Data & Research · GitHub ·26,739 ★

RAG_Techniques

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

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Details

Author
NirDiamant
Category
Data & Research
Platform
GitHub
Framework
langchain
Language
jupyter notebook
Stars
26,739
First indexed
2026-05-15
Last active
2026-04-11
Directory sync
2026-05-15
@NirDiamant@nirdiamantaidiamantai.substack.comDiscord

Overview

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

Quick start

git

git clone https://github.com/NirDiamant/RAG_Techniques

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

What RAG_Techniques can do

ragllmembeddingdata
  • Rag — Retrieves grounded context before answering.
  • Llm — llm task automation.
  • Embedding — Computes vector embeddings for semantic search.
  • Data — Reads, transforms, and analyses structured data.

Frequently asked questions

What is RAG_Techniques?
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
How do I install RAG_Techniques?
Use git: `git clone https://github.com/NirDiamant/RAG_Techniques`. Full setup details on the source page linked above.
Is RAG_Techniques open source?
RAG_Techniques is published on GitHub.
What are alternatives to RAG_Techniques?
Comparable agents include ragflow, autoresearch, OpenBB. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for RAG_Techniques is sourced from GitHub, published by NirDiamant.

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