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RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data.
Features
- Deep document understanding-based knowledge extraction from unstructured data with complicated formats
- Finds "needle in a data haystack" of literally unlimited tokens
- Template-based chunking
- Grounded citations with reduced hallucinations
- Compatibility with heterogeneous data sources
- Automated and effortless RAG workflow
- Streamlined RAG orchestration catered to both personal and large businesses
- Intuitive APIs for seamless integration with business
Project Samples
