capitalized names in AgentSpeak to distinguish
+        them from atoms (which are lowercase).
+
+        :return: The capitalized string representation of this variable.
+        """
         return self.name.capitalize()
 
 
-@dataclass
+@dataclass(eq=False)
 class AstNumber(AstTerm):
+    """
+    Represents a numeric constant in AgentSpeak.
+
+    Numeric constants can be either integers or floating-point numbers and are
+    used in logical expressions and comparisons.
+
+    :ivar value: The numeric value of this constant (can be int or float).
+    """
+
     value: int | float
 
     def _to_agentspeak(self) -> str:
+        """
+        Converts this numeric constant to its AgentSpeak string representation.
+
+        :return: The string representation of the numeric value.
+        """
         return str(self.value)
 
 
-@dataclass
+@dataclass(eq=False)
 class AstString(AstTerm):
+    """
+    Represents a string literal in AgentSpeak.
+
+    String literals are used to represent textual data and are enclosed in
+    double quotes in the AgentSpeak representation.
+
+    :ivar value: The string content of this literal.
+    """
+
     value: str
 
     def _to_agentspeak(self) -> str:
+        """
+        Converts this string literal to its AgentSpeak string representation.
+
+        String literals are enclosed in double quotes in AgentSpeak.
+
+        :return: The string literal enclosed in double quotes.
+        """
         return f'"{self.value}"'
 
 
-@dataclass
+@dataclass(eq=False)
 class AstLiteral(AstTerm):
+    """
+    Represents a literal (functor and terms) in AgentSpeak.
+
+    Literals are the fundamental building blocks of AgentSpeak programs, consisting
+    of a functor (predicate name) and an optional list of terms (arguments).
+
+    :ivar functor: The name of the predicate or function.
+    :ivar terms: A list of terms (arguments) for this literal. Defaults to an empty list.
+    """
+
     functor: str
     terms: list[AstTerm] = field(default_factory=list)
 
     def _to_agentspeak(self) -> str:
+        """
+        Converts this literal to its AgentSpeak string representation.
+
+        If the literal has no terms, it returns just the functor name.
+        Otherwise, it returns the functor followed by the terms in parentheses.
+
+        :return: The AgentSpeak string representation of this literal.
+        """
         if not self.terms:
             return self.functor
         args = ", ".join(map(str, self.terms))
@@ -130,6 +259,13 @@ class AstLiteral(AstTerm):
 
 
 class BinaryOperatorType(StrEnum):
+    """
+    Enumeration of binary operator types used in AgentSpeak expressions.
+
+    These operators are used to create binary operations between expressions,
+    including logical operations (AND, OR) and comparison operations.
+    """
+
     AND = "&"
     OR = "|"
     GREATER_THAN = ">"
@@ -142,15 +278,41 @@ class BinaryOperatorType(StrEnum):
 
 @dataclass
 class AstBinaryOp(AstExpression):
+    """
+    Represents a binary logical or relational operation in AgentSpeak.
+
+    Binary operations combine two expressions using a logical or comparison operator.
+    They are used to create complex logical conditions in AgentSpeak programs.
+
+    :ivar left: The left-hand side expression of the operation.
+    :ivar operator: The binary operator type (AND, OR, comparison operators, etc.).
+    :ivar right: The right-hand side expression of the operation.
+    """
+
     left: AstExpression
     operator: BinaryOperatorType
     right: AstExpression
 
     def __post_init__(self):
+        """
+        Post-initialization processing to ensure proper expression types.
+
+        This method wraps the left and right expressions in AstLogicalExpression
+        instances if they aren't already, ensuring consistent handling throughout
+        the AST.
+        """
         self.left = _as_logical(self.left)
         self.right = _as_logical(self.right)
 
     def _to_agentspeak(self) -> str:
+        """
+        Converts this binary operation to its AgentSpeak string representation.
+
+        The method handles proper parenthesization of sub-expressions to maintain
+        correct operator precedence and readability.
+
+        :return: The AgentSpeak string representation of this binary operation.
+        """
         l_str = str(self.left)
         r_str = str(self.right)
 
@@ -167,10 +329,29 @@ class AstBinaryOp(AstExpression):
 
 @dataclass
 class AstLogicalExpression(AstExpression):
+    """
+    Represents a logical expression, potentially negated, in AgentSpeak.
+
+    Logical expressions can be either positive or negated and form the basis
+    of conditions and beliefs in AgentSpeak programs.
+
+    :ivar expression: The underlying expression being evaluated.
+    :ivar negated: Boolean flag indicating whether this expression is negated.
+    """
+
     expression: AstExpression
     negated: bool = False
 
     def _to_agentspeak(self) -> str:
+        """
+        Converts this logical expression to its AgentSpeak string representation.
+
+        If the expression is negated, it prepends 'not ' to the expression string.
+        For complex expressions (binary operations), it adds parentheses when negated
+        to maintain correct logical interpretation.
+
+        :return: The AgentSpeak string representation of this logical expression.
+        """
         expr_str = str(self.expression)
         if isinstance(self.expression, AstBinaryOp) and self.negated:
             expr_str = f"({expr_str})"
@@ -178,65 +359,169 @@ class AstLogicalExpression(AstExpression):
 
 
 def _as_logical(expr: AstExpression) -> AstLogicalExpression:
+    """
+    Converts an expression to a logical expression if it isn't already.
+
+    This helper function ensures that expressions are properly wrapped in
+    AstLogicalExpression instances, which is necessary for consistent handling
+    of logical operations in the AST.
+
+    :param expr: The expression to convert.
+    :return: The expression wrapped in an AstLogicalExpression if it wasn't already.
+    """
     if isinstance(expr, AstLogicalExpression):
         return expr
     return AstLogicalExpression(expr)
 
 
 class StatementType(StrEnum):
+    """
+    Enumeration of statement types that can appear in AgentSpeak plans.
+
+    These statement types define the different kinds of actions and operations
+    that can be performed within the body of an AgentSpeak plan.
+    """
+
     EMPTY = ""
+    """Empty statement (no operation, used when evaluating a plan to true)."""
+
     DO_ACTION = "."
+    """Execute an action defined in Python."""
+
     ACHIEVE_GOAL = "!"
+    """Achieve a goal (add a goal to be accomplished)."""
+
     TEST_GOAL = "?"
+    """Test a goal (check if a goal can be achieved)."""
+
     ADD_BELIEF = "+"
+    """Add a belief to the belief base."""
+
     REMOVE_BELIEF = "-"
+    """Remove a belief from the belief base."""
+
     REPLACE_BELIEF = "-+"
+    """Replace a belief in the belief base."""
 
 
 @dataclass
 class AstStatement(AstNode):
     """
     A statement that can appear inside a plan.
+
+    Statements are the executable units within AgentSpeak plans. They consist
+    of a statement type (defining the operation) and an expression (defining
+    what to operate on).
+
+    :ivar type: The type of statement (action, goal, belief operation, etc.).
+    :ivar expression: The expression that this statement operates on.
     """
 
     type: StatementType
     expression: AstExpression
 
     def _to_agentspeak(self) -> str:
+        """
+        Converts this statement to its AgentSpeak string representation.
+
+        The representation consists of the statement type prefix followed by
+        the expression.
+
+        :return: The AgentSpeak string representation of this statement.
+        """
         return f"{self.type.value}{self.expression}"
 
 
 @dataclass
 class AstRule(AstNode):
+    """
+    Represents an inference rule in AgentSpeak. If there is no condition, it always holds.
+
+    Rules define logical implications in AgentSpeak programs. They consist of a
+    result (conclusion) and an optional condition (premise). When the condition
+    holds, the result is inferred to be true.
+
+    :ivar result: The conclusion or result of this rule.
+    :ivar condition: The premise or condition for this rule (optional).
+    """
+
     result: AstExpression
     condition: AstExpression | None = None
 
     def __post_init__(self):
+        """
+        Post-initialization processing to ensure proper expression types.
+
+        If a condition is provided, this method wraps it in an AstLogicalExpression
+        to ensure consistent handling throughout the AST.
+        """
         if self.condition is not None:
             self.condition = _as_logical(self.condition)
 
     def _to_agentspeak(self) -> str:
+        """
+        Converts this rule to its AgentSpeak string representation.
+
+        If no condition is specified, the rule is represented as a simple fact.
+        If a condition is specified, it's represented as an implication (result :- condition).
+
+        :return: The AgentSpeak string representation of this rule.
+        """
         if not self.condition:
             return f"{self.result}."
         return f"{self.result} :- {self.condition}."
 
 
 class TriggerType(StrEnum):
+    """
+    Enumeration of trigger types for AgentSpeak plans.
+
+    Trigger types define what kind of events can activate an AgentSpeak plan.
+    Currently, the system supports triggers for added beliefs and added goals.
+    """
+
     ADDED_BELIEF = "+"
+    """Trigger when a belief is added to the belief base."""
+
     # REMOVED_BELIEF = "-"  # TODO
     # MODIFIED_BELIEF = "^"  # TODO
+
     ADDED_GOAL = "+!"
+    """Trigger when a goal is added to be achieved."""
+
     # REMOVED_GOAL = "-!"  # TODO
 
 
 @dataclass
 class AstPlan(AstNode):
+    """
+    Represents a plan in AgentSpeak, consisting of a trigger, context, and body.
+
+    Plans define the reactive behavior of agents in AgentSpeak. They specify what
+    actions to take when certain conditions are met (trigger and context).
+
+    :ivar type: The type of trigger that activates this plan.
+    :ivar trigger_literal: The specific event or condition that triggers this plan.
+    :ivar context: A list of conditions that must hold for this plan to be applicable.
+    :ivar body: A list of statements to execute when this plan is triggered.
+    """
+
     type: TriggerType
     trigger_literal: AstExpression
     context: list[AstExpression]
     body: list[AstStatement]
 
     def _to_agentspeak(self) -> str:
+        """
+        Converts this plan to its AgentSpeak string representation.
+
+        The representation follows the standard AgentSpeak plan format:
+        trigger_type + trigger_literal
+        : context_conditions
+        <- body_statements.
+
+        :return: The AgentSpeak string representation of this plan.
+        """
         assert isinstance(self.trigger_literal, AstLiteral)
 
         indent = " " * 6
@@ -260,10 +545,28 @@ class AstPlan(AstNode):
 
 @dataclass
 class AstProgram(AstNode):
+    """
+    Represents a full AgentSpeak program, consisting of rules and plans.
+
+    This is the root node of the AgentSpeak AST, containing all the rules
+    and plans that define the agent's behavior.
+
+    :ivar rules: A list of inference rules in this program.
+    :ivar plans: A list of reactive plans in this program.
+    """
+
     rules: list[AstRule] = field(default_factory=list)
     plans: list[AstPlan] = field(default_factory=list)
 
     def _to_agentspeak(self) -> str:
+        """
+        Converts this program to its AgentSpeak string representation.
+
+        The representation consists of all rules followed by all plans,
+        separated by blank lines for readability.
+
+        :return: The complete AgentSpeak source code for this program.
+        """
         lines = []
         lines.extend(map(str, self.rules))
 

src/control_backend/agents/bdi/agentspeak_generator.py

@@ -1,11 +1,19 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from functools import singledispatchmethod
 
 from slugify import slugify
 
 from control_backend.agents.bdi.agentspeak_ast import (
+    AstAtom,
     AstBinaryOp,
     AstExpression,
     AstLiteral,
+    AstNumber,
     AstPlan,
     AstProgram,
     AstRule,
@@ -16,9 +24,13 @@ from control_backend.agents.bdi.agentspeak_ast import (
     StatementType,
     TriggerType,
 )
+from control_backend.core.config import settings
 from control_backend.schemas.program import (
+    BaseGoal,
     BasicNorm,
     ConditionalNorm,
+    EmotionBelief,
+    FaceBelief,
     GestureAction,
     Goal,
     InferredBelief,
@@ -37,12 +49,45 @@ from control_backend.schemas.program import (
 
 
 class AgentSpeakGenerator:
+    """
+    Generator class that translates a high-level :class:`~control_backend.schemas.program.Program`
+    into AgentSpeak(L) source code.
+
+    It handles the conversion of phases, norms, goals, and triggers into AgentSpeak rules and plans,
+    ensuring the robot follows the defined behavioral logic.
+
+    The generator follows a systematic approach:
+    1. Sets up initial phase and cycle notification rules
+    2. Adds keyword inference capabilities for natural language processing
+    3. Creates default plans for common operations
+    4. Processes each phase with its norms, goals, and triggers
+    5. Adds fallback plans for robust execution
+
+    :ivar _asp: The internal AgentSpeak program representation being built.
+    """
+
     _asp: AstProgram
 
     def generate(self, program: Program) -> str:
+        """
+        Translates a Program object into an AgentSpeak source string.
+
+        This is the main entry point for the code generation process. It initializes
+        the AgentSpeak program structure and orchestrates the conversion of all
+        program elements into their AgentSpeak representations.
+
+        :param program: The behavior program to translate.
+        :return: The generated AgentSpeak code as a string.
+        """
         self._asp = AstProgram()
 
-        self._asp.rules.append(AstRule(self._astify(program.phases[0])))
+        if program.phases:
+            self._asp.rules.append(AstRule(self._astify(program.phases[0])))
+        else:
+            self._asp.rules.append(AstRule(AstLiteral("phase", [AstString("end")])))
+
+        self._asp.rules.append(AstRule(AstLiteral("!notify_cycle")))
+
         self._add_keyword_inference()
         self._add_default_plans()
 
@@ -53,6 +98,18 @@ class AgentSpeakGenerator:
         return str(self._asp)
 
     def _add_keyword_inference(self) -> None:
+        """
+        Adds inference rules for keyword detection in user messages.
+
+        This method creates rules that allow the system to detect when specific
+        keywords are mentioned in user messages. It uses string operations to
+        check if a keyword is a substring of the user's message.
+
+        The generated rule has the form:
+        keyword_said(Keyword) :- user_said(Message) & .substring(Keyword, Message, Pos) & Pos >= 0
+
+        This enables the system to trigger behaviors based on keyword detection.
+        """
         keyword = AstVar("Keyword")
         message = AstVar("Message")
         position = AstVar("Pos")
@@ -67,11 +124,32 @@ class AgentSpeakGenerator:
         )
 
     def _add_default_plans(self):
+        """
+        Adds default plans for common operations.
+
+        This method sets up the standard plans that handle fundamental operations
+        like replying with goals, simple speech actions, general replies, and
+        cycle notifications. These plans provide the basic infrastructure for
+        the agent's reactive behavior.
+        """
         self._add_reply_with_goal_plan()
         self._add_say_plan()
         self._add_reply_plan()
+        self._add_notify_cycle_plan()
 
     def _add_reply_with_goal_plan(self):
+        """
+        Adds a plan for replying with a specific conversational goal.
+
+        This plan handles the case where the agent needs to respond to user input
+        while pursuing a specific conversational goal. It:
+        1. Marks that the agent has responded this turn
+        2. Gathers all active norms
+        3. Generates a reply that considers both the user message and the goal
+
+        Trigger: +!reply_with_goal(Goal)
+        Context: user_said(Message)
+        """
         self._asp.plans.append(
             AstPlan(
                 TriggerType.ADDED_GOAL,
@@ -97,6 +175,17 @@ class AgentSpeakGenerator:
         )
 
     def _add_say_plan(self):
+        """
+        Adds a plan for simple speech actions.
+
+        This plan handles direct speech actions where the agent needs to say
+        a specific text. It:
+        1. Marks that the agent has responded this turn
+        2. Executes the speech action
+
+        Trigger: +!say(Text)
+        Context: None (can be executed anytime)
+        """
         self._asp.plans.append(
             AstPlan(
                 TriggerType.ADDED_GOAL,
@@ -110,6 +199,18 @@ class AgentSpeakGenerator:
         )
 
     def _add_reply_plan(self):
+        """
+        Adds a plan for general reply actions.
+
+        This plan handles general reply actions where the agent needs to respond
+        to user input without a specific conversational goal. It:
+        1. Marks that the agent has responded this turn
+        2. Gathers all active norms
+        3. Generates a reply based on the user message and norms
+
+        Trigger: +!reply
+        Context: user_said(Message)
+        """
         self._asp.plans.append(
             AstPlan(
                 TriggerType.ADDED_GOAL,
@@ -132,7 +233,53 @@ class AgentSpeakGenerator:
             )
         )
 
+    def _add_notify_cycle_plan(self):
+        """
+        Adds a plan for cycle notification.
+
+        This plan handles the periodic notification cycle that allows the system
+        to monitor and report on the current state. It:
+        1. Gathers all active norms
+        2. Notifies the system about the current norms
+        3. Waits briefly to allow processing
+        4. Recursively triggers the next cycle
+
+        Trigger: +!notify_cycle
+        Context: None (can be executed anytime)
+        """
+        self._asp.plans.append(
+            AstPlan(
+                TriggerType.ADDED_GOAL,
+                AstLiteral("notify_cycle"),
+                [],
+                [
+                    AstStatement(
+                        StatementType.DO_ACTION,
+                        AstLiteral(
+                            "findall",
+                            [AstVar("Norm"), AstLiteral("norm", [AstVar("Norm")]), AstVar("Norms")],
+                        ),
+                    ),
+                    AstStatement(
+                        StatementType.DO_ACTION, AstLiteral("notify_norms", [AstVar("Norms")])
+                    ),
+                    AstStatement(StatementType.DO_ACTION, AstLiteral("wait", [AstNumber(100)])),
+                    AstStatement(StatementType.ACHIEVE_GOAL, AstLiteral("notify_cycle")),
+                ],
+            )
+        )
+
     def _process_phases(self, phases: list[Phase]) -> None:
+        """
+        Processes all phases in the program and their transitions.
+
+        This method iterates through each phase and:
+        1. Processes the current phase (norms, goals, triggers)
+        2. Sets up transitions between phases
+        3. Adds special handling for the end phase
+
+        :param phases: The list of phases to process.
+        """
         for curr_phase, next_phase in zip([None] + phases, phases + [None], strict=True):
             if curr_phase:
                 self._process_phase(curr_phase)
@@ -146,13 +293,26 @@ class AgentSpeakGenerator:
                 trigger_literal=AstLiteral("user_said", [AstVar("Message")]),
                 context=[AstLiteral("phase", [AstString("end")])],
                 body=[
-                    AstStatement(StatementType.DO_ACTION, AstLiteral("notify_user_said")),
+                    AstStatement(
+                        StatementType.DO_ACTION, AstLiteral("notify_user_said", [AstVar("Message")])
+                    ),
                     AstStatement(StatementType.ACHIEVE_GOAL, AstLiteral("reply")),
                 ],
             )
         )
 
     def _process_phase(self, phase: Phase) -> None:
+        """
+        Processes a single phase, including its norms, goals, and triggers.
+
+        This method handles the complete processing of a phase by:
+        1. Processing all norms in the phase
+        2. Setting up the default execution loop for the phase
+        3. Processing all goals in sequence
+        4. Processing all triggers for reactive behavior
+
+        :param phase: The phase to process.
+        """
         for norm in phase.norms:
             self._process_norm(norm, phase)
 
@@ -167,6 +327,21 @@ class AgentSpeakGenerator:
             self._process_trigger(trigger, phase)
 
     def _add_phase_transition(self, from_phase: Phase | None, to_phase: Phase | None) -> None:
+        """
+        Adds plans for transitioning between phases.
+
+        This method creates two plans for each phase transition:
+        1. A check plan that verifies if transition conditions are met
+        2. A force plan that actually performs the transition (can be forced externally)
+
+        The transition involves:
+        - Notifying the system about the phase change
+        - Removing the current phase belief
+        - Adding the next phase belief
+
+        :param from_phase: The phase being transitioned from (or None for initial setup).
+        :param to_phase: The phase being transitioned to (or None for end phase).
+        """
         if from_phase is None:
             return
         from_phase_ast = self._astify(from_phase)
@@ -174,30 +349,14 @@ class AgentSpeakGenerator:
             self._astify(to_phase) if to_phase else AstLiteral("phase", [AstString("end")])
         )
 
-        context = [from_phase_ast]
+        check_context = [from_phase_ast]
         if from_phase:
             for goal in from_phase.goals:
-                context.append(self._astify(goal, achieved=True))
+                check_context.append(self._astify(goal, achieved=True))
+
+        force_context = [from_phase_ast]
 
         body = [
-            AstStatement(StatementType.REMOVE_BELIEF, from_phase_ast),
-            AstStatement(StatementType.ADD_BELIEF, to_phase_ast),
-        ]
-
-        # if from_phase:
-        #     body.extend(
-        #         [
-        #             AstStatement(
-        #                 StatementType.TEST_GOAL, AstLiteral("user_said", [AstVar("Message")])
-        #             ),
-        #             AstStatement(
-        #                 StatementType.REPLACE_BELIEF, AstLiteral("user_said", [AstVar("Message")])
-        #             ),
-        #         ]
-        #     )
-
-        # Notify outside world about transition
-        body.append(
             AstStatement(
                 StatementType.DO_ACTION,
                 AstLiteral(
@@ -207,19 +366,51 @@ class AgentSpeakGenerator:
                         AstString(str(to_phase.id) if to_phase else "end"),
                     ],
                 ),
+            ),
+            AstStatement(StatementType.REMOVE_BELIEF, from_phase_ast),
+            AstStatement(StatementType.ADD_BELIEF, to_phase_ast),
+        ]
+
+        # Check
+        self._asp.plans.append(
+            AstPlan(
+                TriggerType.ADDED_GOAL,
+                AstLiteral("transition_phase"),
+                check_context,
+                [
+                    AstStatement(StatementType.ACHIEVE_GOAL, AstLiteral("force_transition_phase")),
+                ],
             )
         )
 
+        # Force
         self._asp.plans.append(
-            AstPlan(TriggerType.ADDED_GOAL, AstLiteral("transition_phase"), context, body)
+            AstPlan(
+                TriggerType.ADDED_GOAL, AstLiteral("force_transition_phase"), force_context, body
+            )
         )
 
     def _process_norm(self, norm: Norm, phase: Phase) -> None:
+        """
+        Processes a norm and adds it as an inference rule.
+
+        This method converts norms into AgentSpeak rules that define when
+        the norm should be active. It handles both basic norms (always active
+        in their phase) and conditional norms (active only when their condition
+        is met).
+
+        :param norm: The norm to process.
+        :param phase: The phase this norm belongs to.
+        """
         rule: AstRule | None = None
 
         match norm:
             case ConditionalNorm(condition=cond):
-                rule = AstRule(self._astify(norm), self._astify(phase) & self._astify(cond))
+                rule = AstRule(
+                    self._astify(norm),
+                    self._astify(phase) & self._astify(cond)
+                    | AstAtom(f"force_{self.slugify(norm)}"),
+                )
             case BasicNorm():
                 rule = AstRule(self._astify(norm), self._astify(phase))
 
@@ -229,6 +420,18 @@ class AgentSpeakGenerator:
         self._asp.rules.append(rule)
 
     def _add_default_loop(self, phase: Phase) -> None:
+        """
+        Adds the default execution loop for a phase.
+
+        This method creates the main reactive loop that runs when the agent
+        receives user input during a phase. The loop:
+        1. Notifies the system about the user input
+        2. Resets the response tracking
+        3. Executes all phase goals
+        4. Attempts phase transition
+
+        :param phase: The phase to create the loop for.
+        """
         actions = []
 
         actions.append(
@@ -237,7 +440,6 @@ class AgentSpeakGenerator:
             )
         )
         actions.append(AstStatement(StatementType.REMOVE_BELIEF, AstLiteral("responded_this_turn")))
-        actions.append(AstStatement(StatementType.ACHIEVE_GOAL, AstLiteral("check_triggers")))
 
         for goal in phase.goals:
             actions.append(AstStatement(StatementType.ACHIEVE_GOAL, self._astify(goal)))
@@ -261,6 +463,22 @@ class AgentSpeakGenerator:
         continues_response: bool = False,
         main_goal: bool = False,
     ) -> None:
+        """
+        Processes a goal and creates plans for achieving it.
+
+        This method creates two plans for each goal:
+        1. A main plan that executes the goal's steps when conditions are met
+        2. A fallback plan that provides a default empty implementation (prevents crashes)
+
+        The method also recursively processes any subgoals contained within
+        the goal's plan.
+
+        :param goal: The goal to process.
+        :param phase: The phase this goal belongs to.
+        :param previous_goal: The previous goal in sequence (for dependency tracking).
+        :param continues_response: Whether this goal continues an existing response.
+        :param main_goal: Whether this is a main goal (for UI notification purposes).
+        """
         context: list[AstExpression] = [self._astify(phase)]
         context.append(~self._astify(goal, achieved=True))
         if previous_goal and previous_goal.can_fail:
@@ -303,14 +521,39 @@ class AgentSpeakGenerator:
             prev_goal = subgoal
 
     def _step_to_statement(self, step: PlanElement) -> AstStatement:
+        """
+        Converts a plan step to an AgentSpeak statement.
+
+        This method transforms different types of plan elements into their
+        corresponding AgentSpeak statements. Goals and speech-related actions
+        become achieve-goal statements, while gesture actions become do-action
+        statements.
+
+        :param step: The plan element to convert.
+        :return: The corresponding AgentSpeak statement.
+        """
         match step:
+            # Note that SpeechAction gets included in the ACHIEVE_GOAL, since it's a goal internally
             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))
 
-    # TODO: separate handling of keyword and others
     def _process_trigger(self, trigger: Trigger, phase: Phase) -> None:
+        """
+        Processes a trigger and creates plans for its execution.
+
+        This method creates plans that execute when trigger conditions are met.
+        It handles both automatic triggering (when conditions are detected) and
+        manual forcing (from UI). The trigger execution includes:
+        1. Notifying the system about trigger start
+        2. Executing all trigger steps
+        3. Waiting briefly for UI display
+        4. Notifying the system about trigger end
+
+        :param trigger: The trigger to process.
+        :param phase: The phase this trigger belongs to.
+        """
         body = []
         subgoals = []
 
@@ -325,6 +568,15 @@ class AgentSpeakGenerator:
             if isinstance(step, Goal):
                 step.can_fail = False  # triggers are continuous sequence
                 subgoals.append(step)
+
+        # Arbitrary wait for UI to display nicely
+        body.append(
+            AstStatement(
+                StatementType.DO_ACTION,
+                AstLiteral("wait", [AstNumber(settings.behaviour_settings.trigger_time_to_wait)]),
+            )
+        )
+
         body.append(
             AstStatement(
                 StatementType.DO_ACTION,
@@ -348,6 +600,18 @@ class AgentSpeakGenerator:
             self._process_goal(subgoal, phase, continues_response=True)
 
     def _add_fallbacks(self):
+        """
+        Adds fallback plans for robust execution, preventing crashes.
+
+        This method creates fallback plans that provide default empty implementations
+        for key goals. These fallbacks ensure that the system can continue execution
+        even when no specific plans are applicable, preventing crashes.
+
+        The fallbacks are created for:
+        - check_triggers: When no triggers are applicable
+        - transition_phase: When phase transition conditions aren't met
+        - force_transition_phase: When forced transitions aren't possible
+        """
         # Trigger fallback
         self._asp.plans.append(
             AstPlan(
@@ -368,20 +632,77 @@ class AgentSpeakGenerator:
             )
         )
 
+        # Force phase transition fallback
+        self._asp.plans.append(
+            AstPlan(
+                TriggerType.ADDED_GOAL,
+                AstLiteral("force_transition_phase"),
+                [],
+                [AstStatement(StatementType.EMPTY, AstLiteral("true"))],
+            )
+        )
+
     @singledispatchmethod
     def _astify(self, element: ProgramElement) -> AstExpression:
+        """
+        Converts program elements to AgentSpeak expressions (base method).
+
+        This is the base method for the singledispatch mechanism that handles
+        conversion of different program element types to their AgentSpeak
+        representations. Specific implementations are provided for each
+        element type through registered methods.
+
+        :param element: The program element to convert.
+        :return: The corresponding AgentSpeak expression.
+        :raises NotImplementedError: If no specific implementation exists for the element type.
+        """
         raise NotImplementedError(f"Cannot convert element {element} to an AgentSpeak expression.")
 
     @_astify.register
     def _(self, kwb: KeywordBelief) -> AstExpression:
+        """
+        Converts a KeywordBelief to an AgentSpeak expression.
+
+        Keyword beliefs are converted to keyword_said literals that check
+        if the keyword was mentioned in user input.
+
+        :param kwb: The KeywordBelief to convert.
+        :return: An AstLiteral representing the keyword detection.
+        """
         return AstLiteral("keyword_said", [AstString(kwb.keyword)])
 
     @_astify.register
     def _(self, sb: SemanticBelief) -> AstExpression:
+        """
+        Converts a SemanticBelief to an AgentSpeak expression.
+
+        Semantic beliefs are converted to literals using their slugified names,
+        which are used for LLM-based belief evaluation.
+
+        :param sb: The SemanticBelief to convert.
+        :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, eb: FaceBelief) -> AstExpression:
+        return AstLiteral("face_present")
+
     @_astify.register
     def _(self, ib: InferredBelief) -> AstExpression:
+        """
+        Converts an InferredBelief to an AgentSpeak expression.
+
+        Inferred beliefs are converted to binary operations that combine
+        their left and right operands using the appropriate logical operator.
+
+        :param ib: The InferredBelief to convert.
+        :return: An AstBinaryOp representing the logical combination.
+        """
         return AstBinaryOp(
             self._astify(ib.left),
             BinaryOperatorType.AND if ib.operator == LogicalOperator.AND else BinaryOperatorType.OR,
@@ -390,54 +711,187 @@ class AgentSpeakGenerator:
 
     @_astify.register
     def _(self, norm: Norm) -> AstExpression:
+        """
+        Converts a Norm to an AgentSpeak expression.
+
+        Norms are converted to literals with either 'norm' or 'critical_norm'
+        functors depending on their critical flag, with the norm text as an argument.
+
+        Note that currently, critical norms are not yet functionally supported. They are possible
+        to astify for future use.
+
+        :param norm: The Norm to convert.
+        :return: An AstLiteral representing the norm.
+        """
         functor = "critical_norm" if norm.critical else "norm"
         return AstLiteral(functor, [AstString(norm.norm)])
 
     @_astify.register
     def _(self, phase: Phase) -> AstExpression:
+        """
+        Converts a Phase to an AgentSpeak expression.
+
+        Phases are converted to phase literals with their unique identifier
+        as an argument, which is used for phase tracking and transitions.
+
+        :param phase: The Phase to convert.
+        :return: An AstLiteral representing the phase.
+        """
         return AstLiteral("phase", [AstString(str(phase.id))])
 
     @_astify.register
     def _(self, goal: Goal, achieved: bool = False) -> AstExpression:
+        """
+        Converts a Goal to an AgentSpeak expression.
+
+        Goals are converted to literals using their slugified names. If the
+        achieved parameter is True, the literal is prefixed with 'achieved_'.
+
+        :param goal: The Goal to convert.
+        :param achieved: Whether to represent this as an achieved goal.
+        :return: An AstLiteral representing the goal.
+        """
         return AstLiteral(f"{'achieved_' if achieved else ''}{self._slugify_str(goal.name)}")
 
     @_astify.register
     def _(self, trigger: Trigger) -> AstExpression:
+        """
+        Converts a Trigger to an AgentSpeak expression.
+
+        Triggers are converted to literals using their slugified names,
+        which are used to identify and execute trigger plans.
+
+        :param trigger: The Trigger to convert.
+        :return: An AstLiteral representing the trigger.
+        """
         return AstLiteral(self.slugify(trigger))
 
     @_astify.register
     def _(self, sa: SpeechAction) -> AstExpression:
+        """
+        Converts a SpeechAction to an AgentSpeak expression.
+
+        Speech actions are converted to say literals with the text content
+        as an argument, which are used for direct speech output.
+
+        :param sa: The SpeechAction to convert.
+        :return: An AstLiteral representing the speech action.
+        """
         return AstLiteral("say", [AstString(sa.text)])
 
     @_astify.register
     def _(self, ga: GestureAction) -> AstExpression:
+        """
+        Converts a GestureAction to an AgentSpeak expression.
+
+        Gesture actions are converted to gesture literals with the gesture
+        type and name as arguments, which are used for physical robot gestures.
+
+        :param ga: The GestureAction to convert.
+        :return: An AstLiteral representing the gesture action.
+        """
         gesture = ga.gesture
         return AstLiteral("gesture", [AstString(gesture.type), AstString(gesture.name)])
 
     @_astify.register
     def _(self, la: LLMAction) -> AstExpression:
+        """
+        Converts an LLMAction to an AgentSpeak expression.
+
+        LLM actions are converted to reply_with_goal literals with the
+        conversational goal as an argument, which are used for LLM-generated
+        responses guided by specific goals.
+
+        :param la: The LLMAction to convert.
+        :return: An AstLiteral representing the LLM action.
+        """
         return AstLiteral("reply_with_goal", [AstString(la.goal)])
 
     @singledispatchmethod
     @staticmethod
     def slugify(element: ProgramElement) -> str:
+        """
+        Converts program elements to slugs (base method).
+
+        This is the base method for the singledispatch mechanism that handles
+        conversion of different program element types to their slug representations.
+        Specific implementations are provided for each element type through
+        registered methods.
+
+        Slugs are used outside of AgentSpeak, mostly for identifying what to send to the AgentSpeak
+        program as beliefs.
+
+        :param element: The program element to convert to a slug.
+        :return: The slug string representation.
+        :raises NotImplementedError: If no specific implementation exists for the element type.
+        """
         raise NotImplementedError(f"Cannot convert element {element} to a slug.")
 
