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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7.5

GitHub Metrics

Stars

28.7k

Forks

3.5k

Open Issues

Watchers

256

Contributors

Weekly Commits

Language

Jupyter Notebook

License

NOASSERTION

Last Commit

Jul 14, 2026

Created

Jul 13, 2024

Latest Release

book-v1.0

Release Date

Apr 15, 2026

Synced: Jul 18, 2026

Quality Scores

Documentation Qualityw: 20%

6.3

No dedicated docs site. Description: 221 chars. Stars signal: 28,669. Contributors: 44. Score: 6.3/10

Community Healthw: 20%

8.3

Stars: 28,669. Contributors: 44. Watchers: 256. Forks: 3,502. Issue ratio: 0.0%. Score: 8.3/10

Maintenance Velocityw: 15%

8.3

Last commit: 4d ago. Weekly commits: 2. Latest release: book-v1.0. Maturity bonus: 2.0y old. Score: 8.3/10

API Design & DXw: 20%

7.1

Stars/issues ratio: 2205. No dedicated API docs. License: NOASSERTION. Popularity signal: 28,669 stars. Score: 7.1/10

Production Readinessw: 15%

7.8

Battle-tested: 28,669 stars. Peer review: 44 contributors. Versioned: book-v1.0. Licensed: NOASSERTION. Age: 2.0 years. Maintenance: last commit 4d ago. Score: 7.8/10

Ecosystem Integrationw: 10%

7.8

Fork interest: 3,502. Ecosystem: Jupyter Notebook. License: NOASSERTION. Adoption: 28,669 stars. Score: 7.8/10