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: 26,800. Contributors: 42. Score: 6.3/10
Stars: 26,800. Contributors: 42. Watchers: 247. Forks: 3,207. Issue ratio: 0.0%. Score: 8.2/10
Last commit: 1d ago. Weekly commits: 0. Latest release: book-v1.0. Maturity bonus: 1.8y old. Score: 7.6/10
Stars/issues ratio: 2680. No dedicated API docs. License: NOASSERTION. Popularity signal: 26,800 stars. Score: 7.1/10
Battle-tested: 26,800 stars. Peer review: 42 contributors. Versioned: book-v1.0. Licensed: NOASSERTION. Age: 1.8 years. Maintenance: last commit 1d ago. Score: 7.5/10
Fork interest: 3,207. Ecosystem: Jupyter Notebook. License: NOASSERTION. Adoption: 26,800 stars. Score: 7.7/10