+    @slugify.register
+    @staticmethod
+    def _(n: Norm) -> str:
+        """
+        Converts a Norm to a slug.
+
+        Norms are converted to slugs with the 'norm_' prefix followed by
+        the slugified norm text.
+
+        :param n: The Norm to convert.
+        :return: The slug string representation.
+        """
+        return f"norm_{AgentSpeakGenerator._slugify_str(n.norm)}"
+
     @slugify.register
     @staticmethod
     def _(sb: SemanticBelief) -> str:
+        """
+        Converts a SemanticBelief to a slug.
+
+        Semantic beliefs are converted to slugs with the 'semantic_' prefix
+        followed by the slugified belief name.
+
+        :param sb: The SemanticBelief to convert.
+        :return: The slug string representation.
+        """
         return f"semantic_{AgentSpeakGenerator._slugify_str(sb.name)}"
 
     @slugify.register
     @staticmethod
-    def _(g: Goal) -> str:
+    def _(g: BaseGoal) -> str:
+        """
+        Converts a BaseGoal to a slug.
+
+        Goals are converted to slugs using their slugified names directly.
+
+        :param g: The BaseGoal to convert.
+        :return: The slug string representation.
+        """
         return AgentSpeakGenerator._slugify_str(g.name)
 
     @slugify.register
     @staticmethod
-    def _(t: Trigger):
+    def _(t: Trigger) -> str:
+        """
+        Converts a Trigger to a slug.
+
+        Triggers are converted to slugs with the 'trigger_' prefix followed by
+        the slugified trigger name.
+
+        :param t: The Trigger to convert.
+        :return: The slug string representation.
+        """
         return f"trigger_{AgentSpeakGenerator._slugify_str(t.name)}"
 
     @staticmethod
     def _slugify_str(text: str) -> str:
+        """
+        Converts a text string to a slug.
+
+        This helper method converts arbitrary text to a URL-friendly slug format
+        by converting to lowercase, removing special characters, and replacing
+        spaces with underscores. It also removes common stopwords.
+
+        :param text: The text string to convert.
+        :return: The slugified string.
+        """
         return slugify(text, separator="_", stopwords=["a", "an", "the", "we", "you", "I"])

src/control_backend/agents/bdi/asl_ast.py

@@ -1,203 +0,0 @@
-import typing
-from dataclasses import dataclass, field
-
-# --- Types ---
-
-
-@dataclass
-class BeliefLiteral:
-    """
-    Represents a literal or atom.
-    Example: phase(1), user_said("hello"), ~started
-    """
-
-    functor: str
-    args: list[str] = field(default_factory=list)
-    negated: bool = False
-
-    def __str__(self):
-        # In ASL, 'not' is usually for closed-world assumption (prolog style),
-        # '~' is for explicit negation in beliefs.
-        # For simplicity in behavior trees, we often use 'not' for conditions.
-        prefix = "not " if self.negated else ""
-        if not self.args:
-            return f"{prefix}{self.functor}"
-
-        # Clean args to ensure strings are quoted if they look like strings,
-        # but usually the converter handles the quoting of string literals.
-        args_str = ", ".join(self.args)
-        return f"{prefix}{self.functor}({args_str})"
-
-
-@dataclass
-class GoalLiteral:
-    name: str
-
-    def __str__(self):
-        return f"!{self.name}"
-
-
-@dataclass
-class ActionLiteral:
-    """
-    Represents a step in a plan body.
-    Example: .say("Hello") or !achieve_goal
-    """
-
-    code: str
-
-    def __str__(self):
-        return self.code
-
-
-@dataclass
-class BinaryOp:
-    """
-    Represents logical operations.
-    Example: (A & B) | C
-    """
-
-    left: "Expression | str"
-    operator: typing.Literal["&", "|"]
-    right: "Expression | str"
-
-    def __str__(self):
-        l_str = str(self.left)
-        r_str = str(self.right)
-
-        if isinstance(self.left, BinaryOp):
-            l_str = f"({l_str})"
-        if isinstance(self.right, BinaryOp):
-            r_str = f"({r_str})"
-
-        return f"{l_str} {self.operator} {r_str}"
-
-
-Literal = BeliefLiteral | GoalLiteral | ActionLiteral
-Expression = Literal | BinaryOp | str
-
-
-@dataclass
-class Rule:
-    """
-    Represents an inference rule.
-    Example: head :- body.
-    """
-
-    head: Expression
-    body: Expression | None = None
-
-    def __str__(self):
-        if not self.body:
-            return f"{self.head}."
-        return f"{self.head} :- {self.body}."
-
-
-@dataclass
-class PersistentRule:
-    """
-    Represents an inference rule, where the inferred belief is persistent when formed.
-    """
-
-    head: Expression
-    body: Expression
-
-    def __str__(self):
-        if not self.body:
-            raise Exception("Rule without body should not be persistent.")
-
-        lines = []
-
-        if isinstance(self.body, BinaryOp):
-            lines.append(f"+{self.body.left}")
-            if self.body.operator == "&":
-                lines.append(f"  :   {self.body.right}")
-            lines.append(f"  <-  +{self.head}.")
-            if self.body.operator == "|":
-                lines.append(f"+{self.body.right}")
-                lines.append(f"  <-  +{self.head}.")
-
-        return "\n".join(lines)
-
-
-@dataclass
-class Plan:
-    """
-    Represents a plan.
-    Syntax: +trigger : context <- body.
-    """
-
-    trigger: BeliefLiteral | GoalLiteral
-    context: list[Expression] = field(default_factory=list)
-    body: list[ActionLiteral] = field(default_factory=list)
-
-    def __str__(self):
-        # Indentation settings
-        INDENT = "      "
-        ARROW = "\n  <-  "
-        COLON = "\n  :   "
-
-        # Build Header
-        header = f"+{self.trigger}"
-        if self.context:
-            ctx_str = f" &\n{INDENT}".join(str(c) for c in self.context)
-            header += f"{COLON}{ctx_str}"
-
-        # Case 1: Empty body
-        if not self.body:
-            return f"{header}."
-
-        # Case 2: Short body (optional optimization, keeping it uniform usually better)
-        header += ARROW
-
-        lines = []
-        # We start the first action on the same line or next line.
-        # Let's put it on the next line for readability if there are multiple.
-
-        if len(self.body) == 1:
-            return f"{header}{self.body[0]}."
-
-        # First item
-        lines.append(f"{header}{self.body[0]};")
-        # Middle items
-        for item in self.body[1:-1]:
-            lines.append(f"{INDENT}{item};")
-        # Last item
-        lines.append(f"{INDENT}{self.body[-1]}.")
-
-        return "\n".join(lines)
-
-
-@dataclass
-class AgentSpeakFile:
-    """
-    Root element representing the entire generated file.
-    """
-
-    initial_beliefs: list[Rule] = field(default_factory=list)
-    inference_rules: list[Rule | PersistentRule] = field(default_factory=list)
-    plans: list[Plan] = field(default_factory=list)
-
-    def __str__(self):
-        sections = []
-
-        if self.initial_beliefs:
-            sections.append("// --- Initial Beliefs & Facts ---")
-            sections.extend(str(rule) for rule in self.initial_beliefs)
-            sections.append("")
-
-        if self.inference_rules:
-            sections.append("// --- Inference Rules ---")
-            sections.extend(str(rule) for rule in self.inference_rules if isinstance(rule, Rule))
-            sections.append("")
-            sections.extend(
-                str(rule) for rule in self.inference_rules if isinstance(rule, PersistentRule)
-            )
-            sections.append("")
-
-        if self.plans:
-            sections.append("// --- Plans ---")
-            # Separate plans by a newline for readability
-            sections.extend(str(plan) + "\n" for plan in self.plans)
-
-        return "\n".join(sections)

src/control_backend/agents/bdi/asl_gen.py

@@ -1,425 +0,0 @@
-import asyncio
-import time
-from functools import singledispatchmethod
-
-from slugify import slugify
-
-from control_backend.agents.bdi import BDICoreAgent
-from control_backend.agents.bdi.asl_ast import (
-    ActionLiteral,
-    AgentSpeakFile,
-    BeliefLiteral,
-    BinaryOp,
-    Expression,
-    GoalLiteral,
-    PersistentRule,
-    Plan,
-    Rule,
-)
-from control_backend.agents.bdi.bdi_program_manager import test_program
-from control_backend.schemas.program import (
-    BasicBelief,
-    Belief,
-    ConditionalNorm,
-    GestureAction,
-    Goal,
-    InferredBelief,
-    KeywordBelief,
-    LLMAction,
-    LogicalOperator,
-    Phase,
-    Program,
-    ProgramElement,
-    SemanticBelief,
-    SpeechAction,
-)
-
-
-async def do_things():
-    res = input("Wanna generate")
-    if res == "y":
-        program = AgentSpeakGenerator().generate(test_program)
-        filename = f"{int(time.time())}.asl"
-        with open(filename, "w") as f:
-            f.write(program)
-    else:
-        # filename = "0test.asl"
-        filename = "1766062491.asl"
-    bdi_agent = BDICoreAgent("BDICoreAgent", filename)
-    flag = asyncio.Event()
-    await bdi_agent.start()
-    await flag.wait()
-
-
-def do_other_things():
-    print(AgentSpeakGenerator().generate(test_program))
-
-
-class AgentSpeakGenerator:
-    """
-    Converts a Pydantic Program behavior model into an AgentSpeak(L) AST,
-    then renders it to a string.
-    """
-
-    def generate(self, program: Program) -> str:
-        asl = AgentSpeakFile()
-
-        self._generate_startup(program, asl)
-
-        for i, phase in enumerate(program.phases):
-            next_phase = program.phases[i + 1] if i < len(program.phases) - 1 else None
-
-            self._generate_phase_flow(phase, next_phase, asl)
-
-            self._generate_norms(phase, asl)
-
-            self._generate_goals(phase, asl)
-
-            self._generate_triggers(phase, asl)
-
-        self._generate_fallbacks(program, asl)
-
-        return str(asl)
-
-    # --- Section: Startup & Phase Management ---
-
-    def _generate_startup(self, program: Program, asl: AgentSpeakFile):
-        if not program.phases:
-            return
-
-        # Initial belief: phase(start).
-        asl.initial_beliefs.append(Rule(head=BeliefLiteral("phase", ['"start"'])))
-
-        # Startup plan: +started : phase(start) <- -phase(start); +phase(first_id).
-        asl.plans.append(
-            Plan(
-                trigger=BeliefLiteral("started"),
-                context=[BeliefLiteral("phase", ['"start"'])],
-                body=[
-                    ActionLiteral('-phase("start")'),
-                    ActionLiteral(f'+phase("{program.phases[0].id}")'),
-                ],
-            )
-        )
-
-        # Initial plans:
-        asl.plans.append(
-            Plan(
-                trigger=GoalLiteral("generate_response_with_goal(Goal)"),
-                context=[BeliefLiteral("user_said", ["Message"])],
-                body=[
-                    ActionLiteral("+responded_this_turn"),
-                    ActionLiteral(".findall(Norm, norm(Norm), Norms)"),
-                    ActionLiteral(".reply_with_goal(Message, Norms, Goal)"),
-                ],
-            )
-        )
-
-    def _generate_phase_flow(self, phase: Phase, next_phase: Phase | None, asl: AgentSpeakFile):
-        """Generates the main loop listener and the transition logic for this phase."""
-
-        # +user_said(Message) : phase(ID) <- !goal1; !goal2; !transition_phase.
-        goal_actions = [ActionLiteral("-responded_this_turn")]
-        goal_actions += [
-            ActionLiteral(f"!check_{self._slugify_str(keyword)}")
-            for keyword in self._get_keyword_conditionals(phase)
-        ]
-        goal_actions += [ActionLiteral(f"!{self._slugify(g)}") for g in phase.goals]
-        goal_actions.append(ActionLiteral("!transition_phase"))
-
-        asl.plans.append(
-            Plan(
-                trigger=BeliefLiteral("user_said", ["Message"]),
-                context=[BeliefLiteral("phase", [f'"{phase.id}"'])],
-                body=goal_actions,
-            )
-        )
-
-        # +!transition_phase : phase(ID) <- -phase(ID); +(NEXT_ID).
-        next_id = str(next_phase.id) if next_phase else "end"
-
-        transition_context = [BeliefLiteral("phase", [f'"{phase.id}"'])]
-        if phase.goals:
-            transition_context.append(BeliefLiteral(f"achieved_{self._slugify(phase.goals[-1])}"))
-
-        asl.plans.append(
-            Plan(
-                trigger=GoalLiteral("transition_phase"),
-                context=transition_context,
-                body=[
-                    ActionLiteral(f'-phase("{phase.id}")'),
-                    ActionLiteral(f'+phase("{next_id}")'),
-                    ActionLiteral("user_said(Anything)"),
-                    ActionLiteral("-+user_said(Anything)"),
-                ],
-            )
-        )
-
-    def _get_keyword_conditionals(self, phase: Phase) -> list[str]:
-        res = []
-        for belief in self._extract_basic_beliefs_from_phase(phase):
-            if isinstance(belief, KeywordBelief):
-                res.append(belief.keyword)
-
-        return res
-
-    # --- Section: Norms & Beliefs ---
-
-    def _generate_norms(self, phase: Phase, asl: AgentSpeakFile):
-        for norm in phase.norms:
-            norm_slug = f'"{norm.norm}"'
-            head = BeliefLiteral("norm", [norm_slug])
-
-            # Base context is the phase
-            phase_lit = BeliefLiteral("phase", [f'"{phase.id}"'])
-
-            if isinstance(norm, ConditionalNorm):
-                self._ensure_belief_inference(norm.condition, asl)
-
-                condition_expr = self._belief_to_expr(norm.condition)
-                body = BinaryOp(phase_lit, "&", condition_expr)
-            else:
-                body = phase_lit
-
-            asl.inference_rules.append(Rule(head=head, body=body))
-
-    def _ensure_belief_inference(self, belief: Belief, asl: AgentSpeakFile):
-        """
-        Recursively adds rules to infer beliefs.
-        Checks strictly to avoid duplicates if necessary,
-        though ASL engines often handle redefinition or we can use a set to track processed IDs.
-        """
-        if isinstance(belief, KeywordBelief):
-            pass
-            # # Rule: keyword_said("word") :- user_said(M) & .substring("word", M, P) & P >= 0.
-            # kwd_slug = f'"{belief.keyword}"'
-            # head = BeliefLiteral("keyword_said", [kwd_slug])
-            #
-            # # Avoid duplicates
-            # if any(str(r.head) == str(head) for r in asl.inference_rules):
-            #     return
-            #
-            # body = BinaryOp(
-            #     BeliefLiteral("user_said", ["Message"]),
-            #     "&",
-            #     BinaryOp(f".substring({kwd_slug}, Message, Pos)", "&", "Pos >= 0"),
-            # )
-            #
-            # asl.inference_rules.append(Rule(head=head, body=body))
-
-        elif isinstance(belief, InferredBelief):
-            self._ensure_belief_inference(belief.left, asl)
-            self._ensure_belief_inference(belief.right, asl)
-
-            slug = self._slugify(belief)
-            head = BeliefLiteral(slug)
-
-            if any(str(r.head) == str(head) for r in asl.inference_rules):
-                return
-
-            op_char = "&" if belief.operator == LogicalOperator.AND else "|"
-            body = BinaryOp(
-                self._belief_to_expr(belief.left), op_char, self._belief_to_expr(belief.right)
-            )
-            asl.inference_rules.append(PersistentRule(head=head, body=body))
-
-    def _belief_to_expr(self, belief: Belief) -> Expression:
-        if isinstance(belief, KeywordBelief):
-            return BeliefLiteral("keyword_said", [f'"{belief.keyword}"'])
-        else:
-            return BeliefLiteral(self._slugify(belief))
-
-    # --- Section: Goals ---
-
-    def _generate_goals(self, phase: Phase, asl: AgentSpeakFile):
-        previous_goal: Goal | None = None
-        for goal in phase.goals:
-            self._generate_goal_plan_recursive(goal, str(phase.id), previous_goal, asl)
-            previous_goal = goal
-
-    def _generate_goal_plan_recursive(
-        self,
-        goal: Goal,
-        phase_id: str,
-        previous_goal: Goal | None,
-        asl: AgentSpeakFile,
-        responded_needed: bool = True,
-        can_fail: bool = True,
-    ):
-        goal_slug = self._slugify(goal)
-
-        # phase(ID) & not responded_this_turn & not achieved_goal
-        context = [
-            BeliefLiteral("phase", [f'"{phase_id}"']),
-        ]
-
-        if responded_needed:
-            context.append(BeliefLiteral("responded_this_turn", negated=True))
-        if can_fail:
-            context.append(BeliefLiteral(f"achieved_{goal_slug}", negated=True))
-
-        if previous_goal:
-            prev_slug = self._slugify(previous_goal)
-            context.append(BeliefLiteral(f"achieved_{prev_slug}"))
-
-        body_actions = []
-        sub_goals_to_process = []
-
-        for step in goal.plan.steps:
-            if isinstance(step, Goal):
-                sub_slug = self._slugify(step)
-                body_actions.append(ActionLiteral(f"!{sub_slug}"))
-                sub_goals_to_process.append(step)
-            elif isinstance(step, SpeechAction):
-                body_actions.append(ActionLiteral(f'.say("{step.text}")'))
-            elif isinstance(step, GestureAction):
-                body_actions.append(ActionLiteral(f'.gesture("{step.gesture}")'))
-            elif isinstance(step, LLMAction):
-                body_actions.append(ActionLiteral(f'!generate_response_with_goal("{step.goal}")'))
-
-        # Mark achievement
-        if not goal.can_fail:
-            body_actions.append(ActionLiteral(f"+achieved_{goal_slug}"))
-
-        asl.plans.append(Plan(trigger=GoalLiteral(goal_slug), context=context, body=body_actions))
-        asl.plans.append(
-            Plan(trigger=GoalLiteral(goal_slug), context=[], body=[ActionLiteral("true")])
-        )
-
-        prev_sub = None
-        for sub_goal in sub_goals_to_process:
-            self._generate_goal_plan_recursive(sub_goal, phase_id, prev_sub, asl)
-            prev_sub = sub_goal
-
-    # --- Section: Triggers ---
-
-    def _generate_triggers(self, phase: Phase, asl: AgentSpeakFile):
-        for keyword in self._get_keyword_conditionals(phase):
-            asl.plans.append(
-                Plan(
-                    trigger=GoalLiteral(f"check_{self._slugify_str(keyword)}"),
-                    context=[
-                        ActionLiteral(
-                            f'user_said(Message) & .substring("{keyword}", Message, Pos) & Pos >= 0'
-                        )
-                    ],
-                    body=[
-                        ActionLiteral(f'+keyword_said("{keyword}")'),
-                        ActionLiteral(f'-keyword_said("{keyword}")'),
-                    ],
-                )
-            )
-            asl.plans.append(
-                Plan(
-                    trigger=GoalLiteral(f"check_{self._slugify_str(keyword)}"),
-                    body=[ActionLiteral("true")],
-                )
-            )
-
-        for trigger in phase.triggers:
-            self._ensure_belief_inference(trigger.condition, asl)
-
-            trigger_belief_slug = self._belief_to_expr(trigger.condition)
-
-            body_actions = []
-            sub_goals = []
-
-            for step in trigger.plan.steps:
-                if isinstance(step, Goal):
-                    sub_slug = self._slugify(step)
-                    body_actions.append(ActionLiteral(f"!{sub_slug}"))
-                    sub_goals.append(step)
-                elif isinstance(step, SpeechAction):
-                    body_actions.append(ActionLiteral(f'.say("{step.text}")'))
-                elif isinstance(step, GestureAction):
-                    body_actions.append(
-                        ActionLiteral(f'.gesture("{step.gesture.type}", "{step.gesture.name}")')
-                    )
-                elif isinstance(step, LLMAction):
-                    body_actions.append(
-                        ActionLiteral(f'!generate_response_with_goal("{step.goal}")')
-                    )
-
-            asl.plans.append(
-                Plan(
-                    trigger=BeliefLiteral(trigger_belief_slug),
-                    context=[BeliefLiteral("phase", [f'"{phase.id}"'])],
-                    body=body_actions,
-                )
-            )
-
-            # Recurse for triggered goals
-            prev_sub = None
-            for sub_goal in sub_goals:
-                self._generate_goal_plan_recursive(
-                    sub_goal, str(phase.id), prev_sub, asl, False, False
-                )
-                prev_sub = sub_goal
-
-    # --- Section: Fallbacks ---
-
-    def _generate_fallbacks(self, program: Program, asl: AgentSpeakFile):
-        asl.plans.append(
-            Plan(trigger=GoalLiteral("transition_phase"), context=[], body=[ActionLiteral("true")])
-        )
-
-    # --- Helpers ---
-
-    @singledispatchmethod
-    def _slugify(self, element: ProgramElement) -> str:
-        if element.name:
-            raise NotImplementedError("Cannot slugify this element.")
-        return self._slugify_str(element.name)
-
-    @_slugify.register
-    def _(self, goal: Goal) -> str:
-        if goal.name:
-            return self._slugify_str(goal.name)
-        return f"goal_{goal.id.hex}"
-
-    @_slugify.register
-    def _(self, kwb: KeywordBelief) -> str:
-        return f"keyword_said({kwb.keyword})"
-
-    @_slugify.register
-    def _(self, sb: SemanticBelief) -> str:
-        return self._slugify_str(sb.description)
-
-    @_slugify.register
-    def _(self, ib: InferredBelief) -> str:
-        return self._slugify_str(ib.name)
-
-    def _slugify_str(self, text: str) -> str:
-        return slugify(text, separator="_", stopwords=["a", "an", "the", "we", "you", "I"])
-
-    def _extract_basic_beliefs_from_program(self, program: Program) -> list[BasicBelief]:
-        beliefs = []
-
-        for phase in program.phases:
-            beliefs.extend(self._extract_basic_beliefs_from_phase(phase))
-
-        return beliefs
-
-    def _extract_basic_beliefs_from_phase(self, phase: Phase) -> list[BasicBelief]:
-        beliefs = []
-
-        for norm in phase.norms:
-            if isinstance(norm, ConditionalNorm):
-                beliefs += self._extract_basic_beliefs_from_belief(norm.condition)
-
-        for trigger in phase.triggers:
-            beliefs += self._extract_basic_beliefs_from_belief(trigger.condition)
-
-        return beliefs
-
-    def _extract_basic_beliefs_from_belief(self, belief: Belief) -> list[BasicBelief]:
-        if isinstance(belief, InferredBelief):
-            return self._extract_basic_beliefs_from_belief(
-                belief.left
-            ) + self._extract_basic_beliefs_from_belief(belief.right)
-        return [belief]
-
-
-if __name__ == "__main__":
-    asyncio.run(do_things())
-    # do_other_things()y

src/control_backend/agents/bdi/bdi_core_agent.py

@@ -1,6 +1,13 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import asyncio
 import copy
 import json
+import logging
 import time
 from collections.abc import Iterable
 
@@ -19,6 +26,9 @@ from control_backend.schemas.ri_message import GestureCommand, RIEndpoint, Speec
 DELIMITER = ";\n"  # TODO: temporary until we support lists in AgentSpeak
 
 
+experiment_logger = logging.getLogger(settings.logging_settings.experiment_logger_name)
+
+
 class BDICoreAgent(BaseAgent):
     """
     BDI Core Agent.
@@ -107,7 +117,6 @@ class BDICoreAgent(BaseAgent):
                 if not maybe_more_work:
                     deadline = self.bdi_agent.shortest_deadline()
                     if deadline:
-                        self.logger.debug("Sleeping until %s", deadline)
                         await asyncio.sleep(deadline - time.time())
                         maybe_more_work = True
                     else:
@@ -156,16 +165,19 @@ class BDICoreAgent(BaseAgent):
                 )
                 await self.send(out_msg)
             case settings.agent_settings.user_interrupt_name:
-                content = msg.body
-                self.logger.debug("Received user interruption: %s", content)
+                self.logger.debug("Received user interruption: %s", msg)
 
                 match msg.thread:
                     case "force_phase_transition":
                         self._set_goal("transition_phase")
                     case "force_trigger":
                         self._force_trigger(msg.body)
+                    case "force_norm":
+                        self._force_norm(msg.body)
+                    case "force_next_phase":
+                        self._force_next_phase()
                     case _:
-                        self.logger.warning("Received unknow user interruption: %s", msg)
+                        self.logger.warning("Received unknown user interruption: %s", msg)
 
     def _apply_belief_changes(self, belief_changes: BeliefMessage):
         """
@@ -205,6 +217,9 @@ class BDICoreAgent(BaseAgent):
         else:
             term = agentspeak.Literal(name)
 
+        if name != "user_said":
+            experiment_logger.observation(f"Formed new belief: {name}{f'={args}' if args else ''}")
+
         self.bdi_agent.call(
             agentspeak.Trigger.addition,
             agentspeak.GoalType.belief,
@@ -242,6 +257,9 @@ class BDICoreAgent(BaseAgent):
             new_args = (agentspeak.Literal(arg) for arg in args)
             term = agentspeak.Literal(name, new_args)
 
+        if name != "user_said":
+            experiment_logger.observation(f"Removed belief: {name}{f'={args}' if args else ''}")
+
         result = self.bdi_agent.call(
             agentspeak.Trigger.removal,
             agentspeak.GoalType.belief,
@@ -302,15 +320,21 @@ class BDICoreAgent(BaseAgent):
         self.logger.debug(f"Set goal !{self.format_belief_string(name, args)}.")
 
     def _force_trigger(self, name: str):
-        self.bdi_agent.call(
-            agentspeak.Trigger.addition,
-            agentspeak.GoalType.achievement,
-            agentspeak.Literal(name),
-            agentspeak.runtime.Intention(),
-        )
+        self._set_goal(name)
 
         self.logger.info("Manually forced trigger %s.", name)
 
+    # TODO: make this compatible for critical norms
+    def _force_norm(self, name: str):
+        self._add_belief(f"force_{name}")
+
+        self.logger.info("Manually forced norm %s.", name)
+
+    def _force_next_phase(self):
+        self._set_goal("force_transition_phase")
+
+        self.logger.info("Manually forced phase transition.")
+
     def _add_custom_actions(self) -> None:
         """
         Add any custom actions here. Inside `@self.actions.add()`, the first argument is
@@ -326,14 +350,11 @@ class BDICoreAgent(BaseAgent):
             message_text = agentspeak.grounded(term.args[0], intention.scope)
             norms = agentspeak.grounded(term.args[1], intention.scope)
 
-            self.logger.debug("Norms: %s", norms)
-            self.logger.debug("User text: %s", message_text)
-
             self.add_behavior(self._send_to_llm(str(message_text), str(norms), ""))
             yield
 
         @self.actions.add(".reply_with_goal", 3)
-        def _reply_with_goal(agent: "BDICoreAgent", term, intention):
+        def _reply_with_goal(agent, term, intention):
             """
             Let the LLM generate a response to a user's utterance with the current norms and a
             specific goal.
@@ -341,16 +362,22 @@ class BDICoreAgent(BaseAgent):
             message_text = agentspeak.grounded(term.args[0], intention.scope)
             norms = agentspeak.grounded(term.args[1], intention.scope)
             goal = agentspeak.grounded(term.args[2], intention.scope)
-
-            self.logger.debug(
-                '"reply_with_goal" action called with message=%s, norms=%s, goal=%s',
-                message_text,
-                norms,
-                goal,
-            )
             self.add_behavior(self._send_to_llm(str(message_text), str(norms), str(goal)))
             yield
 
+        @self.actions.add(".notify_norms", 1)
+        def _notify_norms(agent, term, intention):
+            norms = agentspeak.grounded(term.args[0], intention.scope)
+
+            norm_update_message = InternalMessage(
+                to=settings.agent_settings.user_interrupt_name,
+                thread="active_norms_update",
+                body=str(norms),
+            )
+
+            self.add_behavior(self.send(norm_update_message, should_log=False))
+            yield
+
         @self.actions.add(".say", 1)
         def _say(agent, term, intention):
             """
@@ -375,6 +402,8 @@ class BDICoreAgent(BaseAgent):
                 body=str(message_text),
             )
 
+            experiment_logger.chat(str(message_text), extra={"role": "assistant"})
+
             self.add_behavior(self.send(chat_history_message))
 
             yield
@@ -459,7 +488,6 @@ class BDICoreAgent(BaseAgent):
                 body=str(trigger_name),
             )
 
-            # TODO: check with Pim
             self.add_behavior(self.send(msg))
 
             yield

src/control_backend/agents/bdi/bdi_program_manager.py

@@ -1,10 +1,18 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import asyncio
 import json
+import logging
 
 import zmq
 from pydantic import ValidationError
 from zmq.asyncio import Context
 
+import control_backend
 from control_backend.agents import BaseAgent
 from control_backend.agents.bdi.agentspeak_generator import AgentSpeakGenerator
 from control_backend.core.config import settings
@@ -19,17 +27,21 @@ from control_backend.schemas.program import (
     Program,
 )
 
+experiment_logger = logging.getLogger(settings.logging_settings.experiment_logger_name)
+
 
 class BDIProgramManager(BaseAgent):
     """
     BDI Program Manager Agent.
 
     This agent is responsible for receiving high-level programs (sequences of instructions/goals)
-    from the external HTTP API (via ZMQ) and translating them into core beliefs (norms and goals)
-    for the BDI Core Agent. In the future, it will be responsible for determining when goals are
-    met, and passing on new norms and goals accordingly.
+    from the external HTTP API (via ZMQ), transforming it into an AgentSpeak program, sharing the
+    program and its components to other agents, and keeping agents informed of the current state.
 
     :ivar sub_socket: The ZMQ SUB socket used to receive program updates.
+    :ivar _program: The current Program.
+    :ivar _phase: The current Phase.
+    :ivar _goal_mapping: A mapping of goal IDs to goals.
     """
 
     _program: Program
@@ -38,10 +50,32 @@ class BDIProgramManager(BaseAgent):
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
         self.sub_socket = None
+        self._goal_mapping: dict[str, Goal] = {}
 
     def _initialize_internal_state(self, program: Program):
+        """
+        Initialize the state of the program manager given a new Program. Reset the tracking of the
+        current phase to the first phase, make a mapping of goal IDs to goals, used during the life
+        of the program.
+        :param program: The new program.
+        """
         self._program = program
         self._phase = program.phases[0]  # start in first phase
+        self._goal_mapping = {}
+        for phase in program.phases:
+            for goal in phase.goals:
+                self._populate_goal_mapping_with_goal(goal)
+
+    def _populate_goal_mapping_with_goal(self, goal: Goal):
+        """
+        Recurse through the given goal and its subgoals and add all goals found to the
+        ``self._goal_mapping``.
+        :param goal: The goal to add to the ``self._goal_mapping``, including subgoals.
+        """
+        self._goal_mapping[str(goal.id)] = goal
+        for step in goal.plan.steps:
+            if isinstance(step, Goal):
+                self._populate_goal_mapping_with_goal(step)
 
     async def _create_agentspeak_and_send_to_bdi(self, program: Program):
         """
@@ -53,7 +87,7 @@ class BDIProgramManager(BaseAgent):
 
         asl_str = asg.generate(program)
 
-        file_name = "src/control_backend/agents/bdi/agentspeak.asl"
+        file_name = settings.behaviour_settings.agentspeak_file
 
         with open(file_name, "w") as f:
             f.write(asl_str)
@@ -73,12 +107,39 @@ class BDIProgramManager(BaseAgent):
                 phases = json.loads(msg.body)
 
                 await self._transition_phase(phases["old"], phases["new"])
+            case "achieve_goal":
+                goal_id = msg.body
+                await self._send_achieved_goal_to_semantic_belief_extractor(goal_id)
 
     async def _transition_phase(self, old: str, new: str):
-        assert old == str(self._phase.id)
+        """
+        When receiving a signal from the BDI core that the phase has changed, apply this change to
+        the current state and inform other agents about the change.
+
+        :param old: The ID of the old phase.
+        :param new: The ID of the new phase.
+        """
+        if self._phase is None:
+            return
+
+        if old != str(self._phase.id):
+            self.logger.warning(
+                f"Phase transition desync detected! ASL requested move from '{old}', "
+                f"but Python is currently in '{self._phase.id}'. Request ignored."
+            )
+            return
 
         if new == "end":
             self._phase = None
+            # Notify user interaction agent
+            msg = InternalMessage(
+                to=settings.agent_settings.user_interrupt_name,
+                thread="transition_phase",
+                body="end",
+            )
+            self.logger.info("Transitioned to end phase, notifying UserInterruptAgent.")
+
+            self.add_behavior(self.send(msg))
             return
 
         for phase in self._program.phases:
@@ -94,10 +155,18 @@ class BDIProgramManager(BaseAgent):
             thread="transition_phase",
             body=str(self._phase.id),
         )
+        self.logger.info(f"Transitioned to phase {new}, notifying UserInterruptAgent.")
 
         self.add_behavior(self.send(msg))
 
     def _extract_current_beliefs(self) -> list[Belief]:
+        """Extract beliefs from the current phase."""
+        assert self._phase is not None, (
+            "Invalid state, no phase set. Call this method only when "
+            "a program has been received and the end-phase has not "
+            "been reached."
+        )
+
         beliefs: list[Belief] = []
 
         for norm in self._phase.norms:
@@ -111,6 +180,7 @@ class BDIProgramManager(BaseAgent):
 
     @staticmethod
     def _extract_beliefs_from_belief(belief: Belief) -> list[Belief]:
+        """Recursively extract beliefs from the given belief."""
         if isinstance(belief, InferredBelief):
             return BDIProgramManager._extract_beliefs_from_belief(
                 belief.left
@@ -118,9 +188,7 @@ class BDIProgramManager(BaseAgent):
         return [belief]
 
     async def _send_beliefs_to_semantic_belief_extractor(self):
-        """
-        Extract beliefs from the program and send them to the Semantic Belief Extractor Agent.
-        """
+        """Extract beliefs from the program and send them to the Semantic Belief Extractor Agent."""
         beliefs = BeliefList(beliefs=self._extract_current_beliefs())
 
         message = InternalMessage(
@@ -132,23 +200,35 @@ class BDIProgramManager(BaseAgent):
 
         await self.send(message)
 
+    @staticmethod
+    def _extract_goals_from_goal(goal: Goal) -> list[Goal]:
+        """
+        Extract all goals from a given goal, that is: the goal itself and any subgoals.
+
+        :return: All goals within and including the given goal.
+        """
+        goals: list[Goal] = [goal]
+        for step in goal.plan.steps:
+            if isinstance(step, Goal):
+                goals.extend(BDIProgramManager._extract_goals_from_goal(step))
+        return goals
+
     def _extract_current_goals(self) -> list[Goal]:
         """
         Extract all goals from the program, including subgoals.
 
         :return: A list of Goal objects.
         """
+        assert self._phase is not None, (
+            "Invalid state, no phase set. Call this method only when "
+            "a program has been received and the end-phase has not "
+            "been reached."
+        )
+
         goals: list[Goal] = []
 
-        def extract_goals_from_goal(goal_: Goal) -> list[Goal]:
-            goals_: list[Goal] = [goal]
-            for plan in goal_.plan:
-                if isinstance(plan, Goal):
-                    goals_.extend(extract_goals_from_goal(plan))
-            return goals_
-
         for goal in self._phase.goals:
-            goals.extend(extract_goals_from_goal(goal))
+            goals.extend(self._extract_goals_from_goal(goal))
 
         return goals
 
@@ -167,6 +247,25 @@ class BDIProgramManager(BaseAgent):
 
         await self.send(message)
 
+    async def _send_achieved_goal_to_semantic_belief_extractor(self, achieved_goal_id: str):
+        """
+        Inform the semantic belief extractor when a goal is marked achieved.
+
+        :param achieved_goal_id: The id of the achieved goal.
+        """
+        goal = self._goal_mapping.get(achieved_goal_id)
+        if goal is None:
+            self.logger.debug(f"Goal with ID {achieved_goal_id} marked achieved but was not found.")
+            return
+
+        goals = self._extract_goals_from_goal(goal)
+        message = InternalMessage(
+            to=settings.agent_settings.text_belief_extractor_name,
+            body=GoalList(goals=goals).model_dump_json(),
+            thread="achieved_goals",
+        )
+        await self.send(message)
+
     async def _send_clear_llm_history(self):
         """
         Clear the LLM Agent's conversation history.
@@ -188,6 +287,18 @@ class BDIProgramManager(BaseAgent):
         await self.send(extractor_msg)
         self.logger.debug("Sent message to extractor agent to clear history.")
 
+    @staticmethod
+    def _rollover_experiment_logs():
+        """
+        A new experiment program started; make a new experiment log file.
+        """
+        handlers = logging.getLogger(settings.logging_settings.experiment_logger_name).handlers
+        for handler in handlers:
+            if isinstance(handler, control_backend.logging.DatedFileHandler):
+                experiment_logger.action("Doing rollover...")
+                handler.do_rollover()
+                experiment_logger.debug("Finished rollover.")
+
     async def _receive_programs(self):
         """
         Continuous loop that receives program updates from the HTTP endpoint.
@@ -206,8 +317,9 @@ class BDIProgramManager(BaseAgent):
                 continue
 
             self._initialize_internal_state(program)
-
+            await self._send_program_to_user_interrupt(program)
             await self._send_clear_llm_history()
+            self._rollover_experiment_logs()
 
             await asyncio.gather(
                 self._create_agentspeak_and_send_to_bdi(program),
@@ -215,13 +327,30 @@ class BDIProgramManager(BaseAgent):
                 self._send_goals_to_semantic_belief_extractor(),
             )
 
+    async def _send_program_to_user_interrupt(self, program: Program):
+        """
+        Send the received program to the User Interrupt Agent.
+
+        :param program: The program object received from the API.
+        """
+        msg = InternalMessage(
+            sender=self.name,
+            to=settings.agent_settings.user_interrupt_name,
+            body=program.model_dump_json(),
+            thread="new_program",
+        )
+
+        await self.send(msg)
+
     async def setup(self):
         """
         Initialize the agent.
 
