A free Graph / RAG system that works with real data
Iโve tested countless Retrieval-Augmented Generation (RAG) systems, and they all failed to meet my expectations. I found a simple two-stepโฆ
Flexible-GraphRAG
๐๐น๐ฒ๐
๐ถ๐ฏ๐น๐ฒ ๐๐ฟ๐ฎ๐ฝ๐ต๐ฅ๐๐ ๐ผ๐ฟ ๐ฅ๐๐ is now flexing to the max using LlamaIndex, supports ๐ณ ๐ด๐ฟ๐ฎ๐ฝ๐ต ๐ฑ๐ฎ๐๐ฎ๐ฏ๐ฎ๐๐ฒ๐, ๐ญ๐ฌ ๐๐ฒ๐ฐ๐๐ผ๐ฟ ๐ฑ๐ฎ๐๐ฎ๐ฏ๐ฎ๐๐ฒ๐, ๐ญ๐ฏ ๐ฑ๐ฎ๐๐ฎ ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐,
๐๐๐ ๐, Docling ๐ฑ๐ผ๐ฐ ๐ฝ๐ฟ๐ผ๐ฐ๐ฒ๐๐๐ถ๐ป๐ด, ๐ฎ๐๐๐ผ ๐ฐ๐ฟ๐ฒ๐ฎ๐๐ฒ ๐๐๐, ๐๐ฟ๐ฎ๐ฝ๐ต๐ฅ๐๐, ๐๐๐ฏ๐ฟ๐ถ๐ฑ ๐ฆ๐ฒ๐ฎ๐ฟ๐ฐ๐ต, ๐๐ ๐๐ต๐ฎ๐ (shown Hyland products web page data src) ๐๐ฝ๐ฎ๐ฐ๐ต๐ฒ ๐ฎ.๐ฌ ๐ข๐ฝ๐ฒ๐ป ๐ฆ๐ผ๐๐ฟ๐ฐ๐ฒ
๐๐ฟ๐ฎ๐ฝ๐ต: Neo4j ArcadeDB FalkorDB Kuzu NebulaGraph, powered by Vesoft (coming Memgraph and ๐๐บ๐ฎ๐๐ผ๐ป ๐ก๐ฒ๐ฝ๐๐๐ป๐ฒ)
๐ฉ๐ฒ๐ฐ๐๐ผ๐ฟ: Qdrant, Elastic, OpenSearch Project, Neo4j ๐๐ฒ๐ฐ๐๐ผ๐ฟ, Milvus, created by Zilliz (coming Weaviate, Chroma, Pinecone, ๐ฃ๐ผ๐๐๐ด๐ฟ๐ฒ๐ฆ๐ค๐ + ๐ฝ๐ด๐๐ฒ๐ฐ๐๐ผ๐ฟ, LanceDB)
Docling ๐ฑ๐ผ๐ฐ๐๐บ๐ฒ๐ป๐ ๐ฝ๐ฟ๐ผ๐ฐ๐ฒ๐๐๐ถ๐ป๐ด
๐๐ฎ๐๐ฎ ๐ฆ๐ผ๐๐ฟ๐ฐ๐ฒ๐: using LlamaIndex readers: working: Web Pages, Wikipedia, Youtube, untested: Google Drive, Msft OneDrive, S3, Azure Blob, GCS, Box, SharePoint, previous: filesystem, Alfresco, CMIS.
๐๐๐ ๐: ๐๐น๐ฎ๐บ๐ฎ๐๐ป๐ฑ๐ฒ๐
๐๐๐ ๐ (OpenAI, Ollama, Claude, Gemini, etc.)
