# neo4j/neo4j-graphrag-python

Neo4j GraphRAG for Python

Repository: https://github.com/neo4j/neo4j-graphrag-python
Canonical: https://ross.abutalabs.com/products/neo4j-graphrag-python
Homepage: https://neo4j.com/docs/neo4j-graphrag-python/current/
Language: Python
License: NOASSERTION
License Family: other
Topics: ai, cypher, genai, graph-database, neo4j, python, python3, rag, graphrag
Last push: 2026-09-03T00:22:08+00:00

## Health v2 (maintenance only)
Score: 93/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 100, release rhythm 99, longevity 65
- inputs: {"age_days": 918, "days_push": 0, "days_rel": 7, "gap_med": 20.5, "n_releases_24m": 33}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1275, forks 237 (observed 2026-09-03T02:15:15.410988+00:00)

## What it is
The official Neo4j first-party Python library for building graph retrieval-augmented generation (GraphRAG) applications. It provides retrievers (vector, hybrid, Text2Cypher), LLM and embedding provider integrations, and an experimental pipeline for building knowledge graphs from unstructured data.

## Use cases
- build a graphrag application on neo4j
- retrieve context from a knowledge graph with llm
- convert natural language questions to cypher queries
- extract entities and relations from pdfs into a knowledge graph
- combine vector search with graph traversal for retrieval
- create vector indexes and run similarity search in neo4j
- build a rag pipeline with openai or ollama over a graph database

## When to choose
- you use Neo4j as the graph store and want first-party, long-term-supported GraphRAG tooling
- you need hybrid retrieval, graph traversal enrichment, or Text2Cypher retrieval in Python
- you want an end-to-end pipeline to build knowledge graphs from unstructured documents
- you need pluggable LLM/embedding providers (OpenAI, Anthropic, Ollama, Bedrock, etc.) with a LangChain-compatible interface

## When to avoid
- your RAG stack does not involve Neo4j or graph databases
- you need a general-purpose agent framework or non-graph RAG library like LangChain or LlamaIndex
- you require a stable, non-experimental knowledge graph construction pipeline (that feature is still experimental)
- you are not using Python 3.10+ or Neo4j >= 5.18.1

## Facets
- artifact type: library
- maturity: active
- function: rag, llm-inference, agent-framework, search-engine, vector-database, nlp, database-driver, prompt-engineering
- domain: large-language-models, databases, artificial-intelligence
- platform: python, cross-platform
- tags: graphrag, neo4j, knowledge-graph, cypher, text2cypher, retrievers, kg-builder, embeddings, genai, retrieval-augmented-generation, natural-language-processing, search, data-engineering

## Member repositories
- neo4j/neo4j-graphrag-python (main) score 93

## Provenance
- Observed fields: from GitHub, fetched 2026-09-03T02:15:15.410988+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 2026-08-30T05:04:09.594278+00:00, confidence not recorded.
  - readme: https://github.com/neo4j/neo4j-graphrag-python (fetched 2026-09-03T02:15:15.410988+00:00, sha 03edff569af8)
  - homepage: https://neo4j.com/docs/neo4j-graphrag-python/current/ (fetched 2026-08-29T12:16:41.977404+00:00, sha fb44e3dc3751)
  - site_page: https://neo4j.com/docs/neo4j-graphrag-python/current/types.html (fetched 2026-08-29T12:16:42.000891+00:00, sha a3e26db2a8fa)
  - site_page: https://neo4j.com/docs/neo4j-graphrag-python/current/genindex.html (fetched 2026-08-29T12:16:42.003039+00:00, sha e12c2b527774)
  - site_page: https://neo4j.com/docs/neo4j-graphrag-python/current/user_guide_pipeline.html (fetched 2026-08-29T12:16:41.992959+00:00, sha eefac5b3fd50)
  - site_page: https://neo4j.com/docs/neo4j-graphrag-python/current/llm.html (fetched 2026-08-29T12:16:41.994884+00:00, sha febb9cb083b2)
  - site_page: https://neo4j.com/docs/neo4j-graphrag-python/current/api.html (fetched 2026-08-29T12:16:41.997087+00:00, sha 006fc2232a87)
  - site_page: https://neo4j.com/docs/neo4j-graphrag-python/current/user_guide_rag.html (fetched 2026-08-29T12:16:41.986578+00:00, sha 1077237bf4ff)
  - site_page: https://neo4j.com/docs/neo4j-graphrag-python/current/user_guide_kg_builder.html (fetched 2026-08-29T12:16:41.990144+00:00, sha 871755bd12ab)
  - site_page: https://neo4j.com/docs/neo4j-graphrag-python/current/gentree.html (fetched 2026-08-29T12:16:42.005046+00:00, sha ac7c370d46c0)
- Data as of 2026-08-30T08:39:29.467469+00:00.