First read
HKUDS/RAG-Anything has enough public attention and recent movement to stay on the shortlist, but package usage is still partial, so the next step should be source and ecosystem validation rather than a quick yes.
21.3K public stars in the current GitStar snapshot.
Recognizable in the ecosystem
Last commit Jun 10, 2026.
Fresh activity
Treat stars as discovery context until a linked package appears.
No linked package mapping
One or more key signals are partial, so GitStar keeps the interpretation conservative.
Partial snapshot
Snapshot facts
Compare lens
HKUDS/OpenHarness and HKUDS/OpenSpace are the closest comparison targets GitStar found. A side-by-side comparison usually tells you more than a single raw rank.
Signal trail
Read the recent motion first. This block is for deciding whether the repository still looks alive, compounding, or flattening before you trust stars alone.
Package reality
No linked npm or PyPI package is mapped for this repository yet, so the page leans more heavily on GitHub-visible popularity and should be read more conservatively.
GitStar expects a package signal here, but no npm or PyPI package is linked to this repository yet.
Validation note
GitStar can summarize public signals for HKUDS/RAG-Anything, but the GitHub repository is still the primary place to confirm release cadence, issue activity, and maintainer intent.
GitStar surfaces public popularity and package signals. These rankings are not endorsements, security reviews, or investment advice.
Why this rank
This repository stands out because it combines fresh update and stable visibility.
Reconstructed from current stars and cached daily/weekly/monthly deltas.
GitStar can see repository momentum, but it does not have a reliable linked package signal yet.
Treat stars and recent movement as discovery context only until npm or PyPI usage is available.
Lives in the same Python ecosystem, but should still be checked for actual use-case overlap before you treat it as a direct substitute.
Lives in the same Python ecosystem, but should still be checked for actual use-case overlap before you treat it as a direct substitute.
Lives in the same Python ecosystem, but should still be checked for actual use-case overlap before you treat it as a direct substitute.
Overlaps on topics such as retrieval-augmented-generation, which makes it a stronger alternative than a random popularity neighbor.
GitStar picked OpenHarness + OpenSpace as the closest next comparison from the related repository set.
[](https://gitstar.space/repo/HKUDS/RAG-Anything)<a href="https://gitstar.space/repo/HKUDS/RAG-Anything"><img src="https://gitstar.space/api/badge/HKUDS/RAG-Anything" alt="GitStar"></a>"OpenHarness: Open Agent Harness"
"OpenSpace: Make Your Agents: Smarter, Low-Cost, Self-Evolving" -- Community: https://open-space.cloud/
"ClawTeam: Agent Swarm Intelligence" (One Command → Full Automation)
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
The highest-scoring AI memory system ever benchmarked. And it's free.
Fully autonomous & self-evolving research from idea to paper. Chat an Idea. Get a Paper. 🦞
This page provides a quick overview of HKUDS/RAG-Anything based on GitStar's cached data. The signal chart reconstructs approximate checkpoints from current stars plus cached daily, weekly, and monthly star deltas, so it is best read as directional context rather than as a precise historical audit log.
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