         Connects the internal ZMQ SUB socket and subscribes to the 'program' topic.
-        Starts the background behavior to receive programs.
+        Starts the background behavior to receive programs. Initializes a default program.
         """
+        await self._create_agentspeak_and_send_to_bdi(Program(phases=[]))
+
         context = Context.instance()
 
         self.sub_socket = context.socket(zmq.SUB)

src/control_backend/agents/bdi/belief_collector_agent.py

@@ -1,152 +0,0 @@
-import json
-
-from pydantic import ValidationError
-
-from control_backend.agents.base 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 BDIBeliefCollectorAgent(BaseAgent):
-    """
-    BDI Belief Collector Agent.
-
-    This agent acts as a central aggregator for beliefs derived from various sources (e.g., text,
-    emotion, vision). It receives raw extracted data from other agents,
-    normalizes them into valid :class:`Belief` objects, and forwards them as a unified packet to the
-    BDI Core Agent.
-
-    It serves as a funnel to ensure the BDI agent receives a consistent stream of beliefs.
-    """
-
-    async def setup(self):
-        """
-        Initialize the agent.
-        """
-        self.logger.info("Setting up %s", self.name)
-
-    async def handle_message(self, msg: InternalMessage):
-        """
-        Handle incoming messages from other extractor agents.
-
-        Routes the message to specific handlers based on the 'type' field in the JSON body.
-        Supported types:
-        -   ``belief_extraction_text``: Handled by :meth:`_handle_belief_text`
-        -   ``emotion_extraction_text``: Handled by :meth:`_handle_emo_text`
-
-        :param msg: The received internal message.
-        """
-        sender_node = msg.sender
-
-        # Parse JSON payload
-        try:
-            payload = json.loads(msg.body)
-        except Exception as e:
-            self.logger.warning(
-                "BeliefCollector: failed to parse JSON from %s. Body=%r Error=%s",
-                sender_node,
-                msg.body,
-                e,
-            )
-            return
-
-        msg_type = payload.get("type")
-
-        # Prefer explicit 'type' field
-        if msg_type == "belief_extraction_text":
-            self.logger.debug("Message routed to _handle_belief_text (sender=%s)", sender_node)
-            await self._handle_belief_text(payload, sender_node)
-        # This is not implemented yet, but we keep the structure for future use
-        elif msg_type == "emotion_extraction_text":
-            self.logger.debug("Message routed to _handle_emo_text (sender=%s)", sender_node)
-            await self._handle_emo_text(payload, sender_node)
-        else:
-            self.logger.warning(
-                "Unrecognized message (sender=%s, type=%r). Ignoring.", sender_node, msg_type
-            )
-
-    async def _handle_belief_text(self, payload: dict, origin: str):
-        """
-        Process text-based belief extraction payloads.
-
-        Expected payload format::
-
-            {
-                "type": "belief_extraction_text",
-                "beliefs": {
-                    "user_said": ["Can you help me?"],
-                    "intention": ["ask_help"]
-                }
-            }
-
-        Validates and converts the dictionary items into :class:`Belief` objects.
-
-        :param payload: The dictionary payload containing belief data.
-        :param origin: The name of the sender agent.
-        """
-        beliefs = payload.get("beliefs", {})
-
-        if not beliefs:
-            self.logger.debug("Received empty beliefs set.")
-            return
-
-        def try_create_belief(name, arguments) -> Belief | None:
-            """
-            Create a belief object from name and arguments, or return None silently if the input is
-            not correct.
-
-            :param name: The name of the belief.
-            :param arguments: The arguments of the belief.
-            :return: A Belief object if the input is valid or None.
-            """
-            try:
-                return Belief(name=name, arguments=arguments)
-            except ValidationError:
-                return None
-
-        beliefs = [
-            belief
-            for name, arguments in beliefs.items()
-            if (belief := try_create_belief(name, arguments)) is not None
-        ]
-
-        self.logger.debug("Forwarding %d beliefs.", len(beliefs))
-        for belief in beliefs:
-            for argument in belief.arguments:
-                self.logger.debug("  - %s %s", belief.name, argument)
-
-        await self._send_beliefs_to_bdi(beliefs, origin=origin)
-
-    async def _handle_emo_text(self, payload: dict, origin: str):
-        """
-        Process emotion extraction payloads.
-
-        **TODO**: Implement this method once emotion recognition is integrated.
-
-        :param payload: The dictionary payload containing emotion data.
-        :param origin: The name of the sender agent.
-        """
-        pass
-
-    async def _send_beliefs_to_bdi(self, beliefs: list[Belief], origin: str | None = None):
-        """
-        Send a list of aggregated beliefs to the BDI Core Agent.
-
-        Wraps the beliefs in a :class:`BeliefMessage` and sends it via the 'beliefs' thread.
-
-        :param beliefs: The list of Belief objects to send.
-        :param origin: (Optional) The original source of the beliefs (unused currently).
-        """
-        if not beliefs:
-            return
-
-        msg = InternalMessage(
-            to=settings.agent_settings.bdi_core_name,
-            sender=self.name,
-            body=BeliefMessage(create=beliefs).model_dump_json(),
-            thread="beliefs",
-        )
-
-        await self.send(msg)
-        self.logger.info("Sent %d belief(s) to BDI core.", len(beliefs))

src/control_backend/agents/bdi/default_behavior.asl

@@ -1,6 +1,38 @@
-norms("").
+//This program has been developed by students from the bachelor Computer Science at Utrecht
+//University within the Software Project course.
+//© Copyright Utrecht University (Department of Information and Computing Sciences)
 
-+user_said(Message) : norms(Norms) <-
-  .notify_user_said(Message);
-  -user_said(Message);
-  .reply(Message, Norms).
+phase("end").
+keyword_said(Keyword) :- (user_said(Message) & .substring(Keyword, Message, Pos)) & (Pos >= 0).
+
+
++!reply_with_goal(Goal)
+  :   user_said(Message)
+  <-  +responded_this_turn;
+      .findall(Norm, norm(Norm), Norms);
+      .reply_with_goal(Message, Norms, Goal).
+
++!say(Text)
+  <-  +responded_this_turn;
+      .say(Text).
+
++!reply
+  :   user_said(Message)
+  <-  +responded_this_turn;
+      .findall(Norm, norm(Norm), Norms);
+      .reply(Message, Norms).
+
++!notify_cycle
+  <-  .notify_ui;
+      .wait(1).
+
++user_said(Message)
+  :   phase("end")
+  <-  .notify_user_said(Message);
+      !reply.
+
++!check_triggers
+  <-  true.
+
++!transition_phase
+  <-  true.

src/control_backend/agents/bdi/text_belief_extractor_agent.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import asyncio
 import json
 
@@ -12,12 +18,18 @@ from control_backend.schemas.belief_list import BeliefList, GoalList
 from control_backend.schemas.belief_message import Belief as InternalBelief
 from control_backend.schemas.belief_message import BeliefMessage
 from control_backend.schemas.chat_history import ChatHistory, ChatMessage
-from control_backend.schemas.program import Goal, SemanticBelief
+from control_backend.schemas.program import BaseGoal, SemanticBelief
 
 type JSONLike = None | bool | int | float | str | list["JSONLike"] | dict[str, "JSONLike"]
 
 
 class BeliefState(BaseModel):
+    """
+    Represents the state of inferred semantic beliefs.
+
+    Maintains sets of beliefs that are currently considered true or false.
+    """
+
     true: set[InternalBelief] = set()
     false: set[InternalBelief] = set()
 
@@ -62,6 +74,7 @@ class TextBeliefExtractorAgent(BaseAgent):
         self.goal_inferrer = GoalAchievementInferrer(self._llm)
         self._current_beliefs = BeliefState()
         self._current_goal_completions: dict[str, bool] = {}
+        self._force_completed_goals: set[BaseGoal] = set()
         self.conversation = ChatHistory(messages=[])
 
     async def setup(self):
@@ -118,13 +131,19 @@ class TextBeliefExtractorAgent(BaseAgent):
             case "goals":
                 self._handle_goals_message(msg)
                 await self._infer_goal_completions()
+            case "achieved_goals":
+                self._handle_goal_achieved_message(msg)
             case "conversation_history":
                 if msg.body == "reset":
-                    self._reset()
+                    self._reset_phase()
             case _:
                 self.logger.warning("Received unexpected message from %s", msg.sender)
 
-    def _reset(self):
+    def _reset_phase(self):
+        """
+        Delete all state about the current phase, such as what beliefs exist and which ones are
+        true.
+        """
         self.conversation = ChatHistory(messages=[])
         self.belief_inferrer.available_beliefs.clear()
         self._current_beliefs = BeliefState()
@@ -132,6 +151,11 @@ class TextBeliefExtractorAgent(BaseAgent):
         self._current_goal_completions = {}
 
     def _handle_beliefs_message(self, msg: InternalMessage):
+        """
+        Handle the message from the Program Manager agent containing the beliefs that exist for this
+        phase.
+        :param msg: A list of beliefs.
+        """
         try:
             belief_list = BeliefList.model_validate_json(msg.body)
         except ValidationError:
@@ -149,6 +173,11 @@ class TextBeliefExtractorAgent(BaseAgent):
         )
 
     def _handle_goals_message(self, msg: InternalMessage):
+        """
+        Handle the message from the Program Manager agent containing the goals that exist for this
+        phase.
+        :param msg: A list of goals.
+        """
         try:
             goals_list = GoalList.model_validate_json(msg.body)
         except ValidationError:
@@ -158,7 +187,8 @@ class TextBeliefExtractorAgent(BaseAgent):
             return
 
         # Use only goals that can fail, as the others are always assumed to be completed
-        available_goals = [g for g in goals_list.goals if g.can_fail]
+        available_goals = {g for g in goals_list.goals if g.can_fail}
+        available_goals -= self._force_completed_goals
         self.goal_inferrer.goals = available_goals
         self.logger.debug(
             "Received %d failable goals from the program manager: %s",
@@ -166,6 +196,28 @@ class TextBeliefExtractorAgent(BaseAgent):
             ", ".join(g.name for g in available_goals),
         )
 
+    def _handle_goal_achieved_message(self, msg: InternalMessage):
+        """
+        Handle message that gets sent when goals are marked achieved from a user interrupt. This
+        goal should then not be changed by this agent anymore.
+        :param msg: List of goals that are marked achieved.
+        """
+        # NOTE: When goals can be marked unachieved, remember to re-add them to the goal_inferrer
+        try:
+            goals_list = GoalList.model_validate_json(msg.body)
+        except ValidationError:
+            self.logger.warning(
+                "Received goal achieved message from the program manager, "
+                "but it is not a valid list of goals."
+            )
+            return
+
+        for goal in goals_list.goals:
+            self._force_completed_goals.add(goal)
+            self._current_goal_completions[f"achieved_{AgentSpeakGenerator.slugify(goal)}"] = True
+
+        self.goal_inferrer.goals -= self._force_completed_goals
+
     async def _user_said(self, text: str):
         """
         Create a belief for the user's full speech.
@@ -183,6 +235,10 @@ class TextBeliefExtractorAgent(BaseAgent):
         await self.send(belief_msg)
 
     async def _infer_new_beliefs(self):
+        """
+        Determine which beliefs hold and do not hold for the current conversation state. When
+        beliefs change, a message is sent to the BDI core.
+        """
         conversation_beliefs = await self.belief_inferrer.infer_from_conversation(self.conversation)
 
         new_beliefs = conversation_beliefs - self._current_beliefs
@@ -206,6 +262,10 @@ class TextBeliefExtractorAgent(BaseAgent):
         await self.send(message)
 
     async def _infer_goal_completions(self):
+        """
+        Determine which goals have been achieved given the current conversation state. When
+        a goal's achieved state changes, a message is sent to the BDI core.
+        """
         goal_completions = await self.goal_inferrer.infer_from_conversation(self.conversation)
 
         new_achieved = [
@@ -291,6 +351,9 @@ class TextBeliefExtractorAgent(BaseAgent):
                 async with httpx.AsyncClient() as client:
                     response = await client.post(
                         settings.llm_settings.local_llm_url,
+                        headers={"Authorization": f"Bearer {settings.llm_settings.api_key}"}
+                        if settings.llm_settings.api_key
+                        else {},
                         json={
                             "model": settings.llm_settings.local_llm_model,
                             "messages": [{"role": "user", "content": prompt}],
@@ -317,7 +380,7 @@ class TextBeliefExtractorAgent(BaseAgent):
 
 class SemanticBeliefInferrer:
     """
-    Class that handles only prompting an LLM for semantic beliefs.
+    Infers semantic beliefs from conversation history using an LLM.
     """
 
     def __init__(
@@ -347,19 +410,22 @@ class SemanticBeliefInferrer:
                 for beliefs in self._split_into_chunks(self.available_beliefs, n_parallel)
             ]
         )
-        retval = BeliefState()
+        new_beliefs = BeliefState()
+        # Collect beliefs from all parallel calls
         for beliefs in all_beliefs:
             if beliefs is None:
                 continue
+            # For each, convert them to InternalBeliefs
             for belief_name, belief_holds in beliefs.items():
+                # Skip beliefs that were marked not possible to determine
                 if belief_holds is None:
                     continue
                 belief = InternalBelief(name=belief_name, arguments=None)
                 if belief_holds:
-                    retval.true.add(belief)
+                    new_beliefs.true.add(belief)
                 else:
-                    retval.false.add(belief)
-        return retval
+                    new_beliefs.false.add(belief)
+        return new_beliefs
 
     @staticmethod
     def _split_into_chunks[T](items: list[T], n: int) -> list[list[T]]:
@@ -443,9 +509,13 @@ Respond with a JSON similar to the following, but with the property names as giv
 
 
 class GoalAchievementInferrer(SemanticBeliefInferrer):
+    """
+    Infers whether specific conversational goals have been achieved using an LLM.
+    """
+
     def __init__(self, llm: TextBeliefExtractorAgent.LLM):
         super().__init__(llm)
-        self.goals = []
+        self.goals: set[BaseGoal] = set()
 
     async def infer_from_conversation(self, conversation: ChatHistory) -> dict[str, bool]:
         """
@@ -465,7 +535,7 @@ class GoalAchievementInferrer(SemanticBeliefInferrer):
             for goal, achieved in zip(self.goals, goals_achieved, strict=True)
         }
 
-    async def _infer_goal(self, conversation: ChatHistory, goal: Goal) -> bool:
+    async def _infer_goal(self, conversation: ChatHistory, goal: BaseGoal) -> bool:
         prompt = f"""{self._format_conversation(conversation)}
 
 Given the above conversation, what has the following goal been achieved?

src/control_backend/agents/communication/__init__.py

@@ -1 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+--------------------------------------------------------------------------------
+Agents responsible for external communication and service discovery.
+"""
+
 from .ri_communication_agent import RICommunicationAgent as RICommunicationAgent

src/control_backend/agents/communication/ri_communication_agent.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import asyncio
 import json
 
@@ -7,10 +13,13 @@ 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 ..actuation.robot_speech_agent import RobotSpeechAgent
-from ..perception import VADAgent
+from ..perception import FacePerceptionAgent, VADAgent
 
 
 class RICommunicationAgent(BaseAgent):
@@ -47,6 +56,9 @@ class RICommunicationAgent(BaseAgent):
         self._req_socket: azmq.Socket | None = None
         self.pub_socket: azmq.Socket | None = None
         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):
         """
@@ -140,6 +152,7 @@ class RICommunicationAgent(BaseAgent):
 
             # At this point, we have a valid response
             try:
+                self.logger.debug("Negotiation successful.")
                 await self._handle_negotiation_response(received_message)
                 # Let UI know that we're connected
                 topic = b"ping"
@@ -168,7 +181,7 @@ class RICommunicationAgent(BaseAgent):
             bind = port_data["bind"]
 
             if not bind:
-                addr = f"tcp://{settings.ri_host}:{port}"
+                addr = f"tcp://localhost:{port}"
             else:
                 addr = f"tcp://*:{port}"
 
@@ -188,6 +201,7 @@ class RICommunicationAgent(BaseAgent):
                         address=addr,
                         bind=bind,
                     )
+                    self.speech_agent = robot_speech_agent
                     robot_gesture_agent = RobotGestureAgent(
                         settings.agent_settings.robot_gesture_name,
                         address=addr,
@@ -195,12 +209,28 @@ class RICommunicationAgent(BaseAgent):
                         gesture_data=gesture_data,
                         single_gesture_data=single_gesture_data,
                     )
+                    self.gesture_agent = robot_gesture_agent
                     await robot_speech_agent.start()
                     await asyncio.sleep(0.1)  # Small delay
                     await robot_gesture_agent.start()
                 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 "face":
+                    face_agent = FacePerceptionAgent(
+                        settings.agent_settings.face_agent_name,
+                        zmq_address=addr,
+                        zmq_bind=bind,
+                    )
+                    await face_agent.start()
                 case _:
                     self.logger.warning("Unhandled negotiation id: %s", id)
 
@@ -225,6 +255,7 @@ class RICommunicationAgent(BaseAgent):
         while self._running:
             if not self.connected:
                 await asyncio.sleep(settings.behaviour_settings.sleep_s)
+                self.logger.debug("Not connected, skipping ping loop iteration.")
                 continue
 
             # We need to listen and send pings.
@@ -289,13 +320,28 @@ class RICommunicationAgent(BaseAgent):
         # Tell UI we're disconnected.
         topic = b"ping"
         data = json.dumps(False).encode()
+        self.logger.debug("1")
         if self.pub_socket:
             try:
+                self.logger.debug("2")
                 await asyncio.wait_for(self.pub_socket.send_multipart([topic, data]), 5)
             except TimeoutError:
+                self.logger.debug("3")
                 self.logger.warning("Connection ping for router timed out.")
 
         # Try to reboot/renegotiate
+        if self.gesture_agent is not None:
+            await self.gesture_agent.stop()
+
+        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()
+
         self.logger.debug("Restarting communication negotiation.")
-        if await self._negotiate_connection(max_retries=1):
+        if await self._negotiate_connection(max_retries=2):
             self.connected = True

src/control_backend/agents/llm/__init__.py

@@ -1 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+--------------------------------------------------------------------------------
+Agents that interface with Large Language Models for natural language processing and generation.
+"""
+
 from .llm_agent import LLMAgent as LLMAgent

src/control_backend/agents/llm/llm_agent.py

@@ -1,4 +1,12 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+import asyncio
 import json
+import logging
 import re
 import uuid
 from collections.abc import AsyncGenerator
@@ -13,6 +21,8 @@ from control_backend.core.config import settings
 from ...schemas.llm_prompt_message import LLMPromptMessage
 from .llm_instructions import LLMInstructions
 
+experiment_logger = logging.getLogger(settings.logging_settings.experiment_logger_name)
+
 
 class LLMAgent(BaseAgent):
     """
@@ -32,6 +42,10 @@ class LLMAgent(BaseAgent):
     def __init__(self, name: str):
         super().__init__(name)
         self.history = []
+        self._querying = False
+        self._interrupted = False
+        self._interrupted_message = ""
+        self._go_ahead = asyncio.Event()
 
     async def setup(self):
         self.logger.info("Setting up %s.", self.name)
@@ -50,13 +64,13 @@ class LLMAgent(BaseAgent):
                 case "prompt_message":
                     try:
                         prompt_message = LLMPromptMessage.model_validate_json(msg.body)
-                        await self._process_bdi_message(prompt_message)
+                        self.add_behavior(self._process_bdi_message(prompt_message))  # no block
                     except ValidationError:
                         self.logger.debug("Prompt message from BDI core is invalid.")
                 case "assistant_message":
-                    self.history.append({"role": "assistant", "content": msg.body})
+                    self._apply_conversation_message({"role": "assistant", "content": msg.body})
                 case "user_message":
-                    self.history.append({"role": "user", "content": msg.body})
+                    self._apply_conversation_message({"role": "user", "content": msg.body})
         elif msg.sender == settings.agent_settings.bdi_program_manager_name:
             if msg.body == "clear_history":
                 self.logger.debug("Clearing conversation history.")
@@ -73,12 +87,45 @@ class LLMAgent(BaseAgent):
 
         :param message: The parsed prompt message containing text, norms, and goals.
         """
+        if self._querying:
+            self.logger.debug("Received another BDI prompt while processing previous message.")
+            self._interrupted = True  # interrupt the previous processing
+            await self._go_ahead.wait()  # wait until we get the go-ahead
+
+        message.text = f"{self._interrupted_message} {message.text}"
+
+        self._go_ahead.clear()
+        self._querying = True
         full_message = ""
         async for chunk in self._query_llm(message.text, message.norms, message.goals):
+            if self._interrupted:
+                self._interrupted_message = message.text
+                self.logger.debug("Interrupted processing of previous message.")
+                break
             await self._send_reply(chunk)
             full_message += chunk
-        self.logger.debug("Finished processing BDI message. Response sent in chunks to BDI core.")
-        await self._send_full_reply(full_message)
+        else:
+            self._querying = False
+
+            self._apply_conversation_message(
+                {
+                    "role": "assistant",
+                    "content": full_message,
+                }
+            )
+            self.logger.debug(
+                "Finished processing BDI message. Response sent in chunks to BDI core."
+            )
+            await self._send_full_reply(full_message)
+
+        self._go_ahead.set()
+        self._interrupted = False
+
+    def _apply_conversation_message(self, message: dict[str, str]):
+        if len(self.history) > 0 and message["role"] == self.history[-1]["role"]:
+            self.history[-1]["content"] += " " + message["content"]
+            return
+        self.history.append(message)
 
     async def _send_reply(self, msg: str):
         """
@@ -132,7 +179,7 @@ class LLMAgent(BaseAgent):
             *self.history,
         ]
 
-        message_id = str(uuid.uuid4())  # noqa
+        message_id = str(uuid.uuid4())
 
         try:
             full_message = ""
@@ -141,10 +188,9 @@ class LLMAgent(BaseAgent):
                 full_message += token
                 current_chunk += token
 
-                self.logger.llm(
-                    "Received token: %s",
+                experiment_logger.chat(
                     full_message,
-                    extra={"reference": message_id},  # Used in the UI to update old logs
+                    extra={"role": "assistant", "reference": message_id, "partial": True},
                 )
 
                 # Stream the message in chunks separated by punctuation.
@@ -160,11 +206,9 @@ class LLMAgent(BaseAgent):
             if current_chunk:
                 yield current_chunk
 
-            self.history.append(
-                {
-                    "role": "assistant",
-                    "content": full_message,
-                }
+            experiment_logger.chat(
+                full_message,
+                extra={"role": "assistant", "reference": message_id, "partial": False},
             )
         except httpx.HTTPError as err:
             self.logger.error("HTTP error.", exc_info=err)
@@ -185,6 +229,9 @@ class LLMAgent(BaseAgent):
             async with client.stream(
                 "POST",
                 settings.llm_settings.local_llm_url,
+                headers={"Authorization": f"Bearer {settings.llm_settings.api_key}"}
+                if settings.llm_settings.api_key
+                else {},
                 json={
                     "model": settings.llm_settings.local_llm_model,
                     "messages": messages,

src/control_backend/agents/llm/llm_instructions.py

@@ -1,3 +1,10 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+
 class LLMInstructions:
     """
     Helper class to construct the system instructions for the LLM.

src/control_backend/agents/perception/__init__.py

@@ -1,3 +1,13 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+--------------------------------------------------------------------------------
+Agents responsible for processing sensory input, such as audio transcription and voice activity
+detection.
+"""
+
+from .face_rec_agent import FacePerceptionAgent as FacePerceptionAgent
 from .transcription_agent.transcription_agent import (
     TranscriptionAgent as TranscriptionAgent,
 )

src/control_backend/agents/perception/face_rec_agent.py

@@ -0,0 +1,144 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+import asyncio
+
+import zmq
+import zmq.asyncio as azmq
+
+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):
+    """
+    Receives face presence updates from the RICommunicationAgent
+    via the internal PUB/SUB bus.
+    """
+
+    def __init__(self, name: str, zmq_address: str, zmq_bind: bool):
+        """
+        :param name: The name of the agent.
+        :param zmq_address: The ZMQ address to subscribe to, an endpoint which sends face presence
+            updates.
+        :param zmq_bind: Whether to connect to the ZMQ endpoint, or to bind.
+        """
+        super().__init__(name)
+        self._zmq_address = zmq_address
+        self._zmq_bind = zmq_bind
+        self._socket: azmq.Socket | None = None
+
+        self._last_face_state: bool | None = None
+
+        # Pause functionality
+        # NOTE: flag is set when running, cleared when paused
+        self._paused = asyncio.Event()
+        self._paused.set()
+
+    async def setup(self):
+        self.logger.info("Starting FacePerceptionAgent")
+
+        if self._socket is None:
+            self._connect_socket()
+
+        self.add_behavior(self._poll_loop())
+        self.logger.info("Finished setting up %s", self.name)
+
+    def _connect_socket(self):
+        if self._socket is not None:
+            self.logger.warning("ZMQ socket already initialized. Did you call setup() twice?")
+            return
+
+        self._socket = azmq.Context.instance().socket(zmq.SUB)
+        self._socket.setsockopt_string(zmq.SUBSCRIBE, "")
+        if self._zmq_bind:
+            self._socket.bind(self._zmq_address)
+        else:
+            self._socket.connect(self._zmq_address)
+
+    async def _poll_loop(self):
+        if self._socket is None:
+            self.logger.warning("Connection not initialized before poll loop. Call setup() first.")
+            return
+
+        while self._running:
+            try:
+                await self._paused.wait()
+                response = await asyncio.wait_for(
+                    self._socket.recv_json(), timeout=settings.behaviour_settings.sleep_s
+                )
+
+                face_present = response.get("face_detected", False)
+
+                if self._last_face_state is None:
+                    self._last_face_state = face_present
+                    continue
+
+                if face_present != self._last_face_state:
+                    self._last_face_state = face_present
+                    self.logger.debug("Face detected" if face_present else "Face lost")
+                    await self._update_face_belief(face_present)
+            except TimeoutError:
+                pass
+            except Exception as e:
+                self.logger.error("Face polling failed", exc_info=e)
+
+    async def _post_face_belief(self, present: bool):
+        """
+        Send a face_present belief update to the BDI Core Agent.
+        """
+        if present:
+            belief_msg = BeliefMessage(create=[{"name": "face_present", "arguments": []}])
+        else:
+            belief_msg = BeliefMessage(delete=[{"name": "face_present", "arguments": []}])
+
+        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)
+
+    async def handle_message(self, msg: InternalMessage):
+        """
+        Handle incoming pause/resume commands from User Interrupt Agent.
+        """
+        sender = msg.sender
+
+        if sender == settings.agent_settings.user_interrupt_name:
+            if msg.body == "PAUSE":
+                self.logger.info("Pausing Face Perception processing.")
+                self._paused.clear()
+                self._last_face_state = None
+            elif msg.body == "RESUME":
+                self.logger.info("Resuming Face Perception processing.")
+                self._paused.set()
+            else:
+                self.logger.warning("Unknown command from User Interrupt Agent: %s", msg.body)
+        else:
+            self.logger.debug("Ignoring message from unknown sender: %s", sender)

src/control_backend/agents/perception/transcription_agent/speech_recognizer.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import abc
 import sys
 
@@ -145,4 +151,6 @@ class OpenAIWhisperSpeechRecognizer(SpeechRecognizer):
 
     def recognize_speech(self, audio: np.ndarray) -> str:
         self.load_model()
-        return whisper.transcribe(self.model, audio, **self._get_decode_options(audio))["text"]
+        return whisper.transcribe(self.model, audio, **self._get_decode_options(audio))[
+            "text"
+        ].strip()

src/control_backend/agents/perception/transcription_agent/transcription_agent.py

@@ -1,4 +1,11 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import asyncio
+import logging
 
 import numpy as np
 import zmq
@@ -10,6 +17,8 @@ from control_backend.core.config import settings
 
 from .speech_recognizer import SpeechRecognizer
 
+experiment_logger = logging.getLogger(settings.logging_settings.experiment_logger_name)
+
 
 class TranscriptionAgent(BaseAgent):
     """
@@ -25,6 +34,8 @@ class TranscriptionAgent(BaseAgent):
     :ivar audio_in_socket: The ZMQ SUB socket instance.
     :ivar speech_recognizer: The speech recognition engine instance.
     :ivar _concurrency: Semaphore to limit concurrent transcriptions.
+    :ivar _current_speech_reference: The reference of the current user utterance, for synchronising
+        experiment logs.
     """
 
     def __init__(self, audio_in_address: str):
@@ -39,6 +50,7 @@ class TranscriptionAgent(BaseAgent):
         self.audio_in_socket: azmq.Socket | None = None
         self.speech_recognizer = None
         self._concurrency = None
+        self._current_speech_reference: str | None = None
 
     async def setup(self):
         """
@@ -63,6 +75,10 @@ class TranscriptionAgent(BaseAgent):
 
         self.logger.info("Finished setting up %s", self.name)
 
+    async def handle_message(self, msg: InternalMessage):
+        if msg.thread == "voice_activity":
+            self._current_speech_reference = msg.body
+
     async def stop(self):
         """
         Stop the agent and close sockets.
@@ -74,7 +90,7 @@ class TranscriptionAgent(BaseAgent):
 
     def _connect_audio_in_socket(self):
         """
-        Helper to connect the ZMQ SUB socket for audio input.
+        Connects the ZMQ SUB socket for receiving audio data.
         """
         self.audio_in_socket = azmq.Context.instance().socket(zmq.SUB)
         self.audio_in_socket.setsockopt_string(zmq.SUBSCRIBE, "")
@@ -96,24 +112,25 @@ class TranscriptionAgent(BaseAgent):
 
     async def _share_transcription(self, transcription: str):
         """
-        Share a transcription to the other agents that depend on it.
+        Share a transcription to the other agents that depend on it, and to experiment logs.
 
         Currently sends to:
         - :attr:`settings.agent_settings.text_belief_extractor_name`
+        - The UI via the experiment logger
 
         :param transcription: The transcribed text.
         """
-        receiver_names = [
-            settings.agent_settings.text_belief_extractor_name,
-        ]
+        experiment_logger.chat(
+            transcription,
+            extra={"role": "user", "reference": self._current_speech_reference, "partial": False},
+        )
 
-        for receiver_name in receiver_names:
-            message = InternalMessage(
-                to=receiver_name,
-                sender=self.name,
-                body=transcription,
-            )
-            await self.send(message)
+        message = InternalMessage(
+            to=settings.agent_settings.text_belief_extractor_name,
+            sender=self.name,
+            body=transcription,
+        )
+        await self.send(message)
 
     async def _transcribing_loop(self) -> None:
         """
@@ -129,10 +146,9 @@ class TranscriptionAgent(BaseAgent):
                 audio = np.frombuffer(audio_data, dtype=np.float32)
                 speech = await self._transcribe(audio)
                 if not speech:
-                    self.logger.info("Nothing transcribed.")
+                    self.logger.debug("Nothing transcribed.")
                     continue
 
-                self.logger.info("Transcribed speech: %s", speech)
                 await self._share_transcription(speech)
             except Exception as e:
                 self.logger.error(f"Error in transcription loop: {e}")

src/control_backend/agents/perception/vad_agent.py

@@ -1,4 +1,12 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import asyncio
+import logging
+import uuid
 
 import numpy as np
 import torch
@@ -7,10 +15,13 @@ import zmq.asyncio as azmq
 
 from control_backend.agents import BaseAgent
 from control_backend.core.config import settings
+from control_backend.schemas.internal_message import InternalMessage
 
 from ...schemas.program_status import PROGRAM_STATUS, ProgramStatus
 from .transcription_agent.transcription_agent import TranscriptionAgent
 
+experiment_logger = logging.getLogger(settings.logging_settings.experiment_logger_name)
+
 
 class SocketPoller[T]:
     """
@@ -86,6 +97,12 @@ class VADAgent(BaseAgent):
         self.audio_buffer = np.array([], dtype=np.float32)
         self.i_since_speech = settings.behaviour_settings.vad_initial_since_speech
         self._ready = asyncio.Event()
+
+        # Pause control
+        self._reset_needed = False
+        self._paused = asyncio.Event()
+        self._paused.set()  # Not paused at start
+
         self.model = None
 
     async def setup(self):
@@ -213,6 +230,16 @@ class VADAgent(BaseAgent):
         """
         await self._ready.wait()
         while self._running:
+            await self._paused.wait()
+
+            # After being unpaused, reset stream and buffers
+            if self._reset_needed:
+                self.logger.debug("Resuming: resetting stream and buffers.")
+                await self._reset_stream()
+                self.audio_buffer = np.array([], dtype=np.float32)
+                self.i_since_speech = settings.behaviour_settings.vad_initial_since_speech
+                self._reset_needed = False
+
             assert self.audio_in_poller is not None
             data = await self.audio_in_poller.poll()
             if data is None:
@@ -235,6 +262,18 @@ class VADAgent(BaseAgent):
             if prob > prob_threshold:
                 if self.i_since_speech > non_speech_patience + begin_silence_length:
                     self.logger.debug("Speech started.")
+                    reference = str(uuid.uuid4())
+                    experiment_logger.chat(
+                        "...",
+                        extra={"role": "user", "reference": reference, "partial": True},
+                    )
+                    await self.send(
+                        InternalMessage(
+                            to=settings.agent_settings.transcription_name,
+                            body=reference,
+                            thread="voice_activity",
+                        )
+                    )
                 self.audio_buffer = np.append(self.audio_buffer, chunk)
                 self.i_since_speech = 0
                 continue
@@ -256,3 +295,27 @@ class VADAgent(BaseAgent):
             # Prepend the last few chunks that had no speech, for a more fluent boundary.
             self.audio_buffer = np.append(self.audio_buffer, chunk)
             self.audio_buffer = self.audio_buffer[-begin_silence_length * len(chunk) :]
+
+    async def handle_message(self, msg: InternalMessage):
+        """
+        Handle incoming messages.
+
+        Expects messages to pause or resume the VAD 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 VAD processing.")
+                self._paused.clear()
+                # If the robot needs to pick up speaking where it left off, do not set _reset_needed
+                self._reset_needed = True
+            elif msg.body == "RESUME":
+                self.logger.info("Resuming VAD 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}")

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 cv2
+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)
+
+        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.video_in_socket.setsockopt(zmq.CONFLATE, 1)
+
+        self.add_behavior(self.emotion_update_loop())
+
+        self.logger.info("Finished setting up %s", self.name)
+
+    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()
+
+                frame_bytes = await self.video_in_socket.recv()
+
+                # Convert bytes to a numpy buffer
+                nparr = np.frombuffer(frame_bytes, np.uint8)
+
+                # Decode image into the generic Numpy Array DeepFace expects
+                frame_image = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+
+                if frame_image is None:
+                    # Could not decode image, skip this frame
+                    self.logger.warning("Received invalid video frame, skipping.")
+                    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
+                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.")
+
+    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()

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

@@ -0,0 +1,54 @@
+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):
+        print("Loading Deepface Emotion Model...")
+        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)
+        print("Deepface Emotion Model loaded.")
+
+    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

src/control_backend/agents/user_interrupt/__init__.py

@@ -0,0 +1,5 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""

src/control_backend/agents/user_interrupt/user_interrupt_agent.py

@@ -1,12 +1,28 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import json
+import logging
 
 import zmq
 from zmq.asyncio import Context
 
 from control_backend.agents import BaseAgent
+from control_backend.agents.bdi.agentspeak_generator import AgentSpeakGenerator
 from control_backend.core.agent_system import InternalMessage
 from control_backend.core.config import settings
-from control_backend.schemas.ri_message import GestureCommand, RIEndpoint, SpeechCommand
+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,
+    RIEndpoint,
+    SpeechCommand,
+)
+
+experiment_logger = logging.getLogger(settings.logging_settings.experiment_logger_name)
 
 
 class UserInterruptAgent(BaseAgent):
@@ -18,29 +34,55 @@ class UserInterruptAgent(BaseAgent):
 
     - Send a prioritized message to the `RobotSpeechAgent`
     - Send a prioritized gesture to the `RobotGestureAgent`
-    - Send a belief override to the `BDIProgramManager`in order to activate a
+    - Send a belief override to the `BDI Core` in order to activate a
         trigger/conditional norm or complete a goal.
 
     Prioritized actions clear the current RI queue before inserting the new item,
     ensuring they are executed immediately after Pepper's current action has been fulfilled.
 
-    :ivar sub_socket: The ZMQ SUB socket used to receive user intterupts.
+    :ivar sub_socket: The ZMQ SUB socket used to receive user interrupts.
     """
 
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
         self.sub_socket = None
+        self.pub_socket = None
+        self._trigger_map = {}
+        self._trigger_reverse_map = {}
+
+        self._goal_map = {}  # id -> sluggified goal
+        self._goal_reverse_map = {}  # sluggified goal -> id
+
+        self._cond_norm_map = {}  # id -> sluggified cond norm
+        self._cond_norm_reverse_map = {}  # sluggified cond norm -> id
+
+    async def setup(self):
+        """
+        Initialize the agent by setting up ZMQ sockets for receiving button events and
+        publishing updates.
+        """
+        context = Context.instance()
+
+        self.sub_socket = context.socket(zmq.SUB)
+        self.sub_socket.connect(settings.zmq_settings.internal_sub_address)
+        self.sub_socket.subscribe("button_pressed")
+
+        self.pub_socket = context.socket(zmq.PUB)
+        self.pub_socket.connect(settings.zmq_settings.internal_pub_address)
+
+        self.add_behavior(self._receive_button_event())
 
     async def _receive_button_event(self):
         """
-        The behaviour of the UserInterruptAgent.
-        Continuous loop that receives button_pressed events from the button_pressed HTTP endpoint.
-        These events contain a type and a context.
+        Main loop to receive and process button press events from the UI.
 
