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# -*- coding: utf-8 -*-
"""
Sovereign Polyglot Verification Module
ู
ุญุฑู ุงูุชุญูู ู
ุชุนุฏุฏ ุงููุบุงุช ุงูุณูุงุฏู
Architecture: APL-inspired dense array verification with multi-lingual identifiers
Operator: Ahmad Ali Parr | Infrastructure: Local First Sovereign OS
Author: Ahmad Ali Parr
License: Sovereign Source
"""
import sys
import hashlib
import json
import time
import math
from dataclasses import dataclass, field
from typing import Any, List, Dict, Tuple
from datetime import datetime
# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
# MULTI-LINGUAL IDENTIFIER DECLARATIONS
# ๅค่จ่ช่ญๅฅๅญๅฎฃ่จ | ุฅุนูุงูุงุช ุงูู
ุนุฑูุงุช ู
ุชุนุฏุฏุฉ ุงููุบุงุช
# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
# English (logic descriptors)
VerificationState = "verification_state"
ProofObligation = "proof_obligation"
EntropyBound = "entropy_bound"
# Japanese (้ซๅฏๅบฆๆง้ ๆฆๅฟต - high-density structural concepts)
ๆค่จผ็ถๆ
= "verification_state_ja"
่จผๆ็พฉๅ = "proof_obligation_ja"
ใจใณใใญใใผๅข็ = "entropy_bound_ja"
้
ๅๅคๆ = "array_transform"
ๅถ็ดๆค่จผ = "constraint_validation"
่จผๆ็ๆ = "proof_generation"
# Arabic/RTL (ู
ุนุฑูุงุช RTL - RTL identifiers)
ุญุงูุฉ_ุงูุชุญูู = "verification_state_ar"
ุงูุงูุชุฒุงู
_ุจุงูุฅุซุจุงุช = "proof_obligation_ar"
ุญุฏ_ุงูุฅูุชุฑูุจูุง = "entropy_bound_ar"
ู
ุตูููุฉ_ุงูุชุญููู = "array_transform_ar"
ุงูุชุญูู_ู
ู_ุงููููุฏ = "constraint_validation_ar"
ุชูููุฏ_ุงูุฏููู = "proof_generation_ar"
# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
# APL-INSPIRED BOOLEAN KERNEL (NAND-only basis)
# NANDใฎใฟใฎใใผใซไปฃๆฐใซใผใใซ | ููุงุฉ ุฌุจุฑ ู
ูุทูู ูุงุฆู
ุฉ ุนูู NAND ููุท
# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
class BooleanKernel:
"""
Dyalog APL/K-inspired NAND-only boolean algebra
All boolean operations reduce to NAND gate.
Mathematically universal and language-agnostic.
ใในใฆใฎใใผใซๆผ็ฎใฏNANDใฒใผใใซ้ๅ
ใใใ
ุฌู
ูุน ุงูุนู
ููุงุช ุงูู
ูุทููุฉ ุชูุฎุชุฒู ุฅูู ุจูุงุจุฉ NAND
"""
@staticmethod
def nand(a: int, b: int) -> int:
"""Primitive: NAND(a,b) = 1 - a*b"""
return 1 - (a * b)
@staticmethod
def not_(x: int) -> int:
"""NOT(x) = NAND(x, x)"""
return BooleanKernel.nand(x, x)
@staticmethod
def and_(a: int, b: int) -> int:
"""AND(a,b) = NAND(NAND(a,b), NAND(a,b))"""
nand_ab = BooleanKernel.nand(a, b)
return BooleanKernel.nand(nand_ab, nand_ab)
@staticmethod
def or_(a: int, b: int) -> int:
"""OR(a,b) = NAND(NAND(a,a), NAND(b,b))"""
return BooleanKernel.nand(BooleanKernel.nand(a, a),
BooleanKernel.nand(b, b))
@staticmethod
def implies(a: int, b: int) -> int:
"""IMPLIES(a,b) = OR(NOT(a), b)"""
return BooleanKernel.or_(BooleanKernel.not_(a), b)
@staticmethod
def equal(a: int, b: int) -> int:
"""EQUAL(a,b) = AND(IMPLIES(a,b), IMPLIES(b,a))"""
return BooleanKernel.and_(BooleanKernel.implies(a, b),
BooleanKernel.implies(b, a))
# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
# VERIFICATION CONTEXT
# ๆค่จผใณใณใใญในใ | ุณูุงู ุงูุชุญูู
# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
@dataclass
class VerificationContext:
"""
