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llmshieldr  

Safety Guardrails for Large Language Model Workflows
View on CRAN: Click here


Download and install llmshieldr package within the R console
Install from CRAN:
install.packages("llmshieldr")

Install from Github:
library("remotes")
install_github("cran/llmshieldr")

Install by package version:
library("remotes")
install_version("llmshieldr", "0.1.0")



Attach the package and use:
library("llmshieldr")
Maintained by
Indraneel Chakraborty
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-05-28
Latest Update: 2026-05-28
Description:
A model-agnostic safety layer for developers building with large language model (LLM) applications. Maps starter controls to the Open Worldwide Application Security Project Top 10 for Large Language Model Applications 2025 risk categories <https://genai.owasp.org/llm-top-10/> via a modular rule engine. Supports regular-expression rules, lightweight natural language processing (NLP) intent checks, optional scanners, and semantic large language model reviewer checks on prompts, conversations, retrieved context, tool inputs and outputs, streaming chunks, and model outputs. Supports workflows with the 'Ollama' local web service <https://ollama.com/> via 'ellmer', remote reviewer endpoints, and other chat interfaces callable from 'R'. Intended as an experimental guardrail layer that teams should evaluate against their own workflows before relying on it in production.
How to cite:
Indraneel Chakraborty (2026). llmshieldr: Safety Guardrails for Large Language Model Workflows. R package version 0.1.0, https://cran.r-project.org/web/packages/llmshieldr. Accessed 03 Oct. 2026.
Previous versions and publish date:
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Functions, R codes and Examples using the llmshieldr R package
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