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ff93356a9a
| Author | SHA1 | Date | |
|---|---|---|---|
| ff93356a9a | |||
| c938345fc2 | |||
| 5d90ff4c44 | |||
| b71ec5c76a | |||
| b3caff0f90 |
@@ -24,6 +24,7 @@ dependencies = [
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"sphinx-rtd-theme>=3.0.2",
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"tf-keras>=2.20.1",
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"torch>=2.8.0",
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"tornado ; sys_platform == 'win32'",
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"uvicorn>=0.37.0",
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]
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@@ -107,7 +107,7 @@ class AgentSpeakGenerator:
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check if a keyword is a substring of the user's message.
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The generated rule has the form:
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keyword_said(Keyword) :- user_said(Message) & .substring(Keyword, Message, Pos) & Pos >= 0
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keyword_said(Keyword) :- user_said(Message) & .substring_case_insensitive(Keyword, Message, Pos) & Pos >= 0
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This enables the system to trigger behaviors based on keyword detection.
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"""
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@@ -119,7 +119,7 @@ class AgentSpeakGenerator:
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AstRule(
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AstLiteral("keyword_said", [keyword]),
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AstLiteral("user_said", [message])
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& AstLiteral(".substring", [keyword, message, position])
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& AstLiteral(".substring_case_insensitive", [keyword, message, position])
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& (position >= 0),
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)
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)
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@@ -135,7 +135,6 @@ class AgentSpeakGenerator:
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"""
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self._add_reply_with_goal_plan()
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self._add_say_plan()
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self._add_reply_plan()
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self._add_notify_cycle_plan()
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def _add_reply_with_goal_plan(self):
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@@ -199,40 +198,6 @@ class AgentSpeakGenerator:
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)
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)
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def _add_reply_plan(self):
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"""
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Adds a plan for general reply actions.
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This plan handles general reply actions where the agent needs to respond
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to user input without a specific conversational goal. It:
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1. Marks that the agent has responded this turn
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2. Gathers all active norms
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3. Generates a reply based on the user message and norms
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Trigger: +!reply
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Context: user_said(Message)
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"""
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self._asp.plans.append(
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AstPlan(
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TriggerType.ADDED_GOAL,
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AstLiteral("reply"),
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[AstLiteral("user_said", [AstVar("Message")])],
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[
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AstStatement(StatementType.ADD_BELIEF, AstLiteral("responded_this_turn")),
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AstStatement(
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StatementType.DO_ACTION,
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AstLiteral(
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"findall",
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[AstVar("Norm"), AstLiteral("norm", [AstVar("Norm")]), AstVar("Norms")],
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),
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),
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AstStatement(
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StatementType.DO_ACTION,
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AstLiteral("reply", [AstVar("Message"), AstVar("Norms")]),
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),
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],
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)
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)
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def _add_notify_cycle_plan(self):
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"""
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@@ -270,6 +235,39 @@ class AgentSpeakGenerator:
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)
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)
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def _add_stop_plan(self, phase: Phase):
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"""
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Adds a plan to stop the program. This just skips to the end phase,
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where there is no behavior defined.
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"""
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self._asp.plans.append(
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AstPlan(
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TriggerType.ADDED_GOAL,
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AstLiteral("stop"),
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[AstLiteral("phase", [AstString(phase.id)])],
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[
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AstStatement(
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StatementType.DO_ACTION,
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AstLiteral(
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"notify_transition_phase",
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[
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AstString(phase.id),
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AstString("end")
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]
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)
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),
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AstStatement(
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StatementType.REMOVE_BELIEF,
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AstLiteral("phase", [AstVar("Phase")]),
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),
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AstStatement(
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StatementType.ADD_BELIEF,
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AstLiteral("phase", [AstString("end")])
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)
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]
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)
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)
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def _process_phases(self, phases: list[Phase]) -> None:
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"""
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Processes all phases in the program and their transitions.
