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
infiniflow/ragflow is drawing steady momentum at +54.9 stars/day (93rd percentile in the tracked cohort), for a momentum score of 44.1/100. A recent release is helping fuel the run.
Reconstructed from 352 snapshots — the time-series GitHub’s API doesn’t expose.
~23 forks/day, 4.0× the trailing baseline.
~36 forks/day, 7.5× the trailing baseline.
~28 forks/day, 3.2× the trailing baseline.
Live score, refreshed every 6 hours. Links back to this page.
[](https://breakwave.vercel.app/repo/infiniflow/ragflow)Low breakout odds over the next 14 days, led by star velocity (93th pctl) and fork velocity (93th pctl). Confidence is high given the available history.
Transparent heuristic · logged for model training
Percentile rank within the tracked cohort. The score self-calibrates — it answers “accelerating vs. everything else,” not raw size.
Release count rose to 55.
~38 forks/day, 3.0× the trailing baseline.
~30 forks/day, 4.9× the trailing baseline.
~27 forks/day, 5.4× the trailing baseline.
Release count rose to 54.
Release count rose to 53.
~78 forks/day, 3.0× the trailing baseline.
~34 forks/day, 3.3× the trailing baseline.
~26 forks/day, 3.4× the trailing baseline.