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- Welcome - GraphRAG
Microsoft Research’s new approach, GraphRAG, creates a knowledge graph based on an input corpus This graph, along with community summaries and graph machine learning outputs, are used to augment prompts at query time
- GitHub - microsoft graphrag: A modular graph-based Retrieval-Augmented . . .
The GraphRAG project is a data pipeline and transformation suite that is designed to extract meaningful, structured data from unstructured text using the power of LLMs
- GraphRAG with a Knowledge Graph
Design patterns for improving GenAI applications with a graph
- Retrieval-Augmented Generation with Graphs (GraphRAG)
Following this motivation, we present a comprehensive and up-to-date survey on GraphRAG Our survey first proposes a holistic GraphRAG framework by defining its key components, including query processor, retriever, organizer, generator, and data source
- Project GraphRAG - Microsoft Research
GraphRAG (Graphs + Retrieval Augmented Generation) is a technique for richly understanding text datasets by combining text extraction, network analysis, and LLM prompting and summarization into a single end-to-end system
- Everything You Ever Wanted to Know About GraphRAG - Medium
GraphRAG revolutionises domain-specific LLM applications by leveraging structured knowledge to organise and retrieve information, enhancing performance and reliability It can be formally defined
- What is GraphRAG? - GeeksforGeeks
GraphRAG stands apart from traditional RAG models by applying structured knowledge graph data for both retrieval and generation tasks The system produces more contextually accurate responses by utilizing interconnected information instead of separate data points as its source
- What is GraphRAG? - IBM
GraphRAG is an advanced version of retrieval-augmented generation (RAG) that incorporates graph-structured data, such as knowledge graphs (KGs)
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