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Nano GraphRAG
by gusye1234
System Card
Organizationgusye1234
Released2024-07
Architecturegraph-rag / Minimal GraphRAG reference (~1100 LOC)
DetailsSmall, hackable GraphRAG clone with swappable LLMs (OpenAI/Bedrock/DeepSeek/Ollama), embeddings (SBERT/Bedrock), vector backends (hnswlib/FAISS/Milvus-lite), and graph stores (NetworkX/Neo4j). Async, fully typed.
Parameters—
Domainrag-retrievalknowledge-graph
Open SourceYes
CodeRepository
minimalhackableasync~1100-loc
Capability Profile
Benchmark Scores
6 of 14 benchmarksMulti-Turn Recall0/2
LoCoMo
no dataMemoryBank
no dataCross-Session Memory1/1
Multi-Hop QA2/3
Agent Task Memory0/1
AgentBench-Mem
no dataPersonalization0/1
PerLTQA
no dataFactuality / Grounding1/1
Sources:Nano GraphRAG (gusye1234/nano-graphrag); evaluated on HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering (Stanford / CMU, 1809)Nano GraphRAG (gusye1234/nano-graphrag); evaluated on MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries (HKUST, 2401)Nano GraphRAG (gusye1234/nano-graphrag); evaluated on RAGAS: Automated Evaluation of Retrieval-Augmented Generation (Exploding Gradients, 2309)Nano GraphRAG (gusye1234/nano-graphrag); evaluated on LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding (Tsinghua KEG, 2308)Nano GraphRAG (gusye1234/nano-graphrag); evaluated on LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory (Salesforce AI Research, 2410)Nano GraphRAG (gusye1234/nano-graphrag); evaluated on RULER: What's the Real Context Size of Your Long-Context Language Models (NVIDIA, 2404)