๐ฅ๐ฒ๐ฎ๐ฐ๐, ๐ฉ๐๐ฒ, ๐๐ป๐ด๐๐น๐ฎ๐ฟ ๐จ๐๐, ๐ ๐๐ฃ ๐๐ฒ๐ฟ๐๐ฒ๐ฟ, ๐๐ฎ๐๐๐๐ฃ๐ ๐๐ฒ๐ฟ๐๐ฒ๐ฟ
๐๐ถ๐๐๐๐ฏ ๐๐๐ฒ๐๐ฒ๐ฟ๐ฒ๐ถ๐ป๐ฒ๐ฟ/๐ณ๐น๐ฒ๐
๐ถ๐ฏ๐น๐ฒ-๐ด๐ฟ๐ฎ๐ฝ๐ต๐ฟ๐ฎ๐ด:
https://lnkd.in/eUEeF2cN
๐ซ.๐ฐ๐ผ๐บ ๐ฃ๐ผ๐๐ ๐ผ๐ป ๐๐น๐ฒ๐
๐ถ๐ฏ๐น๐ฒ ๐๐ฟ๐ฎ๐ฝ๐ต๐ฅ๐๐ ๐ผ๐ฟ ๐ฅ๐๐ ๐บ๐ฎ๐
๐ณ๐น๐ฒ๐
๐ถ๐ป๐ด
https://lnkd.in/gHpTupAr
๐๐ป๐๐ฒ๐ด๐ฟ๐ฎ๐๐ฒ๐ฑ ๐ฆ๐ฒ๐บ๐ฎ๐ป๐๐ถ๐ฐ๐ ๐๐น๐ผ๐ด:
https://lnkd.in/ehpjTV7d
A gentle introduction to DSPy for graph data enrichment | Kuzu
๐ข Check out our latest blog post by Prashanth Rao, where we introduce the DSPy framework to help you build composable pipelines with LLMs and graphs. In the post, we dive into a fascinating dataset of Nobel laureates and their mentorship networks for a data enrichment task. ๐๐ฝ
โ The source data that contains the tree structures is enriched with data from the official Nobel Prize API.
โ We showcase a 2-step methodology that combines the benefits of Kuzu's vector search capabilities with DSPy's powerful primitives to build an LLM-as-a-judge pipeline that help disambiguate entities in the data.
โ The DSPy approach is scalable, low-cost and efficient, and is flexible enough to apply to a wide variety of domains and use cases.
A Graph-Native Workflow Application using Neo4j/Cypher | Medium
A full working Cypher script that simulates a Tendering System with multiple workflows, AI agent interactions, conversations, approvals, and more โ all modeled and executed natively in a Graph.
GraphRAG infrastructure for generative AI using Vertex AI and Spanner Graph | Cloud Architecture Center | Google Cloud
Design infrastructure for a generative AI application with GraphRAG using Spanner Graph.
The Developer's Guide to GraphRAG
Find out how to combine a knowledge graph with RAG for GraphRAG. Provide more complete GenAI outputs.
Youโve built a RAG system and grounded it in your own data. Then you ask a complex question that needs to draw from multiple sources. Your heart sinks when the answers you get are vague or plain wrong.ย ย
How could this happen?
Traditional vector-only RAG bases its outputs on just the words you use in your prompt. It misses out on valuable context because it pulls from different documents and data structures. Basically, it misses out on the bigger, more connected picture.
Your AI needs a mental model of your data with all its context and nuances. A knowledge graph provides just that by mapping your data as connected entities and relationships. Pair it with RAG to create a GraphRAG architecture to feed your LLM information about dependencies, sequences, hierarchies, and deeper meaning.
Check out The Developerโs Guide to GraphRAG. Youโll learn how to:
Prepare a knowledge graph for GraphRAG
Combine a knowledge graph with native vector search
Implement three GraphRAG retrieval patterns
Want to explore the Anthropic Transformer-Circuit's as a queryable graph?
Want to explore the Anthropic Transformer-Circuit's as a queryable graph?
Wrote a script to import the graph json into Neo4j - code in Gist.
https://lnkd.in/eT4NjQgY
https://lnkd.in/e38TfQpF
Next step - write directly from the circuit-tracer library to the graph db.
https://lnkd.in/eVU_t6mS
Want to explore the Anthropic Transformer-Circuit's as a queryable graph?
