ragflow and oreilly-retrieval-augmented-gen-ai
One is a comprehensive open-source RAG engine fusing RAG with Agent capabilities, while the other is a demonstration of how to augment LLMs with real-time data using RAG, Agents, and GraphRAG, making them a tool and its educational example, respectively, rather than direct competitors.
About ragflow
infiniflow/ragflow
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
This tool helps create advanced AI assistants that can accurately answer questions using your specific business documents and data. You input various documents like PDFs, Word files, web pages, and even structured data, and it outputs a system that provides precise, traceable answers. It's designed for business leaders, knowledge managers, or AI product developers who need to build reliable question-answering systems for internal teams or customers.
About oreilly-retrieval-augmented-gen-ai
sinanuozdemir/oreilly-retrieval-augmented-gen-ai
See how to augment LLMs with real-time data for dynamic, context-aware apps - Rag + Agents + GraphRAG.
This project helps AI developers build applications that can answer questions using up-to-date, external information. You'll learn how to feed real-time data into large language models (LLMs) to get more accurate and context-aware responses. It's designed for developers with Python skills and some background in machine learning and natural language processing who want to create dynamic, intelligent applications.
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