{ "_id": "6a60a1e6c766cc6deb6a9f6e", "Package": "ragR", "Title": "Retrieval-Augmented Generation and RAG Evaluation Tools", "Version": "0.1.0", "Authors@R": "c(\nperson(\ngiven = \"Muhammad Aimal\",\nfamily = \"Rehman\",\nemail = \"rehman.aimal@gmail.com\",\nrole = c(\"aut\", \"cre\")\n),\nperson(\ngiven = \"Zhili\",\nfamily = \"Lu\",\nrole = \"aut\"\n),\nperson(\ngiven = \"Chi-Kuang\",\nfamily = \"Yeh\",\nrole = \"aut\"\n)\n)", "Description": "Provides tools for document ingestion, embedding storage,\nretrieval-augmented generation (RAG), and evaluation of\nquestion-answering systems. The package includes an R-native\nvector store, wrappers for OpenAI embedding and chat-completion\napplication programming interfaces (APIs), question-answering\nlogging utilities, and large language model (LLM)-based\nevaluation metrics for context precision, context recall,\nanswer relevance, and faithfulness. These metrics are based on\nthe Retrieval-Augmented Generation Assessment (RAGAS)\nframework. The retrieval-augmented generation methodology is\ndescribed by Lewis et al. (2020) \"Retrieval-Augmented\nGeneration for Knowledge-Intensive NLP Tasks\"\n. The evaluation metrics are\nbased on Es et al. (2024) \"RAGAS: Automated Evaluation of\nRetrieval Augmented Generation\"\n.", "License": "GPL-3", "URL": "https://github.com/aimalrehman92/ragR", "BugReports": "https://github.com/aimalrehman92/ragR/issues", "Encoding": "UTF-8", "Language": "en-US", "Config/testthat/edition": "3", "Config/roxygen2/version": "8.0.0", "NeedsCompilation": "no", "Packaged": { "Date": "2026-07-22 10:53:27 UTC", "User": "root" }, "Author": "Muhammad Aimal Rehman [aut, cre], Zhili Lu [aut], Chi-Kuang Yeh\n[aut]", "Maintainer": "Muhammad Aimal Rehman ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-07-22 07:40:02 UTC", "RemoteUrl": "https://github.com/cran/ragR", "RemoteRef": "HEAD", "RemoteSha": "f01a408bd5d8935e6500b18833e581ed89998b6e", "_user": "cran", "_type": "src", "_file": "ragR_0.1.0.tar.gz", "_fileid": "https://r2.ropensci.org/10483bd4e8b0d7df1bb00fcb7f523abfc33c51d53afad977553262af49b4dd1e", "_filesize": 218950, "_sha256": 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