Announcing general availability of Amazon Bedrock Knowledge Bases GraphRAG with Amazon Neptune Analytics | Amazon Web Services
Today, Amazon Web Services (AWS) announced the general availability of Amazon Bedrock Knowledge Bases GraphRAG (GraphRAG), a capability in Amazon Bedrock Knowledge Bases that enhances Retrieval-Augmented Generation (RAG) with graph data in Amazon Neptune Analytics. In this post, we discuss the benefits of GraphRAG and how to get started with it in Amazon Bedrock Knowledge Bases.
Why GraphRAG Feels Hard (and What I Learned Trying to Make It Work)
Integrating Neo4j, DuckDB, and Kestra for Metadata-Driven Graph Design
Graphiti: Knowledge Graph Memory for a Post-RAG Agentic World
An open-source Python framework for real-time, graph-based knowledge in Neo4j
Google Cloud & Neo4j: Teaming Up at the Intersection of Knowledge Graphs, Agents, MCP, and Natural Language Interfaces - Graph Database & Analytics
Weโre thrilled to announce new Text2Cypher models and Googleโs MCP Toolbox for Databases from the collaboration between Google Cloud and Neo4j.
Everything a Developer Needs to Know About the Model Context Protocol (MCP) - Graph Database & Analytics
The Model Context Protocol gives users a wide range of services they can connect to from the comfort of their AI client.
Using Spanner Graph with LangChain for GraphRAG | Google Cloud Blog
Learn how to use Spanner Graph with LangChain workflows to build advanced, relationship-aware RAG systems, a.k.a. GraphRAG.
Talk To Your Graph 2.0 - A Partnerโs View
Read about how our partners from Semantic Partners explore the latest iteration of the GraphDB's Talk To Your Graph feature
Build your hybrid-Graph for RAG & GraphRAG applications using the power of NLP | LinkedIn
Build a graph for RAG application for a price of a chocolate bar! What is GraphRAG for you? What is GraphRAG? What does GraphRAG mean from your perspective? What if you could have a standard RAG and a GraphRAG as a combi-package, with just a query switch? The fact is, there is no concrete, universal
Introduction to the Neo4j LLM Knowledge Graph Builder
Bridge the gap and unlock hidden potential within your unstructured data
LLM Knowledge Graph Builder โ First Release of 2025
New features include community summaries, local and global retrievers, running retrievers in parallel, and custom prompt instructions.
Should you be using GraphRAG?
When (not) to use GraphRAG
Introduction to the Neo4j LLM Knowledge Graph Builder
Explore its functionality and how it leverages the power of LLMs and Neo4j graph databases to improve data analysis and knowledge discovery.
Chatting with your knowledge graph
Enabling an LLM to chat directly with structured graph data
Multimodal Graph RAG (mmGraphRAG): Incorporating Vision in Search and Analytics - Enterprise Knowledge
David Hughes presented โUnleashing the Power of Multimodal GraphRAG: Integrating Image Features for Deeper Insightsโ at Data Day Texas 2025.
GraphRAG interview โ Alonso
As technology advances, large language models (LLMs) and information retrieval/management methods evolve at breakneck speed. Knowledgeโฆ
LangGraph AI Agents with Neo4j Knowledge Graph
A RAG System Built for Both Semantic Search and Structured Data Queries
Introducing the Neo4j Text2Cypher (2024) Dataset
Authors: Makbule Gulcin Ozsoy, Leila Messallem, Jon Besga
Building Knowledge Graphs with LLM Graph Transformer
A deep dive into LangChainโs implementation of graph construction with LLMs
Microsoft GraphRAG with an RDF Knowledge Graph โ Part 3
Using SPARQL and the Knowledge Graph for RAG
loading Microsoft Research GraphRAG data into Neo4j
Many people have asked about loading Microsoft Research #GraphRAG data into Neo4j. I wrote a quick notebook last night to import Documents, Chunks (TextUnit)โฆ | 27 comments on LinkedIn
loading Microsoft Research hashtag#GraphRAG data into Neo4j
This notebook converts CSV data into a Neo4j Graph Database
This notebook converts CSV data into a Neo4j Graph Database. All you do is describe your data. Have you wanted to see what your data looked like as a graphโฆ
Graph Data Models for RAG Applications
When to use graph data models, such as parent-child, question-based, and topic-summary, for RAG applications powered by knowledge graphs.