shamspias/my-graphDB-learning-lab

Explore the realms of graph databases with Neo4j, dive into Cypher queries, and integrate LLMs for dynamic data insights with Langchain. A personal journey to master graph data.

28
/ 100
Experimental

This is a learning guide for software developers who want to understand and apply graph databases, specifically Neo4j, and integrate Large Language Models (LLMs) to enhance data insights. It starts with setting up a Neo4j database and learning Cypher queries, then progresses to using LLMs for tasks like generating queries, interpreting results, and creating data narratives. It's for developers looking to master graph data and leverage AI.

No commits in the last 6 months.

Use this if you are a developer looking for a hands-on guide to learn Neo4j, Cypher, and how to integrate LLMs for dynamic data insights from graph-structured data.

Not ideal if you are a non-technical user looking for an out-of-the-box solution to analyze graph data without writing code.

graph-database-development LLM-integration data-modeling Cypher-querying Neo4j-learning
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 8 / 25

How are scores calculated?

Stars

8

Forks

1

Language

Python

License

Last pushed

Mar 26, 2024

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/shamspias/my-graphDB-learning-lab"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.