ragR
0.1.0Retrieval-Augmented Generation and RAG Evaluation Tools
Overview
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.
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- OK2026-07-237 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
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- Return-value docs
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Checks run against github.com/aimalrehman92/ragr on 2026-07-30.
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1 release. R releases are shown for context.
- 0.1.0Latest2026-07-22 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-07-22
- Total releases
- 1 / 1 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 4.1.0
- Download size
- not tracked yet
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- With dependencies
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