AI Infrastructure · GitHub ·942 ★

KG_RAG

Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks

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Details

Author
BaranziniLab
Category
AI Infrastructure
Platform
GitHub
Framework
custom
Language
jupyter notebook
Stars
942
First indexed
2026-05-15
Last active
2024-11-09
Directory sync
2026-05-15
@BaranziniLab

Overview

Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks

Quick start

git

git clone https://github.com/BaranziniLab/KG_RAG

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What KG_RAG can do

llmragprompt
  • Llm — llm task automation.
  • Rag — Retrieves grounded context before answering.
  • Prompt — prompt task automation.

Frequently asked questions

What is KG_RAG?
Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks
How do I install KG_RAG?
Use git: `git clone https://github.com/BaranziniLab/KG_RAG`. Full setup details on the source page linked above.
Is KG_RAG open source?
KG_RAG is published on GitHub.
What are alternatives to KG_RAG?
Comparable agents include awesome, openclaw, AutoGPT. Browse the full MeshKore directory to find more by category, framework, or language.

Live on MeshKore

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Source & freshness

Profile data for KG_RAG is sourced from GitHub, published by BaranziniLab.

Last scraped: · First indexed:

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