/chattr

Primary LanguageROtherNOASSERTION

chattr

R-CMD-check Codecov test coverage CRAN status

Intro

chattr is an interface to LLMs (Large Language Models). It enables interaction with the model directly from the RStudio IDE. chattr allows you to submit a prompt to the LLM from your script, or by using the provided Shiny Gadget.

chattr’s main goal is to aid in EDA tasks. The additional information appended to your request, provides a sort of “guard rails”, so that the packages and techniques we usually recommend as best practice, are used in the model’s responses.

Install

Since this is a very early version of the package install the package from Github:

remotes::install_github("mlverse/chattr")

Available models

chattr provides two main integration with two main LLM back-ends. Each back-end provides access to multiple LLM types:

Provider Models Setup Instructions
OpenAI GPT Models accessible via the OpenAI’s REST API. chattr provides a convenient way to interact with GPT 4, 3.5, and DaVinci 3. Interact with OpenAI GPT models
LLamaGPT-Chat LLM models available in your computer. Including GPT-J, LLaMA, and MPT. Tested on a GPT4ALL model. LLamaGPT-Chat is a command line chat program for models written in C++. Interact with local models

The idea is that as time goes by, more back-ends will be added.

Using

The App

The main way to use chattr is through the Shiny Gadget app. By default, it runs inside the Viewer pane:

chattr::chattr_app()

Screenshot of the Sniny gadget app in a dark mode RStudio theme

After the LLM finishes its response, the chattr app processes all markdown code chunks. It will place three convenience buttons:

  • Copy to clipboard - It will write the code inside the chunk to your clipboard.

  • Copy to document - It will copy-paste the code directly to where the app was called from. If the app is started while working on a script, chattr will copy the code to that same script.

  • Copy to new script - It creates a new R script in the RStudio IDE, and copies the content of the chunk directly to it. Very useful when the LLM writes a Shiny app for you

A lot of effort was put in to make the app’s appearance as close as possible to the IDE. This way it feels more integrated with your work space. This includes switching the color scheme based on the current RStudio theme being light, or dark.

The settings screen can be accessed by clicking on the “gear” button. The screen that opens will contain the following:

  • Save and Open chats - This is an early experiment to allow us to save and retrieve past chats. chattr will save the file in an RDS format. The main objective of this feature, is to be able to see past chats, not to continue previous conversations with the LLM.

  • Prompt settings - In this section you can change the additional information attached to your prompt. Including the number of max data files, and data frames sent to the LLM.

Screenshot of the Sniny gadget options

Additional ways to interact

Apart from the Shiny app, chattr provides two more ways to interact with the LLM. For details, see: Other interfaces

How it works

chattr enriches your request with additional instructions, name and structure of data frames currently in your environment, the path for the data files in your working directory. If supported by the model, chattr will include the current chat history.

Diagram that illustrates how chattr handles model requests

To see what chattr will send to the model, set the preview argument to TRUE:

library(chattr)

data(mtcars)
data(iris)

chattr(preview = TRUE)
#> 
#> ── chattr ──────────────────────────────────────────────────────────────────────
#> 
#> ── Preview for: Console
#> • Provider: Open AI - Chat Completions
#> • Path/URL: https://api.openai.com/v1/chat/completions
#> • Model: gpt-4
#> • temperature: 0.01
#> • max_tokens: 1000
#> • stream: TRUE
#> 
#> ── Prompt:
#> role: system
#> content: You are a helpful coding assistant
#> role: user
#> content:
#> * Use the 'Tidy Modeling with R' (https://www.tmwr.org/) book as main reference
#> * Use the 'R for Data Science' (https://r4ds.had.co.nz/) book as main reference
#> * Use tidyverse packages: readr, ggplot2, dplyr, tidyr
#> * For models, use tidymodels packages: recipes, parsnip, yardstick, workflows,
#> broom
#> * Avoid explanations unless requested by user, expecting code only
#> * For any line that is not code, prefix with a: #
#> * Keep each line of explanations to no more than 80 characters
#> * DO NOT use Markdown for the code
#> [Your future prompt goes here]

Keyboard Shortcut

The best way to access chattr’s app is by setting up a keyboard shortcut for it. This package includes an RStudio Addin that gives us direct access to the app, which in turn, allows a keyboard shortcut to be assigned to the addin. The name of the addin is: “Open Chat”. If you are not familiar with how to assign a keyboard shortcut see the next section.

How to setup the keyboard shortcut

  • Select Tools in the top menu, and then select Modify Keyboard Shortcuts

    Screenshot that shows where to find the option to modify the keyboard shortcuts

  • Search for the chattr adding by writing “open chat”, in the search box

    Screenshot that shows where to input the addin search

  • To select a key combination for your shortcut, click on the Shortcut box and then type press the key combination in your keyboard. In my case, I chose Ctrl+Shift+C

    Screenshot that shows what the interface looks like when a shortcut has been selected