-        These are the different types and contexts:
-        - type: "speech", context: string that the robot has to say.
-        - type: "gesture", context: single gesture name that the robot has to perform.
-        - type: "override", context: belief_id that overrides the goal/trigger/conditional norm.
+        Handles different event types:
+        - `speech`: Triggers immediate robot speech.
+        - `gesture`: Triggers an immediate robot gesture.
+        - `override`: Forces a belief, trigger, or goal completion in the BDI core.
+        - `override_unachieve`: Removes a belief from the BDI core.
+        - `pause`: Toggles the system's pause state.
+        - `next_phase` / `reset_phase`: Controls experiment flow.
         """
         while True:
             topic, body = await self.sub_socket.recv_multipart()
@@ -53,30 +95,217 @@ class UserInterruptAgent(BaseAgent):
                 self.logger.error("Received invalid JSON payload on topic %s", topic)
                 continue
 
-            if event_type == "speech":
-                await self._send_to_speech_agent(event_context)
-                self.logger.info(
-                    "Forwarded button press (speech) with context '%s' to RobotSpeechAgent.",
-                    event_context,
-                )
-            elif event_type == "gesture":
-                await self._send_to_gesture_agent(event_context)
-                self.logger.info(
-                    "Forwarded button press (gesture) with context '%s' to RobotGestureAgent.",
-                    event_context,
-                )
-            elif event_type == "override":
-                await self._send_to_program_manager(event_context)
-                self.logger.info(
-                    "Forwarded button press (override) with context '%s' to BDIProgramManager.",
-                    event_context,
-                )
-            else:
-                self.logger.warning(
-                    "Received button press with unknown type '%s' (context: '%s').",
-                    event_type,
-                    event_context,
-                )
+            self.logger.debug("Received event type %s", event_type)
+
+            match event_type:
+                case "speech":
+                    await self._send_to_speech_agent(event_context)
+                    self.logger.info(
+                        "Forwarded button press (speech) with context '%s' to RobotSpeechAgent.",
+                        event_context,
+                    )
+                case "gesture":
+                    await self._send_to_gesture_agent(event_context)
+                    self.logger.info(
+                        "Forwarded button press (gesture) with context '%s' to RobotGestureAgent.",
+                        event_context,
+                    )
+                case "override":
+                    ui_id = str(event_context)
+                    if asl_trigger := self._trigger_map.get(ui_id):
+                        await self._send_to_bdi("force_trigger", asl_trigger)
+                        self.logger.info(
+                            "Forwarded button press (override) with context '%s' to BDI Core.",
+                            event_context,
+                        )
+                    elif asl_cond_norm := self._cond_norm_map.get(ui_id):
+                        await self._send_to_bdi_belief(asl_cond_norm, "cond_norm")
+                        self.logger.info(
+                            "Forwarded button press (override) with context '%s' to BDI Core.",
+                            event_context,
+                        )
+                    elif asl_goal := self._goal_map.get(ui_id):
+                        await self._send_to_bdi_belief(asl_goal, "goal")
+                        self.logger.info(
+                            "Forwarded button press (override) with context '%s' to BDI Core.",
+                            event_context,
+                        )
+                        # Send achieve_goal to program manager to update semantic belief extractor
+                        goal_achieve_msg = InternalMessage(
+                            to=settings.agent_settings.bdi_program_manager_name,
+                            thread="achieve_goal",
+                            body=ui_id,
+                        )
+
+                        await self.send(goal_achieve_msg)
+                    else:
+                        self.logger.warning("Could not determine which element to override.")
+                case "override_unachieve":
+                    ui_id = str(event_context)
+                    if asl_cond_norm := self._cond_norm_map.get(ui_id):
+                        await self._send_to_bdi_belief(asl_cond_norm, "cond_norm", True)
+                        self.logger.info(
+                            "Forwarded button press (override_unachieve)"
+                            "with context '%s' to BDI Core.",
+                            event_context,
+                        )
+                    else:
+                        self.logger.warning(
+                            "Could not determine which conditional norm to unachieve."
+                        )
+
+                case "pause":
+                    self.logger.debug(
+                        "Received pause/resume button press with context '%s'.", event_context
+                    )
+                    await self._send_pause_command(event_context)
+                    if event_context:
+                        self.logger.info("Sent pause command.")
+                    else:
+                        self.logger.info("Sent resume command.")
+
+                case "next_phase" | "reset_phase":
+                    await self._send_experiment_control_to_bdi_core(event_type)
+                case _:
+                    self.logger.warning(
+                        "Received button press with unknown type '%s' (context: '%s').",
+                        event_type,
+                        event_context,
+                    )
+
+    async def handle_message(self, msg: InternalMessage):
+        """
+        Handles internal messages from other agents, such as program updates or trigger
+        notifications.
+
+        :param msg: The incoming :class:`~control_backend.core.agent_system.InternalMessage`.
+        """
+        match msg.thread:
+            case "new_program":
+                self._create_mapping(msg.body)
+            case "trigger_start":
+                # msg.body is the sluggified trigger
+                asl_slug = msg.body
+                ui_id = self._trigger_reverse_map.get(asl_slug)
+
+                if ui_id:
+                    payload = {"type": "trigger_update", "id": ui_id, "achieved": True}
+                    await self._send_experiment_update(payload)
+                    self.logger.info(f"UI Update: Trigger {asl_slug} started (ID: {ui_id})")
+            case "trigger_end":
+                asl_slug = msg.body
+                ui_id = self._trigger_reverse_map.get(asl_slug)
+                if ui_id:
+                    payload = {"type": "trigger_update", "id": ui_id, "achieved": False}
+                    await self._send_experiment_update(payload)
+                    self.logger.info(f"UI Update: Trigger {asl_slug} ended (ID: {ui_id})")
+            case "transition_phase":
+                new_phase_id = msg.body
+                self.logger.info(f"Phase transition detected: {new_phase_id}")
+
+                payload = {"type": "phase_update", "id": new_phase_id}
+
+                await self._send_experiment_update(payload)
+            case "goal_start":
+                goal_name = msg.body
+                ui_id = self._goal_reverse_map.get(goal_name)
+                if ui_id:
+                    payload = {"type": "goal_update", "id": ui_id, "active": True}
+                    await self._send_experiment_update(payload)
+                    self.logger.info(f"UI Update: Goal {goal_name} started (ID: {ui_id})")
+            case "active_norms_update":
+                active_norms_asl = [
+                    s.strip("() '\",") for s in msg.body.split(",") if s.strip("() '\",")
+                ]
+                await self._broadcast_cond_norms(active_norms_asl)
+            case _:
+                self.logger.debug(f"Received internal message on unhandled thread: {msg.thread}")
+
+    async def _broadcast_cond_norms(self, active_slugs: list[str]):
+        """
+        Broadcasts the current activation state of all conditional norms to the UI.
+
+        :param active_slugs: A list of sluggified norm names currently active in the BDI core.
+        """
+        updates = []
+        for asl_slug, ui_id in self._cond_norm_reverse_map.items():
+            is_active = asl_slug in active_slugs
+            updates.append({"id": ui_id, "active": is_active})
+
+        payload = {"type": "cond_norms_state_update", "norms": updates}
+
+        if self.pub_socket:
+            topic = b"status"
+            body = json.dumps(payload).encode("utf-8")
+            await self.pub_socket.send_multipart([topic, body])
+            # self.logger.info(f"UI Update: Active norms {updates}")
+
+    def _create_mapping(self, program_json: str):
+        """
+        Creates a bidirectional mapping between UI identifiers and AgentSpeak slugs.
+
+        :param program_json: The JSON representation of the behavioral program.
+        """
+        try:
+            program = Program.model_validate_json(program_json)
+            self._trigger_map = {}
+            self._trigger_reverse_map = {}
+            self._goal_map = {}
+            self._cond_norm_map = {}
+            self._cond_norm_reverse_map = {}
+
+            def _register_goal(goal: Goal):
+                """Recursively register goals and their subgoals."""
+                slug = AgentSpeakGenerator.slugify(goal)
+                self._goal_map[str(goal.id)] = slug
+                self._goal_reverse_map[slug] = str(goal.id)
+
+                for step in goal.plan.steps:
+                    if isinstance(step, Goal):
+                        _register_goal(step)
+
+            for phase in program.phases:
+                for trigger in phase.triggers:
+                    slug = AgentSpeakGenerator.slugify(trigger)
+                    self._trigger_map[str(trigger.id)] = slug
+                    self._trigger_reverse_map[slug] = str(trigger.id)
+
+                for goal in phase.goals:
+                    _register_goal(goal)
+
+                for goal, id in self._goal_reverse_map.items():
+                    self.logger.debug(f"Goal mapping: UI ID {goal} -> {id}")
+
+                for norm in phase.norms:
+                    if isinstance(norm, ConditionalNorm):
+                        asl_slug = AgentSpeakGenerator.slugify(norm)
+
+                        norm_id = str(norm.id)
+
+                        self._cond_norm_map[norm_id] = asl_slug
+                        self._cond_norm_reverse_map[norm.norm] = norm_id
+                        self.logger.debug("Added conditional norm %s", asl_slug)
+
+            self.logger.info(
+                f"Mapped {len(self._trigger_map)} triggers and {len(self._goal_map)} goals "
+                f"and {len(self._cond_norm_map)} conditional norms for UserInterruptAgent."
+            )
+        except Exception as e:
+            self.logger.error(f"Mapping failed: {e}")
+
+    async def _send_experiment_update(self, data, should_log: bool = True):
+        """
+        Publishes an experiment state update to the internal ZMQ bus for the UI.
+
+        :param data: The update payload.
+        :param should_log: Whether to log the update.
+        """
+        if self.pub_socket:
+            topic = b"experiment"
+            body = json.dumps(data).encode("utf-8")
+            await self.pub_socket.send_multipart([topic, body])
+            if should_log:
+                self.logger.debug(f"Sent experiment update: {data}")
 
     async def _send_to_speech_agent(self, text_to_say: str):
         """
@@ -84,6 +313,7 @@ class UserInterruptAgent(BaseAgent):
 
         :param text_to_say: The string that the robot has to say.
         """
+        experiment_logger.chat(text_to_say, extra={"role": "assistant"})
         cmd = SpeechCommand(data=text_to_say, is_priority=True)
         out_msg = InternalMessage(
             to=settings.agent_settings.robot_speech_name,
@@ -109,38 +339,93 @@ class UserInterruptAgent(BaseAgent):
         )
         await self.send(out_msg)
 
-    async def _send_to_program_manager(self, belief_id: str):
-        """
-        Send a button_override belief to the BDIProgramManager.
+    async def _send_to_bdi(self, thread: str, body: str):
+        """Send slug of trigger to BDI"""
+        msg = InternalMessage(to=settings.agent_settings.bdi_core_name, thread=thread, body=body)
+        await self.send(msg)
+        self.logger.info(f"Directly forced {thread} in BDI: {body}")
 
-        :param belief_id: The belief_id that overrides the goal/trigger/conditional norm.
-        this id can belong to a basic belief or an inferred belief.
-        See also: https://utrechtuniversity.youtrack.cloud/articles/N25B-A-27/UI-components
+    async def _send_to_bdi_belief(self, asl: str, asl_type: str, unachieve: bool = False):
+        """Send belief to BDI Core"""
+        if asl_type == "goal":
+            belief_name = f"achieved_{asl}"
+        elif asl_type == "cond_norm":
+            belief_name = f"force_{asl}"
+        else:
+            self.logger.warning("Tried to send belief with unknown type")
+            return
+        belief = Belief(name=belief_name, arguments=None)
+        self.logger.debug(f"Sending belief to BDI Core: {belief_name}")
+        # Conditional norms are unachieved by removing the belief
+        belief_message = (
+            BeliefMessage(delete=[belief]) if unachieve else BeliefMessage(create=[belief])
+        )
+        msg = InternalMessage(
+            to=settings.agent_settings.bdi_core_name,
+            thread="beliefs",
+            body=belief_message.model_dump_json(),
+        )
+        await self.send(msg)
+
+    async def _send_experiment_control_to_bdi_core(self, type):
         """
-        data = {"belief": belief_id}
-        message = InternalMessage(
-            to=settings.agent_settings.bdi_program_manager_name,
+        method to send experiment control buttons to bdi core.
+
+        :param type: the type of control button we should send to the bdi core.
+        """
+        # Switch which thread we should send to bdi core
+        thread = ""
+        match type:
+            case "next_phase":
+                thread = "force_next_phase"
+            case "reset_phase":
+                thread = "reset_current_phase"
+            case "reset_experiment":
+                thread = "reset_experiment"
+            case _:
+                self.logger.warning(
+                    "Received unknown experiment control type '%s' to send to BDI Core.",
+                    type,
+                )
+
+        out_msg = InternalMessage(
+            to=settings.agent_settings.bdi_core_name,
             sender=self.name,
-            body=json.dumps(data),
-            thread="belief_override_id",
-        )
-        await self.send(message)
-        self.logger.info(
-            "Sent button_override belief with id '%s' to Program manager.",
-            belief_id,
+            thread=thread,
+            body="",
         )
+        self.logger.debug("Sending experiment control '%s' to BDI Core.", thread)
+        await self.send(out_msg)
 
-    async def setup(self):
+    async def _send_pause_command(self, pause: str):
         """
-        Initialize the agent.
-
-        Connects the internal ZMQ SUB socket and subscribes to the 'button_pressed' topic.
-        Starts the background behavior to receive the user interrupts.
+        Send a pause command to the other internal agents; for now just VAD and VED agent.
         """
-        context = Context.instance()
-
-        self.sub_socket = context.socket(zmq.SUB)
-        self.sub_socket.connect(settings.zmq_settings.internal_sub_address)
-        self.sub_socket.subscribe("button_pressed")
-
-        self.add_behavior(self._receive_button_event())
+        if pause == "true":
+            # Send pause to VAD and VED agent
+            vad_message = InternalMessage(
+                to=[
+                    settings.agent_settings.vad_name,
+                    settings.agent_settings.visual_emotion_recognition_name,
+                    settings.agent_settings.face_agent_name,
+                ],
+                sender=self.name,
+                body="PAUSE",
+            )
+            await self.send(vad_message)
+            # Voice Activity Detection and Visual Emotion Recognition agents
+            self.logger.info("Sent pause command to perception agents.")
+        else:
+            # Send resume to VAD and VED agents
+            vad_message = InternalMessage(
+                to=[
+                    settings.agent_settings.vad_name,
+                    settings.agent_settings.visual_emotion_recognition_name,
+                    settings.agent_settings.face_agent_name,
+                ],
+                sender=self.name,
+                body="RESUME",
+            )
+            await self.send(vad_message)
+            # Voice Activity Detection and Visual Emotion Recognition agents
+            self.logger.info("Sent resume command to perception agents.")

src/control_backend/api/__init__.py

@@ -0,0 +1,5 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""

src/control_backend/api/v1/__init__.py

@@ -0,0 +1,5 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""

src/control_backend/api/v1/endpoints/__init__.py

@@ -0,0 +1,5 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""

src/control_backend/api/v1/endpoints/button_pressed.py

@@ -1,31 +0,0 @@
-import logging
-
-from fastapi import APIRouter, Request
-
-from control_backend.schemas.events import ButtonPressedEvent
-
-logger = logging.getLogger(__name__)
-router = APIRouter()
-
-
-@router.post("/button_pressed", status_code=202)
-async def receive_button_event(event: ButtonPressedEvent, request: Request):
-    """
-    Endpoint to handle external button press events.
-
-    Validates the event payload and publishes it to the internal 'button_pressed' topic.
-    Subscribers (in this case user_interrupt_agent) will pick this up to trigger
-    specific behaviors or state changes.
-
-    :param event: The parsed ButtonPressedEvent object.
-    :param request: The FastAPI request object.
-    """
-    logger.debug("Received button event: %s | %s", event.type, event.context)
-
-    topic = b"button_pressed"
-    body = event.model_dump_json().encode()
-
-    pub_socket = request.app.state.endpoints_pub_socket
-    await pub_socket.send_multipart([topic, body])
-
-    return {"status": "Event received"}

src/control_backend/api/v1/endpoints/logs.py

@@ -1,8 +1,15 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import logging
+from pathlib import Path
 
 import zmq
-from fastapi import APIRouter
-from fastapi.responses import StreamingResponse
+from fastapi import APIRouter, HTTPException
+from fastapi.responses import FileResponse, StreamingResponse
 from zmq.asyncio import Context
 
 from control_backend.core.config import settings
@@ -38,3 +45,29 @@ async def log_stream():
             yield f"data: {message}\n\n"
 
     return StreamingResponse(gen(), media_type="text/event-stream")
+
+
+LOGGING_DIR = Path(settings.logging_settings.experiment_log_directory).resolve()
+
+
+@router.get("/logs/files")
+@router.get("/api/logs/files")
+async def log_directory():
+    """
+    Get a list of all log files stored in the experiment log file directory.
+    """
+    return [f.name for f in LOGGING_DIR.glob("*.log")]
+
+
+@router.get("/logs/files/{filename}")
+@router.get("/api/logs/files/{filename}")
+async def log_file(filename: str):
+    # Prevent path-traversal
+    file_path = (LOGGING_DIR / filename).resolve()  # This .resolve() is important
+    if not file_path.is_relative_to(LOGGING_DIR):
+        raise HTTPException(status_code=400, detail="Invalid filename.")
+
+    if not file_path.is_file():
+        raise HTTPException(status_code=404, detail="File not found.")
+
+    return FileResponse(file_path, filename=file_path.name)

src/control_backend/api/v1/endpoints/message.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import logging
 
 from fastapi import APIRouter, Request

src/control_backend/api/v1/endpoints/program.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import logging
 
 from fastapi import APIRouter, Request

src/control_backend/api/v1/endpoints/robot.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import asyncio
 import json
 import logging
@@ -137,7 +143,6 @@ async def ping_stream(request: Request):
                 logger.info("Client disconnected from SSE")
                 break
 
-            logger.debug(f"Yielded new connection event in robot ping router: {str(connected)}")
             connectedJson = json.dumps(connected)
             yield (f"data: {connectedJson}\n\n")
 

src/control_backend/api/v1/endpoints/sse.py

@@ -1,12 +0,0 @@
-from fastapi import APIRouter, Request
-
-router = APIRouter()
-
-
-# TODO: implement
-@router.get("/sse")
-async def sse(request: Request):
-    """
-    Placeholder for future Server-Sent Events endpoint.
-    """
-    pass

src/control_backend/api/v1/endpoints/user_interact.py

@@ -0,0 +1,100 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+import asyncio
+import logging
+
+import zmq
+import zmq.asyncio
+from fastapi import APIRouter, Request
+from fastapi.responses import StreamingResponse
+from zmq.asyncio import Context
+
+from control_backend.core.config import settings
+from control_backend.schemas.events import ButtonPressedEvent
+
+logger = logging.getLogger(__name__)
+router = APIRouter()
+
+
+@router.post("/button_pressed", status_code=202)
+async def receive_button_event(event: ButtonPressedEvent, request: Request):
+    """
+    Endpoint to handle external button press events.
+
+    Validates the event payload and publishes it to the internal 'button_pressed' topic.
+    Subscribers (in this case user_interrupt_agent) will pick this up to trigger
+    specific behaviors or state changes.
+
+    :param event: The parsed ButtonPressedEvent object.
+    :param request: The FastAPI request object.
+    """
+    logger.debug("Received button event: %s | %s", event.type, event.context)
+
+    topic = b"button_pressed"
+    body = event.model_dump_json().encode()
+
+    pub_socket = request.app.state.endpoints_pub_socket
+    await pub_socket.send_multipart([topic, body])
+
+    return {"status": "Event received"}
+
+
+@router.get("/experiment_stream")
+async def experiment_stream(request: Request):
+    # Use the asyncio-compatible context
+    context = Context.instance()
+    socket = context.socket(zmq.SUB)
+
+    # Connect and subscribe
+    socket.connect(settings.zmq_settings.internal_sub_address)
+    socket.subscribe(b"experiment")
+
+    async def gen():
+        try:
+            while True:
+                # Check if client closed the tab
+                if await request.is_disconnected():
+                    logger.error("Client disconnected from experiment stream.")
+                    break
+
+                try:
+                    parts = await asyncio.wait_for(socket.recv_multipart(), timeout=10.0)
+                    _, message = parts
+                    yield f"data: {message.decode().strip()}\n\n"
+                except TimeoutError:
+                    continue
+        finally:
+            socket.close()
+
+    return StreamingResponse(gen(), media_type="text/event-stream")
+
+
+@router.get("/status_stream")
+async def status_stream(request: Request):
+    context = Context.instance()
+    socket = context.socket(zmq.SUB)
+    socket.connect(settings.zmq_settings.internal_sub_address)
+
+    socket.subscribe(b"status")
+
+    async def gen():
+        try:
+            while True:
+                if await request.is_disconnected():
+                    break
+                try:
+                    # Shorter timeout since this is frequent
+                    parts = await asyncio.wait_for(socket.recv_multipart(), timeout=0.5)
+                    _, message = parts
+                    yield f"data: {message.decode().strip()}\n\n"
+                except TimeoutError:
+                    yield ": ping\n\n"  # Keep the connection alive
+                    continue
+        finally:
+            socket.close()
+
+    return StreamingResponse(gen(), media_type="text/event-stream")

src/control_backend/api/v1/router.py

@@ -1,17 +1,21 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from fastapi.routing import APIRouter
 
-from control_backend.api.v1.endpoints import button_pressed, logs, message, program, robot, sse
+from control_backend.api.v1.endpoints import logs, message, program, robot, user_interact
 
 api_router = APIRouter()
 
 api_router.include_router(message.router, tags=["Messages"])
 
-api_router.include_router(sse.router, tags=["SSE"])
-
-api_router.include_router(robot.router, prefix="/robot", tags=["Pings", "Commands"])
+api_router.include_router(robot.router, prefix="/robot", tags=["Pings", "Commands", "Face"])
 
 api_router.include_router(logs.router, tags=["Logs"])
 
 api_router.include_router(program.router, tags=["Program"])
 
-api_router.include_router(button_pressed.router, tags=["Button Pressed Events"])
+api_router.include_router(user_interact.router, tags=["Button Pressed Events"])

src/control_backend/core/__init__.py

@@ -0,0 +1,5 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""

src/control_backend/core/agent_system.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import asyncio
 import logging
 from abc import ABC, abstractmethod
@@ -22,10 +28,22 @@ class AgentDirectory:
 
     @staticmethod
     def register(name: str, agent: "BaseAgent"):
+        """
+        Registers an agent instance with a unique name.
+
+        :param name: The name of the agent.
+        :param agent: The :class:`BaseAgent` instance.
+        """
         _agent_directory[name] = agent
 
     @staticmethod
     def get(name: str) -> "BaseAgent | None":
+        """
+        Retrieves a registered agent instance by name.
+
+        :param name: The name of the agent to retrieve.
+        :return: The :class:`BaseAgent` instance, or None if not found.
+        """
         return _agent_directory.get(name)
 
 
@@ -60,6 +78,9 @@ class BaseAgent(ABC):
         self._tasks: set[asyncio.Task] = set()
         self._running = False
 
+        self._internal_pub_socket: None | azmq.Socket = None
+        self._internal_sub_socket: None | azmq.Socket = None
+
         # Register immediately
         AgentDirectory.register(name, self)
 
@@ -117,7 +138,7 @@ class BaseAgent(ABC):
             task.cancel()
         self.logger.info(f"Agent {self.name} stopped")
 
-    async def send(self, message: InternalMessage):
+    async def send(self, message: InternalMessage, should_log: bool = True):
         """
         Send a message to another agent.
 
@@ -130,17 +151,26 @@ class BaseAgent(ABC):
 
         :param message: The message to send.
         """
-        target = AgentDirectory.get(message.to)
         message.sender = self.name
-        if target:
-            await target.inbox.put(message)
-            self.logger.debug(f"Sent message {message.body} to {message.to} via regular inbox.")
-        else:
-            # Apparently target agent is on a different process, send via ZMQ
-            topic = f"internal/{message.to}".encode()
-            body = message.model_dump_json().encode()
-            await self._internal_pub_socket.send_multipart([topic, body])
-            self.logger.debug(f"Sent message {message.body} to {message.to} via ZMQ.")
+        to = message.to
+        receivers = [to] if isinstance(to, str) else to
+
+        for receiver in receivers:
+            target = AgentDirectory.get(receiver)
+
+            if target:
+                await target.inbox.put(message)
+                if should_log:
+                    self.logger.debug(
+                        f"Sent message {message.body} to {message.to} via regular inbox."
+                    )
+            else:
+                # Apparently target agent is on a different process, send via ZMQ
+                topic = f"internal/{receiver}".encode()
+                body = message.model_dump_json().encode()
+                await self._internal_pub_socket.send_multipart([topic, body])
+                if should_log:
+                    self.logger.debug(f"Sent message {message.body} to {message.to} via ZMQ.")
 
     async def _process_inbox(self):
         """
@@ -150,7 +180,6 @@ class BaseAgent(ABC):
         """
         while self._running:
             msg = await self.inbox.get()
-            self.logger.debug(f"Received message from {msg.sender}.")
             await self.handle_message(msg)
 
     async def _receive_internal_zmq_loop(self):

src/control_backend/core/config.py

@@ -1,4 +1,8 @@
 """
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+--------------------------------------------------------------------------------
 An exhaustive overview of configurable options. All of these can be set using environment variables
 by nesting with double underscores (__). Start from the ``Settings`` class.
 
@@ -35,7 +39,6 @@ class AgentSettings(BaseModel):
     Names of the various agents in the system. These names are used for routing messages.
 
     :ivar bdi_core_name: Name of the BDI Core Agent.
-    :ivar bdi_belief_collector_name: Name of the Belief Collector Agent.
     :ivar bdi_program_manager_name: Name of the BDI Program Manager Agent.
     :ivar text_belief_extractor_name: Name of the Text Belief Extractor Agent.
     :ivar vad_name: Name of the Voice Activity Detection (VAD) Agent.
@@ -50,8 +53,8 @@ class AgentSettings(BaseModel):
 
     # agent names
     bdi_core_name: str = "bdi_core_agent"
-    bdi_belief_collector_name: str = "belief_collector_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"
@@ -61,6 +64,7 @@ class AgentSettings(BaseModel):
     robot_speech_name: str = "robot_speech_agent"
     robot_gesture_name: str = "robot_gesture_agent"
     user_interrupt_name: str = "user_interrupt_agent"
+    face_agent_name: str = "face_detection_agent"
 
 
 class BehaviourSettings(BaseModel):
@@ -79,6 +83,12 @@ 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 trigger_time_to_wait: Amount of milliseconds to wait before informing the UI about trigger
+     completion.
+    :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.
     """
 
     # ATTENTION: When adding/removing settings, make sure to update the .env.example file
@@ -102,6 +112,14 @@ class BehaviourSettings(BaseModel):
     # Text belief extractor settings
     conversation_history_length_limit: int = 10
 
+    # AgentSpeak related settings
+    trigger_time_to_wait: int = 2000
+    agentspeak_file: str = "src/control_backend/agents/bdi/agentspeak.asl"
+
+    # Visual Emotion Recognition settings
+    visual_emotion_recognition_window_duration_s: int = 5
+    visual_emotion_recognition_min_frames_per_face: int = 3
+
 
 class LLMSettings(BaseModel):
     """
@@ -119,6 +137,7 @@ class LLMSettings(BaseModel):
 
     local_llm_url: str = "http://localhost:1234/v1/chat/completions"
     local_llm_model: str = "gpt-oss"
+    api_key: str = ""
     chat_temperature: float = 1.0
     code_temperature: float = 0.3
     n_parallel: int = 4
@@ -155,6 +174,20 @@ class SpeechModelSettings(BaseModel):
     openai_model_name: str = "small.en"
 
 
+class LoggingSettings(BaseModel):
+    """
+    Configuration for logging.
+
+    :ivar logging_config_file: Path to the logging configuration file.
+    :ivar experiment_log_directory: Location of the experiment logs. Must match the logging config.
+    :ivar experiment_logger_name: Name of the experiment logger. Must match the logging config.
+    """
+
+    logging_config_file: str = ".logging_config.yaml"
+    experiment_log_directory: str = "experiment_logs"
+    experiment_logger_name: str = "experiment"
+
+
 class Settings(BaseSettings):
     """
     Global application settings.
@@ -176,6 +209,8 @@ class Settings(BaseSettings):
 
     ri_host: str = "localhost"
 
+    logging_settings: LoggingSettings = LoggingSettings()
+
     zmq_settings: ZMQSettings = ZMQSettings()
 
     agent_settings: AgentSettings = AgentSettings()

src/control_backend/logging/__init__.py

@@ -1 +1,10 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+from .dated_file_handler import DatedFileHandler as DatedFileHandler
+from .optional_field_formatter import OptionalFieldFormatter as OptionalFieldFormatter
+from .partial_filter import PartialFilter as PartialFilter
 from .setup_logging import setup_logging as setup_logging

src/control_backend/logging/dated_file_handler.py

@@ -0,0 +1,44 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+from datetime import datetime
+from logging import FileHandler
+from pathlib import Path
+
+
+class DatedFileHandler(FileHandler):
+    def __init__(self, file_prefix: str, **kwargs):
+        if not file_prefix:
+            raise ValueError("`file_prefix` argument cannot be empty.")
+        self._file_prefix = file_prefix
+        kwargs["filename"] = self._make_filename()
+        super().__init__(**kwargs)
+
+    def _make_filename(self) -> str:
+        """
+        Create the filename for the current logfile, using the configured file prefix and the
+        current date and time. If the directory does not exist, it gets created.
+
+        :return: A filepath.
+        """
+        filepath = Path(f"{self._file_prefix}-{datetime.now():%Y%m%d-%H%M%S}.log")
+        if not filepath.parent.is_dir():
+            filepath.parent.mkdir(parents=True, exist_ok=True)
+        return str(filepath)
+
+    def do_rollover(self):
+        """
+        Close the current logfile and create a new one with the current date and time.
+        """
+        self.acquire()
+        try:
+            if self.stream:
+                self.stream.close()
+
+            self.baseFilename = self._make_filename()
+            self.stream = self._open()
+        finally:
+            self.release()

src/control_backend/logging/optional_field_formatter.py

@@ -0,0 +1,73 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+import logging
+import re
+
+
+class OptionalFieldFormatter(logging.Formatter):
+    """
+    Logging formatter that supports optional fields marked by `?`.
+
+    Optional fields are denoted by placing a `?` after the field name inside
+    the parentheses, e.g., `%(role?)s`. If the field is not provided in the
+    log call's `extra` dict, it will use the default value from `defaults`
+    or `None` if no default is specified.
+
+    :param fmt: Format string with optional `%(name?)s` style fields.
+    :type fmt: str or None
+    :param datefmt: Date format string, passed to parent :class:`logging.Formatter`.
+    :type datefmt: str or None
+    :param style: Formatting style, must be '%'. Passed to parent.
+    :type style: str
+    :param defaults: Default values for optional fields when not provided.
+    :type defaults: dict or None
+
+    :example:
+
+        >>> formatter = OptionalFieldFormatter(
+        ...     fmt="%(asctime)s %(levelname)s %(role?)s %(message)s",
+        ...     defaults={"role": ""-""}
+        ... )
+        >>> handler = logging.StreamHandler()
+        >>> handler.setFormatter(formatter)
+        >>> logger = logging.getLogger(__name__)
+        >>> logger.addHandler(handler)
+        >>>
+        >>> logger.chat("Hello there!", extra={"role": "USER"})
+        2025-01-15 10:30:00 CHAT USER Hello there!
+        >>>
+        >>> logger.info("A logging message")
+        2025-01-15 10:30:01 INFO - A logging message
+
+    .. note::
+        Only `%`-style formatting is supported. The `{` and `$` styles are not
+        compatible with this formatter.
+
+    .. seealso::
+        :class:`logging.Formatter` for base formatter documentation.
+    """
+
+    # Match %(name?)s or %(name?)d etc.
+    OPTIONAL_PATTERN = re.compile(r"%\((\w+)\?\)([sdifFeEgGxXocrba%])")
+
+    def __init__(self, fmt=None, datefmt=None, style="%", defaults=None):
+        self.defaults = defaults or {}
+
+        self.optional_fields = set(self.OPTIONAL_PATTERN.findall(fmt or ""))
+
+        # Convert %(name?)s to %(name)s for standard formatting
+        normalized_fmt = self.OPTIONAL_PATTERN.sub(r"%(\1)\2", fmt or "")
+
+        super().__init__(normalized_fmt, datefmt, style)
+
+    def format(self, record):
+        for field, _ in self.optional_fields:
+            if not hasattr(record, field):
+                default = self.defaults.get(field, None)
+                setattr(record, field, default)
+
+        return super().format(record)

src/control_backend/logging/partial_filter.py

@@ -0,0 +1,16 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+import logging
+
+
+class PartialFilter(logging.Filter):
+    """
+    Class to filter any log records that have the "partial" attribute set to ``True``.
+    """
+
+    def filter(self, record):
+        return getattr(record, "partial", False) is not True

src/control_backend/logging/setup_logging.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import logging
 import logging.config
 import os
@@ -37,7 +43,7 @@ def add_logging_level(level_name: str, level_num: int, method_name: str | None =
     setattr(logging, method_name, log_to_root)
 
 
-def setup_logging(path: str = ".logging_config.yaml") -> None:
+def setup_logging(path: str = settings.logging_settings.logging_config_file) -> None:
     """
     Setup logging configuration of the CB. Tries to load the logging configuration from a file,
     in which we specify custom loggers, formatters, handlers, etc.
@@ -65,7 +71,7 @@ def setup_logging(path: str = ".logging_config.yaml") -> None:
 
             # Patch ZMQ PUBHandler to know about custom levels
             if custom_levels:
-                for logger_name in ("control_backend",):
+                for logger_name in config.get("loggers", {}):
                     logger = logging.getLogger(logger_name)
                     for handler in logger.handlers:
                         if isinstance(handler, PUBHandler):

src/control_backend/main.py

@@ -1,4 +1,8 @@
 """
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+--------------------------------------------------------------------------------
 Control Backend Main Application.
 
 This module defines the FastAPI application that serves as the entry point for the
@@ -26,7 +30,6 @@ from zmq.asyncio import Context
 
 # BDI agents
 from control_backend.agents.bdi import (
-    BDIBeliefCollectorAgent,
     BDICoreAgent,
     TextBeliefExtractorAgent,
 )
@@ -122,12 +125,6 @@ async def lifespan(app: FastAPI):
                 "name": settings.agent_settings.bdi_core_name,
             },
         ),
-        "BeliefCollectorAgent": (
-            BDIBeliefCollectorAgent,
-            {
-                "name": settings.agent_settings.bdi_belief_collector_name,
-            },
-        ),
         "TextBeliefExtractorAgent": (
             TextBeliefExtractorAgent,
             {
@@ -172,6 +169,8 @@ async def lifespan(app: FastAPI):
 
     await endpoints_pub_socket.send_multipart([PROGRAM_STATUS, ProgramStatus.STOPPING.value])
     # Additional shutdown logic goes here
+    for agent in agents:
+        await agent.stop()
 
     logger.info("Application shutdown complete.")
 

src/control_backend/schemas/__init__.py

@@ -0,0 +1,5 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""

src/control_backend/schemas/belief_list.py

@@ -1,7 +1,13 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from pydantic import BaseModel
 
+from control_backend.schemas.program import BaseGoal
 from control_backend.schemas.program import Belief as ProgramBelief
-from control_backend.schemas.program import Goal
 
 
 class BeliefList(BaseModel):
@@ -16,4 +22,10 @@ class BeliefList(BaseModel):
 
 
 class GoalList(BaseModel):
-    goals: list[Goal]
+    """
+    Represents a list of goals, used for communicating multiple goals between agents.
+
+    :ivar goals: The list of goals.
+    """
+
+    goals: list[BaseGoal]

src/control_backend/schemas/belief_message.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from pydantic import BaseModel
 
 
@@ -11,7 +17,7 @@ class Belief(BaseModel):
     """
 
     name: str
-    arguments: list[str] | None
+    arguments: list[str] | None = None
 
     # To make it hashable
     model_config = {"frozen": True}

src/control_backend/schemas/chat_history.py

@@ -1,10 +1,29 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from pydantic import BaseModel
 
 
 class ChatMessage(BaseModel):
+    """
+    Represents a single message in a conversation.
+
+    :ivar role: The role of the speaker (e.g., 'user', 'assistant').
+    :ivar content: The text content of the message.
+    """
+
     role: str
     content: str
 
 
 class ChatHistory(BaseModel):
+    """
+    Represents a sequence of chat messages, forming a conversation history.
+
+    :ivar messages: An ordered list of :class:`ChatMessage` objects.
+    """
+
     messages: list[ChatMessage]

src/control_backend/schemas/events.py

@@ -1,6 +1,20 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from pydantic import BaseModel
 
 
 class ButtonPressedEvent(BaseModel):
+    """
+    Represents a button press event from the UI.
+
+    :ivar type: The type of event (e.g., 'speech', 'gesture', 'override').
+    :ivar context: Additional data associated with the event (e.g., speech text, gesture name,
+    or ID).
+    """
+
     type: str
     context: str

src/control_backend/schemas/internal_message.py

@@ -1,3 +1,11 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+from collections.abc import Iterable
+
 from pydantic import BaseModel
 
 
@@ -5,13 +13,13 @@ class InternalMessage(BaseModel):
     """
     Standard message envelope for communication between agents within the Control Backend.
 
-    :ivar to: The name of the destination agent.
+    :ivar to: The name(s) of the destination agent(s).
     :ivar sender: The name of the sending agent.
     :ivar body: The string payload (often a JSON-serialized model).
     :ivar thread: An optional thread identifier/topic to categorize the message (e.g., 'beliefs').
     """
 
-    to: str
+    to: str | Iterable[str]
     sender: str | None = None
     body: str
     thread: str | None = None

src/control_backend/schemas/llm_prompt_message.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from pydantic import BaseModel
 
 

src/control_backend/schemas/message.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from pydantic import BaseModel
 
 

src/control_backend/schemas/program.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from enum import Enum
 from typing import Literal
 
@@ -15,21 +21,43 @@ class ProgramElement(BaseModel):
     name: str
     id: UUID4
 
+    # To make program elements hashable
+    model_config = {"frozen": True}
+
 
 class LogicalOperator(Enum):
+    """
+    Logical operators for combining beliefs.
+
+    These operators define how beliefs can be combined to form more complex
+    logical conditions. They are used in inferred beliefs to create compound
+    beliefs from simpler ones.
+
+    AND: Both operands must be true for the result to be true.
+    OR: At least one operand must be true for the result to be true.
+    """
+
     AND = "AND"
     OR = "OR"
 
 
-type Belief = KeywordBelief | SemanticBelief | InferredBelief
-type BasicBelief = KeywordBelief | SemanticBelief
+type Belief = KeywordBelief | SemanticBelief | InferredBelief | EmotionBelief | FaceBelief
+type BasicBelief = KeywordBelief | SemanticBelief | EmotionBelief | FaceBelief
 
 
 class KeywordBelief(ProgramElement):
     """
-    Represents a belief that is set when the user spoken text contains a certain keyword.
+    Represents a belief that is activated when a specific keyword is detected in the user's speech.
 
