Hallucination Python Packages

nkama-fact-benchmark

Evidence-gated benchmark for testing whether AI assistants can prove what they claim

uqlm

UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination detection

openfactverification-kongzii

Loki: An Open-source Tool for Fact Verification

fathom-rules

Deterministic reasoning runtime for AI agents. YAML rules, microsecond evaluation, zero hallucinations. Built on CLIPS.

antemortem

Make your AI coding agent prove every claim with a file:line citation, then machine-check each one offline. A verified-citation gate (CLI + MCP server + GitHub Action) that catches LLM hallucinations before merge.

wauldo

Official Python SDK for Wauldo — verified AI answers with zero hallucinations. pip install wauldo

qwed

A deterministic verification layer for AI systems. QWED verifies AI outputs using mathematics, symbolic reasoning, and formal methods (Z3, SMT, SymPy), creating an auditable trust boundary for agentic AI. Not generation. Verification.

dingo-python

Dingo: A Comprehensive AI Data, Model and Application Quality Evaluation Tool

groundguard

Verify LLM output against your source documents. Catch hallucinations in RAG pipelines and agentic workflows before they reach users.

grounded-reasoning

Zero-token, precision-guaranteed relation-algebra verifier for LLM/agent multi-hop reasoning

pope-audit

Companion code and data for: Token-Set Choice Confounds POPE: A Systematic Audit of Yes/No Extraction in VLM Hallucination Evaluation (2026)

fastmemory

FastMemory is a topological representation of text data using concepts as the primary input. It helps in improving the RAG(by replacing embedding and vectors entirely), AI memory and LLM queries by upto 100% as in the huggingface benchmarks(22+ SOTA)

ai-trust-validator

Validate AI-generated code for security vulnerabilities, hallucinations, and logic errors

jingu-trust-gate

A deterministic trust gate for LLM systems

ishvacerto

Prove AI-written code, refute it with the exact failing input, or honestly abstain. Never guesses. Runs locally.

llm-testlab

Comprehensive testing suite for LLM evaluation: hallucination detection, consistency, robustness, safety, and multi-language code generation assessment.

evidence-gate-py

Stop your AI from making up facts about your own data. A pre-generation grounding gate for LLM/RAG apps — zero-dep, MIT, JS + Python, with an MCP server.

orca-verify

Your agent proposes. Orca verifies. You decide. A drop-in verification layer for LLM/agent outputs.

pkgguard-cli

Vet the packages and repos your AI assistant recommended — before you install. Catches hallucinated/slopsquatted names, malware signals, license traps, dead repos, and fake-star inflation.

hallx

Lightweight, model-agnostic hallucination risk Analysis Library for LLM outputs

hdm2

A tool for detecting and quantifying hallucinations in LLM responses through context and common knowledge verification

glassbox-framework

Glass Box Framework — runtime constitutional verification for AI answers. Trust Cards with claim-level reasoning chains, formal ECS scoring, the 7-angle Glassbox Court red team, and deterministic audit logs. MCP-native.

phase-slip-sampler

Phase-Slip is a stochastic intervention architecture that operates on the Key-Value Cache of the model. Phase-Slip gently rotates the semantic vectors of the context window, asking the model: "How would you finish this sentence if you looked at it from a slightly different perspective?"

cgd-validator

Validator for Clarity-Gated Document (.cgd) files - verified documents for safe LLM ingestion