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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>.

Versions across snapshots

VersionRepositoryFileSize
0.1.0 rolling linux/jammy R-4.5 ragR_0.1.0.tar.gz 191.9 KiB
0.1.0 rolling linux/noble R-4.5 ragR_0.1.0.tar.gz 191.8 KiB
0.1.0 rolling source/ R- ragR_0.1.0.tar.gz 46.0 KiB
0.1.0 latest linux/jammy R-4.5 ragR_0.1.0.tar.gz 191.9 KiB
0.1.0 latest linux/noble R-4.5 ragR_0.1.0.tar.gz 191.8 KiB
0.1.0 latest source/ R- ragR_0.1.0.tar.gz 46.0 KiB
0.1.0 2026-04-23 source/ R- ragR_0.1.0.tar.gz 0 B

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