| from pydantic import BaseModel, Field, field_validator, ConfigDict |
| import hashlib |
| from typing import Dict, Any, List |
|
|
| class Phase11AgentOutput(BaseModel): |
| """Base class for all Phase 11 Enterprise Hyperscale Agent Outputs.""" |
| model_config = ConfigDict(populate_by_name=True) |
| |
| status: str |
| measured: bool = Field(default=True, alias="_measured", repr=False) |
| |
| @field_validator('status') |
| @classmethod |
| def status_must_be_valid(cls, v): |
| valid = {"CERTIFIED", "FAILED", "SCAFFOLDING_ONLY", "VERIFIED", "REJECTED"} |
| if v not in valid: |
| raise ValueError(f"Status {v} not in {valid}") |
| return v |
|
|
| class RunuxMPIHyperscaleMetrics(Phase11AgentOutput): |
| """ |
| H62: Hyperscale Rust-Native Execution Engine. |
| Ensures zero-copy scaling up to 1000+ nodes. |
| """ |
| nodes_scaled: int |
| zero_copy_verified: bool |
| network_latency_ms: float |
| |
| def verify_h62(self) -> bool: |
| return self.nodes_scaled >= 1000 and self.zero_copy_verified and self.network_latency_ms < 1.0 |
|
|
| class DO178CAerospaceCert(Phase11AgentOutput): |
| """ |
| H63: Lean 4 Aerospace Certification (DO-178C). |
| Zero variance in latency and deterministic transonic buffet bounds. |
| """ |
| latency_variance_us: float |
| buffet_amplitude_bound: float |
| lean4_proof_hash: str |
| |
| def verify_h63(self) -> bool: |
| |
| return self.latency_variance_us == 0.0 and self.buffet_amplitude_bound < 0.05 and len(self.lean4_proof_hash) == 64 |
|
|
| class FDAMedicalClassIIICert(Phase11AgentOutput): |
| """ |
| H64: FDA Class III Medical Device Certification. |
| Monotonic hemodynamics and bounded shear stress to prevent hemolysis. |
| """ |
| reverse_flow_events: int |
| max_shear_stress_pa: float |
| lean4_proof_hash: str |
| |
| def verify_h64(self) -> bool: |
| return self.reverse_flow_events == 0 and self.max_shear_stress_pa <= 150.0 and len(self.lean4_proof_hash) == 64 |
|
|
| class EdgeSwarmConsensusMetrics(Phase11AgentOutput): |
| """ |
| H65: Edge Swarm AI Consensus. |
| Byzantine fault tolerance and quantized AI model consensus. |
| """ |
| swarm_size: int |
| byzantine_nodes_tolerated: int |
| consensus_reached_ms: float |
| ai_model_quantization: str |
| |
| def verify_h65(self) -> bool: |
| return self.consensus_reached_ms < 5.0 and self.byzantine_nodes_tolerated >= (self.swarm_size - 1) // 3 and self.ai_model_quantization in ["INT8", "INT4", "GGUF"] |
|
|
| class Phase11HyperscaleAuditCertificate(BaseModel): |
| certificate_id: str |
| overall_status: str |
| invariants_verified: Dict[str, bool] |
| sha256_hash: str |
| |
| def is_fully_certified(self) -> bool: |
| return self.overall_status == "CERTIFIED" and all(self.invariants_verified.values()) |
|
|
| def generate_phase11_certificate(h62: bool, h63: bool, h64: bool, h65: bool) -> Phase11HyperscaleAuditCertificate: |
| invariants = { |
| "H62_runux_mpi_hyperscale": h62, |
| "H63_do178c_aerospace": h63, |
| "H64_fda_class_iii_medical": h64, |
| "H65_edge_swarm_consensus": h65 |
| } |
| |
| all_pass = all(invariants.values()) |
| status = "CERTIFIED" if all_pass else "REJECTED" |
| |
| raw_str = f"P11_CERT_{h62}_{h63}_{h64}_{h65}" |
| cert_hash = hashlib.sha256(raw_str.encode()).hexdigest() |
| cert_id = f"CERT-P11-HYPER-{cert_hash[:16].upper()}" |
| |
| return Phase11HyperscaleAuditCertificate( |
| certificate_id=cert_id, |
| overall_status=status, |
| invariants_verified=invariants, |
| sha256_hash=cert_hash |
| ) |
|
|
