Local Large Language Model Inference Engine R package edgemodelr version 0.4.1 Enables R users to run large language models locally using 'GGUF' model files and the 'llama.cpp' inference engine. Provides a complete R interface for loading models, generating text completions, extracting vector representations, and streaming responses in real-time. Includes grammar-constrained generation for structured output, text classification, and retrieval-augmented generation (RAG) pipelines. Supports local inference without requiring cloud APIs or internet connectivity, ensuring complete data privacy and control. Based on the 'llama.cpp' project by Georgi Gerganov (2023) <https://github.com/ggml-org/llama.cpp>. Software Depends: R (>= 4.0) Imports: Rcpp (>= 1.0.0), utils, tools LinkingTo: Rcpp Suggests: testthat (>= 3.0.0), knitr, rmarkdown, curl, shiny, openssl, jsonlite, httr, plumber Pawan Rama Mali <prm@outlook.in> Comprehensive R Archive Network (CRAN) Pawan Rama Mali [aut, cre, cph], Georgi Gerganov [aut, cph] (Author of llama.cpp and GGML library), The ggml authors [cph] (llama.cpp and GGML contributors), Jeffrey Quesnelle [ctb, cph] (YaRN RoPE implementation), Bowen Peng [ctb, cph] (YaRN RoPE implementation), pi6am [ctb] (DRY sampler from Koboldcpp), Ivan Yurchenko [ctb] (Z-algorithm implementation), Dirk Eddelbuettel [ctb, rev] MIT + file LICENSE (https://CRAN.R-project.org/package=edgemodelr/LICENSE) 2026-05-26 application/tgz https://CRAN.R-project.org/package=edgemodelr doi:10.32614/CRAN.package.edgemodelr