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@@ -286,21 +284,6 @@ class AgentSpeakGenerator:
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self._process_phase(curr_phase)
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self._add_phase_transition(curr_phase, next_phase)
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# End phase behavior
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# When deleting this, the entire `reply` plan and action can be deleted
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self._asp.plans.append(
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AstPlan(
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type=TriggerType.ADDED_BELIEF,
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trigger_literal=AstLiteral("user_said", [AstVar("Message")]),
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context=[AstLiteral("phase", [AstString("end")])],
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body=[
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AstStatement(
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StatementType.DO_ACTION, AstLiteral("notify_user_said", [AstVar("Message")])
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),
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AstStatement(StatementType.ACHIEVE_GOAL, AstLiteral("reply")),
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],
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)
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)
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def _process_phase(self, phase: Phase) -> None:
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"""
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@@ -327,6 +310,9 @@ class AgentSpeakGenerator:
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for trigger in phase.triggers:
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self._process_trigger(trigger, phase)
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# Add force transition to end phase
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self._add_stop_plan(phase)
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def _add_phase_transition(self, from_phase: Phase | None, to_phase: Phase | None) -> None:
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"""
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Adds plans for transitioning between phases.
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@@ -617,6 +603,7 @@ class AgentSpeakGenerator:
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- check_triggers: When no triggers are applicable
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- transition_phase: When phase transition conditions aren't met
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- force_transition_phase: When forced transitions aren't possible
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- stop: When we are already in the end phase
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"""
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# Trigger fallback
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self._asp.plans.append(
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@@ -648,6 +635,16 @@ class AgentSpeakGenerator:
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)
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)
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# Stop fallback
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self._asp.plans.append(
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AstPlan(
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TriggerType.ADDED_GOAL,
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AstLiteral("stop"),
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[],
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[AstStatement(StatementType.EMPTY, AstLiteral("true"))],
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)
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)
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@singledispatchmethod
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def _astify(self, element: ProgramElement) -> AstExpression:
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"""
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@@ -176,6 +176,8 @@ class BDICoreAgent(BaseAgent):
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self._force_norm(msg.body)
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case "force_next_phase":
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self._force_next_phase()
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case "stop":
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self._stop()
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case _:
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self.logger.warning("Received unknown user interruption: %s", msg)
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@@ -335,6 +337,11 @@ class BDICoreAgent(BaseAgent):
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self.logger.info("Manually forced phase transition.")
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def _stop(self):
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self._set_goal("stop")
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self.logger.info("Stopped the program (skipped to end phase).")
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def _add_custom_actions(self) -> None:
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"""
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Add any custom actions here. Inside `@self.actions.add()`, the first argument is
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@@ -342,6 +349,28 @@ class BDICoreAgent(BaseAgent):
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the function expects (which will be located in `term.args`).
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"""
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@self.actions.add(".substring_case_insensitive", 3)
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@agentspeak.optimizer.function_like
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def _substring(agent, term, intention):
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"""
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Find out if a string is a substring of another (case insensitive). Copied mostly from
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the agentspeak library method .substring.
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"""
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needle = agentspeak.asl_str(agentspeak.grounded(term.args[0], intention.scope)).lower()
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haystack = agentspeak.asl_str(agentspeak.grounded(term.args[1], intention.scope)).lower()
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choicepoint = object()
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pos = haystack.find(needle)
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while pos != -1:
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intention.stack.append(choicepoint)
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if agentspeak.unify(term.args[2], pos, intention.scope, intention.stack):
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yield
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agentspeak.reroll(intention.scope, intention.stack, choicepoint)
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pos = haystack.find(needle, pos + 1)
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@self.actions.add(".reply", 2)
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def _reply(agent, term, intention):
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"""
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@@ -467,7 +496,6 @@ class BDICoreAgent(BaseAgent):
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body=str(trigger_name),
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)
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# TODO: check with Pim
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self.add_behavior(self.send(msg))
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yield
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@@ -128,7 +128,7 @@ class VisualEmotionRecognitionAgent(BaseAgent):
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next_window_time = time.time() + self.window_duration
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except zmq.Again:
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self.logger.warning("No video frame received within timeout.")
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pass
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except Exception as e:
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self.logger.error(f"Error in emotion recognition loop: {e}")
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@@ -164,6 +164,12 @@ class UserInterruptAgent(BaseAgent):
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else:
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self.logger.info("Sent resume command.")
