Hallucination Python Packages

qwed

Open-source AI verification infrastructure for deterministic verification of LLM outputs, tool calls, code, schemas, and agent state before production execution.

living-memory-model

A verifiable memory layer for language models — facts in a graph, every claim with its source.

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)

reverify

Stop your AI from making things up — it proposes, deterministic tools decide, every claim checked against ground truth with evidence. Grounded facts and context survive resets. Reverse engineering is the proving ground. MCP server + CLI.

aiexpect

Assertions for non-deterministic AI text. Drop into pytest, get a Trust Score + HTML report. Free-first: rules, local embeddings, then your own LLM judge.

figured

Show your work: verify that every number in an LLM-generated answer traces to the rows it was derived from. Zero dependencies.

uqlm

[JMLR 2026] UQLM: A Python package for LLM hallucination detection using uncertainty quantification

ghostpkg

Catch AI-hallucinated package names before you install them

sooth

Claim-by-claim fact-checking for AI output, designed for CI. PASS/FAIL/REVIEW with calibrated probabilities and source evidence.

groundline

Verifiable AI agent for engine test data: every number in the report traces back to a reproducible computation.

halu

Python SDK for Komplex AI — a hallucination detector for LLM output. Score any response for hallucination risk in one call. Includes an MCP server.

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.

dingo-python

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

scholarcheck

Stop hallucinated citations - verify any reference against real metadata. Zero dependencies.

fathom-rules

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

grounded-reasoning

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

nkama-fact-benchmark

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

grounding-gate

Zero-token structural verifier for agent loops: one choke point at the submit boundary, no LLM calls, no dependencies

ancora-rag

Grounded answers, or an honest escalation. A dependency-free hallucination gate for RAG chatbots — rejects invented numbers, not just low similarity.

resultseal

Deterministic observation-integrity contracts for AI-agent tool results. HTTP 200 is not an observation.

strata-bench

STRATA-Bench: Spatial-Temporal Retrieval, Alignment, Transparency & Audit — a benchmark for AI agents on fragmented geographic and longitudinal market intelligence.

replysignal

Catch broken LLM generations in production, without ground-truth labels or an LLM judge.

refproof

Catch fake, wrong and retracted references in your paper. Checks BibTeX, LaTeX, Word and pasted reference lists against Crossref, arXiv and OpenAlex. CLI, browser app and GitHub Action.

onus

A claim checker: verifies a document's claims against its evidence, numbers deterministically