# DEEP-PolyU/Awesome-GraphRAG

Awesome-GraphRAG: A curated list of resources (surveys, papers, benchmarks, and opensource projects) on graph-based retrieval-augmented generation.

Repository: https://github.com/DEEP-PolyU/Awesome-GraphRAG
Canonical: https://ross.abutalabs.com/products/awesome-graphrag
Homepage: https://arxiv.org/abs/2501.13958
License: MIT
License Family: permissive
Topics: knowledge-graph, large-language-models, retrieval-augmented-generation, graphrag, rag, graphrag-survey, graphrag-paper
Last push: 2026-06-02T12:52:38+00:00

## Health v2 (maintenance only)
Score: 60/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 85, release rhythm 35, longevity 48
- inputs: {"age_days": 681, "days_push": 92, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2613, forks 233 (observed 2026-08-28T04:07:04.433773+00:00)

## What it is
A curated awesome-list of resources on graph-based retrieval-augmented generation (GraphRAG), organized according to the authors' survey paper 'A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models'. It catalogs surveys, papers, benchmarks, and open-source projects and is continuously updated.

## Use cases
- find papers on graph-based RAG
- learn about GraphRAG techniques
- find GraphRAG benchmarks and datasets
- survey knowledge-graph-enhanced LLM retrieval methods
- keep up with new GraphRAG research
- find open-source GraphRAG implementations

## When to choose
- you are researching GraphRAG and want a structured reading list
- you need benchmarks or datasets for evaluating GraphRAG systems
- you want a taxonomy of graph-based RAG approaches tied to a peer survey

## When to avoid
- you need a ready-to-run GraphRAG library or framework rather than a resource list
- you want non-graph, plain vector RAG resources
- you expect maintained software with releases and support

## Facets
- artifact type: learning-resource
- maturity: active
- function: rag, search-engine, documentation
- domain: large-language-models, artificial-intelligence, tutorials, awesome-lists
- platform: -
- tags: graphrag, knowledge-graph, survey, curated-list, papers, benchmarks, retrieval-augmented-generation, web-server

## Member repositories
- DEEP-PolyU/Awesome-GraphRAG (main) score 60

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:04.433773+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:20:37.925881+00:00, confidence not recorded.
  - readme: https://github.com/DEEP-PolyU/Awesome-GraphRAG (fetched 2026-08-28T04:07:04.433773+00:00, sha 8a3247699944)
  - homepage: https://arxiv.org/abs/2501.13958 (fetched 2026-08-29T10:03:53.414808+00:00, sha c9e8c81fc0fb)
  - site_page: https://info.arxiv.org/about/donate.html (fetched 2026-08-29T10:03:53.424000+00:00, sha cca9c3a11c56)
  - site_page: https://info.arxiv.org/about/ourmembers.html (fetched 2026-08-29T10:03:53.427335+00:00, sha 47cbc55ff1de)
  - site_page: https://info.arxiv.org/about (fetched 2026-08-29T10:03:53.429190+00:00, sha a1f16f915a9a)
  - site_page: https://info.arxiv.org/labs/index.html (fetched 2026-08-29T10:03:53.425742+00:00, sha b14a8d05a0ec)
- Data as of 2026-08-30T08:39:29.467469+00:00.