# lizhe2004/Awesome-LLM-RAG-Application

the resources about the application based on LLM with RAG pattern

Repository: https://github.com/lizhe2004/Awesome-LLM-RAG-Application
Canonical: https://ross.abutalabs.com/products/awesome-llm-rag-application
License Family: other
Last push: 2026-03-10T02:50:02+00:00

## Health v2 (maintenance only)
Score: 58/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 71, release rhythm 35, longevity 70
- inputs: {"age_days": 981, "days_push": 176, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1650, forks 114 (observed 2026-08-28T04:05:16.853445+00:00)

## What it is
A curated awesome-list of resources for building LLM applications using the RAG (Retrieval-Augmented Generation) pattern. It collects papers, open-source tools, frameworks, evaluation methods, courses, and enterprise practices related to RAG and agentic deep research.

## Use cases
- find open-source RAG frameworks
- learn how to build a RAG application
- find papers on retrieval-augmented generation
- compare RAG evaluation frameworks
- learn about GraphRAG and agentic RAG
- find embedding and reranking tools
- study enterprise RAG knowledge base practices

## When to choose
- you are researching or learning RAG techniques and want a curated starting point
- you need to survey tools for retrieval, reranking, evaluation, or LLM serving
- you want recent papers on agentic RAG and deep research agents

## When to avoid
- you need a runnable RAG implementation rather than a resource list
- you want a maintained software library with a license and releases

## Facets
- artifact type: learning-resource
- maturity: active
- function: rag, llm-inference, prompt-engineering, agent-framework, search-engine
- domain: large-language-models, artificial-intelligence, awesome-lists, tutorials
- platform: python, cross-platform
- tags: awesome-list, rag-frameworks, papers, deep-research, graphrag, evaluation, embeddings, reranking, retrieval-augmented-generation, ai-agents, web-server

## Member repositories
- lizhe2004/Awesome-LLM-RAG-Application (main) score 58

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:16.853445+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:45:05.423629+00:00, confidence not recorded.
  - readme: https://github.com/lizhe2004/Awesome-LLM-RAG-Application (fetched 2026-08-28T04:05:16.853445+00:00, sha 4513f63c90ef)
- Data as of 2026-08-30T08:39:29.467469+00:00.