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ai-agent

graphrag: Smarter AI Agents

Get modular graph-based Retrieval-Augmented Generation with graphrag, ideal for founders working with GPT and LLMs, backed by 33k+ GitHub stars
33,467 stars3,541 forksPythonQuality 8/10Updated 6/5/2026100% free ยท open source
What it does

Transforms complex, unstructured data into clear insights by creating intelligent knowledge graphs that help you extract meaningful strategic information.

When to use it
  • โ€ขAnalyzing large volumes of text documents for research and competitive intelligence
  • โ€ขBreaking down complex industry reports or market research into digestible insights
  • โ€ขCreating comprehensive knowledge bases from scattered information sources
Quick start
  1. 1Install via pip: pip install graphrag
  2. 2Prepare your input data documents in a clean text or CSV format
  3. 3Configure graph settings and embedding model in config file
  4. 4Run initial graph generation and query your knowledge base
Ready-to-paste prompt
graphrag analyze --input market_reports/ --output insights.json --model gpt-4
Saves to your device

Topics

gpt
gpt-4
gpt4
graphrag
llm
llms
rag
What's inside โ€” free to inspect
No purchase needed

Read the entire source before you build โ€” unlike paid marketplaces that hide it behind a buy button.

20
top-level files
8
folders
201.2M
repo size
MIT
license
Key files
cspell.config.yaml
README.md
File tree
.github/
.semversioner/
.vscode/
docs/
packages/
scripts/
tests/
unified-search-app/
.gitattributes
.gitignore
.vsts-ci.yml
breaking-changes.md
CHANGELOG.md
CODE_OF_CONDUCT.md
CODEOWNERS
CONTRIBUTING.md
cspell.config.yaml
DEVELOPING.md
dictionary.txt
LICENSE
mkdocs.yaml
pyproject.toml
RAI_TRANSPARENCY.md
README.md
Quick Actions
Details
Creator
microsoft
Language
Python
Category
ai-agent
Published
3/27/2024

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