📊RAG-Anything
HKUDS/RAG-Anything · homepage ↗
"RAG-Anything: All-in-One RAG Framework"
⭐ Very popular: 23k stars, gaining about 147 a week
View on GitHub ↗repo profile
momentum
durability
bus factor = how many people it takes to cover more than half the commits (6 months). 1 is a solo project; higher means the work is spread across a team. top-author share is the single busiest author's slice of those commits.
since we covered it
why it's a big deal
- Lets teams run RAG over mixed-content documents, PDFs, Office files, and images containing text, tables, equations, and charts, without stitching together separate pipelines.
- Targets developers whose source material is not plain text, handling scanned tables, LaTeX equations, and image captions that text-only RAG systems drop.
- Ships as a pip-installable Python package, so existing LightRAG users can extend to multimodal retrieval without rebuilding their stack.
under the hood
- Runs a five-stage pipeline in Python: parsing, content understanding, multimodal analysis, knowledge graph construction, and modality-aware retrieval, built on top of LightRAG.
- Parses documents with MinerU by default, with Docling and PaddleOCR as alternatives, and routes images, tables, and equations to dedicated analyzers including vision language models for captioning.
- Retrieval combines vector similarity with knowledge graph traversal and supports text, VLM-enhanced, and multimodal query modes, with direct content-list insertion to skip parsing for pre-processed input.
Radar summary, generated from the project's public sources
star history
- PR#18 7k 2025-10-01
- now 23k + 16k since first covered
curve is sampled from GitHub's star history, plus our own daily readings since we covered it; the dashed stretch is before we first covered it, the solid line since. figures at coverage are the numbers we printed then (approx.), current count is live.
understory
Better known than its recent output, coasting a little on attention.
- output, commits & releases
- clout, star velocity
output = commits & releases; clout = star velocity, both 0 to 100 monthly indices; the gap where output runs above clout is the understory. The understory →
covered in
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All-in-One Multimodal RAG System
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