---
title: "RAG_Techniques"
type: "tool"
slug: "nirdiamant-rag-techniques"
canonical_url: "https://www.graphcanon.com/tools/nirdiamant-rag-techniques"
github_url: "https://github.com/NirDiamant/RAG_Techniques"
homepage_url: "https://amzn.to/4cvxqSw"
stars: 28402
forks: 3452
primary_language: "Jupyter Notebook"
license: "Other"
categories: ["data-retrieval", "llm-frameworks"]
tags: ["llms", "vector-database", "nlp", "machine-learning", "semantic-search", "retrieval-augmented-generation", "gpt", "langchain"]
updated_at: "2026-07-07T19:42:33.963284+00:00"
---

# RAG_Techniques

> Repository showcasing advanced techniques for Retrieval-Augmented Generation (RAG) systems.

This repository contains tutorials and runnable notebooks that cover a range of RAG techniques, from foundational concepts to cutting-edge methods. It aims to provide detailed insights into building more accurate and context-rich retrieval systems.

## Facts

- Repository: https://github.com/NirDiamant/RAG_Techniques
- Homepage: https://amzn.to/4cvxqSw
- Stars: 28,402 · Forks: 3,452 · Open issues: 16 · Watchers: 253
- Primary language: Jupyter Notebook
- License: Other
- Last pushed: 2026-07-04T12:53:20+00:00

## Categories

- [Data & Retrieval](/categories/data-retrieval.md)
- [LLM Frameworks](/categories/llm-frameworks.md)

## Tags

llms, vector-database, nlp, machine-learning, semantic search, retrieval-augmented-generation, gpt, langchain

## Related tools

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- [prompts.chat](/tools/f-prompts-chat.md) - The world's largest open-source prompt library for AI (★ 165,025)
- [transformers](/tools/huggingface-transformers.md) - 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models (★ 162,350)
- [langflow](/tools/langflow-ai-langflow.md) - Langflow is a powerful platform for building and deploying AI-powered agents and workflows. (★ 151,311)
- [firecrawl](/tools/firecrawl-firecrawl.md) - The API to search, scrape, and interact with the web at scale. (★ 147,150)
- [open-webui](/tools/open-webui-open-webui.md) - User-friendly AI Interface (Supports Ollama, OpenAI API, ...) (★ 144,582)
- [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) - 100+ AI Agent & RAG apps you can actually run — clone, customize, ship. (★ 116,702)
- [LLMs-from-scratch](/tools/rasbt-llms-from-scratch.md) - Implement a ChatGPT-like LLM in PyTorch from scratch (★ 98,715)

## README (excerpt)

```text
<div align="center">

# Advanced RAG Techniques 🚀
### Elevating Your Retrieval-Augmented Generation Systems

A community-driven hub of **42+ runnable notebooks** covering RAG techniques from foundational to cutting-edge - the intuition, the code, and the references to build more accurate, context-rich retrieval systems.

</div>

---








## Sponsors ❤️

We gratefully acknowledge the organizations and individuals who have made significant contributions to this project.

**Company Sponsors**

<div align="center">

<table style="border: none; border-collapse: collapse; width: 100%; max-width: 840px; margin: 0 auto; background: transparent; table-layout: fixed;">
  <tr>
    <td style="border: none; text-align: center; padding: 16px 24px; width: 33.33%; vertical-align: top;">
      <a href="https://app.contextual.ai?utm_campaign=rag-techniques&utm_source=diamantai&utm_medium=github&utm_content=notebook" target="_blank" style="text-decoration: none; display: inline-block; transition: transform 0.2s ease;">
        <img src="images/trimmed_padded_contextual_white.png#gh-light-mode-only" 
             alt="Contextual AI"
             style="height: 28px; width: auto; border-radius: 12px; vertical-align: middle; box-shadow: 0 2px 8px rgba(0,0,0,0.1);">
        <img src="images/trimmed_padded_contextual_black.png#gh-dark-mode-only" 
             alt="Contextual AI"
             style="height: 28px; width: auto; border-radius: 12px; vertical-align: middle; box-shadow: 0 2px 8px rgba(0,0,0,0.1);">
      </a>
    </td>
    <td style="border: none; text-align: center; padding: 16px 24px; width: 33.33%; vertical-align: middle;">
      <a href="https://coderabbit.link/nir" target="_blank" style="text-decoration: none; display: inline-block; transition: transform 0.2s ease;">
        <img src="images/coderabbit_Light_Type_Mark_Orange.png#gh-light-mode-only"
             alt="CodeRabbit"
             style="height: 28px; width: auto; border-radius: 12px; vertical-align: middle; box-shadow: 0 2px 8px rgba(0,0,0,0.1);">
        <img src="images/coderabbit_Dark_Type_Mark.png#gh-dark-mode-only"
             alt="CodeRabbit"
             style="height: 28px; width: auto; border-radius: 12px; vertical-align: middle; box-shadow: 0 2px 8px rgba(0,0,0,0.1);">
      </a>
    </td>
  </tr>
</table>
</div>

**Individual Sponsors**

<a href="https://github.com/sponsors/Eisenh"><img src="https://github.com/Eisenh.png" style="border-radius: 50%;" width="64" height="64" alt=""></a>

## 📫 Stay Updated!

<div align="center">
<table>
<tr>
<td align="center">🚀<br><b>Cutting-edge<br>Updates</b></td>
<td align="center">💡<br><b>Expert<br>Insights</b></td>
<td align="center">🎯<br><b>Top 0.1%<br>Content</b></td>

</tr>
</table>



*Join over 50,000 AI enthusiasts getting unique cutting-edge insights and free tutorials!* ***Plus, subscribers get exclusive early access and special 33% discounts to my book and the upcoming RAG Techniques course!***
</div>



## Introduction

Retrieval-Augmented Generation (RAG) is revolutionizing the way we combine information retrieval with generative AI. This repository showcases a curated collection of advanced techniques designed to supercharge your RAG systems, enabling them to deliver more accurate, contextually relevant, and comprehensive responses.

Our goal is to provide a valuable resource for researchers and practitioners looking to push the boundaries of what's possible with RAG. By fostering a collaborative environment, we aim to accelerate innovation in this exciting field.

## 📖 Go deeper: the book

<div align="center">

<a href="https://europe-west1-rag-techniques-views-tracker.cloudfunctions.net/rag-techniques-tracker?notebook=main-readme&amp;click=book-buy-gumroad-rag-image&amp;target=https%3A%2F%2Fdiamant-ai.com%2Frag-made-simple%3Fcode%3DRAGKING&amp;retarget=0&amp;text=book-buy-gumroad-rag-image"><img src="images/rag_book_best_seller.png" alt="RAG Made Simple" width="360"></a>

**[RAG Made Simple](https://euro
```

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/nirdiamant-rag-techniques`](/api/graphcanon/tools/nirdiamant-rag-techniques)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_