ai-agent

LightRAG: Fast AI Generation

Get simple retrieval-augmented generation with LightRAG, a tool for founders using large language models.
intermediate1-2 hours💵 Free + LLM API costs
39,793 stars5,604 forksPythonGuide quality 8/10 · reviewed Jun 5Updated 9/21/2026100% free · open source
What it is

Use LightRAG to generate text based on existing information with the help of large language models.

Real use case example

"A founder of an ecommerce startup wants to generate product descriptions for their website, so they use LightRAG to connect to their product database, and then use the tool to generate detailed and accurate descriptions, they then use these descriptions on their website, resulting in a more professional and polished product listing."

When to use it
  • Building AI-powered research assistants that pull from specific knowledge bases
  • Creating customer support chatbots with deep, domain-specific knowledge retrieval
  • Developing intelligent Q&A systems that dynamically source precise information
Ready-to-paste prompt
from lightrag import Retriever, Generator

retriever = Retriever(documents=['tech_docs.txt'])
response = Generator.augment_with_retrieval(query='How does this system work?')
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

🛠️ Technical setup

Expect 20–40 minutes in a terminal — or let your AI agent drive it.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/lightrag && curl -fsSL https://workflowstacks.com/api/skills/lightrag/claude-skill -o ~/.claude/skills/lightrag/SKILL.md
Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How LightRAG: Fast AI Generation works
Codeflow
Free to inspect

LightRAG: Fast AI Generation is a very large Python project (~138k lines across 346 code files, plus 486 test files). It is a full software project: use it through its install path rather than reading it end to end. Last commit this month, MIT license, has a test suite.

Size
Very large codebase
~138k lines · 346 code files · days to read — use, don't read
Setup
Developer setup
A real software project. Use it via its install path; don't expect to read it all.
Runs on
Python · Docker
Needs API keys (.env)
Python 93%TypeScript 5%Shell 2%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    AGENTS.md
    The instructions the AI actually follows
  3. 3
    pyproject.toml
    Dependencies and the commands it exposes
  4. 4
    env.example
    The API keys and settings you must provide
  5. 5
    lightrag/__init__.py
    Inside lightrag/ — the main logic begins here
What's in each folder
lightrag/Core code — the actual logic187 files
prompts/Prompts, skills & agent definitions2 files
docs/Documentation32 files
examples/Examples you can copy30 files
lightrag_webui/Folder140 files
k8s-deploy/Folder30 files
scripts/Helper scripts25 files
reproduce/Folder7 files
READMEHas testsDocumentedCI checksDocker readyExamples includedMIT licenseUpdated this month
Quick Actions
Details
Creator
HKUDS
Language
Python
Category
ai-agent
Published
10/2/2024

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Featured on WorkflowStacks
[![Featured on WorkflowStacks](https://workflowstacks.com/api/badge/lightrag.svg)](https://workflowstacks.com/skills/lightrag?utm_source=github&utm_medium=badge)
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