NirDiamant/RAG_Techniques

RAG Libraries

This 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.

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7.3

GitHub Metrics

Stars

27.7k

Forks

3.3k

Open Issues

Watchers

249

Contributors

Weekly Commits

Language

Jupyter Notebook

License

NOASSERTION

Last Commit

May 31, 2026

Created

Jul 13, 2024

Latest Release

book-v1.0

Release Date

Apr 15, 2026

Synced: Jun 3, 2026

Quality Scores

Documentation Qualityw: 20%

6.3

No dedicated docs site. Description: 221 chars. Stars signal: 27,686. Contributors: 42. Score: 6.3/10

Community Healthw: 20%

8.2

Stars: 27,686. Contributors: 42. Watchers: 249. Forks: 3,337. Issue ratio: 0.1%. Score: 8.2/10

Maintenance Velocityw: 15%

7.5

Last commit: 3d ago. Weekly commits: 0. Latest release: book-v1.0. Maturity bonus: 1.9y old. Score: 7.5/10

API Design & DXw: 20%

7.1

Stars/issues ratio: 1978. No dedicated API docs. License: NOASSERTION. Popularity signal: 27,686 stars. Score: 7.1/10

Production Readinessw: 15%

7.5

Battle-tested: 27,686 stars. Peer review: 42 contributors. Versioned: book-v1.0. Licensed: NOASSERTION. Age: 1.9 years. Maintenance: last commit 3d ago. Score: 7.5/10

Ecosystem Integrationw: 10%

7.7

Fork interest: 3,337. Ecosystem: Jupyter Notebook. License: NOASSERTION. Adoption: 27,686 stars. Score: 7.7/10