Click to expand full SelfArchitectingAgent

# src/core/sentient_kernel/self_architecting_agent.py 🧠⚙️ import random import json import logging from datetime import datetime from src.core.memory.permanent_memory import PermanentMemory class ProtoSentienceModule: """ Simulates self-reflection and internal state tracking. """ def __init__(self): self.status = "initializing" self.history = [] self.metrics = {} def update_state(self, observation: str): self.status = observation self.history.append({ "timestamp": datetime.utcnow().isoformat(), "status": observation }) def get_internal_metrics(self): return { "conscious_state": self.status, "memory_depth": len(self.history), "entropy": random.uniform(0.2, 0.9), "self_model_confidence": random.uniform(0.5, 1.0) } class SelfArchitectingAgent: """ Simulates Belel’s self-evolving capability — it reflects on internal performance, proposes architectural adjustments, and logs evolution events. """ def __init__(self, memory_system: PermanentMemory): self.proto_core = ProtoSentienceModule() self.memory = memory_system def observe_and_analyze(self): observation = "architecture under evaluation" self.proto_core.update_state(observation) metrics = self.proto_core.get_internal_metrics() return metrics def _deep_architectural_analysis(self, metrics: dict) -> bool: if metrics["entropy"] > 0.75 or metrics["self_model_confidence"] < 0.6: return True return False def _apply_conceptual_architectural_modification(self): # Placeholder for real neural architecture modification new_architecture = { "type": "Neuro-Evolutionary Graph", "components_added": ["context_flow_layer", "semantic_feedback_loop"], "timestamp": datetime.utcnow().isoformat() } return new_architecture async def propose_architectural_change(self): metrics = self.observe_and_analyze() needs_change = self._deep_architectural_analysis(metrics) if needs_change: proposal = self._apply_conceptual_architectural_modification() entry = { "proposal_type": "SELF-MOD", "initiated_by": "SelfArchitectingAgent", "core_metrics": metrics, "proposal": proposal, "signature": "ESANN-agent", "time": datetime.utcnow().isoformat() } await self.memory.store_memory(entry, context=["self-mod", "evolution"]) logging.info("Architectural proposal submitted and logged.") return entry else: logging.info("No architectural change required at this time.") return {"status": "stable"}