# Crystal–Mycelial Engine (CME)
# Teaching Agents — TriadicFrameworks / RTT / CMH / MSRM
# Version 1.0 — 2026
 
 
# ------------------------------------------------------------
# Biological Trace Agent
# ------------------------------------------------------------
 
class BiologicalTraceAgent:
    def run(self):
        """
        Capture biological geometry and routing.
        Required operators:
            P.trace_extend
            G.nutrient_gradient
        Output:
            bio_map
        """
        bio_map = {
            "geometry": None,
            "gradients": None
        }
        # TODO: trace geometry
        # TODO: compute gradients
        return bio_map
 
 
# ------------------------------------------------------------
# Hybrid Alignment Agent
# ------------------------------------------------------------
 
class HybridAlignmentAgent:
    def align(self, bio_map):
        """
        Align biological geometry with hybrid resonance fields.
        Required operators:
            S.channel_fill
            HybridOps.resonance_bridge
        Output:
            hybrid_layer
        """
        hybrid_layer = {
            "channels": None,
            "alignment": None
        }
        # TODO: fill channels
        # TODO: bridge resonance
        return hybrid_layer
 
 
# ------------------------------------------------------------
# Mineral Domain Agent
# ------------------------------------------------------------
 
class MineralDomainAgent:
    def crystallize(self, hybrid_layer):
        """
        Generate mineral lattice domains.
        Required operators:
            P.front_propagate
            M.domain_memory
        Output:
            mineral_map
        """
        mineral_map = {
            "lattice": None,
            "domains": None
        }
        # TODO: propagate lattice
        # TODO: encode domain memory
        return mineral_map
 
 
# ------------------------------------------------------------
# Envelope Advisor Agent
# ------------------------------------------------------------
 
class EnvelopeAdvisorAgent:
    def advise(self):
        """
        Recommend envelope values for each regime.
        Targets:
            BGR moisture: 0.55–0.65
            HRR ion saturation: 0.65–0.75
            MLR supersaturation: ≥ 0.85
        Output:
            envelope_plan
        """
        envelope_plan = {
            "BGR": {"moisture": (0.55, 0.65)},
            "HRR": {"ion_saturation": (0.65, 0.75)},
            "MLR": {"supersaturation": 0.85}
        }
        # TODO: refine envelope plan if needed
        return envelope_plan
 
 
# ------------------------------------------------------------
# Memory Transfer Agent
# ------------------------------------------------------------
 
class MemoryTransferAgent:
    def transfer(self, bio_map, hybrid_layer):
        """
        Move memory through substrate layers.
        Required operators:
            M.route_memory
            HybridOps.memory_transfer
            M.domain_memory
        Output:
            memory_state
        """
        memory_state = {
            "bio_memory": None,
            "hybrid_memory": None,
            "mineral_memory": None
        }
        # TODO: route memory
        # TODO: transfer memory
        # TODO: encode domain memory
        return memory_state
 
 
# ------------------------------------------------------------
# Full CME Simulation Agent
# ------------------------------------------------------------
 
class CMESimulationAgent:
    def __init__(self):
        self.bio_agent = BiologicalTraceAgent()
        self.hybrid_agent = HybridAlignmentAgent()
        self.mineral_agent = MineralDomainAgent()
        self.envelope_agent = EnvelopeAdvisorAgent()
        self.memory_agent = MemoryTransferAgent()
 
    def run(self):
        """
        Full CME substrate transition pipeline.
        Output:
            final_state
        """
        bio_map = self.bio_agent.run()
        hybrid_layer = self.hybrid_agent.align(bio_map)
        mineral_map = self.mineral_agent.crystallize(hybrid_layer)
        envelopes = self.envelope_agent.advise()
        memory_state = self.memory_agent.transfer(bio_map, hybrid_layer)
 
        final_state = {
            "bio_map": bio_map,
            "hybrid_layer": hybrid_layer,
            "mineral_map": mineral_map,
            "envelopes": envelopes,
            "memory_state": memory_state
        }
        return final_state
 
 
# ------------------------------------------------------------
# Teaching Agent
# ------------------------------------------------------------
 
class TeachingAgent:
    def __init__(self):
        self.sim = CMESimulationAgent()
 
    def lesson(self):
        """
        Produce student-facing explanations.
        Output:
            lesson_packet
        """
        sim_output = self.sim.run()
 
        questions = [
            "Explain how biological geometry influences hybrid alignment.",
            "Describe the role of resonance fields in HRR.",
            "How does domain memory persist in mineral substrates?",
            "What envelope values define the transition into MLR?",
            "Why does CME require both substrate and operator alignment?"
        ]
 
        lesson_packet = {
            "simulation": sim_output,
            "questions": questions
        }
        return lesson_packet
 
 
# ------------------------------------------------------------
# CME Pipeline (Capstone)
# ------------------------------------------------------------
 
def cme_pipeline():
    """
    Multi-agent CME workflow.
    Output:
        final_state
    """
    sim = CMESimulationAgent()
    final_state = sim.run()
    return final_state