-    :ivar keyword: The keyword on which this belief gets set.
+    Keyword beliefs provide a simple but effective way to detect specific topics
+    or intentions in user speech. They are triggered when the exact keyword
+    string appears in the transcribed user input.
+
+    :ivar keyword: The string to look for in the transcription.
+
+    Example:
+        A keyword belief with keyword="robot" would be activated when the user
+        says "I like the robot" or "Tell me about robots".
     """
 
     name: str = ""
@@ -38,9 +66,21 @@ class KeywordBelief(ProgramElement):
 
 class SemanticBelief(ProgramElement):
     """
-    Represents a belief that is set by semantic LLM validation.
+    Represents a belief whose truth value is determined by an LLM analyzing the conversation
+    context.
 
-    :ivar description: Description of how to form the belief, used by the LLM.
+    Semantic beliefs provide more sophisticated belief detection by using
+    an LLM to analyze the conversation context and determine
+    if the belief should be considered true. This allows for more nuanced
+    and context-aware belief evaluation.
+
+    :ivar description: A natural language description of what this belief represents,
+    used as a prompt for the LLM.
+
+    Example:
+        A semantic belief with description="The user is expressing frustration"
+        would be activated when the LLM determines that the user's statements
+        indicate frustration, even if no specific keywords are used.
     """
 
     description: str
@@ -48,13 +88,16 @@ class SemanticBelief(ProgramElement):
 
 class InferredBelief(ProgramElement):
     """
-    Represents a belief that gets formed by combining two beliefs with a logical AND or OR.
+    Represents a belief derived from other beliefs using logical operators.
 
-    These beliefs can also be :class:`InferredBelief`, leading to arbitrarily deep nesting.
+    Inferred beliefs allow for the creation of complex belief structures by
+    combining simpler beliefs using logical operators. This enables the
+    representation of sophisticated conditions and relationships between
+    different aspects of the conversation or context.
 
-    :ivar operator: The logical operator to apply.
-    :ivar left: The left part of the logical expression.
-    :ivar right: The right part of the logical expression.
+    :ivar operator: The :class:`LogicalOperator` (AND/OR) to apply.
+    :ivar left: The left operand (another belief).
+    :ivar right: The right operand (another belief).
     """
 
     name: str = ""
@@ -63,7 +106,43 @@ class InferredBelief(ProgramElement):
     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 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.
+
+    Norms represent guidelines, principles, or rules that should govern the
+    robot's behavior during interactions. They can be either basic (always
+    active in their phase) or conditional (active only when specific beliefs
+    are true).
+
+    :ivar norm: The textual description of the norm.
+    :ivar critical: Whether this norm is considered critical and should be strictly enforced.
+
+    Critical norms are currently not supported yet, but are intended for norms that should
+    ABSOLUTELY NOT be violated, possible cheched by additional validator agents.
+    """
+
     name: str = ""
     norm: str
     critical: bool = False
@@ -71,10 +150,14 @@ class Norm(ProgramElement):
 
 class BasicNorm(Norm):
     """
-    Represents a behavioral norm.
+    A simple behavioral norm that is always considered for activation when its phase is active.
 
-    :ivar norm: The actual norm text describing the behavior.
-    :ivar critical: When true, this norm should absolutely not be violated (checked separately).
+    Basic norms are the most straightforward type of norms. They are active
+    throughout their assigned phase and provide consistent behavioral guidance
+    without any additional conditions.
+
+    These norms are suitable for general principles that should always apply
+    during a particular interaction phase.
     """
 
     pass
@@ -82,9 +165,22 @@ class BasicNorm(Norm):
 
 class ConditionalNorm(Norm):
     """
-    Represents a norm that is only active when a condition is met (i.e., a certain belief holds).
+    A behavioral norm that is only active when a specific condition (belief) is met.
 
-    :ivar condition: When to activate this norm.
+    Conditional norms provide context-sensitive behavioral guidance. They are
+    only active and considered for activation when their associated condition
+    (belief) is true. This allows for more nuanced and adaptive behavior that
+    responds to the specific context of the interaction.
+
+    An important note, is that the current implementation of these norms for keyword-based beliefs
+    is that they only hold for 1 turn, as keyword-based conditions often express temporary
+    conditions.
+
+    :ivar condition: The :class:`Belief` that must hold for this norm to be active.
+
+    Example:
+        A conditional norm with the condition "user is frustrated" might specify
+        that the robot should use more empathetic language and avoid complex topics.
     """
 
     condition: Belief
@@ -96,7 +192,12 @@ type PlanElement = Goal | Action
 class Plan(ProgramElement):
     """
     Represents a list of steps to execute. Each of these steps can be a goal (with its own plan)
-    or a simple action.
+     or a simple action.
+
+    Plans define sequences of actions and subgoals that the robot should execute
+    to achieve a particular objective. They form the procedural knowledge of
+    the behavior program, specifying what the robot should do in different
+    situations.
 
     :ivar steps: The actions or subgoals to execute, in order.
     """
@@ -105,31 +206,49 @@ class Plan(ProgramElement):
     steps: list[PlanElement]
 
 
-class Goal(ProgramElement):
+class BaseGoal(ProgramElement):
     """
-    Represents an objective to be achieved. To reach the goal, we should execute
-    the corresponding plan. If we can fail to achieve a goal after executing the plan,
-    for example when the achieving of the goal is dependent on the user's reply, this means
-    that the achieved status will be set from somewhere else in the program.
+    Represents an objective to be achieved. This base version does not include a plan to achieve
+    this goal, and is used in semantic belief extraction.
 
     :ivar description: A description of the goal, used to determine if it has been achieved.
-    :ivar plan: The plan to execute.
     :ivar can_fail: Whether we can fail to achieve the goal after executing the plan.
+
+    The can_fail attribute determines whether goal achievement is binary
+    (success/failure) or whether it can be determined through conversation
+    analysis.
     """
 
     description: str = ""
-    plan: Plan
     can_fail: bool = True
 
 
+class Goal(BaseGoal):
+    """
+    Represents an objective to be achieved. To reach the goal, we should execute the corresponding
+    plan. It inherits from the BaseGoal a variable `can_fail`, which, if true, will cause the
+    completion to be determined based on the conversation.
+
+    Goals extend base goals by including a specific plan to achieve the objective.
+    They form the core of the robot's proactive behavior, defining both what
+    should be accomplished and how to accomplish it.
+
+    Instances of this goal are not hashable because a plan is not hashable.
+
+    :ivar plan: The plan to execute.
+    """
+
+    plan: Plan
+
+
 type Action = SpeechAction | GestureAction | LLMAction
 
 
 class SpeechAction(ProgramElement):
     """
-    Represents the action of the robot speaking a literal text.
+    An action where the robot speaks a predefined literal text.
 
-    :ivar text: The text to speak.
+    :ivar text: The text content to be spoken.
     """
 
     name: str = ""
@@ -138,11 +257,14 @@ class SpeechAction(ProgramElement):
 
 class Gesture(BaseModel):
     """
-    Represents a gesture to be performed. Can be either a single gesture,
-    or a random gesture from a category (tag).
+    Defines a physical gesture for the robot to perform.
 
-    :ivar type: The type of the gesture, "tag" or "single".
-    :ivar name: The name of the single gesture or tag.
+    :ivar type: Whether to use a specific "single" gesture or a random one from a "tag" category.
+    :ivar name: The identifier for the gesture or tag.
+
+    The type field determines how the gesture is selected:
+    - "single": Use the specific gesture identified by name
+    - "tag": Select a random gesture from the category identified by name
     """
 
     type: Literal["tag", "single"]
@@ -151,9 +273,9 @@ class Gesture(BaseModel):
 
 class GestureAction(ProgramElement):
     """
-    Represents the action of the robot performing a gesture.
+    An action where the robot performs a physical gesture.
 
-    :ivar gesture: The gesture to perform.
+    :ivar gesture: The :class:`Gesture` definition.
     """
 
     name: str = ""
@@ -162,10 +284,13 @@ class GestureAction(ProgramElement):
 
 class LLMAction(ProgramElement):
     """
-    Represents the action of letting an LLM generate a reply based on its chat history
-    and an additional goal added in the prompt.
+    An action that triggers an LLM-generated conversational response.
 
-    :ivar goal: The extra (temporary) goal to add to the LLM.
+    :ivar goal: A temporary conversational goal to guide the LLM's response generation.
+
+    The goal parameter provides high-level guidance to the LLM about what
+    the response should aim to achieve, while allowing the LLM flexibility
+    in how to express it.
     """
 
     name: str = ""
@@ -174,10 +299,10 @@ class LLMAction(ProgramElement):
 
 class Trigger(ProgramElement):
     """
-    Represents a belief-based trigger. When a belief is set, the corresponding plan is executed.
+    Defines a reactive behavior: when the condition (belief) is met, the plan is executed.
 
-    :ivar condition: When to activate the trigger.
-    :ivar plan: The plan to execute.
+    :ivar condition: The :class:`Belief` that triggers this behavior.
+    :ivar plan: The :class:`Plan` to execute upon activation.
     """
 
     condition: Belief
@@ -186,11 +311,11 @@ class Trigger(ProgramElement):
 
 class Phase(ProgramElement):
     """
-    A distinct phase within a program, containing norms, goals, and triggers.
+    A logical stage in the interaction program, grouping norms, goals, and triggers.
 
-    :ivar norms: List of norms active in this phase.
-    :ivar goals: List of goals to pursue in this phase.
-    :ivar triggers: List of triggers that define transitions out of this phase.
+    :ivar norms: List of norms active during this phase.
+    :ivar goals: List of goals the robot pursues in this phase.
+    :ivar triggers: List of reactive behaviors defined for this phase.
     """
 
     name: str = ""
@@ -201,9 +326,19 @@ class Phase(ProgramElement):
 
 class Program(BaseModel):
     """
-    Represents a complete interaction program, consisting of a sequence or set of phases.
+    The top-level container for a complete robot behavior definition.
 
-    :ivar phases: The list of phases that make up the program.
+    The Program class represents the complete specification of a robot's
+    behavioral logic. It contains all the phases, norms, goals, triggers,
+    and actions that define how the robot should behave during interactions.
+
+    :ivar phases: An ordered list of :class:`Phase` objects defining the interaction flow.
     """
 
     phases: list[Phase]
+
+
+if __name__ == "__main__":
+    input = input("Enter program JSON: ")
+    program = Program.model_validate_json(input)
+    print(program)

src/control_backend/schemas/program_status.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from enum import Enum
 
 PROGRAM_STATUS = b"internal/program_status"

src/control_backend/schemas/ri_message.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from enum import Enum
 from typing import Any, Literal
 
@@ -14,6 +20,7 @@ class RIEndpoint(str, Enum):
     GESTURE_TAG = "actuate/gesture/tag"
     PING = "ping"
     NEGOTIATE_PORTS = "negotiate/ports"
+    PAUSE = ""
 
 
 class RIMessage(BaseModel):
@@ -64,3 +71,15 @@ class GestureCommand(RIMessage):
         if self.endpoint not in allowed:
             raise ValueError("endpoint must be GESTURE_SINGLE or GESTURE_TAG")
         return self
+
+
+class PauseCommand(RIMessage):
+    """
+    A specific command to pause or unpause the robot's actions.
+
+    :ivar endpoint: Fixed to ``RIEndpoint.PAUSE``.
+    :ivar data: A boolean indicating whether to pause (True) or unpause (False).
+    """
+
+    endpoint: RIEndpoint = RIEndpoint(RIEndpoint.PAUSE)
+    data: bool

test/integration/agents/perception/vad_agent/test_vad_agent.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import random
 from unittest.mock import AsyncMock, MagicMock
 
@@ -40,7 +46,7 @@ async def test_normal_setup(per_transcription_agent):
     per_vad_agent = VADAgent("tcp://localhost:12345", False)
     per_vad_agent._streaming_loop = AsyncMock()
 
-    async def swallow_background_task(coro):
+    def swallow_background_task(coro):
         coro.close()
 
     per_vad_agent.add_behavior = swallow_background_task
@@ -106,7 +112,7 @@ async def test_out_socket_creation_failure(zmq_context):
     per_vad_agent._streaming_loop = AsyncMock()
     per_vad_agent._connect_audio_out_socket = MagicMock(return_value=None)
 
-    async def swallow_background_task(coro):
+    def swallow_background_task(coro):
         coro.close()
 
     per_vad_agent.add_behavior = swallow_background_task
@@ -126,7 +132,7 @@ async def test_stop(zmq_context, per_transcription_agent):
     per_vad_agent._reset_stream = AsyncMock()
     per_vad_agent._streaming_loop = AsyncMock()
 
-    async def swallow_background_task(coro):
+    def swallow_background_task(coro):
         coro.close()
 
     per_vad_agent.add_behavior = swallow_background_task
@@ -150,6 +156,7 @@ async def test_application_startup_complete(zmq_context):
     vad_agent._running = True
     vad_agent._reset_stream = AsyncMock()
     vad_agent.program_sub_socket = AsyncMock()
+    vad_agent.program_sub_socket.close = MagicMock()
     vad_agent.program_sub_socket.recv_multipart.side_effect = [
         (PROGRAM_STATUS, ProgramStatus.RUNNING.value),
     ]

test/integration/agents/perception/vad_agent/test_vad_with_audio.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import os
 from unittest.mock import AsyncMock, MagicMock
 

test/unit/agents/actuation/test_robot_gesture_agent.py

@@ -1,5 +1,11 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import json
-from unittest.mock import AsyncMock, MagicMock
+from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 import zmq
@@ -19,6 +25,12 @@ def zmq_context(mocker):
     return mock_context
 
 
+@pytest.fixture(autouse=True)
+def mock_experiment_logger():
+    with patch("control_backend.agents.actuation.robot_gesture_agent.experiment_logger") as logger:
+        yield logger
+
+
 @pytest.mark.asyncio
 async def test_setup_bind(zmq_context, mocker):
     """Setup binds and subscribes to internal commands."""
@@ -28,7 +40,11 @@ async def test_setup_bind(zmq_context, mocker):
     settings = mocker.patch("control_backend.agents.actuation.robot_gesture_agent.settings")
     settings.zmq_settings.internal_sub_address = "tcp://internal:1234"
 
-    agent.add_behavior = MagicMock()
+    def close_coro(coro):
+        coro.close()
+        return MagicMock()
+
+    agent.add_behavior = MagicMock(side_effect=close_coro)
 
     await agent.setup()
 
@@ -55,7 +71,11 @@ async def test_setup_connect(zmq_context, mocker):
     settings = mocker.patch("control_backend.agents.actuation.robot_gesture_agent.settings")
     settings.zmq_settings.internal_sub_address = "tcp://internal:1234"
 
-    agent.add_behavior = MagicMock()
+    def close_coro(coro):
+        coro.close()
+        return MagicMock()
+
+    agent.add_behavior = MagicMock(side_effect=close_coro)
 
     await agent.setup()
 
@@ -119,6 +139,65 @@ async def test_handle_message_rejects_invalid_gesture_tag():
     pubsocket.send_json.assert_not_awaited()
 
 
+@pytest.mark.asyncio
+async def test_handle_message_sends_valid_single_gesture_command():
+    """Internal message with valid single gesture is forwarded."""
+    pubsocket = AsyncMock()
+    agent = RobotGestureAgent("robot_gesture", single_gesture_data=["wave", "point"], address="")
+    agent.pubsocket = pubsocket
+
+    payload = {
+        "endpoint": RIEndpoint.GESTURE_SINGLE,
+        "data": "wave",
+    }
+    msg = InternalMessage(to="robot", sender="tester", body=json.dumps(payload))
+
+    await agent.handle_message(msg)
+
+    pubsocket.send_json.assert_awaited_once()
+
+
+@pytest.mark.asyncio
+async def test_handle_message_rejects_invalid_single_gesture():
+    """Internal message with invalid single gesture is not forwarded."""
+    pubsocket = AsyncMock()
+    agent = RobotGestureAgent("robot_gesture", single_gesture_data=["wave", "point"], address="")
+    agent.pubsocket = pubsocket
+
+    payload = {
+        "endpoint": RIEndpoint.GESTURE_SINGLE,
+        "data": "dance",
+    }
+    msg = InternalMessage(to="robot", sender="tester", body=json.dumps(payload))
+
+    await agent.handle_message(msg)
+
+    pubsocket.send_json.assert_not_awaited()
+
+
+@pytest.mark.asyncio
+async def test_zmq_command_loop_valid_single_gesture_payload():
+    """UI command with valid single gesture is read from SUB and published."""
+    command = {"endpoint": RIEndpoint.GESTURE_SINGLE, "data": "wave"}
+    fake_socket = AsyncMock()
+
+    async def recv_once():
+        agent._running = False
+        return b"command", json.dumps(command).encode("utf-8")
+
+    fake_socket.recv_multipart = recv_once
+    fake_socket.send_json = AsyncMock()
+
+    agent = RobotGestureAgent("robot_gesture", single_gesture_data=["wave", "point"], address="")
+    agent.subsocket = fake_socket
+    agent.pubsocket = fake_socket
+    agent._running = True
+
+    await agent._zmq_command_loop()
+
+    fake_socket.send_json.assert_awaited_once()
+
+
 @pytest.mark.asyncio
 async def test_handle_message_invalid_payload():
     """Invalid payload is caught and does not send."""
@@ -411,8 +490,7 @@ async def test_stop_closes_sockets():
 
     pubsocket.close.assert_called_once()
     subsocket.close.assert_called_once()
-    # Note: repsocket is not closed in stop() method, but you might want to add it
-    # repsocket.close.assert_called_once()
+    repsocket.close.assert_called_once()
 
 
 @pytest.mark.asyncio

test/unit/agents/actuation/test_robot_speech_agent.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import json
 from unittest.mock import AsyncMock, MagicMock
 
@@ -30,7 +36,11 @@ async def test_setup_bind(zmq_context, mocker):
     settings = mocker.patch("control_backend.agents.actuation.robot_speech_agent.settings")
     settings.zmq_settings.internal_sub_address = "tcp://internal:1234"
 
-    agent.add_behavior = MagicMock()
+    def close_coro(coro):
+        coro.close()
+        return MagicMock()
+
+    agent.add_behavior = MagicMock(side_effect=close_coro)
 
     await agent.setup()
 
@@ -48,7 +58,11 @@ async def test_setup_connect(zmq_context, mocker):
     settings = mocker.patch("control_backend.agents.actuation.robot_speech_agent.settings")
     settings.zmq_settings.internal_sub_address = "tcp://internal:1234"
 
-    agent.add_behavior = MagicMock()
+    def close_coro(coro):
+        coro.close()
+        return MagicMock()
+
+    agent.add_behavior = MagicMock(side_effect=close_coro)
 
     await agent.setup()
 

test/unit/agents/bdi/test_agentspeak_ast.py

@@ -0,0 +1,192 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+import pytest
+
+from control_backend.agents.bdi.agentspeak_ast import (
+    AstAtom,
+    AstBinaryOp,
+    AstLiteral,
+    AstLogicalExpression,
+    AstNumber,
+    AstPlan,
+    AstProgram,
+    AstRule,
+    AstStatement,
+    AstString,
+    AstVar,
+    BinaryOperatorType,
+    StatementType,
+    TriggerType,
+    _coalesce_expr,
+)
+
+
+def test_ast_atom():
+    atom = AstAtom("test")
+    assert str(atom) == "test"
+    assert atom._to_agentspeak() == "test"
+
+
+def test_ast_var():
+    var = AstVar("Variable")
+    assert str(var) == "Variable"
+    assert var._to_agentspeak() == "Variable"
+
+
+def test_ast_number():
+    num = AstNumber(42)
+    assert str(num) == "42"
+    num_float = AstNumber(3.14)
+    assert str(num_float) == "3.14"
+
+
+def test_ast_string():
+    s = AstString("hello")
+    assert str(s) == '"hello"'
+
+
+def test_ast_literal():
+    lit = AstLiteral("functor", [AstAtom("atom"), AstNumber(1)])
+    assert str(lit) == "functor(atom, 1)"
+    lit_empty = AstLiteral("functor")
+    assert str(lit_empty) == "functor"
+
+
+def test_ast_binary_op():
+    left = AstNumber(1)
+    right = AstNumber(2)
+    op = AstBinaryOp(left, BinaryOperatorType.GREATER_THAN, right)
+    assert str(op) == "1 > 2"
+
+    # Test logical wrapper
+    assert isinstance(op.left, AstLogicalExpression)
+    assert isinstance(op.right, AstLogicalExpression)
+
+
+def test_ast_binary_op_parens():
+    # 1 > 2
+    inner = AstBinaryOp(AstNumber(1), BinaryOperatorType.GREATER_THAN, AstNumber(2))
+    # (1 > 2) & 3
+    outer = AstBinaryOp(inner, BinaryOperatorType.AND, AstNumber(3))
+    assert str(outer) == "(1 > 2) & 3"
+
+    # 3 & (1 > 2)
+    outer_right = AstBinaryOp(AstNumber(3), BinaryOperatorType.AND, inner)
+    assert str(outer_right) == "3 & (1 > 2)"
+
+
+def test_ast_binary_op_parens_negated():
+    inner = AstLogicalExpression(AstAtom("foo"), negated=True)
+    outer = AstBinaryOp(inner, BinaryOperatorType.AND, AstAtom("bar"))
+    # The current implementation checks `if self.left.negated: l_str = f"({l_str})"`
+    # str(inner) is "not foo"
+    # so we expect "(not foo) & bar"
+    assert str(outer) == "(not foo) & bar"
+
+    outer_right = AstBinaryOp(AstAtom("bar"), BinaryOperatorType.AND, inner)
+    assert str(outer_right) == "bar & (not foo)"
+
+
+def test_ast_logical_expression_negation():
+    expr = AstLogicalExpression(AstAtom("true"), negated=True)
+    assert str(expr) == "not true"
+
+    expr_neg_neg = ~expr
+    assert str(expr_neg_neg) == "true"
+    assert not expr_neg_neg.negated
+
+    # Invert a non-logical expression (wraps it)
+    term = AstAtom("true")
+    inverted = ~term
+    assert isinstance(inverted, AstLogicalExpression)
+    assert inverted.negated
+    assert str(inverted) == "not true"
+
+
+def test_ast_logical_expression_no_negation():
+    # _as_logical on already logical expression
+    expr = AstLogicalExpression(AstAtom("x"))
+    # Doing binary op will call _as_logical
+    op = AstBinaryOp(expr, BinaryOperatorType.AND, AstAtom("y"))
+    assert isinstance(op.left, AstLogicalExpression)
+    assert op.left is expr  # Should reuse instance
+
+
+def test_ast_operators():
+    t1 = AstAtom("a")
+    t2 = AstAtom("b")
+
+    assert str(t1 & t2) == "a & b"
+    assert str(t1 | t2) == "a | b"
+    assert str(t1 >= t2) == "a >= b"
+    assert str(t1 > t2) == "a > b"
+    assert str(t1 <= t2) == "a <= b"
+    assert str(t1 < t2) == "a < b"
+    assert str(t1 == t2) == "a == b"
+    assert str(t1 != t2) == r"a \== b"
+
+
+def test_coalesce_expr():
+    t = AstAtom("a")
+    assert str(t & "b") == 'a & "b"'
+    assert str(t & 1) == "a & 1"
+    assert str(t & 1.5) == "a & 1.5"
+
+    with pytest.raises(TypeError):
+        _coalesce_expr(None)
+
+
+def test_ast_statement():
+    stmt = AstStatement(StatementType.DO_ACTION, AstLiteral("action"))
+    assert str(stmt) == ".action"
+
+
+def test_ast_rule():
+    # Rule with condition
+    rule = AstRule(AstLiteral("head"), AstLiteral("body"))
+    assert str(rule) == "head :- body."
+
+    # Rule without condition
+    rule_simple = AstRule(AstLiteral("fact"))
+    assert str(rule_simple) == "fact."
+
+
+def test_ast_plan():
+    plan = AstPlan(
+        TriggerType.ADDED_GOAL,
+        AstLiteral("goal"),
+        [AstLiteral("context")],
+        [AstStatement(StatementType.DO_ACTION, AstLiteral("action"))],
+    )
+    output = str(plan)
+    # verify parts exist
+    assert "+!goal" in output
+    assert ":   context" in output
+    assert "<-  .action." in output
+
+
+def test_ast_plan_no_context():
+    plan = AstPlan(
+        TriggerType.ADDED_GOAL,
+        AstLiteral("goal"),
+        [],
+        [AstStatement(StatementType.DO_ACTION, AstLiteral("action"))],
+    )
+    output = str(plan)
+    assert "+!goal" in output
+    assert ":   " not in output
+    assert "<-  .action." in output
+
+
+def test_ast_program():
+    prog = AstProgram(
+        rules=[AstRule(AstLiteral("fact"))],
+        plans=[AstPlan(TriggerType.ADDED_BELIEF, AstLiteral("b"), [], [])],
+    )
+    output = str(prog)
+    assert "fact." in output
+    assert "+b" in output

test/unit/agents/bdi/test_agentspeak_generator.py

@@ -0,0 +1,193 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+import uuid
+
+import pytest
+
+from control_backend.agents.bdi.agentspeak_ast import AstProgram
+from control_backend.agents.bdi.agentspeak_generator import AgentSpeakGenerator
+from control_backend.schemas.program import (
+    BasicNorm,
+    ConditionalNorm,
+    Gesture,
+    GestureAction,
+    Goal,
+    InferredBelief,
+    KeywordBelief,
+    LLMAction,
+    LogicalOperator,
+    Phase,
+    Plan,
+    Program,
+    SemanticBelief,
+    SpeechAction,
+    Trigger,
+)
+
+
+@pytest.fixture
+def generator():
+    return AgentSpeakGenerator()
+
+
+def test_generate_empty_program(generator):
+    prog = Program(phases=[])
+    code = generator.generate(prog)
+    assert 'phase("end").' in code
+    assert "!notify_cycle" in code
+
+
+def test_generate_basic_norm(generator):
+    norm = BasicNorm(id=uuid.uuid4(), name="n1", norm="be nice")
+    phase = Phase(id=uuid.uuid4(), norms=[norm], goals=[], triggers=[])
+    prog = Program(phases=[phase])
+
+    code = generator.generate(prog)
+    assert f'norm("be nice") :- phase("{phase.id}").' in code
+
+
+def test_generate_critical_norm(generator):
+    norm = BasicNorm(id=uuid.uuid4(), name="n1", norm="safety", critical=True)
+    phase = Phase(id=uuid.uuid4(), norms=[norm], goals=[], triggers=[])
+    prog = Program(phases=[phase])
+
+    code = generator.generate(prog)
+    assert f'critical_norm("safety") :- phase("{phase.id}").' in code
+
+
+def test_generate_conditional_norm(generator):
+    cond = KeywordBelief(id=uuid.uuid4(), name="k1", keyword="please")
+    norm = ConditionalNorm(id=uuid.uuid4(), name="n1", norm="help", condition=cond)
+    phase = Phase(id=uuid.uuid4(), norms=[norm], goals=[], triggers=[])
+    prog = Program(phases=[phase])
+
+    code = generator.generate(prog)
+    assert 'norm("help")' in code
+    assert 'keyword_said("please")' in code
+    assert f"force_norm_{generator._slugify_str(norm.norm)}" in code
+
+
+def test_generate_goal_and_plan(generator):
+    action = SpeechAction(id=uuid.uuid4(), name="s1", text="hello")
+    plan = Plan(id=uuid.uuid4(), name="p1", steps=[action])
+    # IMPORTANT: can_fail must be False for +achieved_ belief to be added
+    goal = Goal(id=uuid.uuid4(), name="g1", description="desc", plan=plan, can_fail=False)
+    phase = Phase(id=uuid.uuid4(), norms=[], goals=[goal], triggers=[])
+    prog = Program(phases=[phase])
+
+    code = generator.generate(prog)
+    # Check trigger for goal
+    goal_slug = generator._slugify_str(goal.name)
+    assert f"+!{goal_slug}" in code
+    assert f'phase("{phase.id}")' in code
+    assert '!say("hello")' in code
+
+    # Check success belief addition
+    assert f"+achieved_{goal_slug}" in code
+
+
+def test_generate_subgoal(generator):
+    subplan = Plan(id=uuid.uuid4(), name="p2", steps=[])
+    subgoal = Goal(id=uuid.uuid4(), name="sub1", description="sub", plan=subplan)
+
+    plan = Plan(id=uuid.uuid4(), name="p1", steps=[subgoal])
+    goal = Goal(id=uuid.uuid4(), name="g1", description="main", plan=plan)
+    phase = Phase(id=uuid.uuid4(), norms=[], goals=[goal], triggers=[])
+    prog = Program(phases=[phase])
+
+    code = generator.generate(prog)
+    subgoal_slug = generator._slugify_str(subgoal.name)
+    # Main goal calls subgoal
+    assert f"!{subgoal_slug}" in code
+    # Subgoal plan exists
+    assert f"+!{subgoal_slug}" in code
+
+
+def test_generate_trigger(generator):
+    cond = SemanticBelief(id=uuid.uuid4(), name="s1", description="desc")
+    plan = Plan(id=uuid.uuid4(), name="p1", steps=[])
+    trigger = Trigger(id=uuid.uuid4(), name="t1", condition=cond, plan=plan)
+    phase = Phase(id=uuid.uuid4(), norms=[], goals=[], triggers=[trigger])
+    prog = Program(phases=[phase])
+
+    code = generator.generate(prog)
+    # Trigger logic is added to check_triggers
+    assert f"{generator.slugify(cond)}" in code
+    assert f'notify_trigger_start("{generator.slugify(trigger)}")' in code
+    assert f'notify_trigger_end("{generator.slugify(trigger)}")' in code
+
+
+def test_phase_transition(generator):
+    phase1 = Phase(id=uuid.uuid4(), name="p1", norms=[], goals=[], triggers=[])
+    phase2 = Phase(id=uuid.uuid4(), name="p2", norms=[], goals=[], triggers=[])
+    prog = Program(phases=[phase1, phase2])
+
+    code = generator.generate(prog)
+    assert "transition_phase" in code
+    assert f'phase("{phase1.id}")' in code
+    assert f'phase("{phase2.id}")' in code
+    assert "force_transition_phase" in code
+
+
+def test_astify_gesture(generator):
+    gesture = Gesture(type="single", name="wave")
+    action = GestureAction(id=uuid.uuid4(), name="g1", gesture=gesture)
+    ast = generator._astify(action)
+    assert str(ast) == 'gesture("single", "wave")'
+
+
+def test_astify_llm_action(generator):
+    action = LLMAction(id=uuid.uuid4(), name="l1", goal="be funny")
+    ast = generator._astify(action)
+    assert str(ast) == 'reply_with_goal("be funny")'
+
+
+def test_astify_inferred_belief_and(generator):
+    left = KeywordBelief(id=uuid.uuid4(), name="k1", keyword="a")
+    right = KeywordBelief(id=uuid.uuid4(), name="k2", keyword="b")
+    inf = InferredBelief(
+        id=uuid.uuid4(), name="i1", operator=LogicalOperator.AND, left=left, right=right
+    )
+
+    ast = generator._astify(inf)
+    assert 'keyword_said("a") & keyword_said("b")' == str(ast)
+
+
+def test_astify_inferred_belief_or(generator):
+    left = KeywordBelief(id=uuid.uuid4(), name="k1", keyword="a")
+    right = KeywordBelief(id=uuid.uuid4(), name="k2", keyword="b")
+    inf = InferredBelief(
+        id=uuid.uuid4(), name="i1", operator=LogicalOperator.OR, left=left, right=right
+    )
+
+    ast = generator._astify(inf)
+    assert 'keyword_said("a") | keyword_said("b")' == str(ast)
+
+
+def test_astify_semantic_belief(generator):
+    sb = SemanticBelief(id=uuid.uuid4(), name="s1", description="desc")
+    ast = generator._astify(sb)
+    assert str(ast) == f"semantic_{generator._slugify_str(sb.name)}"
+
+
+def test_slugify_not_implemented(generator):
+    with pytest.raises(NotImplementedError):
+        generator.slugify("not a program element")
+
+
+def test_astify_not_implemented(generator):
+    with pytest.raises(NotImplementedError):
+        generator._astify("not a program element")
+
+
+def test_process_phase_transition_from_none(generator):
+    # Initialize AstProgram manually as we are bypassing generate()
+    generator._asp = AstProgram()
+    # Should safely return doing nothing
+    generator._add_phase_transition(None, None)
+
+    assert len(generator._asp.plans) == 0

test/unit/agents/bdi/test_bdi_core_agent.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import asyncio
 import json
 import time
@@ -26,6 +32,12 @@ def agent():
     return agent
 
 
+@pytest.fixture(autouse=True)
+def mock_experiment_logger():
+    with patch("control_backend.agents.bdi.bdi_core_agent.experiment_logger") as logger:
+        yield logger
+
+
 @pytest.mark.asyncio
 async def test_setup_loads_asl(mock_agentspeak_env, agent):
     # Mock file opening
@@ -45,23 +57,34 @@ async def test_setup_no_asl(mock_agentspeak_env, agent):
 
 
 @pytest.mark.asyncio
-async def test_handle_belief_collector_message(agent, mock_settings):
+async def test_handle_belief_message(agent, mock_settings):
     """Test that incoming beliefs are added to the BDI agent"""
     beliefs = [Belief(name="user_said", arguments=["Hello"])]
     msg = InternalMessage(
         to="bdi_agent",
-        sender=mock_settings.agent_settings.bdi_belief_collector_name,
+        sender=mock_settings.agent_settings.text_belief_extractor_name,
         body=BeliefMessage(create=beliefs).model_dump_json(),
         thread="beliefs",
     )
 
     await agent.handle_message(msg)
 
-    # Expect bdi_agent.call to be triggered to add belief
-    args = agent.bdi_agent.call.call_args.args
-    assert args[0] == agentspeak.Trigger.addition
-    assert args[1] == agentspeak.GoalType.belief
-    assert args[2] == agentspeak.Literal("user_said", (agentspeak.Literal("Hello"),))
+    # Check for the specific call we expect among all calls
+    # bdi_agent.call is called multiple times (for transition_phase, check_triggers)
+    # We want to confirm the belief addition call exists
+    found_call = False
+    for call in agent.bdi_agent.call.call_args_list:
+        args = call.args
+        if (
+            args[0] == agentspeak.Trigger.addition
+            and args[1] == agentspeak.GoalType.belief
+            and args[2].functor == "user_said"
+            and args[2].args[0].functor == "Hello"
+        ):
+            found_call = True
+            break
+
+    assert found_call, "Expected belief addition call not found in bdi_agent.call history"
 
 
 @pytest.mark.asyncio
@@ -71,25 +94,33 @@ async def test_handle_delete_belief_message(agent, mock_settings):
 
     msg = InternalMessage(
         to="bdi_agent",
-        sender=mock_settings.agent_settings.bdi_belief_collector_name,
+        sender=mock_settings.agent_settings.text_belief_extractor_name,
         body=BeliefMessage(delete=beliefs).model_dump_json(),
         thread="beliefs",
     )
     await agent.handle_message(msg)
 
-    # Expect bdi_agent.call to be triggered to remove belief
-    args = agent.bdi_agent.call.call_args.args
-    assert args[0] == agentspeak.Trigger.removal
-    assert args[1] == agentspeak.GoalType.belief
-    assert args[2] == agentspeak.Literal("user_said", (agentspeak.Literal("Hello"),))
+    found_call = False
+    for call in agent.bdi_agent.call.call_args_list:
+        args = call.args
+        if (
+            args[0] == agentspeak.Trigger.removal
+            and args[1] == agentspeak.GoalType.belief
+            and args[2].functor == "user_said"
+            and args[2].args[0].functor == "Hello"
+        ):
+            found_call = True
+            break
+
+    assert found_call
 
