nano-graphrag and llm-graph-builder
Given that `nano-graphrag` provides a GraphRAG implementation and `llm-graph-builder` focuses on constructing Neo4j graphs from unstructured data using LLMs, they are complements: `llm-graph-builder` can be used to populate the knowledge graph that `nano-graphrag` then leverages for its retrieval-augmented generation.
About nano-graphrag
gusye1234/nano-graphrag
A simple, easy-to-hack GraphRAG implementation
Builds knowledge graphs from text by extracting entities and relationships, then performs retrieval-augmented generation through both global and local graph traversal modes. Supports pluggable components including multiple LLM providers (OpenAI, Bedrock, Ollama), vector databases (FAISS, Milvus, HNSWlib), and graph backends (Neo4j, NetworkX), with full async/await support and MD5-based deduplication for incremental inserts.
About llm-graph-builder
neo4j-labs/llm-graph-builder
Neo4j graph construction from unstructured data using LLMs
Supports multiple input sources (PDFs, videos, web pages, S3/GCS buckets) and 10+ LLM providers through LangChain, with configurable embedding models and vector search capabilities. Built on a FastAPI backend and React frontend, featuring conversational graph querying, token usage tracking per user, and real-time visualization in Neo4j Bloom. Deployable locally via Docker Compose, separately for development, or to Google Cloud Run with support for both cloud and local LLMs like Ollama.
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