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Tagged: GraphRAG
Choosing a RAG Architecture: Naive, Advanced, CRAG, GraphRAG, Agentic
A practical comparison of six RAG architectures with pros, cons and use cases, plus a four-step decision path and the cases where RAG is the wrong tool.
10 min readNeo4j and LangChain4j: GraphRAG Ingestors, Filtering and Chat Memory
Neo4j with LangChain4j for GraphRAG: schema discovery, LLM graph building, Cypher DSL, in-index filtering, parent-child retrieval and graph-backed chat memory.
18 min readRAG or Knowledge Graph? 2,160 Graded Answers and a Model Effect
RAG vs knowledge graph, measured: 2,160 graded answers across three model families and 120 questions. The winner flips by model, and the model matters most.
9 min readROE Versus TechRAG: GraphRAG on Docker and Qdrant or on SQLite and LanceDB
Two takes on one GraphRAG thesis: Qdrant, MongoDB and a 120B model against LanceDB, SQLite and qwen2.5 7B, with retrieval logic compared and lessons drawn.
7 min readFour Memory Strategies for AI Agents: Rolling Windows, FAISS and GraphRAG
Compare ways to give an LLM agent memory, from full history and rolling windows to inverted indexes, FAISS semantic search and a GraphRAG knowledge graph.
7 min readA Fully Local GraphRAG Pipeline With LangExtract, Neo4j, Qdrant and Ollama
Build GraphRAG on local models: extract entities with LangExtract, store them in Neo4j, index them in Qdrant, then expand subgraphs for graph-grounded answers.
39 min readSeven RAG Patterns Beyond the Basic Chatbot and When Each One Fits
A field guide to naive, hybrid, corrective, self-reflective, multi-hop, graph and contextual RAG: what gap each one closes, its components, and how to choose.
7 min readGraphRAG Community Reports: Turning a Knowledge Graph Into Answers
How GraphRAG builds a graph from text, finds communities with hierarchical Leiden, writes community reports and uses them for global and local search.
6 min readHybrid Retrieval for RAG: Combining Keyword, Vector and Graph Search
How to combine BM25, vector search and graph retrieval in RAG: rank fusion with RRF, where GraphRAG helps, and a retrieve, fuse, expand, rerank architecture.
6 min read
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