"""
AGI Neural Core (The Thinker)
Authority: F2 (Truth) + F6 (Context)
Metabolic Stages: 111, 222, 333
"""
import logging
import time
from typing import Any, Dict

from arifos_core.agi.atlas import ATLAS

logger = logging.getLogger("agi_kernel")

class AGINeuralCore:
    """
    The Orthogonal Thinking Kernel.
    Pure Logic. No Side Effects.
    """

    @staticmethod
    async def sense(query: str, context_meta: Dict[str, Any] = None) -> Dict[str, Any]:
        """
        Stage 111: Active Context Sensing via ATLAS.
        Maps query to Governance Placement Vector (GPV).
        """
        timestamp = time.time()

        # Use ATLAS for Lane Classification and Context mapping
        gpv = ATLAS.map(query, context_meta)

        return {
            "meta": {
                "timestamp": timestamp,
                "lane": gpv.lane,
                "truth_demand": gpv.truth_demand,
                "care_demand": gpv.care_demand,
                "risk_level": gpv.risk_level,
                "origin_context": context_meta.get("origin", "User_Direct") if context_meta else "User_Direct"
            }
        }

    @staticmethod
    async def reflect(thought: str, thought_number: int, total_thoughts: int, next_needed: bool) -> Dict[str, Any]:
        """Stage 222: Sequential Reflection."""
        # In a real implementation, this would invoke the SequentialThinking model
        # For the kernel, we validate the step
        return {
            "status": "Reflected",
            "thought_index": f"{thought_number}/{total_thoughts}",
            "requires_more": next_needed,
            "integrity_hash": str(hash(thought))
        }

    @staticmethod
    async def atlas_tac_analysis(inputs: List[Dict[str, Any]]) -> Dict[str, Any]:
        """Stage 333: TAC Engine (Theory of Anomalous Contrast)."""
        # Kept as stub for now, focusing on 111-SENSE wiring

# Backward Compatibility
AGIKernel = AGINeuralCore
