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

29.3k

Forks

3.6k

Open Issues

Watchers

261

Contributors

Weekly Commits

Language

Jupyter Notebook

License

NOASSERTION

Last Commit

Aug 29, 2026

Created

Jul 13, 2024

Latest Release

book-v1.0

Release Date

Apr 15, 2026

Synced: Sep 1, 2026

Quality Scores

Documentation Qualityw: 20%

6.4

No dedicated docs site. Description: 221 chars. Stars signal: 29,320. Contributors: 47. Score: 6.4/10

Community Healthw: 20%

8.3

Stars: 29,320. Contributors: 47. Watchers: 261. Forks: 3,585. Issue ratio: 0.0%. Score: 8.3/10

Maintenance Velocityw: 15%

6.9

Last commit: 3d ago. Weekly commits: 0. Latest release: book-v1.0. Maturity bonus: 2.1y old. Score: 6.9/10

API Design & DXw: 20%

7.1

Stars/issues ratio: 4887. No dedicated API docs. License: NOASSERTION. Popularity signal: 29,320 stars. Score: 7.1/10

Production Readinessw: 15%

7.8

Battle-tested: 29,320 stars. Peer review: 47 contributors. Versioned: book-v1.0. Licensed: NOASSERTION. Age: 2.1 years. Maintenance: last commit 3d ago. Score: 7.8/10

Ecosystem Integrationw: 10%

7.8

Fork interest: 3,585. Ecosystem: Jupyter Notebook. License: NOASSERTION. Adoption: 29,320 stars. Score: 7.8/10