Home Projects GraphRAG-SDK
GraphRAG-SDK
Python

GraphRAG-SDK

Build fast and accurate GenAI apps with GraphRAG SDK at scale 🌟

by FalkorDB · GitHub
Stars
Forks
License
Created
Last commit
Category
Language
falkordbgenaigraph-databaseApache-2.0Python
View on GitHub
In plain words

Create applications that retrieve and summarize information from documents quickly and accurately.

You maintain this project?

Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.

Claim this page →
GraphRAG-SDK — GitHub preview card
📈 Star history
972971
2026-07-202026-08-31
📈 Track GraphRAG-SDK

Get an email alert on its next release or when it starts trending — never miss the moment.

Free · no card · unsubscribe anytime
Get email alerts →
📄 About

Build fast and accurate GenAI apps with GraphRAG SDK at scale 🌟

GraphRAG-SDK has 971 stars on GitHub. It has been forked 135 times. GraphRAG-SDK is written mainly in Python. It has been in active development since 2024. GraphRAG-SDK is available under the Apache-2.0 license. Its main topics are falkordb, genai, graph-database, graphrag.

Frequently asked questions

What is GraphRAG-SDK?

Build fast and accurate GenAI apps with GraphRAG SDK at scale 🌟

Is GraphRAG-SDK open source?

GraphRAG-SDK is an open-source project. It is released under the Apache-2.0 license.

Is GraphRAG-SDK free?

Yes. GraphRAG-SDK is free and open source — you can use, modify and self-host it.

What license does GraphRAG-SDK use?

GraphRAG-SDK is available under the Apache-2.0 license.

What language is GraphRAG-SDK written in?

GraphRAG-SDK is written mainly in Python.

🏅 Maintainer of this project?
olud.ai badge — GraphRAG-SDK

Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.

[![olud.ai](https://olud.ai/badge.php?tool=falkordb-graphrag-sdk)](https://olud.ai/project/falkordb-graphrag-sdk.html)
More badge options →
🧬 Shares DNA with🧬 View the DNA map →

Measured from GitHub topics shared by both projects, weighted by how rare each topic is.