LightRAG
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Overview
HEALTH SCORE
Excellent*
Partial score (2/3 categories)
62out of 65
Strong maintainer coverage. Development cadence is the only remaining gap. Security & Supply Chain is unavailable, so weights were redistributed.
LIFECYCLE
Active
Consistent commits, responsive maintainers, regular releases, and healthy issue triage.
Health breakdown
Excellent*(62/65)
Maintainer availability, known risks and supply chain posture, and whether the project is actively developed or appropriately stable.
Maintainer responsiveness
Median response time is 1 day.
Bus factor
19 active maintainers currently have merge rights.
Organization Diversity
Contributors span 1783 organizations.
Project Achievements
Leaderboards
About
LightRAG is a lightweight retrieval-augmented generation framework that aims to improve efficiency and reduce computational costs in large language model applications. It implements techniques for efficient document retrieval and knowledge integration while maintaining performance.
First commit
Software value
$7.2M
Tags
genai
gpt
gpt-4
graphrag
knowledge-graph
large-language-models
llm
rag
retrieval-augmented-generation
License(s)
MIT
Data sources
Git
GitHub