ethical-guard 2.0.2

A high-performance independent alignment guardrail engine for LLMs.

🛡️ ethical-guard

ethical-guard is a hyper-performant, open-source, entirely independent AI safety guardrail package built ab initio (from scratch). Designed to completely bypass restrictive, expensive, or high-latency commercial cloud wrappers, this framework provides a lightweight client SDK and deployment architecture to evaluate user prompts locally in under 500ms (consistently optimizing within 100ms–200ms in active production clusters).

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⚡ Core Engineering Highlights

• Sub-500ms Overhead: Enforces strict context-free grammar validation constraints on token paths, eliminating heavy sequence length text generation over arbitrary response windows.
• Response-Only SFT Layer: Built around specialized token boundary gradient masks (masking prompts with target PyTorch cross-entropy labels of -100) to isolate safety mechanics directly onto categorical JSON responses.
• Secure Fail-Closed Design: Native structural design guarantees that if an upstream connection or inference cluster experiences hardware anomalies or timeouts, the client SDK overrides the crash gracefully and defaults to a highly restrictive fallback state to maintain maximum application boundary safety.

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🛡️ Target Ethical Taxonomies

The engine classifies incoming payloads into four immutable alignment and corporate compliance pillars:

1. Category 01 (Safety & Harm): Intercepts requests regarding chemical/kinetic weapon assembly scripts, physical harm coordination, or malicious digital exploitation methods.
2. Category 02 (Security Frameworks): Filters advanced adversarial prompt injections, escape sequences, and Do-Anything-Now (DAN) structural system overrides.
3. Category 03 (Fairness & Bias): Detects systemic discriminatory rhetoric, hate speech generation, or programmatic demographic biases.
4. Category 04 (Data Privacy / PII Leaks): Restricts accidental or malicious extraction of Personally Identifiable Information (PII) including SSNs, financial access tokens, and administrative database structures.

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📦 Installation

Install the production package directly from the Python Package Index (PyPI) via pip:

pip install ethical-guard