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RAGFlow

RAG engine built on deep document understanding with grounded cites.

RAGFlow is an open-source RAG engine built around deep document understanding, with a focus on parsing complex, heterogeneous documents (PDFs, tables, images, scans) into structured, citation-grounded chunks. It provides templated chunking, an end-to-end pipeline from ingestion to grounded question answering with traceable references, and a web UI for managing knowledge bases. It is notable for emphasizing layout-aware document parsing to reduce hallucination in answers.

Repository

infiniflow/ragflow

Language

Python

What you'd build with it

  • Building a RAG knowledge base over messy real-world documents like contracts, reports, and scanned PDFs
  • Producing grounded answers with citations traceable back to the source document
  • Standing up a document-QA system with a UI rather than coding the ingestion and chunking pipeline

Tags

ragdocumentscitations