ai-agent

Boost LLMs with Awesome RAG

Name: Boost LLMs with Awesome RAG
Author: liunian-Jay

Get Retrieval-Augmented Generation for large language models with Awesome RAG, a resource for startup founders, with 507 GitHub stars

507 stars26 forksHealth Score 9/10Updated 7/26/2026100% free · open source

What it does

Awesome-RAG provides a curated list of resources and tools for developers to implement Retrieval-Augmented Generation (RAG) in Large Language Models (LLMs), focusing on technology development.

Install / run

Clone the repository using the command `git clone https://github.com/liunian-Jay/Awesome-RAG.git`

When to use it

•When building AI-powered applications that require retrieving and generating text based on external knowledge
•When developing LLMs that need to incorporate external information to improve their performance
•When researching or experimenting with RAG techniques for natural language processing tasks

Quick start

1Explore the `README.md` file for an overview of the resources and tools included in Awesome-RAG
2Check the `contributing.md` file for guidelines on how to contribute to the project
3Review the `awesome-rag.md` file for a curated list of RAG-related resources and tools
4Search for specific topics or keywords in the `awesome-rag.md` file to find relevant resources
5Use the provided resources and tools to start implementing RAG in your own LLM projects

Ready-to-paste prompt

Search for 'Question Answering' in the `awesome-rag.md` file to find resources and tools related to this topic, such as `https://github.com/liunian-Jay/Awesome-RAG#question-answering`

Heads up: Be aware that some of the resources and tools listed in Awesome-RAG may require specific hardware or software configurations, such as GPU support or specific library versions, to work properly

Saves to your device

Topics

large-langage-models

llm

rag

retrieval-augmented-generation

How Boost LLMs with Awesome RAG works

Codeflow

Free to inspect

Boost LLMs with Awesome RAG is a documents-only repository (1 doc file) — something you read, not something you run. There is nothing to install. Last commit this month, no license file.

Size

Documents only

1 document · 22 min skim

Setup

Nothing to install

A guide / curated list. Just read it and follow the links.

Runs on

Nowhere — you read it

A reading resource, not a program.

Where to start reading