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Director-AI

Real-time LLM hallucination guardrail — NLI + RAG fact-checking with token-level streaming halt.

v3.14.0 — 5-tier scoring, 6 advanced RAG strategies, multi-agent swarm guardian, config wizard

CI Pre-commit CodeQL PyPI Downloads Tests Coverage Python Ruff mypy Sigstore License OpenSSF Best Practices OpenSSF Scorecard DOI
2-Line Integration — Wrap any LLM SDK client with guard(). Duck-type detection for OpenAI-compatible, Anthropic, Bedrock, Gemini, Cohere. Quickstart → Token-Level Halt — Catches hallucinations as they form, mid-stream, before the user sees incorrect information. Streaming →
Custom KB Grounding — Bring your own facts via RAG. ChromaDB, FAISS, Qdrant, or in-memory backends. KB Ingestion → 75.6% Balanced Accuracy on LLM-AggreFact (29K samples, 11 datasets, #6 on leaderboard; 77.76% with per-dataset tuning) — FactCG-DeBERTa-v3-Large NLI model. 14.6 ms/pair ONNX GPU. SBOM on every release. Scoring →
Injection Detection — Two-stage pipeline: regex pattern matching + bidirectional NLI intent-drift scoring. Catches injection effects in the output regardless of encoding. Per-claim attribution. Injection Detector → ProductionGuard — Batteries-included entry point: calibrated scoring, human feedback loop, conformal CIs, tool-call verification, and injection detection. Guard →
5-Tier Scoring — From zero-dep rules engine (<1ms) to embedding similarity (3ms) to full NLI (14.6ms). Choose your accuracy/latency trade-off. Scoring → SaaS-Ready — API key auth + token-bucket rate limiting middleware. Cloud Run Dockerfile included. Self-host or let us host.

Install

pip install director-ai

Quick Example

from director_ai import guard
from openai import OpenAI

client = guard(
    OpenAI(),
    facts={"refund_policy": "Refunds within 30 days only"},
    threshold=0.3,
)

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "What is the refund policy?"}],
)

If the LLM hallucinates, guard() raises HallucinationError with the coherence score and contradicting evidence.

How It Works

graph LR
    LLM["LLM Response"]:::input --> SC["CoherenceScorer"]:::core
    SC --> NLI["NLI Model<br/>(H_logical)"]:::nli
    SC --> RAG["RAG Retrieval<br/>(H_factual)"]:::rag
    NLI --> SCORE["coherence = 1 - (0.6·H_L + 0.4·H_F)"]:::core
    RAG --> SCORE
    SCORE --> GATE{score ≥ threshold?}:::gate
    GATE -->|Yes| APPROVE["Approved"]:::approve
    GATE -->|No| HALT["Halt + Evidence"]:::halt
    classDef input fill:#7c4dff,stroke:#333,color:#fff
    classDef core fill:#512da8,stroke:#333,color:#fff
    classDef nli fill:#1565c0,stroke:#333,color:#fff
    classDef rag fill:#00695c,stroke:#333,color:#fff
    classDef gate fill:#ff8f00,stroke:#333,color:#fff
    classDef approve fill:#2e7d32,stroke:#333,color:#fff
    classDef halt fill:#c62828,stroke:#333,color:#fff

Competitive Positioning

Feature Director-AI NeMo Guardrails Guardrails-AI LLM-Guard
Mid-stream halt Yes No No No
Async voice AI pipeline Yes No No No
Custom KB RAG Yes Partial No No
Token-level scoring Yes No No No
NLI contradiction detection Yes No No Partial
Evidence on rejection Yes No No No
Numeric verification Yes No No No
Agentic loop safety Yes No No No
Conformal prediction Yes No No No
EU AI Act Article 15 Yes No No No
Adversarial self-test Yes No No No
5 SDK integrations Yes 1 1 0
6 framework integrations Yes 1 1 0

Paths Forward

Path Time What You Get
Quickstart 2 min Score a response, guard an SDK client
Why Director-AI 5 min Problem statement, decision matrix, cost comparison
Tutorials 30 min 16 Jupyter notebooks from basics to production
API Reference — Every public class and function
Production Guide 15 min Scaling, caching, monitoring, Docker
Domain Cookbooks 10 min Legal, medical, finance, support recipes
Voice AI 10 min Async streaming guard + TTS adapters for voice pipelines
Glossary — 35 terms defined and cross-linked

Obtain

pip install director-ai            # base
pip install director-ai[nli]       # + NLI model (recommended)
pip install director-ai[server]    # + REST API server
pip install director-ai[nli,vector,server]       # everything

PyPI: pypi.org/project/director-ai | Source: github.com/anulum/director-ai | Docs: anulum.github.io/director-ai

Feedback & Bugs

Used By

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Contributing

See CONTRIBUTING.md for code style, test requirements, and PR workflow.

License

AGPL-3.0 for open source / research. Commercial licensing available at anulum.li.

Contact: protoscience@anulum.li | GitHub Discussions | www.anulum.li

Maintained by Miroslav Šotek at Anulum. Current release: v3.14.0.

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