The Truth-Locked Architecture: SDK for Constitutive Governance and Statistical Integrity.
Project description
Arqon Anchor (v0.5.0) - Production
Status: PRODUCTION / SOTA
Latency: 77µs (Memory) / 11ms (Process)
Integrity: 100% (Zero False Positives in Benchmarks)
The Arqon Anchor is a hardware-enforced verification engine for Large Language Models. It eliminates hallucination by forcing every claim to be backed by an executable "Witness Program" that runs in a Hardware Vault before the output is released.
📚 The Library of Truth
- The Theory: Whitepaper | Runtime Substrate
- The Manuals: Direct Runtime Manual | Witness Authoring
- The Benchmarks:
ArqonCore/benchmark_direct.py
🏛️ Features
Layer 1: Semantic Enforcement
- GovernanceSentinel (Sandbox): Enforces CPU and filesystem isolation.
- EvidenceGuard (Auditor): Links logical conclusions to verifiable evidence.
Layer 2: Statistical Integrity
- Adversarial Forge (Canary): Detects telepathic state leakage.
- Rarity Engine (Hypothesis E): Blocks rote memorization and disjoint reasoning via Information-Theoretic Rarity (NCD).
Layer 3: Hardware Veto
- OpaqueTunnel (Hypothesis D): Simulates hardware-locked memory to prevent optimizer peeking.
- FormalVerifier (Hypothesis G): Interface for symbolic logic proofs of state separation.
📦 Installation
pip install arqon-anchor
🚀 Usage
from anchor import run_audit
# Verify an LLM output
result = run_audit(llm_output, context="My Context", mode="omega", rarity_check=True)
if result["verified"]:
print("✅ Truth-Locked Conclusion")
else:
print(f"❌ Rejected: {result['error']}")
🛡️ License
MIT
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