Introduce the brand new ipython-ngql python package that enhances your ability to connect to NebulaGraph from your Jupyter Notebook or iPython. Now we can do%ngql MATCH p=(n:player)->() RETURN p to query from Jupyter Notebook and %ng_draw to render the result.

How Graph could help build better In-context Learning LLM Applications.

Introducing a new project! ng_ai: NebulaGraph’s graph algorithm suite, a user-friendly high-level Python Algorithm API for NebulaGraph. Its goal is to enable data scientist users of NebulaGraph to perform graph-related algorithmic tasks with minimal code.

How NebulaGraph helps build social network systems.

An attempt to use ChatGPT to generate code for a data scraper to predict sports events with the help of the NebulaGraph graph database and graph algorithms.

This post was initially published in https://www.nebula-graph.io/posts/predict-fifa-world-cup-with-chatgpt-and-nebulagraph

How could we model data in Tabular sources and ETL it to NebulaGraph? This article demonstrates an end-to-end example of doing so with dbt.

This is a review of Fraud Detection methods based on graph algorithms, graph databases, machine learning, and graph neural networks on NebulaGraph, and in addition to an introduction to the basic methodological ideas, I’ve also got a Playground you can run. it’s worth mentioning that this is the first time I’ve introduced you to the Nebula-DGL project 😁.