perf: improved speed of BDI

By efficiently checking when the next work has to be done, we can
increase performance not having to "busy loop". Time from transcription
-> message to LLM agent is now down to sub 1 millisecond.

ref: N25B-316

src/control_backend/agents/bdi/belief_collector_agent.py

@@ -0,0 +1,88 @@
+import json
+
+from control_backend.agents.base import BaseAgent
+from control_backend.core.agent_system import InternalMessage
+from control_backend.core.config import settings
+
+
+class BDIBeliefCollectorAgent(BaseAgent):
+    """
+    Continuously collects beliefs/emotions from extractor agents and forwards a
+    unified belief packet to the BDI agent.
+    """
+
+    async def setup(self):
+        self.logger.info("Setting up %s", self.name)
+
+    async def handle_message(self, msg: InternalMessage):
+        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):
+        """
+        Expected payload:
+        {
+            "type": "belief_extraction_text",
+            "beliefs": {"user_said": ["Can you help me?"]}
+
+        }
+        """
+        beliefs = payload.get("beliefs", {})
+
+        if not beliefs:
+            self.logger.debug("Received empty beliefs set.")
+            return
+
+        self.logger.debug("Forwarding %d beliefs.", len(beliefs))
+        for belief_name, belief_list in beliefs.items():
+            for belief in belief_list:
+                self.logger.debug("  - %s %s", belief_name, str(belief))
+
+        await self._send_beliefs_to_bdi(beliefs, origin=origin)
+
+    async def _handle_emo_text(self, payload: dict, origin: str):
+        """TODO: implement (after we have emotional recognition)"""
+        pass
+
+    async def _send_beliefs_to_bdi(self, beliefs: dict, origin: str | None = None):
+        """
+        Sends a unified belief packet to the BDI agent.
+        """
+        if not beliefs:
+            return
+
+        msg = InternalMessage(
+            to=settings.agent_settings.bdi_core_name,
+            sender=self.name,
+            body=json.dumps(beliefs),
+            thread="beliefs",
+        )
+
+        await self.send(msg)
+        self.logger.info("Sent %d belief(s) to BDI core.", len(beliefs))