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Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models
| Date | Stars |
|---|---|
| 2026-07-24 | 1339 |
| 2026-07-25 | 1339 |
| 2026-07-28 | 1339 |
| 2026-07-30 | 1339 |
| 2026-07-31 | 1341 |
| 2026-08-06 | 1341 |
Today
— stars today
This week
+2 stars this week
This month
— stars this month
Momentum
12.0
growth rate 0.15%/day
<div align="center">
<h1>Awesome LLM RAG</h1>
<a href="https://awesome.re"><img src="https://awesome.re/badge.svg"/></a>
</div>
\
[](https://github.com/hee9joon/Awesome-Diffusion-Models)
[](https://opensource.org/licenses/MIT)
[](https://github.com/chetanraj/awesome-github-badges)
This repo aims to record advanced papers on Retrieval Augmented Generation (RAG) in LLMs.
We strongly encourage the researchers that want to promote their fantastic work to the LLM RAG to make pull request to update their paper's information!
---
## Contents
- [Bernstein](https://github.com/chernistry/bernstein) - Multi-agent orchestrator with RAG-enhanced task planning. Decomposes goals using context from codebase analysis.
- [Resources](#resources)
- [Workshops and Tutorials](#workshops-and-tutorials)
- [Books](#books)
- [Papers](#papers)
- [Survey and Benchmark](#survey-and-benchmark)
- [Retrieval-enhanced LLMs](#retrieval-enhanced-llms)
- [RAG Instruction Tuning](#rag-instruction-tuning)
- [RAG In-Context Learning](#rag-in-context-learning)
- [RAG Embeddings](#rag-embeddings)
- [RAG Simulators](#rag-simulators)
- [RAG Search](#rag-search)
- [RAG Long-text and Memory](#rag-long-text-and-memory)
- [RAG Evaluation](#rag-evaluation)
- [RAG Optimization](#rag-optimization)
- [RAG Application](#rag-application)
- [RAG for Missing Modalities](#rag-for-missing-modalities)
---
# Resources
- [guardian-agent-prompts](https://github.com/milkomida77/guardian-agent-prompts) - 49 production-tested AI agent system prompts for Claude Code multi-agent orchestration with retrieval-augmented generation patterns. MIT licensed.
- [CCHub](https://github.com/Moresl/cchub) - A desktop control panel for the Claude Code / Codex / Gemini CLI ecosystem. Manage MCP servers, config profiles, agent skills, CLAUDE.md, hooks, and workflow templates from a single Tauri app (Windows / macOS / Linux).
- [ChunkTuner](https://github.com/shantanu-deshmukh/chunktuner) - Open-source Python/CLI/MCP tooling to benchmark chunking strategies for RAG and recommend configurations using retrieval metrics (optional RAGAS).
## Workshops and Tutorials
- [Agent Shadow Brain](https://github.com/theihtisham/agent-shadow-brain) - Self-evolving AI coding intelligence with infinite memory (TurboQuant), genetic algorithm self-evolution, predictive bug detection, PageRank knowledge graphs, swarm intelligence, and adversarial defense.
- [Omni Skills Forge](https://github.com/theihtisham/omni-skills-forge) - 50,000+ curated AI agent skills for Claude Code, Cursor, Copilot, Windsurf, Cline. Visual dashboard, one-click install, skill doctor, auto-update.
- [RAG Techniques](https://github.com/NirDiamant/RAG_Techniques) - 35+ runnable Jupyter-notebook tutorials covering advanced RAG techniques: chunking, query transformation/HyDE, reranking, self-RAG, graph RAG, and evaluation.
**Personalized Generative AI**
*Zheng Chen, Ziyan Jiang, Fan Yang, Zhankui He, Yupeng Hou, Eunah Cho, Julian McAuley, Aram Galstyan, Xiaohua Hu, Jie Yang*
CIKM 23 – Oct 2023 [[link](https://sites.google.com/view/pgai2023/home)]
**First Workshop on Recommendation with Generative Models**
*Wenjie Wang, Yong Liu, Yang Zhang, Weiwen Liu, Fuli Feng, Xiangnan He, Aixin Sun*
CIKM 23 – Oct 2023 [[link](https://rgm-cikm23.github.io/)]
**First Workshop on Generative Information Retrieval**
*Gabriel Bénédict, Ruqing Zhang, Donald Metzler*
SIGIR 23 – Jul 2023 [[link](https://coda.io/@sigir/gen-ir)]
**Retrieval-based Language Models and Applications**
*Akari Asai, Sewon Min, Zexuan Zhong, Danqi Chen*
ACL 23 – Jul 2023 [[link](https://acl2023-retrieval-lm.github.io/)]
**Become a Generative AI Developer**
*Richie Cotton, Olivier MerExcerpt of 18,395 characters
Read on GitHub
Jiaxin Zhang · United States
52
Stjepan Jureković · Manning Publication · Croatia
3
Suhani Nagpal
3
Zhmin Zhao · Software Analysis and Intelligence Lab (SAIL) & Lab on Maintenance, Construction and Intelligence of Software (MCIS) · Canada
2
Nir Diamant · DiamantAI
2
1
Aryan Budukh
1
1
1
1
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Kai Zhang · https://neocognition.io/ · United States
1
1
1
1
Pat Walls · United States
1
Viktor Moskvoretskii
1
Alex Chernysh · Sip Your Drink · Israel
1
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:14de1d97ce00f4ab, topic:rag, topic:retrieval-augmented-generation, desc:retrieval-augmented generation
matched fp:14de1d97ce00f4ab, topic:large-language-models, topic:llm