NirDiamant/RAG_Techniques
RAG LibrariesThis repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and contextually rich responses.
No dedicated docs site. Description: 221 chars. Stars signal: 29,253. Contributors: 44. Score: 6.3/10
Stars: 29,253. Contributors: 44. Watchers: 259. Forks: 3,571. Issue ratio: 0.1%. Score: 8.3/10
Last commit: 0d ago. Weekly commits: 1. Latest release: book-v1.0. Maturity bonus: 2.1y old. Score: 7.5/10
Stars/issues ratio: 1828. No dedicated API docs. License: NOASSERTION. Popularity signal: 29,253 stars. Score: 7.1/10
Battle-tested: 29,253 stars. Peer review: 44 contributors. Versioned: book-v1.0. Licensed: NOASSERTION. Age: 2.1 years. Maintenance: last commit 0d ago. Score: 7.8/10
Fork interest: 3,571. Ecosystem: Jupyter Notebook. License: NOASSERTION. Adoption: 29,253 stars. Score: 7.8/10