verbatim-rag and RAGGuard

These are complementary tools: Verbatim-RAG prevents hallucinations through grounded generation with exact citation extraction, while RAGGuard detects hallucinations post-generation through faithfulness scoring, allowing them to be used together in a defense-in-depth approach to hallucination mitigation.

verbatim-rag
63
Established
RAGGuard
22
Experimental
Maintenance 13/25
Adoption 10/25
Maturity 25/25
Community 15/25
Maintenance 13/25
Adoption 0/25
Maturity 9/25
Community 0/25
Stars: 170
Forks: 21
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars:
Forks:
Downloads:
Commits (30d): 0
Language: Python
License: MIT
No risk flags
No Package No Dependents

About verbatim-rag

KRLabsOrg/verbatim-rag

Hallucination-prevention RAG system with verbatim span extraction. Ensures all generated content is grounded in source documents with exact citations.

Implements pluggable span extractors—either LLM-based or fine-tuned ModernBERT models—to extract verbatim passages from retrieved documents rather than allowing free-form generation. The entire pipeline can run without LLMs and on CPU-only hardware using SPLADE sparse embeddings and Milvus vector storage, with both core extraction logic and a full web interface (FastAPI + React) included.

About RAGGuard

MukundaKatta/RAGGuard

RAG hallucination detection — verify LLM responses are grounded in source documents with faithfulness scoring

Related comparisons

Scores updated daily from GitHub, PyPI, and npm data. How scores work