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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7.4

GitHub Metrics

Stars

26.8k

Forks

3.2k

Open Issues

Watchers

247

Contributors

Weekly Commits

Language

Jupyter Notebook

License

NOASSERTION

Last Commit

Apr 15, 2026

Created

Jul 13, 2024

Latest Release

book-v1.0

Release Date

Apr 15, 2026

Synced: Apr 17, 2026

Quality Scores

Documentation Qualityw: 20%

6.3

No dedicated docs site. Description: 221 chars. Stars signal: 26,813. Contributors: 42. Score: 6.3/10

Community Healthw: 20%

8.2

Stars: 26,813. Contributors: 42. Watchers: 247. Forks: 3,208. Issue ratio: 0.0%. Score: 8.2/10

Maintenance Velocityw: 15%

7.6

Last commit: 2d ago. Weekly commits: 0. Latest release: book-v1.0. Maturity bonus: 1.8y old. Score: 7.6/10

API Design & DXw: 20%

7.1

Stars/issues ratio: 2681. No dedicated API docs. License: NOASSERTION. Popularity signal: 26,813 stars. Score: 7.1/10

Production Readinessw: 15%

7.5

Battle-tested: 26,813 stars. Peer review: 42 contributors. Versioned: book-v1.0. Licensed: NOASSERTION. Age: 1.8 years. Maintenance: last commit 2d ago. Score: 7.5/10

Ecosystem Integrationw: 10%

7.7

Fork interest: 3,208. Ecosystem: Jupyter Notebook. License: NOASSERTION. Adoption: 26,813 stars. Score: 7.7/10