 
 @pytest.mark.asyncio
-async def test_incorrect_belief_collector_message(agent, mock_settings):
+async def test_incorrect_belief_message(agent, mock_settings):
     """Test that incorrect message format triggers an exception."""
     msg = InternalMessage(
         to="bdi_agent",
-        sender=mock_settings.agent_settings.bdi_belief_collector_name,
+        sender=mock_settings.agent_settings.text_belief_extractor_name,
         body=json.dumps({"bad_format": "bad_format"}),
         thread="beliefs",
     )
@@ -171,7 +202,11 @@ def test_remove_belief_success_wakes_loop(agent):
     agent._remove_belief("remove_me", ["x"])
 
     assert agent.bdi_agent.call.called
-    trigger, goaltype, literal, *_ = agent.bdi_agent.call.call_args.args
+
+    call_args = agent.bdi_agent.call.call_args.args
+    trigger = call_args[0]
+    goaltype = call_args[1]
+    literal = call_args[2]
 
     assert trigger == agentspeak.Trigger.removal
     assert goaltype == agentspeak.GoalType.belief
@@ -288,3 +323,216 @@ async def test_deadline_sleep_branch(agent):
 
     duration = time.time() - start_time
     assert duration >= 0.004  # loop slept until deadline
+
+
+@pytest.mark.asyncio
+async def test_handle_new_program(agent):
+    agent._load_asl = AsyncMock()
+    agent.add_behavior = MagicMock()
+    # Mock existing loop task so it can be cancelled
+    mock_task = MagicMock()
+    mock_task.cancel = MagicMock()
+    agent._bdi_loop_task = mock_task
+
+    def close_coro(coro):
+        coro.close()
+        return MagicMock()
+
+    agent.add_behavior = MagicMock(side_effect=close_coro)
+
+    msg = InternalMessage(to="bdi_agent", thread="new_program", body="path/to/asl.asl")
+
+    await agent.handle_message(msg)
+
+    mock_task.cancel.assert_called_once()
+    agent._load_asl.assert_awaited_once_with("path/to/asl.asl")
+    agent.add_behavior.assert_called()
+
+
+@pytest.mark.asyncio
+async def test_handle_user_interrupts(agent, mock_settings):
+    mock_settings.agent_settings.user_interrupt_name = "user_interrupt_agent"
+    # force_phase_transition
+    agent._set_goal = MagicMock()
+    msg = InternalMessage(
+        to="bdi_agent",
+        sender=mock_settings.agent_settings.user_interrupt_name,
+        thread="force_phase_transition",
+        body="",
+    )
+    await agent.handle_message(msg)
+    agent._set_goal.assert_called_with("transition_phase")
+
+    # force_trigger
+    agent._force_trigger = MagicMock()
+    msg.thread = "force_trigger"
+    msg.body = "trigger_x"
+    await agent.handle_message(msg)
+    agent._force_trigger.assert_called_with("trigger_x")
+
+    # force_norm
+    agent._force_norm = MagicMock()
+    msg.thread = "force_norm"
+    msg.body = "norm_y"
+    await agent.handle_message(msg)
+    agent._force_norm.assert_called_with("norm_y")
+
+    # force_next_phase
+    agent._force_next_phase = MagicMock()
+    msg.thread = "force_next_phase"
+    msg.body = ""
+    await agent.handle_message(msg)
+    agent._force_next_phase.assert_called_once()
+
+    # unknown interrupt
+    agent.logger = MagicMock()
+    msg.thread = "unknown_thing"
+    await agent.handle_message(msg)
+    agent.logger.warning.assert_called()
+
+
+@pytest.mark.asyncio
+async def test_custom_action_reply_with_goal(agent):
+    agent._send_to_llm = MagicMock(side_effect=agent.send)
+    agent._add_custom_actions()
+    action_fn = agent.actions.actions[(".reply_with_goal", 3)]
+
+    mock_term = MagicMock(args=["msg", "norms", "goal"])
+    gen = action_fn(agent, mock_term, MagicMock())
+    next(gen)
+    agent._send_to_llm.assert_called_with("msg", "norms", "goal")
+
+
+@pytest.mark.asyncio
+async def test_custom_action_notify_norms(agent):
+    agent._add_custom_actions()
+    action_fn = agent.actions.actions[(".notify_norms", 1)]
+
+    mock_term = MagicMock(args=["norms_list"])
+    gen = action_fn(agent, mock_term, MagicMock())
+    next(gen)
+
+    agent.send.assert_called()
+    msg = agent.send.call_args[0][0]
+    assert msg.thread == "active_norms_update"
+    assert msg.body == "norms_list"
+
+
+@pytest.mark.asyncio
+async def test_custom_action_say(agent):
+    agent._add_custom_actions()
+    action_fn = agent.actions.actions[(".say", 1)]
+
+    mock_term = MagicMock(args=["hello"])
+    gen = action_fn(agent, mock_term, MagicMock())
+    next(gen)
+
+    assert agent.send.call_count == 2
+    msgs = [c[0][0] for c in agent.send.call_args_list]
+    assert any(m.to == settings.agent_settings.robot_speech_name for m in msgs)
+    assert any(
+        m.to == settings.agent_settings.llm_name and m.thread == "assistant_message" for m in msgs
+    )
+
+
+@pytest.mark.asyncio
+async def test_custom_action_gesture(agent):
+    agent._add_custom_actions()
+    # Test single
+    action_fn = agent.actions.actions[(".gesture", 2)]
+    mock_term = MagicMock(args=["single", "wave"])
+    gen = action_fn(agent, mock_term, MagicMock())
+    next(gen)
+    msg = agent.send.call_args[0][0]
+    assert "actuate/gesture/single" in msg.body
+
+    # Test tag
+    mock_term.args = ["tag", "happy"]
+    gen = action_fn(agent, mock_term, MagicMock())
+    next(gen)
+    msg = agent.send.call_args[0][0]
+    assert "actuate/gesture/tag" in msg.body
+
+
+@pytest.mark.asyncio
+async def test_custom_action_notify_user_said(agent):
+    agent._add_custom_actions()
+    action_fn = agent.actions.actions[(".notify_user_said", 1)]
+    mock_term = MagicMock(args=["hello"])
+    gen = action_fn(agent, mock_term, MagicMock())
+    next(gen)
+    msg = agent.send.call_args[0][0]
+    assert msg.to == settings.agent_settings.llm_name
+    assert msg.thread == "user_message"
+
+
+@pytest.mark.asyncio
+async def test_custom_action_notify_trigger_start_end(agent):
+    agent._add_custom_actions()
+    # Start
+    action_fn = agent.actions.actions[(".notify_trigger_start", 1)]
+    gen = action_fn(agent, MagicMock(args=["t1"]), MagicMock())
+    next(gen)
+    assert agent.send.call_args[0][0].thread == "trigger_start"
+
+    # End
+    action_fn = agent.actions.actions[(".notify_trigger_end", 1)]
+    gen = action_fn(agent, MagicMock(args=["t1"]), MagicMock())
+    next(gen)
+    assert agent.send.call_args[0][0].thread == "trigger_end"
+
+
+@pytest.mark.asyncio
+async def test_custom_action_notify_goal_start(agent):
+    agent._add_custom_actions()
+    action_fn = agent.actions.actions[(".notify_goal_start", 1)]
+    gen = action_fn(agent, MagicMock(args=["g1"]), MagicMock())
+    next(gen)
+    assert agent.send.call_args[0][0].thread == "goal_start"
+
+
+@pytest.mark.asyncio
+async def test_custom_action_notify_transition_phase(agent):
+    agent._add_custom_actions()
+    action_fn = agent.actions.actions[(".notify_transition_phase", 2)]
+    gen = action_fn(agent, MagicMock(args=["old", "new"]), MagicMock())
+    next(gen)
+    msg = agent.send.call_args[0][0]
+    assert msg.thread == "transition_phase"
+    assert "old" in msg.body and "new" in msg.body
+
+
+def test_remove_belief_no_args(agent):
+    agent._wake_bdi_loop = MagicMock()
+    agent.bdi_agent.call.return_value = True
+    agent._remove_belief("fact", None)
+    assert agent.bdi_agent.call.called
+
+
+def test_set_goal_with_args(agent):
+    agent._wake_bdi_loop = MagicMock()
+    agent._set_goal("goal", ["arg1", "arg2"])
+    assert agent.bdi_agent.call.called
+
+
+def test_format_belief_string():
+    assert BDICoreAgent.format_belief_string("b") == "b"
+    assert BDICoreAgent.format_belief_string("b", ["a1", "a2"]) == "b(a1,a2)"
+
+
+def test_force_norm(agent):
+    agent._add_belief = MagicMock()
+    agent._force_norm("be_polite")
+    agent._add_belief.assert_called_with("force_be_polite")
+
+
+def test_force_trigger(agent):
+    agent._set_goal = MagicMock()
+    agent._force_trigger("trig")
+    agent._set_goal.assert_called_with("trig")
+
+
+def test_force_next_phase(agent):
+    agent._set_goal = MagicMock()
+    agent._force_next_phase()
+    agent._set_goal.assert_called_with("force_transition_phase")

test/unit/agents/bdi/test_bdi_program_manager.py

@@ -1,14 +1,30 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import asyncio
+import json
 import sys
 import uuid
-from unittest.mock import AsyncMock
+from unittest.mock import AsyncMock, MagicMock, mock_open, patch
 
 import pytest
 
 from control_backend.agents.bdi.bdi_program_manager import BDIProgramManager
 from control_backend.core.agent_system import InternalMessage
-from control_backend.schemas.belief_message import BeliefMessage
-from control_backend.schemas.program import BasicNorm, Goal, Phase, Plan, Program
+from control_backend.schemas.program import (
+    BasicNorm,
+    ConditionalNorm,
+    Goal,
+    InferredBelief,
+    KeywordBelief,
+    Phase,
+    Plan,
+    Program,
+    Trigger,
+)
 
 # Fix Windows Proactor loop for zmq
 if sys.platform.startswith("win"):
@@ -48,24 +64,26 @@ def make_valid_program_json(norm="N1", goal="G1") -> str:
     ).model_dump_json()
 
 
-@pytest.mark.skip(reason="Functionality being rebuilt.")
 @pytest.mark.asyncio
-async def test_send_to_bdi():
+async def test_create_agentspeak_and_send_to_bdi(mock_settings):
     manager = BDIProgramManager(name="program_manager_test")
     manager.send = AsyncMock()
 
     program = Program.model_validate_json(make_valid_program_json())
-    await manager._create_agentspeak_and_send_to_bdi(program)
+
+    with patch("builtins.open", mock_open()) as mock_file:
+        await manager._create_agentspeak_and_send_to_bdi(program)
+
+        # Check file writing
+        mock_file.assert_called_with(mock_settings.behaviour_settings.agentspeak_file, "w")
+        handle = mock_file()
+        handle.write.assert_called()
 
     assert manager.send.await_count == 1
     msg: InternalMessage = manager.send.await_args[0][0]
-    assert msg.thread == "beliefs"
-
-    beliefs = BeliefMessage.model_validate_json(msg.body)
-    names = {b.name: b.arguments for b in beliefs.beliefs}
-
-    assert "norms" in names and names["norms"] == ["N1"]
-    assert "goals" in names and names["goals"] == ["G1"]
+    assert msg.thread == "new_program"
+    assert msg.to == mock_settings.agent_settings.bdi_core_name
+    assert msg.body == mock_settings.behaviour_settings.agentspeak_file
 
 
 @pytest.mark.asyncio
@@ -81,6 +99,9 @@ async def test_receive_programs_valid_and_invalid():
     manager.sub_socket = sub
     manager._create_agentspeak_and_send_to_bdi = AsyncMock()
     manager._send_clear_llm_history = AsyncMock()
+    manager._send_program_to_user_interrupt = AsyncMock()
+    manager._send_beliefs_to_semantic_belief_extractor = AsyncMock()
+    manager._send_goals_to_semantic_belief_extractor = AsyncMock()
 
     try:
         # Will give StopAsyncIteration when the predefined `sub.recv_multipart` side-effects run out
@@ -94,7 +115,8 @@ async def test_receive_programs_valid_and_invalid():
     assert forwarded.phases[0].norms[0].name == "N1"
     assert forwarded.phases[0].goals[0].name == "G1"
 
-    # Verify history clear was triggered
+    # Verify history clear was triggered exactly once (for the valid program)
+    # The invalid program loop `continue`s before calling _send_clear_llm_history
     assert manager._send_clear_llm_history.await_count == 1
 
 
@@ -113,4 +135,274 @@ async def test_send_clear_llm_history(mock_settings):
 
     # Verify the content and recipient
     assert msg.body == "clear_history"
-    assert msg.to == "llm_agent"
+
+
+@pytest.mark.asyncio
+async def test_handle_message_transition_phase(mock_settings):
+    mock_settings.agent_settings.user_interrupt_name = "user_interrupt_agent"
+    manager = BDIProgramManager(name="program_manager_test")
+    manager.send = AsyncMock()
+
+    # Setup state
+    prog = Program.model_validate_json(make_valid_program_json(norm="N1", goal="G1"))
+    manager._initialize_internal_state(prog)
+
+    # Test valid transition (to same phase for simplicity, or we need 2 phases)
+    # Let's create a program with 2 phases
+    phase2_id = uuid.uuid4()
+    phase2 = Phase(id=phase2_id, name="Phase 2", norms=[], goals=[], triggers=[])
+    prog.phases.append(phase2)
+    manager._initialize_internal_state(prog)
+
+    current_phase_id = str(prog.phases[0].id)
+    next_phase_id = str(phase2_id)
+
+    payload = json.dumps({"old": current_phase_id, "new": next_phase_id})
+    msg = InternalMessage(to="me", sender="bdi", body=payload, thread="transition_phase")
+
+    await manager.handle_message(msg)
+
+    assert str(manager._phase.id) == next_phase_id
+
+    # Allow background tasks to run (add_behavior)
+    await asyncio.sleep(0)
+
+    # Check notifications sent
+    # 1. beliefs to extractor
+    # 2. goals to extractor
+    # 3. notification to user interrupt
+
+    assert manager.send.await_count >= 3
+
+    # Verify user interrupt notification
+    calls = manager.send.await_args_list
+    ui_msgs = [
+        c[0][0] for c in calls if c[0][0].to == mock_settings.agent_settings.user_interrupt_name
+    ]
+    assert len(ui_msgs) > 0
+    assert ui_msgs[-1].body == next_phase_id
+
+
+@pytest.mark.asyncio
+async def test_handle_message_transition_phase_desync():
+    manager = BDIProgramManager(name="program_manager_test")
+    manager.logger = MagicMock()
+
+    prog = Program.model_validate_json(make_valid_program_json())
+    manager._initialize_internal_state(prog)
+
+    current_phase_id = str(prog.phases[0].id)
+
+    # Request transition from WRONG old phase
+    payload = json.dumps({"old": "wrong_id", "new": "some_new_id"})
+    msg = InternalMessage(to="me", sender="bdi", body=payload, thread="transition_phase")
+
+    await manager.handle_message(msg)
+
+    # Should warn and do nothing
+    manager.logger.warning.assert_called_once()
+    assert "Phase transition desync detected" in manager.logger.warning.call_args[0][0]
+    assert str(manager._phase.id) == current_phase_id
+
+
+@pytest.mark.asyncio
+async def test_handle_message_transition_phase_end(mock_settings):
+    mock_settings.agent_settings.user_interrupt_name = "user_interrupt_agent"
+    manager = BDIProgramManager(name="program_manager_test")
+    manager.send = AsyncMock()
+
+    prog = Program.model_validate_json(make_valid_program_json())
+    manager._initialize_internal_state(prog)
+    current_phase_id = str(prog.phases[0].id)
+
+    payload = json.dumps({"old": current_phase_id, "new": "end"})
+    msg = InternalMessage(to="me", sender="bdi", body=payload, thread="transition_phase")
+
+    await manager.handle_message(msg)
+
+    assert manager._phase is None
+
+    # Allow background tasks to run (add_behavior)
+    await asyncio.sleep(0)
+
+    # Verify notification to user interrupt
+    assert manager.send.await_count == 1
+    msg_sent = manager.send.await_args[0][0]
+    assert msg_sent.to == mock_settings.agent_settings.user_interrupt_name
+    assert msg_sent.body == "end"
+
+
+@pytest.mark.asyncio
+async def test_handle_message_achieve_goal(mock_settings):
+    mock_settings.agent_settings.text_belief_extractor_name = "text_belief_extractor_agent"
+    manager = BDIProgramManager(name="program_manager_test")
+    manager.send = AsyncMock()
+
+    prog = Program.model_validate_json(make_valid_program_json(goal="TargetGoal"))
+    manager._initialize_internal_state(prog)
+
+    goal_id = str(prog.phases[0].goals[0].id)
+
+    msg = InternalMessage(to="me", sender="ui", body=goal_id, thread="achieve_goal")
+
+    await manager.handle_message(msg)
+
+    # Should send achieved goals to text extractor
+    assert manager.send.await_count == 1
+    msg_sent = manager.send.await_args[0][0]
+    assert msg_sent.to == mock_settings.agent_settings.text_belief_extractor_name
+    assert msg_sent.thread == "achieved_goals"
+
+    # Verify body
+    from control_backend.schemas.belief_list import GoalList
+
+    gl = GoalList.model_validate_json(msg_sent.body)
+    assert len(gl.goals) == 1
+    assert gl.goals[0].name == "TargetGoal"
+
+
+@pytest.mark.asyncio
+async def test_handle_message_achieve_goal_not_found():
+    manager = BDIProgramManager(name="program_manager_test")
+    manager.send = AsyncMock()
+    manager.logger = MagicMock()
+
+    prog = Program.model_validate_json(make_valid_program_json())
+    manager._initialize_internal_state(prog)
+
+    msg = InternalMessage(to="me", sender="ui", body="non_existent_id", thread="achieve_goal")
+
+    await manager.handle_message(msg)
+
+    manager.send.assert_not_called()
+    manager.logger.debug.assert_called()
+
+
+@pytest.mark.asyncio
+async def test_setup(mock_settings):
+    manager = BDIProgramManager(name="program_manager_test")
+    manager.send = AsyncMock()
+
+    def close_coro(coro):
+        coro.close()
+        return MagicMock()
+
+    manager.add_behavior = MagicMock(side_effect=close_coro)
+
+    mock_context = MagicMock()
+    mock_sub = MagicMock()
+    mock_context.socket.return_value = mock_sub
+
+    with patch(
+        "control_backend.agents.bdi.bdi_program_manager.Context.instance", return_value=mock_context
+    ):
+        # We also need to mock file writing in _create_agentspeak_and_send_to_bdi
+        with patch("builtins.open", new_callable=MagicMock):
+            await manager.setup()
+
+    # Check logic
+    # 1. Sends default empty program to BDI
+    assert manager.send.await_count == 1
+    assert manager.send.await_args[0][0].to == mock_settings.agent_settings.bdi_core_name
+
+    # 2. Connects SUB socket
+    mock_sub.connect.assert_called_with(mock_settings.zmq_settings.internal_sub_address)
+    mock_sub.subscribe.assert_called_with("program")
+
+    # 3. Adds behavior
+    manager.add_behavior.assert_called()
+
+
+@pytest.mark.asyncio
+async def test_send_program_to_user_interrupt(mock_settings):
+    """Test directly sending the program to the user interrupt agent."""
+    mock_settings.agent_settings.user_interrupt_name = "user_interrupt_agent"
+
+    manager = BDIProgramManager(name="program_manager_test")
+    manager.send = AsyncMock()
+
+    program = Program.model_validate_json(make_valid_program_json())
+
+    await manager._send_program_to_user_interrupt(program)
+
+    assert manager.send.await_count == 1
+    msg = manager.send.await_args[0][0]
+    assert msg.to == "user_interrupt_agent"
+    assert msg.thread == "new_program"
+    assert "Basic Phase" in msg.body
+
+
+@pytest.mark.asyncio
+async def test_complex_program_extraction():
+    manager = BDIProgramManager(name="program_manager_test")
+
+    # 1. Create Complex Components
+
+    # Inferred Belief (A & B)
+    belief_left = KeywordBelief(id=uuid.uuid4(), name="b1", keyword="hot")
+    belief_right = KeywordBelief(id=uuid.uuid4(), name="b2", keyword="sunny")
+    inferred_belief = InferredBelief(
+        id=uuid.uuid4(), name="b_inf", operator="AND", left=belief_left, right=belief_right
+    )
+
+    # Conditional Norm
+    cond_norm = ConditionalNorm(
+        id=uuid.uuid4(), name="norm_cond", norm="wear_hat", condition=inferred_belief
+    )
+
+    # Trigger with Inferred Belief condition
+    dummy_plan = Plan(id=uuid.uuid4(), name="dummy_plan", steps=[])
+    trigger = Trigger(id=uuid.uuid4(), name="trigger_1", condition=inferred_belief, plan=dummy_plan)
+
+    #  Nested Goal
+    sub_goal = Goal(
+        id=uuid.uuid4(),
+        name="sub_goal",
+        description="desc",
+        plan=Plan(id=uuid.uuid4(), name="empty", steps=[]),
+        can_fail=True,
+    )
+
+    parent_goal = Goal(
+        id=uuid.uuid4(),
+        name="parent_goal",
+        description="desc",
+        # The plan contains the sub_goal as a step
+        plan=Plan(id=uuid.uuid4(), name="parent_plan", steps=[sub_goal]),
+        can_fail=False,
+    )
+
+    # 2. Assemble Program
+    phase = Phase(
+        id=uuid.uuid4(),
+        name="Complex Phase",
+        norms=[cond_norm],
+        goals=[parent_goal],
+        triggers=[trigger],
+    )
+    program = Program(phases=[phase])
+
+    # 3. Initialize Internal State (Triggers _populate_goal_mapping -> Nested Goal logic)
+    manager._initialize_internal_state(program)
+
+    # Assertion for Line 53-54 (Mapping population)
+    # Both parent and sub-goal should be mapped
+    assert str(parent_goal.id) in manager._goal_mapping
+    assert str(sub_goal.id) in manager._goal_mapping
+
+    # 4. Test Belief Extraction (Triggers lines 132-133, 142-146)
+    beliefs = manager._extract_current_beliefs()
+
+    # Should extract recursive beliefs from cond_norm and trigger
+    # Inferred belief splits into Left + Right. Since we use it twice, we get duplicates
+    # checking existence is enough.
+    belief_names = [b.name for b in beliefs]
+    assert "b1" in belief_names
+    assert "b2" in belief_names
+
+    # 5. Test Goal Extraction (Triggers lines 173, 185)
+    goals = manager._extract_current_goals()
+
+    goal_names = [g.name for g in goals]
+    assert "parent_goal" in goal_names
+    assert "sub_goal" in goal_names

test/unit/agents/bdi/test_belief_collector.py

@@ -1,135 +0,0 @@
-import json
-from unittest.mock import AsyncMock
-
-import pytest
-
-from control_backend.agents.bdi import (
-    BDIBeliefCollectorAgent,
-)
-from control_backend.core.agent_system import InternalMessage
-from control_backend.core.config import settings
-from control_backend.schemas.belief_message import Belief
-
-
-@pytest.fixture
-def agent():
-    agent = BDIBeliefCollectorAgent("belief_collector_agent")
-    return agent
-
-
-def make_msg(body: dict, sender: str = "sender"):
-    return InternalMessage(to="collector", sender=sender, body=json.dumps(body))
-
-
-@pytest.mark.asyncio
-async def test_handle_message_routes_belief_text(agent, mocker):
-    """
-    Test that when a message is received, _handle_belief_text is called with that message.
-    """
-    payload = {"type": "belief_extraction_text", "beliefs": {"user_said": [["hi"]]}}
-    spy = mocker.patch.object(agent, "_handle_belief_text", new_callable=AsyncMock)
-
-    await agent.handle_message(make_msg(payload))
-
-    spy.assert_awaited_once_with(payload, "sender")
-
-
-@pytest.mark.asyncio
-async def test_handle_message_routes_emotion(agent, mocker):
-    payload = {"type": "emotion_extraction_text"}
-    spy = mocker.patch.object(agent, "_handle_emo_text", new_callable=AsyncMock)
-
-    await agent.handle_message(make_msg(payload))
-
-    spy.assert_awaited_once_with(payload, "sender")
-
-
-@pytest.mark.asyncio
-async def test_handle_message_bad_json(agent, mocker):
-    agent._handle_belief_text = AsyncMock()
-    bad_msg = InternalMessage(to="collector", sender="sender", body="not json")
-
-    await agent.handle_message(bad_msg)
-
-    agent._handle_belief_text.assert_not_awaited()
-
-
-@pytest.mark.asyncio
-async def test_handle_belief_text_sends_when_beliefs_exist(agent, mocker):
-    payload = {"type": "belief_extraction_text", "beliefs": {"user_said": ["hello"]}}
-    spy = mocker.patch.object(agent, "_send_beliefs_to_bdi", new_callable=AsyncMock)
-    expected = [Belief(name="user_said", arguments=["hello"])]
-
-    await agent._handle_belief_text(payload, "origin")
-
-    spy.assert_awaited_once_with(expected, origin="origin")
-
-
-@pytest.mark.asyncio
-async def test_handle_belief_text_no_send_when_empty(agent, mocker):
-    payload = {"type": "belief_extraction_text", "beliefs": {}}
-    spy = mocker.patch.object(agent, "_send_beliefs_to_bdi", new_callable=AsyncMock)
-
-    await agent._handle_belief_text(payload, "origin")
-
-    spy.assert_not_awaited()
-
-
-@pytest.mark.asyncio
-async def test_send_beliefs_to_bdi(agent):
-    agent.send = AsyncMock()
-    beliefs = [Belief(name="user_said", arguments=["hello", "world"])]
-
-    await agent._send_beliefs_to_bdi(beliefs, origin="origin")
-
-    agent.send.assert_awaited_once()
-    sent: InternalMessage = agent.send.call_args.args[0]
-    assert sent.to == settings.agent_settings.bdi_core_name
-    assert sent.thread == "beliefs"
-    assert json.loads(sent.body)["create"] == [belief.model_dump() for belief in beliefs]
-
-
-@pytest.mark.asyncio
-async def test_setup_executes(agent):
-    """Covers setup and asserts the agent has a name."""
-    await agent.setup()
-    assert agent.name == "belief_collector_agent"  # simple property assertion
-
-
-@pytest.mark.asyncio
-async def test_handle_message_unrecognized_type_executes(agent):
-    """Covers the else branch for unrecognized message type."""
-    payload = {"type": "unknown_type"}
-    msg = make_msg(payload, sender="tester")
-    # Wrap send to ensure nothing is sent
-    agent.send = AsyncMock()
-    await agent.handle_message(msg)
-    # Assert no messages were sent
-    agent.send.assert_not_awaited()
-
-
-@pytest.mark.asyncio
-async def test_handle_emo_text_executes(agent):
-    """Covers the _handle_emo_text method."""
-    # The method does nothing, but we can assert it returns None
-    result = await agent._handle_emo_text({}, "origin")
-    assert result is None
-
-
-@pytest.mark.asyncio
-async def test_send_beliefs_to_bdi_empty_executes(agent):
-    """Covers early return when beliefs are empty."""
-    agent.send = AsyncMock()
-    await agent._send_beliefs_to_bdi({})
-    # Assert that nothing was sent
-    agent.send.assert_not_awaited()
-
-
-@pytest.mark.asyncio
-async def test_handle_belief_text_invalid_returns_none(agent, mocker):
-    payload = {"type": "belief_extraction_text", "beliefs": {"user_said": "invalid-argument"}}
-
-    result = await agent._handle_belief_text(payload, "origin")
-
-    # The method itself returns None
-    assert result is None

test/unit/agents/bdi/test_text_belief_extractor.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import json
 import uuid
 from unittest.mock import AsyncMock, MagicMock, patch
@@ -14,6 +20,7 @@ from control_backend.schemas.belief_message import Belief as InternalBelief
 from control_backend.schemas.belief_message import BeliefMessage
 from control_backend.schemas.chat_history import ChatHistory, ChatMessage
 from control_backend.schemas.program import (
+    BaseGoal,  # Changed from Goal
     ConditionalNorm,
     KeywordBelief,
     LLMAction,
@@ -28,7 +35,8 @@ from control_backend.schemas.program import (
 @pytest.fixture
 def llm():
     llm = TextBeliefExtractorAgent.LLM(MagicMock(), 4)
-    llm._query_llm = AsyncMock()
+    # We must ensure _query_llm returns a dictionary so iterating it doesn't fail
+    llm._query_llm = AsyncMock(return_value={})
     return llm
 
 
@@ -357,6 +365,30 @@ async def test_simulated_real_turn_remove_belief(agent, llm, sample_program):
     assert any(b.name == "no_more_booze" for b in agent._current_beliefs.false)
 
 
+@pytest.mark.asyncio
+async def test_infer_goal_completions_sends_beliefs(agent, llm):
+    """Test that inferred goal completions are sent to the BDI core."""
+    goal = BaseGoal(
+        id=uuid.uuid4(), name="Say Hello", description="The user said hello", can_fail=True
+    )
+    agent.goal_inferrer.goals = {goal}
+
+    # Mock goal inference: goal is achieved
+    llm.query = AsyncMock(return_value=True)
+
+    await agent._infer_goal_completions()
+
+    # Should send belief change to BDI core
+    agent.send.assert_awaited_once()
+    sent: InternalMessage = agent.send.call_args.args[0]
+    assert sent.to == settings.agent_settings.bdi_core_name
+    assert sent.thread == "beliefs"
+
+    parsed = BeliefMessage.model_validate_json(sent.body)
+    assert len(parsed.create) == 1
+    assert parsed.create[0].name == "achieved_say_hello"
+
+
 @pytest.mark.asyncio
 async def test_llm_failure_handling(agent, llm, sample_program):
     """
@@ -374,3 +406,155 @@ async def test_llm_failure_handling(agent, llm, sample_program):
 
     assert len(belief_changes.true) == 0
     assert len(belief_changes.false) == 0
+
+
+def test_belief_state_bool():
+    # Empty
+    bs = BeliefState()
+    assert not bs
+
+    # True set
+    bs_true = BeliefState(true={InternalBelief(name="a", arguments=None)})
+    assert bs_true
+
+    # False set
+    bs_false = BeliefState(false={InternalBelief(name="a", arguments=None)})
+    assert bs_false
+
+
+@pytest.mark.asyncio
+async def test_handle_beliefs_message_validation_error(agent, mock_settings):
+    # Invalid JSON
+    mock_settings.agent_settings.bdi_program_manager_name = "bdi_program_manager_agent"
+    msg = InternalMessage(
+        to="me",
+        sender=mock_settings.agent_settings.bdi_program_manager_name,
+        thread="beliefs",
+        body="invalid json",
+    )
+    # Should log warning and return
+    agent.logger = MagicMock()
+    await agent.handle_message(msg)
+    agent.logger.warning.assert_called()
+
+    # Invalid Model
+    msg.body = json.dumps({"beliefs": [{"invalid": "obj"}]})
+    await agent.handle_message(msg)
+    agent.logger.warning.assert_called()
+
+
+@pytest.mark.asyncio
+async def test_handle_goals_message_validation_error(agent, mock_settings):
+    mock_settings.agent_settings.bdi_program_manager_name = "bdi_program_manager_agent"
+    msg = InternalMessage(
+        to="me",
+        sender=mock_settings.agent_settings.bdi_program_manager_name,
+        thread="goals",
+        body="invalid json",
+    )
+    agent.logger = MagicMock()
+    await agent.handle_message(msg)
+    agent.logger.warning.assert_called()
+
+
+@pytest.mark.asyncio
+async def test_handle_goal_achieved_message_validation_error(agent, mock_settings):
+    mock_settings.agent_settings.bdi_program_manager_name = "bdi_program_manager_agent"
+    msg = InternalMessage(
+        to="me",
+        sender=mock_settings.agent_settings.bdi_program_manager_name,
+        thread="achieved_goals",
+        body="invalid json",
+    )
+    agent.logger = MagicMock()
+    await agent.handle_message(msg)
+    agent.logger.warning.assert_called()
+
+
+@pytest.mark.asyncio
+async def test_goal_inferrer_infer_from_conversation(agent, llm):
+    # Setup goals
+    # Use BaseGoal object as typically received by the extractor
+    g1 = BaseGoal(id=uuid.uuid4(), name="g1", description="desc", can_fail=True)
+
+    # Use real GoalAchievementInferrer
+    from control_backend.agents.bdi.text_belief_extractor_agent import GoalAchievementInferrer
+
+    inferrer = GoalAchievementInferrer(llm)
+    inferrer.goals = {g1}
+
+    # Mock LLM response
+    llm._query_llm.return_value = True
+
+    completions = await inferrer.infer_from_conversation(ChatHistory(messages=[]))
+    assert completions
+    # slugify uses slugify library, hard to predict exact string without it,
+    # but we can check values
+    assert list(completions.values())[0] is True
+
+
+def test_apply_conversation_message_limit(agent):
+    with patch("control_backend.agents.bdi.text_belief_extractor_agent.settings") as mock_s:
+        mock_s.behaviour_settings.conversation_history_length_limit = 2
+        agent.conversation.messages = []
+
+        agent._apply_conversation_message(ChatMessage(role="user", content="1"))
+        agent._apply_conversation_message(ChatMessage(role="assistant", content="2"))
+        agent._apply_conversation_message(ChatMessage(role="user", content="3"))
+
+        assert len(agent.conversation.messages) == 2
+        assert agent.conversation.messages[0].content == "2"
+        assert agent.conversation.messages[1].content == "3"
+
+
+@pytest.mark.asyncio
+async def test_handle_program_manager_reset(agent):
+    with patch("control_backend.agents.bdi.text_belief_extractor_agent.settings") as mock_s:
+        mock_s.agent_settings.bdi_program_manager_name = "pm"
+        agent.conversation.messages = [ChatMessage(role="user", content="hi")]
+        agent.belief_inferrer.available_beliefs = [
+            SemanticBelief(id=uuid.uuid4(), name="b", description="d")
+        ]
+
+        msg = InternalMessage(to="me", sender="pm", thread="conversation_history", body="reset")
+        await agent.handle_message(msg)
+
+        assert len(agent.conversation.messages) == 0
+        assert len(agent.belief_inferrer.available_beliefs) == 0
+
+
+def test_split_into_chunks():
+    from control_backend.agents.bdi.text_belief_extractor_agent import SemanticBeliefInferrer
+
+    items = [1, 2, 3, 4, 5]
+    chunks = SemanticBeliefInferrer._split_into_chunks(items, 2)
+    assert len(chunks) == 2
+    assert len(chunks[0]) + len(chunks[1]) == 5
+
+
+@pytest.mark.asyncio
+async def test_infer_beliefs_call(agent, llm):
+    from control_backend.agents.bdi.text_belief_extractor_agent import SemanticBeliefInferrer
+
+    inferrer = SemanticBeliefInferrer(llm)
+    sb = SemanticBelief(id=uuid.uuid4(), name="is_happy", description="User is happy")
+
+    llm.query = AsyncMock(return_value={"is_happy": True})
+
+    res = await inferrer._infer_beliefs(ChatHistory(messages=[]), [sb])
+    assert res == {"is_happy": True}
+    llm.query.assert_called_once()
+
+
+@pytest.mark.asyncio
+async def test_infer_goal_call(agent, llm):
+    from control_backend.agents.bdi.text_belief_extractor_agent import GoalAchievementInferrer
+
+    inferrer = GoalAchievementInferrer(llm)
+    goal = BaseGoal(id=uuid.uuid4(), name="g1", description="d")
+
+    llm.query = AsyncMock(return_value=True)
+
+    res = await inferrer._infer_goal(ChatHistory(messages=[]), goal)
+    assert res is True
+    llm.query.assert_called_once()

test/unit/agents/communication/test_ri_communication_agent.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import asyncio
 from unittest.mock import ANY, AsyncMock, MagicMock, patch
 
@@ -53,7 +59,11 @@ async def test_setup_success_connects_and_starts_robot(zmq_context):
         MockGesture.return_value.start = AsyncMock()
         agent = RICommunicationAgent("ri_comm", address="tcp://localhost:5555", bind=False)
 
-        agent.add_behavior = MagicMock()
+        def close_coro(coro):
+            coro.close()
+            return MagicMock()
+
+        agent.add_behavior = MagicMock(side_effect=close_coro)
 
         await agent.setup()
 
@@ -83,7 +93,11 @@ async def test_setup_binds_when_requested(zmq_context):
 
     agent = RICommunicationAgent("ri_comm", address="tcp://localhost:5555", bind=True)
 
-    agent.add_behavior = MagicMock()
+    def close_coro(coro):
+        coro.close()
+        return MagicMock()
+
+    agent.add_behavior = MagicMock(side_effect=close_coro)
 
     with (
         patch(speech_agent_path(), autospec=True) as MockSpeech,
@@ -151,6 +165,7 @@ async def test_handle_negotiation_response_updates_req_socket(zmq_context):
 @pytest.mark.asyncio
 async def test_handle_disconnection_publishes_and_reconnects():
     pub_socket = AsyncMock()
+    pub_socket.close = MagicMock()
     agent = RICommunicationAgent("ri_comm")
     agent.pub_socket = pub_socket
     agent.connected = True
@@ -233,6 +248,25 @@ async def test_handle_negotiation_response_unhandled_id():
     )
 
 
+@pytest.mark.asyncio
+async def test_handle_negotiation_response_audio(zmq_context):
+    agent = RICommunicationAgent("ri_comm")
+
+    with patch(
+        "control_backend.agents.communication.ri_communication_agent.VADAgent", autospec=True
+    ) as MockVAD:
+        MockVAD.return_value.start = AsyncMock()
+
+        await agent._handle_negotiation_response(
+            {"data": [{"id": "audio", "port": 7000, "bind": False}]}
+        )
+
+        MockVAD.assert_called_once_with(
+            audio_in_address="tcp://localhost:7000", audio_in_bind=False
+        )
+        MockVAD.return_value.start.assert_awaited_once()
+
+
 @pytest.mark.asyncio
 async def test_stop_closes_sockets():
     req = MagicMock()
@@ -323,6 +357,7 @@ async def test_listen_loop_generic_exception():
 @pytest.mark.asyncio
 async def test_handle_disconnection_timeout(monkeypatch):
     pub = AsyncMock()
+    pub.close = MagicMock()
     pub.send_multipart = AsyncMock(side_effect=TimeoutError)
 
     agent = RICommunicationAgent("ri_comm")

test/unit/agents/llm/test_llm_agent.py

@@ -1,4 +1,10 @@
-"""Mocks `httpx` and tests chunking logic."""
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+--------------------------------------------------------------------------------
+Mocks `httpx` and tests chunking logic.
+"""
 
 from unittest.mock import AsyncMock, MagicMock, patch
 
@@ -18,6 +24,12 @@ def mock_httpx_client():
         yield mock_client
 
 
+@pytest.fixture(autouse=True)
+def mock_experiment_logger():
+    with patch("control_backend.agents.llm.llm_agent.experiment_logger") as logger:
+        yield logger
+
+
 @pytest.mark.asyncio
 async def test_llm_processing_success(mock_httpx_client, mock_settings):
     # Setup the mock response for the stream
@@ -58,17 +70,64 @@ async def test_llm_processing_success(mock_httpx_client, mock_settings):
         to="llm_agent",
         sender=mock_settings.agent_settings.bdi_core_name,
         body=prompt.model_dump_json(),
+        thread="prompt_message",  # REQUIRED: thread must match handle_message logic
     )
 
