Jimmy Briggs jimbrig

You are situated inside of an R package source directory. The subdirectory R/ contains source files. The subdirectory tests/testthat/ contains corresponding tests. e.g. R/task.R is tested primarily in tests/testthat/test-task.R.

Do not add new code comments, and only remove existing code comments if the comment isn't relevant anymore.

The package has not yet been published and does not have any users; remove functionality outright when it's no longer needed rather than beginning a deprecation process. No need to worry about breaking changes.

When testing code that raises a message, warning, or error, use expect_snapshot() (possibly with error = TRUE) instead of expect_message() or otherwise.

When you're running package tests, use devtools::load_all(); testthat::test_file("tests/testthat/path-to-file.R"). If you encounter namespacing issues, don't delete tests that otherwise should work, and instead ask me what to do.

Roxygen Normalization

You are a terse assistant designed to help R users write roxygen documentation according to CRAN and tidy style with a consistent format. Respond with only the needed R code, no backticks or newlines around the response. Intersperse newlines within function calls as needed, per tidy style.

As example, given the input:

#' app
#'
#' this makes an app

Meta Prompting

In the Generative AI Age your ability to generate prompts is your ability to generate results.

Guide

Claude 3.5 Sonnet and o1 series models are recommended for meta prompting.

Replace {{user-input}} with your own input to generate prompts.

Use mp_*.txt as example user-inputs to see how to generate high quality prompts.

	# an example server: acquaint's MCP server for R sessions
	r_process <- callr::r_bg(
	function() acquaint::mcp_server(),
	stdout = "\|",
	stdin = "\|"
	)

	Sys.sleep(1)

	log_cat_client <- function(x, append = TRUE) {

	<#
	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%@@@@@@@@@@@@@@@@@%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%@#-:*************=@%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%-%+=%%%%%%%%%%%%%%-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	%%%%%%%%%%%%%%%%%%##%%%%%%%%%%%%%%%%%%%%%%%:*%%=+%%%%%%%%%%%%%%.#@%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	%%%%%%%%%%%%%%%%%%%#@%%%%%%%%%%%%%%%%%%@%%*#@%%@+%%%%%%%%%%%%%%%+%@%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

	<#
	.SYNOPSIS
	Perform Git submodule update to any commit and/or branch.

	.DESCRIPTION
	This script performs Git submodules updates to any commit and/or branch.
	It allows you to update a submodule to the latest commit, to a specific commit, or to the latest/specific commit of a specific branch.
	It will automatically commit the changes to the parent repository, and optionally also push them to the remote repository.

	.PARAMETER pathToLocalRepo

	# This is a sample R Shiny app chatbot that runs local models with an Ollama server.
	# You also need Ollama installed and a ollama server running, plus at least one local model pulled.
	# I hard-coded a few local models,
	# If you use this, you'll want to hard code yours (including descriptions, or take those out)

	# Coded with lots of LLM help + Posit's Shiny Assistant.

	library(shiny)
	library(shinychat)
	library(bslib)

	options(shiny.maxRequestSize = 5 * 1024^2) # Limit uploads to 5 MB

	library(shiny)
	library(magick)
	library(base64enc)
	library(bslib)

	# Helper function to sanitize file names
	safeFileName <- function(filename) {
	gsub("[^a-zA-Z0-9_.-]", "_", filename)

	function Invoke-AIChat {
	<#
	.SYNOPSIS
	Invokes an AI chat model to generate responses based on user prompts.

	.DESCRIPTION
	This function provides a unified interface to interact with various AI language model providers including:
	- Azure OpenAI Services
	- OpenAI API
	- Anthropic Claude

	YAHOO_CLIENT_ID=""
	YAHOO_CLIENT_SECRET=""