Multi-lingual verification context with entropy tracking
Invariants:
- active => trusted (active agents must be trusted)
- entropy <= 0.20 (Shannon entropy bound ฯ < ฮฉ)
ไธๅคๆกไปถ:
- ใขใฏใใฃใ => ไฟก้ ผๆธใฟ
- ใจใณใใญใใผ <= 0.20
ุงูุซูุงุจุช:
- ูุดุท => ู
ูุซูู
- ุงูุฅูุชุฑูุจูุง <= 0.20
"""
agent_id: str
role: str
entropy: float = 0.0
trusted: bool = False
active: bool = False
็ถๆ
: str = "ๅๆๅ" # Japanese state
ุญุงูุฉ: str = "ู
ูููุฃ" # Arabic state
def __post_init__(self):
# Invariant: active => trusted
if self.active and not self.trusted:
raise ValueError(
"INVARIANT VIOLATION: active(agent) => trusted(agent)\n"
"ไธๅคๆกไปถ้ๅ: ใขใฏใใฃใ => ไฟก้ ผๆธใฟ\n"
"ุงูุชูุงู ุงูุซุงุจุช: ูุดุท => ู
ูุซูู"
)
# Invariant: entropy <= 0.20
if self.entropy > 0.20:
raise ValueError(
f"ENTROPY VIOLATION: {self.entropy} > 0.20\n"
f"ใจใณใใญใใผ้ๅ: {self.entropy} > 0.20\n"
f"ุงูุชูุงู ุงูุฅูุชุฑูุจูุง: {self.entropy} > 0.20"
)
# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
# DENSE ARRAY VERIFICATION ENGINE
# ๅฏ้
ๅๆค่จผใจใณใธใณ | ู
ุญุฑู ุงูุชุญูู ู
ู ุงูู
ุตูููุงุช ุงููุซููุฉ
# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
class DenseArrayVerifier:
"""
APL-inspired dense array verification with multi-lingual telemetry
Provides:
- NAND-based array transformations
- Shannon entropy constraint validation (H โค 0.20 nats)
- Cryptographic proof obligation generation
- Tri-lingual execution logging
APLใซใคใณในใใคใขใใใๅฏ้
ๅๆค่จผใจๅค่จ่ชใใฌใกใใชใผ
ุงูุชุญูู ู
ู ุงูู
ุตูููุงุช ุงููุซููุฉ ู
ุณุชูุญู ู
ู APL ู
ุน ุงูููุงุณ ู
ุชุนุฏุฏ ุงููุบุงุช
"""
def __init__(self, context: VerificationContext):
self.ctx = context
self.kernel = BooleanKernel()
self.execution_log: List[Dict] = []
self.memory_states: List[Dict] = []
self.artifact_hashes: List[str] = []
def _log(self, stage: str, data: Any, lang: str = "en"):
"""
Multi-lingual execution logging
ๅค่จ่ชๅฎ่กใญใฐ่จ้ฒ
ุชุณุฌูู ุงูุชูููุฐ ู
ุชุนุฏุฏ ุงููุบุงุช
"""
stage_translations = {
"verification": {"ja": "ๆค่จผ", "ar": "ุงูุชุญูู"},
"transform": {"ja": "ๅคๆ", "ar": "ุชุญููู"},
"proof": {"ja": "่จผๆ", "ar": "ุฅุซุจุงุช"},
"entropy_check": {"ja": "ใจใณใใญใใผ็ขบ่ช", "ar": "ูุญุต_ุงูุฅูุชุฑูุจูุง"},
"array_transform": {"ja": "้
ๅๅคๆ", "ar": "ุชุญููู_ุงูู
ุตูููุฉ"},
"constraint_validation": {"ja": "ๅถ็ดๆค่จผ", "ar": "ุงูุชุญูู_ู
ู_ุงููููุฏ"},
"proof_generation": {"ja": "่จผๆ็ๆ", "ar": "ุชูููุฏ_ุงูุฏููู"},
"transform_complete": {"ja": "ๅคๆๅฎไบ", "ar": "ุงูุชู
ุงู_ุงูุชุญููู"},
"proof_complete": {"ja": "่จผๆๅฎไบ", "ar": "ุงูุชู
ุงู_ุงูุฏููู"}
}
trans = stage_translations.get(stage, {"ja": stage, "ar": stage})
entry = {
"timestamp": time.time_ns(),
"stage": stage,
"stage_ja": trans["ja"],
"stage_ar": trans["ar"],
"data": data,
"entropy": self.ctx.entropy,
"trusted": self.ctx.trusted
}
self.execution_log.append(entry)
return entry
def _hash_state(self, state: Any) -> str:
"""
Generate deterministic hash of state
็ถๆ
ใฎๆฑบๅฎ่ซ็ใใใทใฅใ็ๆ
ุชูููุฏ ูุงุด ุญุชู
ู ููุญุงูุฉ
"""
serialized = json.dumps(state, sort_keys=True, default=str)
return hashlib.sha256(serialized.encode()).hexdigest()[:16]
