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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# Your pal <img src="man/figures/logo.png" align="right" height="200" alt="" />
<!-- badges: start -->
[](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[](https://CRAN.R-project.org/package=pal)
<!-- badges: end -->
Pals are persistent, ergonomic LLM assistants designed to help you complete repetitive, hard-to-automate tasks quickly. When created, they automatically generate RStudio add-ins registered to keyboard shortcuts. After selecting some code, press the keyboard shortcut you've chosen and watch your code be rewritten.
**Much of the documentation in this package is aspirational and its interface is likely to change rapidly.** Note, especially, that keyboard shortcuts will have to registered in the usual way (via Tools > Modify Keyboard Shortcuts > search "Pal"), for now.
## Installation
You can install pal like so:
``` r
pak::pak("simonpcouch/pal")
```
Then, ensure that you have an [`ANTHROPIC_API_KEY`](https://console.anthropic.com/) set in your [`.env`](https://github.com/gaborcsardi/dotenv). If you'd like to use an LLM other than Anthropic's Claude 3.5 Sonnet—like OpenAI's ChatGPT—to power the pal, see `?pal()` to set default metadata on that model.
## Example
To create a pal, simply pass `pal()` a pre-defined "role" and a keybinding you'd like it attached to. For example, to use the [cli pal](https://simonpcouch.github.io/pal/reference/pal_cli.html):
```r
pal("cli", "Ctrl+Shift+C")
```
Then, highlight some code, press the keyboard shortcut, and watch your code be rewritten:
As-is, the package provides ergonomic LLM assistants for R package development:
* `"cli"`: [Convert to cli](https://simonpcouch.github.io/pal/reference/pal_cli.html)
* `"testthat"`: [Convert to testthat 3](https://simonpcouch.github.io/pal/reference/pal_testthat.html)
* `"roxygen"`: [Document functions with roxygen](https://simonpcouch.github.io/pal/reference/pal_roxygen.html)
That said, the package provides infrastructure for others to make LLM assistants for any task in R, from authoring to interactive data analysis. With only a markdown file and a function call, users can extend pal to assist with their own repetitive but hard-to-automate tasks.
## How much do pals cost?
The cost of using pals depends on 1) the length of the underlying prompt for a given pal and 2) the cost per token of the chosen model. Using the cli pal with Anthropic's Claude Sonnet 3.5, for example, [costs something like](https://simonpcouch.github.io/pal/reference/pal_cli.html#cost) \$15 per 1,000 code refactorings, while using the testthat pal with OpenAI's GPT 4o-mini would cost something like \$1 per 1,000 refactorings. Pals using a locally-served LLM are "free" (in the usual sense of code execution, ignoring the cost of increased battery usage).