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case "stop":
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self.logger.debug(
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"Received stop command."
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)
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await self._send_stop_command()
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case "next_phase" | "reset_phase":
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await self._send_experiment_control_to_bdi_core(event_type)
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case _:
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@@ -423,3 +429,15 @@ class UserInterruptAgent(BaseAgent):
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await self.send(vad_message)
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# Voice Activity Detection and Visual Emotion Recognition agents
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self.logger.info("Sent resume command to VAD and VED agents.")
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async def _send_stop_command(self):
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"""
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Send a command to the BDI to stop the program (i.e., skip to end phase).
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"""
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msg = InternalMessage(
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to=settings.agent_settings.bdi_core_name,
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body="",
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thread="stop"
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)
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await self.send(msg)
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15
uv.lock
generated
15
uv.lock
generated
@@ -1,5 +1,5 @@
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version = 1
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revision = 3
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revision = 2
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requires-python = ">=3.13"
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resolution-markers = [
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"python_full_version >= '3.14' and sys_platform == 'darwin'",
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@@ -1524,6 +1524,7 @@ dependencies = [
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{ name = "sphinx-rtd-theme" },
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{ name = "tf-keras" },
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{ name = "torch" },
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{ name = "tornado", marker = "sys_platform == 'win32'" },
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{ name = "uvicorn" },
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]
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@@ -1579,6 +1580,7 @@ requires-dist = [
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{ name = "sphinx-rtd-theme", specifier = ">=3.0.2" },
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{ name = "tf-keras", specifier = ">=2.20.1" },
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{ name = "torch", specifier = ">=2.8.0" },
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{ name = "tornado", marker = "sys_platform == 'win32'" },
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{ name = "uvicorn", specifier = ">=0.37.0" },
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]
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@@ -2724,6 +2726,17 @@ wheels = [
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{ url = "https://files.pythonhosted.org/packages/52/27/7fc2d7435af044ffbe0b9b8e98d99eac096d43f128a5cde23c04825d5dcf/torchaudio-2.8.0-cp313-cp313t-win_amd64.whl", hash = "sha256:d4a715d09ac28c920d031ee1e60ecbc91e8a5079ad8c61c0277e658436c821a6", size = 2549553, upload-time = "2025-08-06T14:59:00.019Z" },
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]
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[[package]]
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name = "tornado"
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version = "6.5.4"
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source = { registry = "https://pypi.org/simple" }
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sdist = { url = "https://files.pythonhosted.org/packages/37/1d/0a336abf618272d53f62ebe274f712e213f5a03c0b2339575430b8362ef2/tornado-6.5.4.tar.gz", hash = "sha256:a22fa9047405d03260b483980635f0b041989d8bcc9a313f8fe18b411d84b1d7", size = 513632, upload-time = "2025-12-15T19:21:03.836Z" }
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/0c/1a/d7592328d037d36f2d2462f4bc1fbb383eec9278bc786c1b111cbbd44cfa/tornado-6.5.4-cp39-abi3-win32.whl", hash = "sha256:1768110f2411d5cd281bac0a090f707223ce77fd110424361092859e089b38d1", size = 446481, upload-time = "2025-12-15T19:21:00.008Z" },
|
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{ url = "https://files.pythonhosted.org/packages/d6/6d/c69be695a0a64fd37a97db12355a035a6d90f79067a3cf936ec2b1dc38cd/tornado-6.5.4-cp39-abi3-win_amd64.whl", hash = "sha256:fa07d31e0cd85c60713f2b995da613588aa03e1303d75705dca6af8babc18ddc", size = 446886, upload-time = "2025-12-15T19:21:01.287Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/50/49/8dc3fd90902f70084bd2cd059d576ddb4f8bb44c2c7c0e33a11422acb17e/tornado-6.5.4-cp39-abi3-win_arm64.whl", hash = "sha256:053e6e16701eb6cbe641f308f4c1a9541f91b6261991160391bfc342e8a551a1", size = 445910, upload-time = "2025-12-15T19:21:02.571Z" },
|
||||
]
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[[package]]
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name = "tqdm"
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version = "4.67.1"
|
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Block a user