def verify_entropy_constraint(self, candidates: List[float]) -> Tuple[List[float], List[bool]]:
"""
Shannon entropy constraint: H = -ฮฃ(p ln p) <= 0.20 nats
ใทใฃใใณใจใณใใญใใผๅถ็ด: H = -ฮฃ(p ln p) <= 0.20 ใใใ
ููุฏ ุฅูุชุฑูุจูุง ุดุงููู: H = -ฮฃ(p ln p) <= 0.20 ูุงุชุงุช
"""
self._log("entropy_check", {"input_candidates": candidates})
accepted = []
proofs = []
for i, c in enumerate(candidates):
# Simulate probability distribution
p = max(c, 1e-10) # Avoid log(0)
H = -p * math.log(p)
valid = H <= 0.20
accepted.append(c if valid else 0.0)
proofs.append(valid)
self._log("constraint_validation", {
"index": i,
"candidate": c,
"entropy": H,
"accepted": valid,
"ใจใณใใญใใผ": H,
"ุงูุฅูุชุฑูุจูุง": H
})
return accepted, proofs
def apl_transform(self, matrix: List[List[int]]) -> List[List[int]]:
"""
APL-style dense matrix transformation using NAND kernel
NANDใซใผใใซใไฝฟ็จใใAPLในใฟใคใซใฎๅฏ่กๅๅคๆ
ุชุญููู ุงูู
ุตูููุฉ ุงููุซููุฉ ุจุฃุณููุจ APL ุจุงุณุชุฎุฏุงู
ููุงุฉ NAND
"""
self._log("array_transform", {
"input_shape": (len(matrix), len(matrix[0]) if matrix else 0),
"้
ๅๅฝข็ถ": (len(matrix), len(matrix[0]) if matrix else 0),
"ุดูู_ุงูู
ุตูููุฉ": (len(matrix), len(matrix[0]) if matrix else 0)
})
# Transpose + NAND reduction (APL-inspired)
rows, cols = len(matrix), len(matrix[0]) if matrix else 0
result = []
for i in range(rows):
row_result = []
for j in range(cols):
# NAND-based cellular automaton step
neighbors = []
for di in [-1, 0, 1]:
for dj in [-1, 0, 1]:
ni, nj = i + di, j + dj
if 0 <= ni < rows and 0 <= nj < cols:
neighbors.append(matrix[ni][nj])
# Reduce via NAND chain
acc = neighbors[0] if neighbors else 0
for n in neighbors[1:]:
acc = self.kernel.nand(acc, n)
row_result.append(acc)
result.append(row_result)
self._log("transform_complete", {
"output_hash": self._hash_state(result),
"ๅบๅใใใทใฅ": self._hash_state(result),
"ูุงุด_ุงูุฅุฎุฑุงุฌ": self._hash_state(result)
})
return result
def generate_proof_obligation(self, transformed: List[List[int]]) -> Dict:
"""
Generate cryptographic proof obligation (Bifrost-style)
ๆๅท็่จผๆ็พฉๅใ็ๆ (Bifrostในใฟใคใซ)
ุชูููุฏ ุงูุชุฒุงู
ุงูุฅุซุจุงุช ุงูุชุดููุฑู (ุฃุณููุจ Bifrost)
"""
self._log("proof_generation", {"phase": "obligation_creation"})
# Flatten and hash
flat = [v for row in transformed for v in row]
artifact_hash = self._hash_state(flat)
# Build proof structure
proof = {
"obligation_id": f"PO-{artifact_hash[:8]}",
"schema_hash": "4b565498-9afc-4782-af4a-c6b11a5d0058", # Saint Errant audit spec
"rule_hash": self._hash_state(self.kernel.__dict__),
"transform_hash": artifact_hash,
"constraint_graph": {
"nodes": ["๐ง Input", "๐Memory", "๐Retrieval", "โTransform",
"โConstraint", "๐Proof", "๐Output"],
"edges": [
["๐ง Input", "๐Memory"],
["๐Memory", "๐Retrieval"],
["๐Retrieval", "โTransform"],
["โTransform", "โConstraint"],
["โConstraint", "๐Proof"],
["๐Proof", "๐Output"]
]
},
"validation_result": all(v == 0 or v == 1 for v in flat),
"artifact_hash": artifact_hash,
"่จผๆ็พฉๅID": f"PO-{artifact_hash[:8]}",
"ุงูุชุฒุงู
_ุงูุฅุซุจุงุช": f"PO-{artifact_hash[:8]}"
}
self.artifact_hashes.append(artifact_hash)
self._log("proof_complete", proof)
return proof
|