KRLabsOrg/verbatim-rag
Hallucination-prevention RAG system with verbatim span extraction. Ensures all generated content is grounded in source documents with exact citations.
Verbatim RAG helps researchers, analysts, and knowledge workers get accurate answers from large collections of documents without worrying about fabricated information. You input a question and a set of source documents (like research papers or reports), and it provides a direct answer composed of exact sentences from those documents, along with precise citations. This is ideal for anyone needing highly trustworthy, evidence-based information extraction.
170 stars. Available on PyPI.
Use this if you need to extract precise, verifiable answers directly from your documents and ensure that no generated information is made up or 'hallucinated'.
Not ideal if you need creative summaries, interpretations, or responses that synthesize information beyond direct verbatim extraction from your source material.
Stars
170
Forks
21
Language
Python
License
MIT
Category
Last pushed
Mar 10, 2026
Commits (30d)
0
Dependencies
20
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/KRLabsOrg/verbatim-rag"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Related tools
onestardao/WFGY
WFGY: open-source reasoning and debugging infrastructure for RAG and AI agents. Includes the...
iMoonLab/Hyper-RAG
"Hyper-RAG: Combating LLM Hallucinations using Hypergraph-Driven Retrieval-Augmented Generation"...
frmoretto/clarity-gate
Stop LLMs from hallucinating your guesses as facts. Clarity Gate is a verification protocol for...
project-miracl/nomiracl
NoMIRACL: A multilingual hallucination evaluation dataset to evaluate LLM robustness in RAG...
chensyCN/LogicRAG
Source code of LogicRAG at AAAI'26.