The Leanpub 60 Day 100% Happiness Guarantee
Within 60 days of purchase you can get a 100% refund on any Leanpub purchase, in two clicks.
See full terms...
Programming Knowledge Graphs with Python
Model, Build, and Query AI-Ready Knowledge with Cypher, Neo4j, and AI Agents
This book is 100% completeLast updated on 2026-10-28
We'll start with nodes, relationships and Cypher, as it'll make everything else easier later on. Then, we design a schema, chunk documents, extract entities and add embeddings. Then, we'll mix vectors with structure, run graph algorithms, think about rules and ontologies, and connect AI agents through safe, traceable tools. We'll also keep the graph fresh, measured and recoverable, because if it's stale, users won't trust it.
Minimum price
$29.99
$29.99
You pay
Author earns
PDF
EPUB
About
About the Book
Get practical hands-on to build your own knowledge graph, and use it across retrieval, analytics and agents
LLMs sound confident, but they forget context, invent facts and can't show their reasoning. A knowledge graph gives them structured, traceable facts to work from. What you'll do in this book is grow a single Neo4j graph from the Python Enhancement Proposals, which are the documents that shaped the language. It starts with getting to grips with nodes and relationships and writing Cypher like a pro. Then you design a schema in Pydantic, chunk documents into a lexical graph and extract entities with spaCy and local LLMs. Then, you add vector embeddings and indexes, and combine full-text search, vector search and graph traversal into GraphRAG retrieval that cites its sources.
The rest of the book goes into more detail. You can rank and cluster nodes with Graph Data Science, infer new facts with rules, import ontologies and validate data with SHACL. You also give LangGraph agents guarded Cypher tools, serve the graph over MCP, store agent memory with Graphiti and trace every decision. At the end of the day, you keep the graph healthy with regular refreshes, time-bound facts, evaluation runs, query tuning and backups.
Key Learnings
- Write expressive, parameterized Cypher queries from Python.
- Design graph schemas with Pydantic, constraints and indexes.
- Chunk documents into lexical graphs with batched ingestion pipelines.
- Extract entities and relationships using spaCy rules and schema-guided local LLMs.
- Store embeddings in Neo4j and query them through vector indexes and similarity metrics.
- Build GraphRAG retrievers for full-text, vector search and subgraph expansion.
- Rank, cluster and predict links with PageRank, Leiden and GDS pipelines.
- Infer facts with Cypher rules, SKOS ontologies and SHACL shape validation.
- Connect LangGraph agents to graphs through guarded Cypher tools, MCP and Graphiti memory.
- Operate graphs with incremental refreshes, temporal facts, evaluation runs, tuning and backups.
Table of Content
- Thinking in Nodes and Relationships
- Writing Cypher with Confidence
- Designing Graph Schema
- Preparing Data and Chunks
- Extracting Entities and Relationships
- Structuring Embeddings in Graphs
- Retrieving with Vectors and Structure
- Analyzing Graph Structure
- Reasoning Symbolically over Knowledge
- Connecting AI Agents to Graphs
- Keeping Knowledge Graphs Healthy
Author
About the Author
GitforGits | Asian Publishing House
We are the engineer’s publisher, the coder’s mentor, and the content alchemist—meticulously turning dense tech into practical gold. With a growing library of 100+ titles, we don’t just develop technical books, rather we build roadmaps for professionals across Python, MySQL, DevOps, Rust, AI, Kotlin, Arduino, Golang and everything around the massive IT ecosystem. Every chapter, every script, every project is a tool in the hands of developers who want to get things done.
Where others summarize, we construct step-by-step learning blueprints, cutting through clutter, banning the fluff, and ensuring every paragraph delivers hands-on value. Our audience isn’t learning from scratch—they’re leveling up with purpose, and we stand by them with code-first content, consistent project workflows, and a zero-redundancy approach.
Earn $8 on a $10 Purchase, and $16 on a $20 Purchase
We pay 80% royalties on purchases of $7.99 or more, and 80% royalties minus a 50 cent flat fee on purchases between $0.99 and $7.98. You earn $8 on a $10 sale, and $16 on a $20 sale. So, if we sell 5000 non-refunded copies of your book for $20, you'll earn $80,000.
(Yes, some authors have already earned much more than that on Leanpub.)
Learn more about writing on Leanpub
Free Updates. DRM Free.
If you buy a Leanpub book, you get free updates for as long as the author updates the book! Many authors use Leanpub to publish their books in-progress, while they are writing them. All readers get free updates, regardless of when they bought the book or how much they paid (including free).
Most Leanpub books are available in PDF (for computers) and EPUB (for phones, tablets and Kindle). The formats that a book includes are shown at the top right corner of this page.
Finally, Leanpub books don't have any DRM copy-protection nonsense, so you can easily read them on any supported device.
Learn more about Leanpub's ebook formats and where to read them
Write and Publish on Leanpub
You can use Leanpub to easily write, publish and sell in-progress and completed ebooks and online courses!
Leanpub is a powerful platform for serious authors, combining a simple, elegant writing and publishing workflow with a store focused on selling in-progress ebooks.
Leanpub is a magical typewriter for authors: just write in plain text, and to publish your ebook, just click a button. (Or, if you are producing your ebook your own way, you can even upload your own PDF and/or EPUB files and then publish with one click!) It really is that easy.