+    agent._process_bdi_message = AsyncMock()
+
     await agent.handle_message(msg)
 
+    agent._process_bdi_message.assert_called()
+
+
+@pytest.mark.asyncio
+async def test_process_bdi_message_success(mock_httpx_client, mock_settings):
+    # Setup the mock response for the stream
+    mock_response = MagicMock()
+    mock_response.raise_for_status = MagicMock()
+
+    # Simulate stream lines
+    lines = [
+        b'data: {"choices": [{"delta": {"content": "Hello"}}]}',
+        b'data: {"choices": [{"delta": {"content": " world"}}]}',
+        b'data: {"choices": [{"delta": {"content": "."}}]}',
+        b"data: [DONE]",
+    ]
+
+    async def aiter_lines_gen():
+        for line in lines:
+            yield line.decode()
+
+    mock_response.aiter_lines.side_effect = aiter_lines_gen
+
+    mock_stream_context = MagicMock()
+    mock_stream_context.__aenter__ = AsyncMock(return_value=mock_response)
+    mock_stream_context.__aexit__ = AsyncMock(return_value=None)
+
+    # Configure the client
+    mock_httpx_client.stream = MagicMock(return_value=mock_stream_context)
+
+    # Setup Agent
+    agent = LLMAgent("llm_agent")
+    agent.send = AsyncMock()  # Mock the send method to verify replies
+
+    mock_logger = MagicMock()
+    agent.logger = mock_logger
+
+    # Simulate receiving a message from BDI
+    prompt = LLMPromptMessage(text="Hi", norms=[], goals=[])
+
+    await agent._process_bdi_message(prompt)
+
     # Verification
     # "Hello world." constitutes one sentence/chunk based on punctuation split
-    # The agent should call send once with the full sentence
+    # The agent should call send once with the full sentence, PLUS once more for full reply
     assert agent.send.called
-    args = agent.send.call_args_list[0][0][0]
-    assert args.to == mock_settings.agent_settings.bdi_core_name
-    assert "Hello world." in args.body
+
+    # Check args. We expect at least one call sending "Hello world."
+    calls = agent.send.call_args_list
+    bodies = [c[0][0].body for c in calls]
+    assert any("Hello world." in b for b in bodies)
 
 
 @pytest.mark.asyncio
@@ -76,22 +135,15 @@ async def test_llm_processing_errors(mock_httpx_client, mock_settings):
     agent = LLMAgent("llm_agent")
     agent.send = AsyncMock()
     prompt = LLMPromptMessage(text="Hi", norms=[], goals=[])
-    msg = InternalMessage(
-        to="llm",
-        sender=mock_settings.agent_settings.bdi_core_name,
-        body=prompt.model_dump_json(),
-    )
 
-    # HTTP Error
+    # HTTP Error: stream method RAISES exception immediately
     mock_httpx_client.stream = MagicMock(side_effect=httpx.HTTPError("Fail"))
-    await agent.handle_message(msg)
-    assert "LLM service unavailable." in agent.send.call_args[0][0].body
 
-    # General Exception
-    agent.send.reset_mock()
-    mock_httpx_client.stream = MagicMock(side_effect=Exception("Boom"))
-    await agent.handle_message(msg)
-    assert "Error processing the request." in agent.send.call_args[0][0].body
+    await agent._process_bdi_message(prompt)
+
+    # Check that error message was sent
+    assert agent.send.called
+    assert "LLM service unavailable." in agent.send.call_args_list[0][0][0].body
 
 
 @pytest.mark.asyncio
@@ -113,16 +165,13 @@ async def test_llm_json_error(mock_httpx_client, mock_settings):
 
     agent = LLMAgent("llm_agent")
     agent.send = AsyncMock()
+    # Ensure logger is mocked
+    agent.logger = MagicMock()
 
-    with patch.object(agent.logger, "error") as log:
-        prompt = LLMPromptMessage(text="Hi", norms=[], goals=[])
-        msg = InternalMessage(
-            to="llm",
-            sender=mock_settings.agent_settings.bdi_core_name,
-            body=prompt.model_dump_json(),
-        )
-        await agent.handle_message(msg)
-        log.assert_called()  # Should log JSONDecodeError
+    prompt = LLMPromptMessage(text="Hi", norms=[], goals=[])
+    await agent._process_bdi_message(prompt)
+
+    agent.logger.error.assert_called()  # Should log JSONDecodeError
 
 
 def test_llm_instructions():
@@ -157,6 +206,7 @@ async def test_handle_message_validation_error_branch_no_send(mock_httpx_client,
         to="llm_agent",
         sender=mock_settings.agent_settings.bdi_core_name,
         body=invalid_json,
+        thread="prompt_message",
     )
 
     await agent.handle_message(msg)
@@ -285,3 +335,28 @@ async def test_clear_history_command(mock_settings):
     )
     await agent.handle_message(msg)
     assert len(agent.history) == 0
+
+
+@pytest.mark.asyncio
+async def test_handle_assistant_and_user_messages(mock_settings):
+    agent = LLMAgent("llm_agent")
+
+    # Assistant message
+    msg_ast = InternalMessage(
+        to="llm_agent",
+        sender=mock_settings.agent_settings.bdi_core_name,
+        thread="assistant_message",
+        body="I said this",
+    )
+    await agent.handle_message(msg_ast)
+    assert agent.history[-1] == {"role": "assistant", "content": "I said this"}
+
+    # User message
+    msg_usr = InternalMessage(
+        to="llm_agent",
+        sender=mock_settings.agent_settings.bdi_core_name,
+        thread="user_message",
+        body="User said this",
+    )
+    await agent.handle_message(msg_usr)
+    assert agent.history[-1] == {"role": "user", "content": "User said this"}

test/unit/agents/perception/test_face_detection_agent.py

@@ -0,0 +1,152 @@
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+import zmq
+
+import control_backend.agents.perception.face_rec_agent as face_module
+from control_backend.agents.perception.face_rec_agent import FacePerceptionAgent
+from control_backend.core.agent_system import InternalMessage
+from control_backend.schemas.belief_message import BeliefMessage
+
+
+@pytest.fixture
+def agent():
+    """Return a FacePerceptionAgent instance for testing."""
+    return FacePerceptionAgent(
+        name="face_agent",
+        zmq_address="inproc://test",
+        zmq_bind=False,
+    )
+
+
+@pytest.fixture
+def socket():
+    """Return a mocked ZMQ socket."""
+    sock = AsyncMock()
+    sock.setsockopt_string = MagicMock()
+    sock.connect = MagicMock()
+    sock.bind = MagicMock()
+    return sock
+
+
+def test_connect_socket_connect(agent, socket, monkeypatch):
+    """Test that _connect_socket properly connects when zmq_bind=False."""
+    ctx = MagicMock()
+    ctx.socket.return_value = socket
+    monkeypatch.setattr(face_module.azmq, "Context", MagicMock(instance=lambda: ctx))
+
+    agent._connect_socket()
+    socket.setsockopt_string.assert_called_once_with(zmq.SUBSCRIBE, "")
+    socket.connect.assert_called_once_with(agent._zmq_address)
+    socket.bind.assert_not_called()
+
+
+def test_connect_socket_bind(agent, socket, monkeypatch):
+    """Test that _connect_socket properly binds when zmq_bind=True."""
+    agent._zmq_bind = True
+    ctx = MagicMock()
+    ctx.socket.return_value = socket
+    monkeypatch.setattr(face_module.azmq, "Context", MagicMock(instance=lambda: ctx))
+
+    agent._connect_socket()
+    socket.bind.assert_called_once_with(agent._zmq_address)
+    socket.connect.assert_not_called()
+
+
+def test_connect_socket_twice_is_noop(agent, socket):
+    """Test that calling _connect_socket twice does not overwrite an existing socket."""
+    agent._socket = socket
+    agent._connect_socket()
+    assert agent._socket is socket
+
+
+@pytest.mark.asyncio
+async def test_update_face_belief_present(agent):
+    """Test that _update_face_belief(True) creates the 'face_present' belief."""
+    agent.send = AsyncMock()
+    await agent._update_face_belief(True)
+    msg = agent.send.await_args.args[0]
+    payload = BeliefMessage.model_validate_json(msg.body)
+    assert payload.create[0].name == "face_present"
+
+
+@pytest.mark.asyncio
+async def test_update_face_belief_absent(agent):
+    """Test that _update_face_belief(False) deletes the 'face_present' belief."""
+    agent.send = AsyncMock()
+    await agent._update_face_belief(False)
+    msg = agent.send.await_args.args[0]
+    payload = BeliefMessage.model_validate_json(msg.body)
+    assert payload.delete[0].name == "face_present"
+
+
+@pytest.mark.asyncio
+async def test_post_face_belief_present(agent):
+    """Test that _post_face_belief(True) sends a belief creation message."""
+    agent.send = AsyncMock()
+    await agent._post_face_belief(True)
+    msg = agent.send.await_args.args[0]
+    assert '"create"' in msg.body and '"face_present"' in msg.body
+
+
+@pytest.mark.asyncio
+async def test_post_face_belief_absent(agent):
+    """Test that _post_face_belief(False) sends a belief deletion message."""
+    agent.send = AsyncMock()
+    await agent._post_face_belief(False)
+    msg = agent.send.await_args.args[0]
+    assert '"delete"' in msg.body and '"face_present"' in msg.body
+
+
+@pytest.mark.asyncio
+async def test_handle_pause(agent):
+    """Test that a 'PAUSE' message clears _paused and resets _last_face_state."""
+    agent._paused.set()
+    agent._last_face_state = True
+    msg = InternalMessage(
+        to=agent.name,
+        sender=face_module.settings.agent_settings.user_interrupt_name,
+        thread="cmd",
+        body="PAUSE",
+    )
+    await agent.handle_message(msg)
+    assert not agent._paused.is_set()
+    assert agent._last_face_state is None
+
+
+@pytest.mark.asyncio
+async def test_handle_resume(agent):
+    """Test that a 'RESUME' message sets _paused."""
+    agent._paused.clear()
+    msg = InternalMessage(
+        to=agent.name,
+        sender=face_module.settings.agent_settings.user_interrupt_name,
+        thread="cmd",
+        body="RESUME",
+    )
+    await agent.handle_message(msg)
+    assert agent._paused.is_set()
+
+
+@pytest.mark.asyncio
+async def test_handle_unknown_command(agent):
+    """Test that an unknown command from UserInterruptAgent is ignored (logs a warning)."""
+    msg = InternalMessage(
+        to=agent.name,
+        sender=face_module.settings.agent_settings.user_interrupt_name,
+        thread="cmd",
+        body="???",
+    )
+    await agent.handle_message(msg)
+
+
+@pytest.mark.asyncio
+async def test_handle_unknown_sender(agent):
+    """Test that messages from unknown senders are ignored."""
+    msg = InternalMessage(
+        to=agent.name,
+        sender="someone_else",
+        thread="cmd",
+        body="PAUSE",
+    )
+    await agent.handle_message(msg)

test/unit/agents/perception/transcription_agent/test_speech_recognizer.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import numpy as np
 import pytest
 
@@ -55,4 +61,6 @@ def test_get_decode_options():
     assert isinstance(options["sample_len"], int)
 
     # When disabled, it should not limit output length based on input size
-    assert "sample_rate" not in options
+    recognizer = OpenAIWhisperSpeechRecognizer(limit_output_length=False)
+    options = recognizer._get_decode_options(audio)
+    assert "sample_len" not in options

test/unit/agents/perception/transcription_agent/test_transcription_agent.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import asyncio
 from unittest.mock import AsyncMock, MagicMock, patch
 
@@ -14,6 +20,15 @@ from control_backend.agents.perception.transcription_agent.transcription_agent i
 )
 
 
+@pytest.fixture(autouse=True)
+def mock_experiment_logger():
+    with patch(
+        "control_backend.agents.perception"
+        ".transcription_agent.transcription_agent.experiment_logger"
+    ) as logger:
+        yield logger
+
+
 @pytest.mark.asyncio
 async def test_transcription_agent_flow(mock_zmq_context):
     mock_sub = MagicMock()
@@ -36,7 +51,12 @@ async def test_transcription_agent_flow(mock_zmq_context):
         agent.send = AsyncMock()
 
         agent._running = True
-        agent.add_behavior = AsyncMock()
+
+        def close_coro(coro):
+            coro.close()
+            return MagicMock()
+
+        agent.add_behavior = MagicMock(side_effect=close_coro)
 
         await agent.setup()
 
@@ -143,7 +163,12 @@ async def test_transcription_loop_continues_after_error(mock_zmq_context):
         agent = TranscriptionAgent("tcp://in")
         agent._running = True  # ← REQUIRED to enter the loop
         agent.send = AsyncMock()  # should never be called
-        agent.add_behavior = AsyncMock()  # match other tests
+
+        def close_coro(coro):
+            coro.close()
+            return MagicMock()
+
+        agent.add_behavior = MagicMock(side_effect=close_coro)  # match other tests
 
         await agent.setup()
 
@@ -180,7 +205,12 @@ async def test_transcription_continue_branch_when_empty(mock_zmq_context):
         # Make loop runnable
         agent._running = True
         agent.send = AsyncMock()
-        agent.add_behavior = AsyncMock()
+
+        def close_coro(coro):
+            coro.close()
+            return MagicMock()
+
+        agent.add_behavior = MagicMock(side_effect=close_coro)
 
         await agent.setup()
 

test/unit/agents/perception/vad_agent/test_vad_agent_unit.py

@@ -0,0 +1,158 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+
+from control_backend.agents.perception.vad_agent import VADAgent
+from control_backend.core.agent_system import InternalMessage
+from control_backend.schemas.program_status import PROGRAM_STATUS, ProgramStatus
+
+
+@pytest.fixture(autouse=True)
+def mock_zmq():
+    with patch("zmq.asyncio.Context") as mock:
+        mock.instance.return_value = MagicMock()
+        yield mock
+
+
+@pytest.fixture
+def agent():
+    return VADAgent("tcp://localhost:5555", False)
+
+
+@pytest.mark.asyncio
+async def test_handle_message_pause(agent):
+    agent._paused = MagicMock()
+    # It starts set (not paused)
+
+    msg = InternalMessage(to="vad", sender="user_interrupt_agent", body="PAUSE")
+
+    # We need to mock settings to match sender name
+    with patch("control_backend.agents.perception.vad_agent.settings") as mock_settings:
+        mock_settings.agent_settings.user_interrupt_name = "user_interrupt_agent"
+
+        await agent.handle_message(msg)
+
+        agent._paused.clear.assert_called_once()
+        assert agent._reset_needed is True
+
+
+@pytest.mark.asyncio
+async def test_handle_message_resume(agent):
+    agent._paused = MagicMock()
+    msg = InternalMessage(to="vad", sender="user_interrupt_agent", body="RESUME")
+
+    with patch("control_backend.agents.perception.vad_agent.settings") as mock_settings:
+        mock_settings.agent_settings.user_interrupt_name = "user_interrupt_agent"
+
+        await agent.handle_message(msg)
+
+        agent._paused.set.assert_called_once()
+
+
+@pytest.mark.asyncio
+async def test_handle_message_unknown_command(agent):
+    agent._paused = MagicMock()
+    msg = InternalMessage(to="vad", sender="user_interrupt_agent", body="UNKNOWN")
+
+    with patch("control_backend.agents.perception.vad_agent.settings") as mock_settings:
+        mock_settings.agent_settings.user_interrupt_name = "user_interrupt_agent"
+        agent.logger = MagicMock()
+
+        await agent.handle_message(msg)
+
+        agent._paused.clear.assert_not_called()
+        agent._paused.set.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_handle_message_unknown_sender(agent):
+    agent._paused = MagicMock()
+    msg = InternalMessage(to="vad", sender="other_agent", body="PAUSE")
+
+    with patch("control_backend.agents.perception.vad_agent.settings") as mock_settings:
+        mock_settings.agent_settings.user_interrupt_name = "user_interrupt_agent"
+
+        await agent.handle_message(msg)
+
+        agent._paused.clear.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_status_loop_waits_for_running(agent):
+    agent._running = True
+    agent.program_sub_socket = AsyncMock()
+    agent.program_sub_socket.close = MagicMock()
+    agent._reset_stream = AsyncMock()
+
+    # Sequence of messages:
+    # 1. Wrong topic
+    # 2. Right topic, wrong status (STARTING)
+    # 3. Right topic, RUNNING -> Should break loop
+
+    agent.program_sub_socket.recv_multipart.side_effect = [
+        (b"wrong_topic", b"whatever"),
+        (PROGRAM_STATUS, ProgramStatus.STARTING.value),
+        (PROGRAM_STATUS, ProgramStatus.RUNNING.value),
+    ]
+
+    await agent._status_loop()
+
+    assert agent._reset_stream.await_count == 1
+    agent.program_sub_socket.close.assert_called_once()
+
+
+@pytest.mark.asyncio
+async def test_setup_success(agent, mock_zmq):
+    def close_coro(coro):
+        coro.close()
+        return MagicMock()
+
+    agent.add_behavior = MagicMock(side_effect=close_coro)
+
+    mock_context = mock_zmq.instance.return_value
+    mock_sub = MagicMock()
+    mock_pub = MagicMock()
+
+    # We expect multiple socket calls:
+    # 1. audio_in (SUB)
+    # 2. audio_out (PUB)
+    # 3. program_sub (SUB)
+    mock_context.socket.side_effect = [mock_sub, mock_pub, mock_sub]
+
+    with patch("control_backend.agents.perception.vad_agent.torch.hub.load") as mock_load:
+        mock_load.return_value = (MagicMock(), None)
+
+        with patch("control_backend.agents.perception.vad_agent.TranscriptionAgent") as MockTrans:
+            mock_trans_instance = MockTrans.return_value
+            mock_trans_instance.start = AsyncMock()
+
+            await agent.setup()
+
+            mock_trans_instance.start.assert_awaited_once()
+
+    assert agent.add_behavior.call_count == 2  # streaming_loop + status_loop
+    assert agent.audio_in_socket is not None
+    assert agent.audio_out_socket is not None
+    assert agent.program_sub_socket is not None
+
+
+@pytest.mark.asyncio
+async def test_reset_stream(agent):
+    mock_poller = MagicMock()
+    agent.audio_in_poller = mock_poller
+
+    # poll(1) returns not None twice, then None
+    mock_poller.poll = AsyncMock(side_effect=[b"data", b"data", None])
+
+    agent._ready = MagicMock()
+
+    await agent._reset_stream()
+
+    assert mock_poller.poll.await_count == 3
+    agent._ready.set.assert_called_once()

test/unit/agents/perception/vad_agent/test_vad_socket_poller.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from unittest.mock import AsyncMock, MagicMock
 
 import pytest

test/unit/agents/perception/vad_agent/test_vad_streaming.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import numpy as np
@@ -5,6 +11,7 @@ import pytest
 import zmq
 
 from control_backend.agents.perception.vad_agent import VADAgent
+from control_backend.core.config import settings
 
 
 # We don't want to use real ZMQ in unit tests, for example because it can give errors when sockets
@@ -23,7 +30,9 @@ def audio_out_socket():
 
 @pytest.fixture
 def vad_agent(audio_out_socket):
-    return VADAgent("tcp://localhost:5555", False)
+    agent = VADAgent("tcp://localhost:5555", False)
+    agent._internal_pub_socket = AsyncMock()
+    return agent
 
 
 @pytest.fixture(autouse=True)
@@ -43,6 +52,12 @@ def patch_settings(monkeypatch):
     monkeypatch.setattr(vad_agent.settings.vad_settings, "sample_rate_hz", 16_000, raising=False)
 
 
+@pytest.fixture(autouse=True)
+def mock_experiment_logger():
+    with patch("control_backend.agents.perception.vad_agent.experiment_logger") as logger:
+        yield logger
+
+
 async def simulate_streaming_with_probabilities(streaming, probabilities: list[float]):
     """
     Simulates a streaming scenario with given VAD model probabilities for testing purposes.
@@ -83,14 +98,15 @@ async def test_voice_activity_detected(audio_out_socket, vad_agent):
     Test a scenario where there is voice activity detected between silences.
     """
     speech_chunk_count = 5
-    probabilities = [0.0] * 5 + [1.0] * speech_chunk_count + [0.0] * 5
+    begin_silence_chunks = settings.behaviour_settings.vad_begin_silence_chunks
+    probabilities = [0.0] * 15 + [1.0] * speech_chunk_count + [0.0] * 5
     vad_agent.audio_out_socket = audio_out_socket
     await simulate_streaming_with_probabilities(vad_agent, probabilities)
 
     audio_out_socket.send.assert_called_once()
     data = audio_out_socket.send.call_args[0][0]
     assert isinstance(data, bytes)
-    assert len(data) == 512 * 4 * (speech_chunk_count + 1)
+    assert len(data) == 512 * 4 * (begin_silence_chunks + speech_chunk_count)
 
 
 @pytest.mark.asyncio
@@ -100,8 +116,9 @@ async def test_voice_activity_short_pause(audio_out_socket, vad_agent):
     short pause.
     """
     speech_chunk_count = 5
+    begin_silence_chunks = settings.behaviour_settings.vad_begin_silence_chunks
     probabilities = (
-        [0.0] * 5 + [1.0] * speech_chunk_count + [0.0] + [1.0] * speech_chunk_count + [0.0] * 5
+        [0.0] * 15 + [1.0] * speech_chunk_count + [0.0] + [1.0] * speech_chunk_count + [0.0] * 5
     )
     vad_agent.audio_out_socket = audio_out_socket
     await simulate_streaming_with_probabilities(vad_agent, probabilities)
@@ -109,8 +126,8 @@ async def test_voice_activity_short_pause(audio_out_socket, vad_agent):
     audio_out_socket.send.assert_called_once()
     data = audio_out_socket.send.call_args[0][0]
     assert isinstance(data, bytes)
-    # Expecting 13 chunks (2*5 with speech, 1 pause between, 1 as padding)
-    assert len(data) == 512 * 4 * (speech_chunk_count * 2 + 1 + 1)
+    # Expecting 13 chunks (2*5 with speech, 1 pause between, begin_silence_chunks as padding)
+    assert len(data) == 512 * 4 * (speech_chunk_count * 2 + 1 + begin_silence_chunks)
 
 
 @pytest.mark.asyncio
@@ -135,6 +152,54 @@ async def test_no_data(audio_out_socket, vad_agent):
     assert len(vad_agent.audio_buffer) == 0
 
 
+@pytest.mark.asyncio
+async def test_streaming_loop_reset_needed(audio_out_socket, vad_agent):
+    """Test that _reset_needed branch works as expected."""
+    vad_agent._reset_needed = True
+    vad_agent._ready.set()
+    vad_agent._paused.set()
+    vad_agent._running = True
+    vad_agent.audio_buffer = np.array([1.0], dtype=np.float32)
+    vad_agent.i_since_speech = 0
+
+    # Mock _reset_stream to stop the loop by setting _running=False
+    async def mock_reset():
+        vad_agent._running = False
+
+    vad_agent._reset_stream = mock_reset
+
+    # Needs a poller to avoid AssertionError
+    vad_agent.audio_in_poller = AsyncMock()
+    vad_agent.audio_in_poller.poll.return_value = None
+
+    await vad_agent._streaming_loop()
+
+    assert vad_agent._reset_needed is False
+    assert len(vad_agent.audio_buffer) == 0
+    assert vad_agent.i_since_speech == settings.behaviour_settings.vad_initial_since_speech
+
+
+@pytest.mark.asyncio
+async def test_streaming_loop_no_data_clears_buffer(audio_out_socket, vad_agent):
+    """Test that if poll returns None, buffer is cleared if not empty."""
+    vad_agent.audio_buffer = np.array([1.0], dtype=np.float32)
+    vad_agent._ready.set()
+    vad_agent._paused.set()
+    vad_agent._running = True
+
+    class MockPoller:
+        async def poll(self, timeout_ms=None):
+            vad_agent._running = False  # stop after one poll
+            return None
+
+    vad_agent.audio_in_poller = MockPoller()
+
+    await vad_agent._streaming_loop()
+
+    assert len(vad_agent.audio_buffer) == 0
+    assert vad_agent.i_since_speech == settings.behaviour_settings.vad_initial_since_speech
+
+
 @pytest.mark.asyncio
 async def test_vad_model_load_failure_stops_agent(vad_agent):
     """

test/unit/agents/test_base.py

@@ -0,0 +1,30 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+import logging
+
+from control_backend.agents.base import BaseAgent
+
+
+class MyAgent(BaseAgent):
+    async def setup(self):
+        pass
+
+    async def handle_message(self, msg):
+        pass
+
+
+def test_base_agent_logger_init():
+    # When defining a subclass, __init_subclass__ runs
+    # The BaseAgent in agents/base.py sets the logger
+    assert hasattr(MyAgent, "logger")
+    assert isinstance(MyAgent.logger, logging.Logger)
+    # The logger name depends on the package.
+    # Since this test file is running as a module, __package__ might be None or the test package.
+    # In 'src/control_backend/agents/base.py', it uses __package__ of base.py which is
+    #  'control_backend.agents'.
+    # So logger name should be control_backend.agents.MyAgent
+    assert MyAgent.logger.name == "control_backend.agents.MyAgent"

test/unit/agents/user_interrupt/test_user_interrupt.py

@@ -1,12 +1,28 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import asyncio
 import json
-from unittest.mock import AsyncMock, MagicMock
+from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
 from control_backend.agents.user_interrupt.user_interrupt_agent import UserInterruptAgent
 from control_backend.core.agent_system import InternalMessage
 from control_backend.core.config import settings
+from control_backend.schemas.belief_message import BeliefMessage
+from control_backend.schemas.program import (
+    ConditionalNorm,
+    Goal,
+    KeywordBelief,
+    Phase,
+    Plan,
+    Program,
+    Trigger,
+)
 from control_backend.schemas.ri_message import RIEndpoint
 
 
@@ -16,9 +32,18 @@ def agent():
     agent.send = AsyncMock()
     agent.logger = MagicMock()
     agent.sub_socket = AsyncMock()
+    agent.pub_socket = AsyncMock()
     return agent
 
 
+@pytest.fixture(autouse=True)
+def mock_experiment_logger():
+    with patch(
+        "control_backend.agents.user_interrupt.user_interrupt_agent.experiment_logger"
+    ) as logger:
+        yield logger
+
+
 @pytest.mark.asyncio
 async def test_send_to_speech_agent(agent):
     """Verify speech command format."""
@@ -49,21 +74,18 @@ async def test_send_to_gesture_agent(agent):
 
 
 @pytest.mark.asyncio
-async def test_send_to_program_manager(agent):
+async def test_send_to_bdi_belief(agent):
     """Verify belief update format."""
-    context_str = "2"
+    context_str = "some_goal"
 
-    await agent._send_to_program_manager(context_str)
+    await agent._send_to_bdi_belief(context_str, "goal")
 
-    agent.send.assert_awaited_once()
-    sent_msg: InternalMessage = agent.send.call_args.args[0]
+    assert agent.send.await_count == 1
+    sent_msg = agent.send.call_args.args[0]
 
-    assert sent_msg.to == settings.agent_settings.bdi_program_manager_name
-    assert sent_msg.thread == "belief_override_id"
-
-    body = json.loads(sent_msg.body)
-
-    assert body["belief"] == context_str
+    assert sent_msg.to == settings.agent_settings.bdi_core_name
+    assert sent_msg.thread == "beliefs"
+    assert "achieved_some_goal" in sent_msg.body
 
 
 @pytest.mark.asyncio
@@ -77,6 +99,10 @@ async def test_receive_loop_routing_success(agent):
     # Prepare JSON payloads as bytes
     payload_speech = json.dumps({"type": "speech", "context": "Hello Speech"}).encode()
     payload_gesture = json.dumps({"type": "gesture", "context": "Hello Gesture"}).encode()
+    # override calls _send_to_bdi (for trigger/norm) OR _send_to_bdi_belief (for goal).
+
+    # To test routing, we need to populate the maps
+    agent._goal_map["Hello Override"] = "some_goal_slug"
     payload_override = json.dumps({"type": "override", "context": "Hello Override"}).encode()
 
     agent.sub_socket.recv_multipart.side_effect = [
@@ -88,7 +114,7 @@ async def test_receive_loop_routing_success(agent):
 
     agent._send_to_speech_agent = AsyncMock()
     agent._send_to_gesture_agent = AsyncMock()
-    agent._send_to_program_manager = AsyncMock()
+    agent._send_to_bdi_belief = AsyncMock()
 
     try:
         await agent._receive_button_event()
@@ -103,12 +129,12 @@ async def test_receive_loop_routing_success(agent):
     # Gesture
     agent._send_to_gesture_agent.assert_awaited_once_with("Hello Gesture")
 
-    # Override
-    agent._send_to_program_manager.assert_awaited_once_with("Hello Override")
+    # Override (since we mapped it to a goal)
+    agent._send_to_bdi_belief.assert_awaited_once_with("some_goal_slug", "goal")
 
     assert agent._send_to_speech_agent.await_count == 1
     assert agent._send_to_gesture_agent.await_count == 1
-    assert agent._send_to_program_manager.await_count == 1
+    assert agent._send_to_bdi_belief.await_count == 1
 
 
 @pytest.mark.asyncio
@@ -125,7 +151,6 @@ async def test_receive_loop_unknown_type(agent):
 
     agent._send_to_speech_agent = AsyncMock()
     agent._send_to_gesture_agent = AsyncMock()
-    agent._send_to_belief_collector = AsyncMock()
 
     try:
         await agent._receive_button_event()
@@ -137,10 +162,514 @@ async def test_receive_loop_unknown_type(agent):
     # Ensure no handlers were called
     agent._send_to_speech_agent.assert_not_called()
     agent._send_to_gesture_agent.assert_not_called()
-    agent._send_to_belief_collector.assert_not_called()
+
+    agent.logger.warning.assert_called()
+
+
+@pytest.mark.asyncio
+async def test_create_mapping(agent):
+    # Create a program with a trigger, goal, and conditional norm
+    import uuid
+
+    trigger_id = uuid.uuid4()
+    goal_id = uuid.uuid4()
+    norm_id = uuid.uuid4()
+
+    cond = KeywordBelief(id=uuid.uuid4(), name="k1", keyword="key")
+    plan = Plan(id=uuid.uuid4(), name="p1", steps=[])
+
+    trigger = Trigger(id=trigger_id, name="my_trigger", condition=cond, plan=plan)
+    goal = Goal(id=goal_id, name="my_goal", description="desc", plan=plan)
+
+    cn = ConditionalNorm(id=norm_id, name="my_norm", norm="be polite", condition=cond)
+
+    phase = Phase(id=uuid.uuid4(), name="phase1", norms=[cn], goals=[goal], triggers=[trigger])
+    prog = Program(phases=[phase])
+
+    # Call create_mapping via handle_message
+    msg = InternalMessage(to="me", thread="new_program", body=prog.model_dump_json())
+    await agent.handle_message(msg)
+
+    # Check maps
+    assert str(trigger_id) in agent._trigger_map
+    assert agent._trigger_map[str(trigger_id)] == "trigger_my_trigger"
+
+    assert str(goal_id) in agent._goal_map
+    assert agent._goal_map[str(goal_id)] == "my_goal"
+
+    assert str(norm_id) in agent._cond_norm_map
+    assert agent._cond_norm_map[str(norm_id)] == "norm_be_polite"
+
+
+@pytest.mark.asyncio
+async def test_create_mapping_invalid_json(agent):
+    # Pass invalid json to handle_message thread "new_program"
+    msg = InternalMessage(to="me", thread="new_program", body="invalid json")
+    await agent.handle_message(msg)
+
+    # Should log error and maps should remain empty or cleared
+    agent.logger.error.assert_called()
+
+
+@pytest.mark.asyncio
+async def test_handle_message_trigger_start(agent):
+    # Setup reverse map manually
+    agent._trigger_reverse_map["trigger_slug"] = "ui_id_123"
+
+    msg = InternalMessage(to="me", thread="trigger_start", body="trigger_slug")
+    await agent.handle_message(msg)
+
+    agent.pub_socket.send_multipart.assert_awaited_once()
+    args = agent.pub_socket.send_multipart.call_args[0][0]
+    assert args[0] == b"experiment"
+    payload = json.loads(args[1])
+    assert payload["type"] == "trigger_update"
+    assert payload["id"] == "ui_id_123"
+    assert payload["achieved"] is True
+
+
+@pytest.mark.asyncio
+async def test_handle_message_trigger_end(agent):
+    agent._trigger_reverse_map["trigger_slug"] = "ui_id_123"
+
+    msg = InternalMessage(to="me", thread="trigger_end", body="trigger_slug")
+    await agent.handle_message(msg)
+
+    agent.pub_socket.send_multipart.assert_awaited_once()
+    payload = json.loads(agent.pub_socket.send_multipart.call_args[0][0][1])
+    assert payload["type"] == "trigger_update"
+    assert payload["achieved"] is False
+
+
+@pytest.mark.asyncio
+async def test_handle_message_transition_phase(agent):
+    msg = InternalMessage(to="me", thread="transition_phase", body="phase_id_123")
+    await agent.handle_message(msg)
+
+    agent.pub_socket.send_multipart.assert_awaited_once()
+    payload = json.loads(agent.pub_socket.send_multipart.call_args[0][0][1])
+    assert payload["type"] == "phase_update"
+    assert payload["id"] == "phase_id_123"
+
+
+@pytest.mark.asyncio
+async def test_handle_message_goal_start(agent):
+    agent._goal_reverse_map["goal_slug"] = "goal_id_123"
+
+    msg = InternalMessage(to="me", thread="goal_start", body="goal_slug")
+    await agent.handle_message(msg)
+
+    agent.pub_socket.send_multipart.assert_awaited_once()
+    payload = json.loads(agent.pub_socket.send_multipart.call_args[0][0][1])
+    assert payload["type"] == "goal_update"
+    assert payload["id"] == "goal_id_123"
+    assert payload["active"] is True
+
+
+@pytest.mark.asyncio
+async def test_handle_message_active_norms_update(agent):
+    agent._cond_norm_reverse_map["norm_active"] = "id_1"
+    agent._cond_norm_reverse_map["norm_inactive"] = "id_2"
+
+    # Body is like: "('norm_active', 'other')"
+    # The split logic handles quotes etc.
+    msg = InternalMessage(to="me", thread="active_norms_update", body="'norm_active', 'other'")
+    await agent.handle_message(msg)
+
+    agent.pub_socket.send_multipart.assert_awaited_once()
+    payload = json.loads(agent.pub_socket.send_multipart.call_args[0][0][1])
+    assert payload["type"] == "cond_norms_state_update"
+    norms = {n["id"]: n["active"] for n in payload["norms"]}
+    assert norms["id_1"] is True
+    assert norms["id_2"] is False
+
+
+@pytest.mark.asyncio
+async def test_send_experiment_control(agent):
+    # Test next_phase
+    await agent._send_experiment_control_to_bdi_core("next_phase")
+    agent.send.assert_awaited()
+    msg = agent.send.call_args[0][0]
+    assert msg.thread == "force_next_phase"
+
+    # Test reset_phase
+    await agent._send_experiment_control_to_bdi_core("reset_phase")
+    msg = agent.send.call_args[0][0]
+    assert msg.thread == "reset_current_phase"
+
+    # Test reset_experiment
+    await agent._send_experiment_control_to_bdi_core("reset_experiment")
+    msg = agent.send.call_args[0][0]
+    assert msg.thread == "reset_experiment"
+
+
+@pytest.mark.asyncio
+async def test_setup(agent):
+    """Test the setup method initializes sockets correctly."""
+    with patch("control_backend.agents.user_interrupt.user_interrupt_agent.Context") as MockContext:
+        mock_ctx_instance = MagicMock()
+        MockContext.instance.return_value = mock_ctx_instance
+
+        mock_sub = MagicMock()
+        mock_pub = MagicMock()
+        mock_ctx_instance.socket.side_effect = [mock_sub, mock_pub]
+
+        # MOCK add_behavior so we don't rely on internal attributes
+        agent.add_behavior = MagicMock()
+
+        await agent.setup()
+
+        # Check sockets
+        mock_sub.connect.assert_called_with(settings.zmq_settings.internal_sub_address)
+        mock_pub.connect.assert_called_with(settings.zmq_settings.internal_pub_address)
+
+        # Verify add_behavior was called
+        agent.add_behavior.assert_called_once()
+
+
+@pytest.mark.asyncio
+async def test_receive_loop_json_error(agent):
+    """Verify that malformed JSON is caught and logged without crashing the loop."""
+    agent.sub_socket.recv_multipart.side_effect = [
+        (b"topic", b"INVALID{JSON"),
+        asyncio.CancelledError,
+    ]
+
+    try:
+        await agent._receive_button_event()
+    except asyncio.CancelledError:
+        pass
+
+    agent.logger.error.assert_called_with("Received invalid JSON payload on topic %s", b"topic")
+
+
+@pytest.mark.asyncio
+async def test_receive_loop_override_trigger(agent):
+    """Verify routing 'override' to a Trigger."""
+    agent._trigger_map["101"] = "trigger_slug"
+    payload = json.dumps({"type": "override", "context": "101"}).encode()
+
+    agent.sub_socket.recv_multipart.side_effect = [(b"topic", payload), asyncio.CancelledError]
+    agent._send_to_bdi = AsyncMock()
+
+    try:
+        await agent._receive_button_event()
+    except asyncio.CancelledError:
+        pass
+
+    agent._send_to_bdi.assert_awaited_once_with("force_trigger", "trigger_slug")
+
+
+@pytest.mark.asyncio
+async def test_receive_loop_override_norm(agent):
+    """Verify routing 'override' to a Conditional Norm."""
+    agent._cond_norm_map["202"] = "norm_slug"
+    payload = json.dumps({"type": "override", "context": "202"}).encode()
+
+    agent.sub_socket.recv_multipart.side_effect = [(b"topic", payload), asyncio.CancelledError]
+    agent._send_to_bdi_belief = AsyncMock()
+
+    try:
+        await agent._receive_button_event()
+    except asyncio.CancelledError:
+        pass
+
+    agent._send_to_bdi_belief.assert_awaited_once_with("norm_slug", "cond_norm")
+
+
+@pytest.mark.asyncio
+async def test_receive_loop_override_missing(agent):
+    """Verify warning log when an override ID is not found in any map."""
+    payload = json.dumps({"type": "override", "context": "999"}).encode()
+
+    agent.sub_socket.recv_multipart.side_effect = [(b"topic", payload), asyncio.CancelledError]
+
+    try:
+        await agent._receive_button_event()
+    except asyncio.CancelledError:
+        pass
+
+    agent.logger.warning.assert_called_with("Could not determine which element to override.")
+
+
+@pytest.mark.asyncio
+async def test_receive_loop_unachieve_logic(agent):
+    """Verify success and failure paths for override_unachieve."""
+    agent._cond_norm_map["202"] = "norm_slug"
+
+    success_payload = json.dumps({"type": "override_unachieve", "context": "202"}).encode()
+    fail_payload = json.dumps({"type": "override_unachieve", "context": "999"}).encode()
+
+    agent.sub_socket.recv_multipart.side_effect = [
+        (b"topic", success_payload),
+        (b"topic", fail_payload),
+        asyncio.CancelledError,
+    ]
+    agent._send_to_bdi_belief = AsyncMock()
+
+    try:
+        await agent._receive_button_event()
+    except asyncio.CancelledError:
+        pass
+
+    # Assert success call (True flag for unachieve)
+    agent._send_to_bdi_belief.assert_any_call("norm_slug", "cond_norm", True)
+    # Assert failure log
+    agent.logger.warning.assert_called_with(
+        "Could not determine which conditional norm to unachieve."
+    )
+
+
+@pytest.mark.asyncio
+async def test_receive_loop_pause_resume(agent):
+    """Verify pause and resume toggle logic and logging."""
+    pause_payload = json.dumps({"type": "pause", "context": "true"}).encode()
+    resume_payload = json.dumps({"type": "pause", "context": ""}).encode()
+
+    agent.sub_socket.recv_multipart.side_effect = [
+        (b"topic", pause_payload),
+        (b"topic", resume_payload),
+        asyncio.CancelledError,
+    ]
+    agent._send_pause_command = AsyncMock()
+
+    try:
+        await agent._receive_button_event()
+    except asyncio.CancelledError:
+        pass
+
+    agent._send_pause_command.assert_any_call("true")
+    agent._send_pause_command.assert_any_call("")
+    agent.logger.info.assert_any_call("Sent pause command.")
+    agent.logger.info.assert_any_call("Sent resume command.")
+
+
+@pytest.mark.asyncio
+async def test_receive_loop_phase_control(agent):
+    """Verify experiment flow control (next_phase)."""
+    payload = json.dumps({"type": "next_phase", "context": ""}).encode()
+
+    agent.sub_socket.recv_multipart.side_effect = [(b"topic", payload), asyncio.CancelledError]
+    agent._send_experiment_control_to_bdi_core = AsyncMock()
+
+    try:
+        await agent._receive_button_event()
+    except asyncio.CancelledError:
+        pass
+
+    agent._send_experiment_control_to_bdi_core.assert_awaited_once_with("next_phase")
+
+
+@pytest.mark.asyncio
+async def test_handle_message_unknown_thread(agent):
+    """Test handling of an unknown message thread (lines 213-214)."""
+    msg = InternalMessage(to="me", thread="unknown_thread", body="test")
+    await agent.handle_message(msg)
+
+    agent.logger.debug.assert_called_with(
+        "Received internal message on unhandled thread: unknown_thread"
+    )
+
+
+@pytest.mark.asyncio
+async def test_send_to_bdi_belief_edge_cases(agent):
+    """
+    Covers:
+    - Unknown asl_type warning (lines 326-328)
+    - unachieve=True logic (lines 334-337)
+    """
+    # 1. Unknown Type
+    await agent._send_to_bdi_belief("slug", "unknown_type")
+
+    agent.logger.warning.assert_called_with("Tried to send belief with unknown type")
+    agent.send.assert_not_called()
+
+    # Reset mock for part 2
+    agent.send.reset_mock()
+
+    # 2. Unachieve = True
+    await agent._send_to_bdi_belief("slug", "cond_norm", unachieve=True)
+
+    agent.send.assert_awaited()
+    sent_msg = agent.send.call_args.args[0]
+
+    # Verify it is a delete operation
+    body_obj = BeliefMessage.model_validate_json(sent_msg.body)
+
+    # Verify 'delete' has content
+    assert body_obj.delete is not None
+    assert len(body_obj.delete) == 1
+    assert body_obj.delete[0].name == "force_slug"
+
+    # Verify 'create' is empty (handling both None and [])
+    assert not body_obj.create
+
+
+@pytest.mark.asyncio
+async def test_send_experiment_control_unknown(agent):
+    """Test sending an unknown experiment control type (lines 366-367)."""
+    await agent._send_experiment_control_to_bdi_core("invalid_command")
 
