gander is a higher-performance and lower-friction chat experience for data scientists in RStudio and Positron–sort of like completions with Copilot, but it knows how to talk to the objects in your R environment. The package brings ellmer chats into your project sessions, automatically incorporating relevant context and streaming their responses directly into your documents.
Why not just chat? In many ways, working with gander is just like using a chat interface online or via shinychat. The gander assistant will automatically find the context it needs, though:
- Code context: File contents from elsewhere in the project you’re working on (e.g. the lines in your source file).
- Environment context: Variables, allowing the assistant to locate the column names and types in data frames you’re working with, images linked to in your documents, and function definitions. This is what differentiates gander from many other assistants out there; gander can interface with your R session to describe your computational environment.
Important
For now, gander is particularly effective in
.R
files but struggles to provide appropriately formatted responses in.Qmd
and related file formats.
You can install gander like so:
install.packages("gander")
To install the developmental version:
pak::pak("simonpcouch/gander")
Then, you’ll need to hook gander up with an ellmer
chat. gander uses the .gander_chat
option to configure which model powers the addin; just set the option to
whatever your usual ellmer setup is. For example, we recommend
Anthropic’s Claude Sonnet 3.5, which you can use via
options(.gander_chat = ellmer::chat_claude())
once you’ve configured
an ANTHROPIC_API_KEY
. Paste that code in your .Rprofile
via
usethis::edit_r_profile()
to always use the same model every time you
start an R session. gander supports any model supported by ellmer, so
you can use Anthropic’s Claude, OpenAI’s GPT-4o, local ollama models,
etc. See “Choosing a model” in vignette("gander", package = "gander")
to learn more.
The gander assistant is interfaced with the via the gander addin. For easiest access, we recommend registering the gander addin to a keyboard shortcut.
In RStudio, navigate to
Tools > Modify Keyboard Shortcuts > Search "gander"
—we suggest
Ctrl+Alt+G
(or Ctrl+Cmd+G
on macOS).
In Positron, you’ll need to open the command palette, run “Open
Keyboard Shortcuts (JSON)”, and paste the following into your
keybindings.json
:
{
"key": "Ctrl+Cmd+G",
"command": "workbench.action.executeCode.console",
"when": "editorTextFocus",
"args": {
"langId": "r",
"code": "gander::gander_addin()",
"focus": true
}
}
The analogous keybinding on non-macOS is Ctrl+Alt+G
. That said, change
the "key"
entry to any keybinding you wish!
Once those steps are completed, you’re ready to use the gander assistant with a keyboard shortcut.
This screencast demonstrates using the gander addin to iterate on a plot:

After loading the stackoverflow data into my environment, I highlight
stackoverflow
and type a plain language request to plot the data. The
LLM’s response—which provides a minimal solution and refers to correct
column names—is streamed directly into my document and selected in
whole. After visually inspecting, I run the code, and then retrigger the
addin and type a followup request to refine the plot, doing so
iteratively until I’m satisfied with my results.
To read more about using the addin, check out the Getting Started
vignette with vignette("gander", package = "gander")
.