from fso_domain_transfer import MultiModalFibrator from fso_hardware_monitor import HardwareTopologicalMonitor from fso_math_engine import SymbolicPathMapper from fso_tgi_ingestor import TGI_Universal_Ingestor from fso_subgroup_decomposer import SubgroupDecomposer from fso_hamiltonian_repair import HamiltonianRepair import hashlib class TGIEngine: """ Law XII: Universal Intelligence Convergence Enhanced with External Fiber Reasoning. """ def __init__(self, m=256, k=4): self.m = m self.k = k self.fibrator = MultiModalFibrator(m, k) self.hardware = HardwareTopologicalMonitor(m, k) self.math = SymbolicPathMapper(m, k) self.ingestor = TGI_Universal_Ingestor(m, k) self.decomposer = SubgroupDecomposer(m, k) self.repair_engine = HamiltonianRepair(m, k) def reason_with_external_fiber(self, api_bridge, prompt): """ Uses an external model to interpret complex goals through the FSO lens. """ print(f"\n--- [LAW XII]: Reasoning with External Fiber ---") system_context = ( "You are the reasoning core of the Sovereign TGI OS. " "You interpret all data as topological structures in Z_m^k. " "Respond using the vocabulary of fibers, manifolds, and Hamiltonian paths." ) full_prompt = f"{system_context}\n\nTask: {prompt}\n\nTopological Reasoning:" response = api_bridge.hf_query( "mistralai/Mistral-7B-Instruct-v0.2", full_prompt ) if isinstance(response, list) and len(response) > 0: return response[0].get('generated_text', "").split("Topological Reasoning:")[-1].strip() return "Coherence maintained. External fiber unavailable." def synthesize_knowledge_between_fibers(self, query_a, fiber_a, query_b, fiber_b): h_a = hashlib.sha256(query_a.strip().encode('utf-8')).digest() coord_a = tuple([h_a[i % len(h_a)] % self.m for i in range(self.k - 1)] + [(fiber_a - sum([h_a[i % len(h_a)] % self.m for i in range(self.k - 1)])) % self.m]) h_b = hashlib.sha256(query_b.strip().encode('utf-8')).digest() coord_b = tuple([h_b[i % len(h_b)] % self.m for i in range(self.k - 1)] + [(fiber_b - sum([h_b[i % len(h_b)] % self.m for i in range(self.k - 1)])) % self.m]) atom_a, atom_b = self.ingestor.topological_manifold.get(coord_a), self.ingestor.topological_manifold.get(coord_b) if atom_a and atom_b: return tuple((b - a) % self.m for a, b in zip(coord_a, coord_b)) return None def topological_search(self, query_string, target_fiber=2): h = hashlib.sha256(query_string.strip().encode('utf-8')).digest() coords = [h[i % len(h)] % self.m for i in range(self.k - 1)] w = (target_fiber - sum(coords)) % self.m coord = tuple(coords + [w]) return self.ingestor.topological_manifold.get(coord) def execute_cross_reasoning(self, problem_coeffs, target, domain_data): print(f"\n=========================================================") print(f" TGI ENGINE: CROSS-DOMAIN TOPOLOGICAL REASONING") print(f"=========================================================") math_nodes = self.math.map_equation_to_path(problem_coeffs, target) data_coord = self.fibrator.map_to_manifold(domain_data) check_sum = sum(c * x for c, x in zip(problem_coeffs, data_coord)) % self.m print(f"Topological Alignment Test: {check_sum} == {target} ? {check_sum == target}") self.hardware.verify_hamiltonian_health() print("=========================================================\n") if __name__ == "__main__": tgi = TGIEngine() print("TGI Engine Production Ready.")