ragR: Retrieval-Augmented Generation and RAG Evaluation Tools
Provides tools for document ingestion, embedding storage,
retrieval-augmented generation (RAG), and evaluation of question-answering
systems. The package includes an R-native vector store, wrappers for OpenAI
embedding and chat-completion application programming interfaces (APIs),
question-answering logging utilities, and large language model (LLM)-based
evaluation metrics for context precision, context recall, answer relevance,
and faithfulness. These metrics are based on the Retrieval-Augmented
Generation Assessment (RAGAS) framework. The retrieval-augmented generation
methodology is described by Lewis et al. (2020) "Retrieval-Augmented
Generation for Knowledge-Intensive NLP Tasks"
<doi:10.48550/arXiv.2005.11401>. The evaluation metrics are based on
Es et al. (2024) "RAGAS: Automated Evaluation of Retrieval Augmented
Generation" <doi:10.18653/v1/2024.eacl-demo.16>.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
dplyr, httr2, jsonlite, pdftools, readtext, tibble |
| Suggests: |
plumber, stringr, yaml, testthat (≥ 3.0.0) |
| Published: |
2026-07-22 |
| DOI: |
10.32614/CRAN.package.ragR (may not be active yet) |
| Author: |
Muhammad Aimal Rehman [aut, cre],
Zhili Lu [aut],
Chi-Kuang Yeh [aut] |
| Maintainer: |
Muhammad Aimal Rehman <rehman.aimal at gmail.com> |
| BugReports: |
https://github.com/aimalrehman92/ragR/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/aimalrehman92/ragR |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Materials: |
README |
| CRAN checks: |
ragR results |
Documentation:
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