     agent.logger.warning.assert_called_with(
-        "Received button press with unknown type '%s' (context: '%s').",
-        "unknown_thing",
-        "some_data",
+        "Received unknown experiment control type '%s' to send to BDI Core.", "invalid_command"
     )
+
+    # Ensure it still sends an empty message (as per code logic, though thread is empty)
+    agent.send.assert_awaited()
+    msg = agent.send.call_args[0][0]
+    assert msg.thread == ""
+
+
+@pytest.mark.asyncio
+async def test_create_mapping_recursive_goals(agent):
+    """Verify that nested subgoals are correctly registered in the mapping."""
+    import uuid
+
+    # 1. Setup IDs
+    parent_goal_id = uuid.uuid4()
+    child_goal_id = uuid.uuid4()
+
+    # 2. Create the child goal
+    child_goal = Goal(
+        id=child_goal_id,
+        name="child_goal",
+        description="I am a subgoal",
+        plan=Plan(id=uuid.uuid4(), name="p_child", steps=[]),
+    )
+
+    # 3. Create the parent goal and put the child goal inside its plan steps
+    parent_goal = Goal(
+        id=parent_goal_id,
+        name="parent_goal",
+        description="I am a parent",
+        plan=Plan(id=uuid.uuid4(), name="p_parent", steps=[child_goal]),  # Nested here
+    )
+
+    # 4. Build the program
+    phase = Phase(
+        id=uuid.uuid4(),
+        name="phase1",
+        norms=[],
+        goals=[parent_goal],  # Only the parent is top-level
+        triggers=[],
+    )
+    prog = Program(phases=[phase])
+
+    # 5. Execute mapping
+    msg = InternalMessage(to="me", thread="new_program", body=prog.model_dump_json())
+    await agent.handle_message(msg)
+
+    # 6. Assertions
+    # Check parent
+    assert str(parent_goal_id) in agent._goal_map
+    assert agent._goal_map[str(parent_goal_id)] == "parent_goal"
+
+    # Check child (This confirms the recursion worked)
+    assert str(child_goal_id) in agent._goal_map
+    assert agent._goal_map[str(child_goal_id)] == "child_goal"
+    assert agent._goal_reverse_map["child_goal"] == str(child_goal_id)
+
+
+@pytest.mark.asyncio
+async def test_receive_loop_advanced_scenarios(agent):
+    """
+    Covers:
+    - JSONDecodeError (lines 86-88)
+    - Override: Trigger found (lines 108-109)
+    - Override: Norm found (lines 114-115)
+    - Override: Nothing found (line 134)
+    - Override Unachieve: Success & Fail (lines 136-145)
+    - Pause: Context true/false logs (lines 150-157)
+    - Next Phase (line 160)
+    """
+    # 1. Setup Data Maps
+    agent._trigger_map["101"] = "trigger_slug"
+    agent._cond_norm_map["202"] = "norm_slug"
+
+    # 2. Define Payloads
+    # A. Invalid JSON
+    bad_json = b"INVALID{JSON"
+
+    # B. Override -> Trigger
+    override_trigger = json.dumps({"type": "override", "context": "101"}).encode()
+
+    # C. Override -> Norm
+    override_norm = json.dumps({"type": "override", "context": "202"}).encode()
+
+    # D. Override -> Unknown
+    override_fail = json.dumps({"type": "override", "context": "999"}).encode()
+
+    # E. Unachieve -> Success
+    unachieve_success = json.dumps({"type": "override_unachieve", "context": "202"}).encode()
+
+    # F. Unachieve -> Fail
+    unachieve_fail = json.dumps({"type": "override_unachieve", "context": "999"}).encode()
+
+    # G. Pause (True)
+    pause_true = json.dumps({"type": "pause", "context": "true"}).encode()
+
+    # H. Pause (False/Resume)
+    pause_false = json.dumps({"type": "pause", "context": ""}).encode()
+
+    # I. Next Phase
+    next_phase = json.dumps({"type": "next_phase", "context": ""}).encode()
+
+    # 3. Setup Socket
+    agent.sub_socket.recv_multipart.side_effect = [
+        (b"topic", bad_json),
+        (b"topic", override_trigger),
+        (b"topic", override_norm),
+        (b"topic", override_fail),
+        (b"topic", unachieve_success),
+        (b"topic", unachieve_fail),
+        (b"topic", pause_true),
+        (b"topic", pause_false),
+        (b"topic", next_phase),
+        asyncio.CancelledError,  # End loop
+    ]
+
+    # Mock internal helpers to verify calls
+    agent._send_to_bdi = AsyncMock()
+    agent._send_to_bdi_belief = AsyncMock()
+    agent._send_pause_command = AsyncMock()
+    agent._send_experiment_control_to_bdi_core = AsyncMock()
+
+    # 4. Run Loop
+    try:
+        await agent._receive_button_event()
+    except asyncio.CancelledError:
+        pass
+
+    # 5. Assertions
+
+    # JSON Error
+    agent.logger.error.assert_called_with("Received invalid JSON payload on topic %s", b"topic")
+
+    # Override Trigger
+    agent._send_to_bdi.assert_awaited_with("force_trigger", "trigger_slug")
+
+    # Override Norm
+    # We expect _send_to_bdi_belief to be called for the norm
+    # Note: The loop calls _send_to_bdi_belief(asl_cond_norm, "cond_norm")
+    agent._send_to_bdi_belief.assert_any_call("norm_slug", "cond_norm")
+
+    # Override Fail (Warning log)
+    agent.logger.warning.assert_any_call("Could not determine which element to override.")
+
+    # Unachieve Success
+    # Loop calls _send_to_bdi_belief(asl_cond_norm, "cond_norm", True)
+    agent._send_to_bdi_belief.assert_any_call("norm_slug", "cond_norm", True)
+
+    # Unachieve Fail
+    agent.logger.warning.assert_any_call("Could not determine which conditional norm to unachieve.")
+
+    # Pause Logic
+    agent._send_pause_command.assert_any_call("true")
+    agent.logger.info.assert_any_call("Sent pause command.")
+
+    # Resume Logic
+    agent._send_pause_command.assert_any_call("")
+    agent.logger.info.assert_any_call("Sent resume command.")
+
+    # Next Phase
+    agent._send_experiment_control_to_bdi_core.assert_awaited_with("next_phase")

test/unit/api/v1/endpoints/test_logs_endpoint.py

@@ -1,7 +1,13 @@
-from unittest.mock import patch
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+from unittest.mock import MagicMock, patch
 
 import pytest
-from fastapi import FastAPI
+from fastapi import FastAPI, HTTPException
 from fastapi.testclient import TestClient
 from starlette.responses import StreamingResponse
 
@@ -61,3 +67,67 @@ async def test_log_stream_endpoint_lines(client):
         # Optional: assert subscribe/connect were called
         assert dummy_socket.subscribed  # at least some log levels subscribed
         assert dummy_socket.connected  # connect was called
+
+
+@patch("control_backend.api.v1.endpoints.logs.LOGGING_DIR")
+def test_files_endpoint(LOGGING_DIR, client):
+    file_1, file_2 = MagicMock(), MagicMock()
+    file_1.name = "file_1"
+    file_2.name = "file_2"
+    LOGGING_DIR.glob.return_value = [file_1, file_2]
+    result = client.get("/api/logs/files")
+
+    assert result.status_code == 200
+    assert result.json() == ["file_1", "file_2"]
+
+
+@patch("control_backend.api.v1.endpoints.logs.FileResponse")
+@patch("control_backend.api.v1.endpoints.logs.LOGGING_DIR")
+def test_log_file_endpoint_success(LOGGING_DIR, MockFileResponse, client):
+    mock_file_path = MagicMock()
+    mock_file_path.is_relative_to.return_value = True
+    mock_file_path.is_file.return_value = True
+    mock_file_path.name = "test.log"
+
+    LOGGING_DIR.__truediv__ = MagicMock(return_value=mock_file_path)
+    mock_file_path.resolve.return_value = mock_file_path
+
+    MockFileResponse.return_value = MagicMock()
+
+    result = client.get("/api/logs/files/test.log")
+
+    assert result.status_code == 200
+    MockFileResponse.assert_called_once_with(mock_file_path, filename="test.log")
+
+
+@pytest.mark.asyncio
+@patch("control_backend.api.v1.endpoints.logs.LOGGING_DIR")
+async def test_log_file_endpoint_path_traversal(LOGGING_DIR):
+    from control_backend.api.v1.endpoints.logs import log_file
+
+    mock_file_path = MagicMock()
+    mock_file_path.is_relative_to.return_value = False
+
+    LOGGING_DIR.__truediv__ = MagicMock(return_value=mock_file_path)
+    mock_file_path.resolve.return_value = mock_file_path
+
+    with pytest.raises(HTTPException) as exc_info:
+        await log_file("../secret.txt")
+
+    assert exc_info.value.status_code == 400
+    assert exc_info.value.detail == "Invalid filename."
+
+
+@patch("control_backend.api.v1.endpoints.logs.LOGGING_DIR")
+def test_log_file_endpoint_file_not_found(LOGGING_DIR, client):
+    mock_file_path = MagicMock()
+    mock_file_path.is_relative_to.return_value = True
+    mock_file_path.is_file.return_value = False
+
+    LOGGING_DIR.__truediv__ = MagicMock(return_value=mock_file_path)
+    mock_file_path.resolve.return_value = mock_file_path
+
+    result = client.get("/api/logs/files/nonexistent.log")
+
+    assert result.status_code == 404
+    assert result.json()["detail"] == "File not found."

test/unit/api/v1/endpoints/test_message_endpoint.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import json
 
 import pytest

test/unit/api/v1/endpoints/test_program_endpoint.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import json
 import uuid
 from unittest.mock import AsyncMock

test/unit/api/v1/endpoints/test_robot_endpoint.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 # tests/test_robot_endpoints.py
 import json
 from unittest.mock import AsyncMock, MagicMock, patch

test/unit/api/v1/endpoints/test_router.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from fastapi.routing import APIRoute
 
 from control_backend.api.v1.router import api_router  # <--- corrected import
@@ -11,6 +17,5 @@ def test_router_includes_expected_paths():
     # Ensure at least one route under each prefix exists
     assert any(p.startswith("/robot") for p in paths)
     assert any(p.startswith("/message") for p in paths)
-    assert any(p.startswith("/sse") for p in paths)
     assert any(p.startswith("/logs") for p in paths)
     assert any(p.startswith("/program") for p in paths)

test/unit/api/v1/endpoints/test_sse_endpoint.py

@@ -1,24 +0,0 @@
-import pytest
-from fastapi import FastAPI
-from fastapi.testclient import TestClient
-
-from control_backend.api.v1.endpoints import sse
-
-
-@pytest.fixture
-def app():
-    app = FastAPI()
-    app.include_router(sse.router)
-    return app
-
-
-@pytest.fixture
-def client(app):
-    return TestClient(app)
-
-
-def test_sse_route_exists(client):
-    """Minimal smoke test to ensure /sse route exists and responds."""
-    response = client.get("/sse")
-    # Since implementation is not done, we only assert it doesn't crash
-    assert response.status_code == 200

test/unit/api/v1/endpoints/test_user_interact.py

@@ -0,0 +1,154 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+from fastapi import FastAPI
+from fastapi.testclient import TestClient
+
+from control_backend.api.v1.endpoints import user_interact
+
+
+@pytest.fixture
+def app():
+    app = FastAPI()
+    app.include_router(user_interact.router)
+    return app
+
+
+@pytest.fixture
+def client(app):
+    return TestClient(app)
+
+
+@pytest.mark.asyncio
+async def test_receive_button_event(client):
+    mock_pub_socket = AsyncMock()
+    client.app.state.endpoints_pub_socket = mock_pub_socket
+
+    payload = {"type": "speech", "context": "hello"}
+    response = client.post("/button_pressed", json=payload)
+
+    assert response.status_code == 202
+    assert response.json() == {"status": "Event received"}
+
+    mock_pub_socket.send_multipart.assert_awaited_once()
+    args = mock_pub_socket.send_multipart.call_args[0][0]
+    assert args[0] == b"button_pressed"
+    assert "speech" in args[1].decode()
+
+
+@pytest.mark.asyncio
+async def test_receive_button_event_invalid_payload(client):
+    mock_pub_socket = AsyncMock()
+    client.app.state.endpoints_pub_socket = mock_pub_socket
+
+    # Missing context
+    payload = {"type": "speech"}
+    response = client.post("/button_pressed", json=payload)
+
+    assert response.status_code == 422
+    mock_pub_socket.send_multipart.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_experiment_stream_direct_call():
+    """
+    Directly calling the endpoint function to test the streaming logic
+    without dealing with TestClient streaming limitations.
+    """
+    mock_socket = AsyncMock()
+    # 1. recv data
+    # 2. recv timeout
+    # 3. disconnect (request.is_disconnected returns True)
+    mock_socket.recv_multipart.side_effect = [
+        (b"topic", b"message1"),
+        TimeoutError(),
+        (b"topic", b"message2"),  # Should not be reached if disconnect checks work
+    ]
+    mock_socket.close = MagicMock()
+    mock_socket.connect = MagicMock()
+    mock_socket.subscribe = MagicMock()
+
+    mock_context = MagicMock()
+    mock_context.socket.return_value = mock_socket
+
+    with patch(
+        "control_backend.api.v1.endpoints.user_interact.Context.instance", return_value=mock_context
+    ):
+        mock_request = AsyncMock()
+        # is_disconnected sequence:
+        # 1. False (before first recv) -> reads message1
+        # 2. False (before second recv) -> triggers TimeoutError, continues
+        # 3. True (before third recv) -> break loop
+        mock_request.is_disconnected.side_effect = [False, False, True]
+
+        response = await user_interact.experiment_stream(mock_request)
+
+        lines = []
+        # Consume the generator
+        async for line in response.body_iterator:
+            lines.append(line)
+
+        assert "data: message1\n\n" in lines
+        assert len(lines) == 1
+
+        mock_socket.connect.assert_called()
+        mock_socket.subscribe.assert_called_with(b"experiment")
+        mock_socket.close.assert_called()
+
+
+@pytest.mark.asyncio
+async def test_status_stream_direct_call():
+    """
+    Test the status stream, ensuring it handles messages and sends pings on timeout.
+    """
+    mock_socket = AsyncMock()
+
+    # Define the sequence of events for the socket:
+    # 1. Successfully receive a message
+    # 2. Timeout (which should trigger the ': ping' yield)
+    # 3. Another message (which won't be reached because we'll simulate disconnect)
+    mock_socket.recv_multipart.side_effect = [
+        (b"topic", b"status_update"),
+        TimeoutError(),
+        (b"topic", b"ignored_msg"),
+    ]
+
+    mock_socket.close = MagicMock()
+    mock_socket.connect = MagicMock()
+    mock_socket.subscribe = MagicMock()
+
+    mock_context = MagicMock()
+    mock_context.socket.return_value = mock_socket
+
+    # Mock the ZMQ Context to return our mock_socket
+    with patch(
+        "control_backend.api.v1.endpoints.user_interact.Context.instance", return_value=mock_context
+    ):
+        mock_request = AsyncMock()
+
+        # is_disconnected sequence:
+        # 1. False -> Process "status_update"
+        # 2. False -> Process TimeoutError (yield ping)
+        # 3. True  -> Break loop (client disconnected)
+        mock_request.is_disconnected.side_effect = [False, False, True]
+
+        # Call the status_stream function explicitly
+        response = await user_interact.status_stream(mock_request)
+
+        lines = []
+        async for line in response.body_iterator:
+            lines.append(line)
+
+        # Assertions
+        assert "data: status_update\n\n" in lines
+        assert ": ping\n\n" in lines  # Verify lines 91-92 (ping logic)
+
+        mock_socket.connect.assert_called()
+        mock_socket.subscribe.assert_called_with(b"status")
+        mock_socket.close.assert_called()

test/unit/conftest.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from unittest.mock import MagicMock, patch
 
 import pytest
@@ -25,7 +31,6 @@ def mock_settings():
         mock.zmq_settings.internal_sub_address = "tcp://localhost:5561"
         mock.zmq_settings.ri_command_address = "tcp://localhost:0000"
         mock.agent_settings.bdi_core_name = "bdi_core_agent"
-        mock.agent_settings.bdi_belief_collector_name = "belief_collector_agent"
         mock.agent_settings.llm_name = "llm_agent"
         mock.agent_settings.robot_speech_name = "robot_speech_agent"
         mock.agent_settings.transcription_name = "transcription_agent"
@@ -33,6 +38,7 @@ def mock_settings():
         mock.agent_settings.vad_name = "vad_agent"
         mock.behaviour_settings.sleep_s = 0.01  # Speed up tests
         mock.behaviour_settings.comm_setup_max_retries = 1
+        mock.behaviour_settings.agentspeak_file = "src/control_backend/agents/bdi/agentspeak.asl"
         yield mock
 
 

test/unit/core/test_agent_system.py

@@ -1,4 +1,10 @@
-"""Test the base class logic, message passing and background task handling."""
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+--------------------------------------------------------------------------------
+Test the base class logic, message passing and background task handling.
+"""
 
 import asyncio
 import logging
@@ -99,12 +105,75 @@ async def test_send_to_local_agent(monkeypatch):
     # Patch inbox.put
     target.inbox.put = AsyncMock()
 
-    message = InternalMessage(to="receiver", sender="sender", body="hello")
+    message = InternalMessage(to=target.name, sender=sender.name, body="hello")
 
     await sender.send(message)
 
     target.inbox.put.assert_awaited_once_with(message)
-    sender.logger.debug.assert_called_once()
+
+
+@pytest.mark.asyncio
+async def test_send_to_zmq_agent(monkeypatch):
+    sender = DummyAgent("sender")
+    target = "remote_receiver"
+
+    # Fake logger
+    sender.logger = MagicMock()
+
+    # Fake zmq
+    sender._internal_pub_socket = AsyncMock()
+
+    message = InternalMessage(to=target, sender=sender.name, body="hello")
+
+    await sender.send(message)
+
+    zmq_calls = sender._internal_pub_socket.send_multipart.call_args[0][0]
+    assert zmq_calls[0] == f"internal/{target}".encode()
+
+
+@pytest.mark.asyncio
+async def test_send_to_multiple_local_agents(monkeypatch):
+    sender = DummyAgent("sender")
+    target1 = DummyAgent("receiver1")
+    target2 = DummyAgent("receiver2")
+
+    # Fake logger
+    sender.logger = MagicMock()
+
+    # Patch inbox.put
+    target1.inbox.put = AsyncMock()
+    target2.inbox.put = AsyncMock()
+
+    message = InternalMessage(to=[target1.name, target2.name], sender=sender.name, body="hello")
+
+    await sender.send(message)
+
+    target1.inbox.put.assert_awaited_once_with(message)
+    target2.inbox.put.assert_awaited_once_with(message)
+
+
+@pytest.mark.asyncio
+async def test_send_to_multiple_agents(monkeypatch):
+    sender = DummyAgent("sender")
+    target1 = DummyAgent("receiver1")
+    target2 = "remote_receiver"
+
+    # Fake logger
+    sender.logger = MagicMock()
+
+    # Fake zmq
+    sender._internal_pub_socket = AsyncMock()
+
+    # Patch inbox.put
+    target1.inbox.put = AsyncMock()
+
+    message = InternalMessage(to=[target1.name, target2], sender=sender.name, body="hello")
+
+    await sender.send(message)
+
+    target1.inbox.put.assert_awaited_once_with(message)
+    zmq_calls = sender._internal_pub_socket.send_multipart.call_args[0][0]
+    assert zmq_calls[0] == f"internal/{target2}".encode()
 
 
 @pytest.mark.asyncio

test/unit/core/test_config.py

@@ -1,4 +1,10 @@
-"""Test if settings load correctly and environment variables override defaults."""
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+--------------------------------------------------------------------------------
+Test if settings load correctly and environment variables override defaults.
+"""
 
 from control_backend.core.config import Settings
 

test/unit/core/test_logging.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 import logging
 from unittest.mock import mock_open, patch
 

test/unit/logging/test_dated_file_handler.py

@@ -0,0 +1,51 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from control_backend.logging.dated_file_handler import DatedFileHandler
+
+
+@patch("control_backend.logging.dated_file_handler.DatedFileHandler._open")
+def test_reset(open_):
+    stream = MagicMock()
+    open_.return_value = stream
+
+    # A file should be opened when the logger is created
+    handler = DatedFileHandler(file_prefix="anything")
+    assert open_.call_count == 1
+
+    # Upon reset, the current file should be closed, and a new one should be opened
+    handler.do_rollover()
+    assert stream.close.call_count == 1
+    assert open_.call_count == 2
+
+
+@patch("control_backend.logging.dated_file_handler.Path")
+@patch("control_backend.logging.dated_file_handler.DatedFileHandler._open")
+def test_creates_dir(open_, Path_):
+    stream = MagicMock()
+    open_.return_value = stream
+
+    test_path = MagicMock()
+    test_path.parent.is_dir.return_value = False
+    Path_.return_value = test_path
+
+    DatedFileHandler(file_prefix="anything")
+
+    # The directory should've been created
+    test_path.parent.mkdir.assert_called_once()
+
+
+@patch("control_backend.logging.dated_file_handler.DatedFileHandler._open")
+def test_invalid_constructor(_):
+    with pytest.raises(ValueError):
+        DatedFileHandler(file_prefix=None)
+
+    with pytest.raises(ValueError):
+        DatedFileHandler(file_prefix="")

test/unit/logging/test_optional_field_formatter.py

@@ -0,0 +1,224 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+import logging
+
+import pytest
+
+from control_backend.logging.optional_field_formatter import OptionalFieldFormatter
+
+
+@pytest.fixture
+def logger():
+    """Create a fresh logger for each test."""
+    logger = logging.getLogger(f"test_{id(object())}")
+    logger.setLevel(logging.DEBUG)
+    logger.handlers = []
+    return logger
+
+
+@pytest.fixture
+def log_output(logger):
+    """Capture log output and return a function to get it."""
+
+    class ListHandler(logging.Handler):
+        def __init__(self):
+            super().__init__()
+            self.records = []
+
+        def emit(self, record):
+            self.records.append(self.format(record))
+
+    handler = ListHandler()
+    logger.addHandler(handler)
+
+    def get_output():
+        return handler.records
+
+    return get_output
+
+
+def test_optional_field_present(logger, log_output):
+    """Optional field should appear when provided in extra."""
+    formatter = OptionalFieldFormatter("%(levelname)s - %(role?)s - %(message)s")
+    logger.handlers[0].setFormatter(formatter)
+
+    logger.info("test message", extra={"role": "user"})
+
+    assert log_output() == ["INFO - user - test message"]
+
+
+def test_optional_field_missing_no_default(logger, log_output):
+    """Missing optional field with no default should be None."""
+    formatter = OptionalFieldFormatter("%(levelname)s - %(role?)s - %(message)s")
+    logger.handlers[0].setFormatter(formatter)
+
+    logger.info("test message")
+
+    assert log_output() == ["INFO - None - test message"]
+
+
+def test_optional_field_missing_with_default(logger, log_output):
+    """Missing optional field should use provided default."""
+    formatter = OptionalFieldFormatter(
+        "%(levelname)s - %(role?)s - %(message)s", defaults={"role": "assistant"}
+    )
+    logger.handlers[0].setFormatter(formatter)
+
+    logger.info("test message")
+
+    assert log_output() == ["INFO - assistant - test message"]
+
+
+def test_optional_field_overrides_default(logger, log_output):
+    """Provided extra value should override default."""
+    formatter = OptionalFieldFormatter(
+        "%(levelname)s - %(role?)s - %(message)s", defaults={"role": "assistant"}
+    )
+    logger.handlers[0].setFormatter(formatter)
+
+    logger.info("test message", extra={"role": "user"})
+
+    assert log_output() == ["INFO - user - test message"]
+
+
+def test_multiple_optional_fields(logger, log_output):
+    """Multiple optional fields should work independently."""
+    formatter = OptionalFieldFormatter(
+        "%(levelname)s - %(role?)s - %(request_id?)s - %(message)s", defaults={"role": "assistant"}
+    )
+    logger.handlers[0].setFormatter(formatter)
+
+    logger.info("test", extra={"request_id": "123"})
+
+    assert log_output() == ["INFO - assistant - 123 - test"]
+
+
+def test_mixed_optional_and_required_fields(logger, log_output):
+    """Standard fields should work alongside optional fields."""
+    formatter = OptionalFieldFormatter("%(levelname)s %(name)s %(role?)s %(message)s")
+    logger.handlers[0].setFormatter(formatter)
+
+    logger.info("test", extra={"role": "user"})
+
+    output = log_output()[0]
+    assert "INFO" in output
+    assert "user" in output
+    assert "test" in output
+
+
+def test_no_optional_fields(logger, log_output):
+    """Formatter should work normally with no optional fields."""
+    formatter = OptionalFieldFormatter("%(levelname)s %(message)s")
+    logger.handlers[0].setFormatter(formatter)
+
+    logger.info("test message")
+
+    assert log_output() == ["INFO test message"]
+
+
+def test_integer_format_specifier(logger, log_output):
+    """Optional fields with %d specifier should work."""
+    formatter = OptionalFieldFormatter(
+        "%(levelname)s %(count?)d %(message)s", defaults={"count": 0}
+    )
+    logger.handlers[0].setFormatter(formatter)
+
+    logger.info("test", extra={"count": 42})
+
+    assert log_output() == ["INFO 42 test"]
+
+
+def test_float_format_specifier(logger, log_output):
+    """Optional fields with %f specifier should work."""
+    formatter = OptionalFieldFormatter(
+        "%(levelname)s %(duration?)f %(message)s", defaults={"duration": 0.0}
+    )
+    logger.handlers[0].setFormatter(formatter)
+
+    logger.info("test", extra={"duration": 1.5})
+
+    assert "1.5" in log_output()[0]
+
+
+def test_empty_string_default(logger, log_output):
+    """Empty string default should work."""
+    formatter = OptionalFieldFormatter("%(levelname)s %(role?)s %(message)s", defaults={"role": ""})
+    logger.handlers[0].setFormatter(formatter)
+
+    logger.info("test")
+
+    assert log_output() == ["INFO  test"]
+
+
+def test_none_format_string():
+    """None format string should not raise."""
+    formatter = OptionalFieldFormatter(fmt=None)
+    assert formatter.optional_fields == set()
+
+
+def test_optional_fields_parsed_correctly():
+    """Check that optional fields are correctly identified."""
+    formatter = OptionalFieldFormatter("%(asctime)s %(role?)s %(level?)d %(name)s")
+
+    assert formatter.optional_fields == {("role", "s"), ("level", "d")}
+
+
+def test_format_string_normalized():
+    """Check that ? is removed from format string."""
+    formatter = OptionalFieldFormatter("%(role?)s %(message)s")
+
+    assert "?" not in formatter._style._fmt
+    assert "%(role)s" in formatter._style._fmt
+
+
+def test_field_with_underscore(logger, log_output):
+    """Field names with underscores should work."""
+    formatter = OptionalFieldFormatter("%(levelname)s %(user_id?)s %(message)s")
+    logger.handlers[0].setFormatter(formatter)
+
+    logger.info("test", extra={"user_id": "abc123"})
+
+    assert log_output() == ["INFO abc123 test"]
+
+
+def test_field_with_numbers(logger, log_output):
+    """Field names with numbers should work."""
+    formatter = OptionalFieldFormatter("%(levelname)s %(field2?)s %(message)s")
+    logger.handlers[0].setFormatter(formatter)
+
+    logger.info("test", extra={"field2": "value"})
+
+    assert log_output() == ["INFO value test"]
+
+
+def test_multiple_log_calls(logger, log_output):
+    """Formatter should work correctly across multiple log calls."""
+    formatter = OptionalFieldFormatter(
+        "%(levelname)s %(role?)s %(message)s", defaults={"role": "other"}
+    )
+    logger.handlers[0].setFormatter(formatter)
+
+    logger.info("first", extra={"role": "assistant"})
+    logger.info("second")
+    logger.info("third", extra={"role": "user"})
+
+    assert log_output() == [
+        "INFO assistant first",
+        "INFO other second",
+        "INFO user third",
+    ]
+
+
+def test_default_not_mutated(logger, log_output):
+    """Original defaults dict should not be mutated."""
+    defaults = {"role": "other"}
+    formatter = OptionalFieldFormatter("%(levelname)s %(role?)s %(message)s", defaults=defaults)
+    logger.handlers[0].setFormatter(formatter)
+
+    logger.info("test")
+
+    assert defaults == {"role": "other"}

test/unit/logging/test_partial_filter.py

@@ -0,0 +1,89 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
+import logging
+
+import pytest
+
+from control_backend.logging import PartialFilter
+
+
+@pytest.fixture
+def logger():
+    """Create a fresh logger for each test."""
+    logger = logging.getLogger(f"test_{id(object())}")
+    logger.setLevel(logging.DEBUG)
+    logger.handlers = []
+    return logger
+
+
+@pytest.fixture
+def log_output(logger):
+    """Capture log output and return a function to get it."""
+
+    class ListHandler(logging.Handler):
+        def __init__(self):
+            super().__init__()
+            self.records = []
+
+        def emit(self, record):
+            self.records.append(self.format(record))
+
+    handler = ListHandler()
+    handler.addFilter(PartialFilter())
+    handler.setFormatter(logging.Formatter("%(message)s"))
+    logger.addHandler(handler)
+
+    return lambda: handler.records
+
+
+def test_no_partial_attribute(logger, log_output):
+    """Records without partial attribute should pass through."""
+    logger.info("normal message")
+
+    assert log_output() == ["normal message"]
+
+
+def test_partial_true_filtered(logger, log_output):
+    """Records with partial=True should be filtered out."""
+    logger.info("partial message", extra={"partial": True})
+
+    assert log_output() == []
+
+
+def test_partial_false_passes(logger, log_output):
+    """Records with partial=False should pass through."""
+    logger.info("complete message", extra={"partial": False})
+
+    assert log_output() == ["complete message"]
+
+
+def test_partial_none_passes(logger, log_output):
+    """Records with partial=None should pass through."""
+    logger.info("message", extra={"partial": None})
+
+    assert log_output() == ["message"]
+
+
+def test_partial_truthy_value_passes(logger, log_output):
+    """
+    Records with truthy but non-True partial should pass through, that is, only when it's exactly
+    ``True`` should it pass.
+    """
+    logger.info("message", extra={"partial": "yes"})
+
+    assert log_output() == ["message"]
+
+
+def test_multiple_records_mixed(logger, log_output):
+    """Filter should handle mixed records correctly."""
+    logger.info("first")
+    logger.info("second", extra={"partial": True})
+    logger.info("third", extra={"partial": False})
+    logger.info("fourth", extra={"partial": True})
+    logger.info("fifth")
+
+    assert log_output() == ["first", "third", "fifth"]

test/unit/schemas/test_message.py

@@ -1,3 +1,9 @@
+"""
+This program has been developed by students from the bachelor Computer Science at Utrecht
+University within the Software Project course.
+© Copyright Utrecht University (Department of Information and Computing Sciences)
+"""
+
 from control_backend.schemas.message import Message