Merge branch 'test/increase-coverage' into feat/reset-experiment-and-phase
This commit is contained in:
@@ -1,8 +1,5 @@
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from control_backend.agents.bdi.bdi_core_agent import BDICoreAgent as BDICoreAgent
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from .belief_collector_agent import (
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BDIBeliefCollectorAgent as BDIBeliefCollectorAgent,
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)
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from .text_belief_extractor_agent import (
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TextBeliefExtractorAgent as TextBeliefExtractorAgent,
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)
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@@ -77,7 +77,7 @@ class AstTerm(AstExpression, ABC):
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return AstBinaryOp(self, BinaryOperatorType.NOT_EQUALS, _coalesce_expr(other))
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@dataclass
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@dataclass(eq=False)
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class AstAtom(AstTerm):
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"""
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Grounded expression in all lowercase.
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@@ -89,7 +89,7 @@ class AstAtom(AstTerm):
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return self.value.lower()
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@dataclass
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@dataclass(eq=False)
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class AstVar(AstTerm):
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"""
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Ungrounded variable expression. First letter capitalized.
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@@ -101,7 +101,7 @@ class AstVar(AstTerm):
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return self.name.capitalize()
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@dataclass
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@dataclass(eq=False)
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class AstNumber(AstTerm):
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value: int | float
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@@ -109,7 +109,7 @@ class AstNumber(AstTerm):
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return str(self.value)
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@dataclass
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@dataclass(eq=False)
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class AstString(AstTerm):
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value: str
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@@ -117,7 +117,7 @@ class AstString(AstTerm):
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return f'"{self.value}"'
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@dataclass
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@dataclass(eq=False)
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class AstLiteral(AstTerm):
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functor: str
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terms: list[AstTerm] = field(default_factory=list)
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@@ -167,7 +167,7 @@ class BDICoreAgent(BaseAgent):
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case "force_next_phase":
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self._force_next_phase()
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case _:
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self.logger.warning("Received unknow user interruption: %s", msg)
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self.logger.warning("Received unknown user interruption: %s", msg)
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def _apply_belief_changes(self, belief_changes: BeliefMessage):
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"""
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@@ -1,152 +0,0 @@
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import json
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from pydantic import ValidationError
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from control_backend.agents.base import BaseAgent
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from control_backend.core.agent_system import InternalMessage
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from control_backend.core.config import settings
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from control_backend.schemas.belief_message import Belief, BeliefMessage
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class BDIBeliefCollectorAgent(BaseAgent):
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"""
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BDI Belief Collector Agent.
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This agent acts as a central aggregator for beliefs derived from various sources (e.g., text,
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emotion, vision). It receives raw extracted data from other agents,
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normalizes them into valid :class:`Belief` objects, and forwards them as a unified packet to the
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BDI Core Agent.
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It serves as a funnel to ensure the BDI agent receives a consistent stream of beliefs.
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"""
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async def setup(self):
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"""
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Initialize the agent.
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"""
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self.logger.info("Setting up %s", self.name)
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async def handle_message(self, msg: InternalMessage):
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"""
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Handle incoming messages from other extractor agents.
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Routes the message to specific handlers based on the 'type' field in the JSON body.
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Supported types:
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- ``belief_extraction_text``: Handled by :meth:`_handle_belief_text`
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- ``emotion_extraction_text``: Handled by :meth:`_handle_emo_text`
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:param msg: The received internal message.
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"""
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sender_node = msg.sender
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# Parse JSON payload
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try:
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payload = json.loads(msg.body)
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except Exception as e:
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self.logger.warning(
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"BeliefCollector: failed to parse JSON from %s. Body=%r Error=%s",
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sender_node,
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msg.body,
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e,
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)
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return
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msg_type = payload.get("type")
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# Prefer explicit 'type' field
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if msg_type == "belief_extraction_text":
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self.logger.debug("Message routed to _handle_belief_text (sender=%s)", sender_node)
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await self._handle_belief_text(payload, sender_node)
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# This is not implemented yet, but we keep the structure for future use
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elif msg_type == "emotion_extraction_text":
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self.logger.debug("Message routed to _handle_emo_text (sender=%s)", sender_node)
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await self._handle_emo_text(payload, sender_node)
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else:
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self.logger.warning(
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"Unrecognized message (sender=%s, type=%r). Ignoring.", sender_node, msg_type
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)
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async def _handle_belief_text(self, payload: dict, origin: str):
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"""
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Process text-based belief extraction payloads.
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Expected payload format::
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{
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"type": "belief_extraction_text",
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"beliefs": {
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"user_said": ["Can you help me?"],
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"intention": ["ask_help"]
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}
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}
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Validates and converts the dictionary items into :class:`Belief` objects.
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:param payload: The dictionary payload containing belief data.
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:param origin: The name of the sender agent.
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"""
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beliefs = payload.get("beliefs", {})
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if not beliefs:
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self.logger.debug("Received empty beliefs set.")
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return
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def try_create_belief(name, arguments) -> Belief | None:
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"""
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Create a belief object from name and arguments, or return None silently if the input is
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not correct.
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:param name: The name of the belief.
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:param arguments: The arguments of the belief.
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:return: A Belief object if the input is valid or None.
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"""
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try:
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return Belief(name=name, arguments=arguments)
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except ValidationError:
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return None
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beliefs = [
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belief
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for name, arguments in beliefs.items()
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if (belief := try_create_belief(name, arguments)) is not None
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]
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self.logger.debug("Forwarding %d beliefs.", len(beliefs))
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for belief in beliefs:
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for argument in belief.arguments:
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self.logger.debug(" - %s %s", belief.name, argument)
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await self._send_beliefs_to_bdi(beliefs, origin=origin)
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async def _handle_emo_text(self, payload: dict, origin: str):
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"""
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Process emotion extraction payloads.
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**TODO**: Implement this method once emotion recognition is integrated.
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:param payload: The dictionary payload containing emotion data.
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:param origin: The name of the sender agent.
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"""
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pass
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async def _send_beliefs_to_bdi(self, beliefs: list[Belief], origin: str | None = None):
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"""
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Send a list of aggregated beliefs to the BDI Core Agent.
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Wraps the beliefs in a :class:`BeliefMessage` and sends it via the 'beliefs' thread.
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:param beliefs: The list of Belief objects to send.
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:param origin: (Optional) The original source of the beliefs (unused currently).
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"""
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if not beliefs:
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return
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msg = InternalMessage(
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to=settings.agent_settings.bdi_core_name,
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sender=self.name,
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body=BeliefMessage(create=beliefs).model_dump_json(),
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thread="beliefs",
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)
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await self.send(msg)
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self.logger.info("Sent %d belief(s) to BDI core.", len(beliefs))
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