This Week in Neo4j: Podcast, Knowledge Graph, text2cypher, Python and more

Welcome to This Week in Neo4j, your weekly fix for news from the world of graph databases!
This week, we have our monthly Podcast with Oleg Šelajev – Neo4j Ninja and speaker at NODES. Additionally, we look at an Open Source Knowledge Graph schema library, learn how to convert text to Cypher and build a chatbot with LangChain.

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I hope you enjoy this issue,
Alexander Erdl


Gary has a B.S., M.S., and Ph.D. in electrical engineering and an M.S. in mathematics. He spent several years working for federal IT contractors designing solutions and writing technical and management proposals and now leads software development teams.
Connect with him on LinkedIn.

Gary is a Neo4j Ninja and one of the most active members of the Community Forum, where he created almost 3k posts receiving over 5k cheers.

Gary Lilienfield
PODCAST: Docker, AI, and More: Catch a Glimpse of the Java Ecosystem with Oleg Šelajev
In the July episode of our Podcast, we discuss Testcontainers and AI in the Java ecosystem. This month’s guest is Oleg Šelajev, developer advocate at Docker, who is working mainly on developer productivity, Testcontainers, and improving how we set up local development environments and tests.
KNOWLEDGE GRAPH: Introducing WhyHow.AI Open-Source Knowledge Graph Schema Library — Start Experimenting Faster
Chia Jeng Yang introduces WhyHow.AI’s Open Source Knowledge Graph schema library. Within this schema library, you can discover a range of schemas created for various use cases in different domains, ranging from Finance to Healthcare, Manufacturing, Meeting Transcripts, and many others. You should get the most value by using the library to brainstorm and ideate the types of schemas relevant to your exact use case and industry.
TEXT2CYPHER: Convert Text to Neo4J Cypher Using LLM – Install Locally
This video by Fahd Mirza shows a step-by-step process to install the text2cypher model locally. This is based on Tomaz Bratanic’s finetuned Llama3-Instruct:8b to generate Neo4j Cypher statements based on the GPT-4o synthetic dataset.
PYTHON: Build an LLM RAG Chatbot With LangChain/
In this tutorial by Harrison Hoffman, you’ll step into the shoes of an AI engineer working for a large hospital system. You’ll build a RAG chatbot in LangChain that uses Neo4j to retrieve data about the patients, patient experiences, hospital locations, visits, insurance payers, and physicians in your hospital system.

POST OF THE WEEK: Purring Lync

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