Site icon R-bloggers

How to Get ChatGPT in R with chattr

[This article was first published on business-science.io, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Hey guys, welcome back to my R-tips newsletter. ChatGPT is a massive productivity enhancer. Lately it’s felt like VSCode, which integrates AI via GitHub Copilot, is moving faster than the RStudio IDE when it comes to integrating AI. Fortunately, I stumbled upon a new R package that integrates ChatGPT in R via RStudio IDE. It’s called chattr, and I’m sharing how to get started in under 5 minutes. Let’s go!

Table of Contents

Here’s what you’re learning today:

Get the Code (In the R-Tip 080 Folder)


SPECIAL ANNOUNCEMENT: ChatGPT for Data Scientists Workshop on June 12th

Inside the workshop I’ll share how I built a Machine Learning Powered Production Shiny App with ChatGPT (extends this data analysis to an insane production app):

What: ChatGPT for Data Scientists

When: Wednesday June 12th, 2pm EST

How It Will Help You: Whether you are new to data science or are an expert, ChatGPT is changing the game. There’s a ton of hype. But how can ChatGPT actually help you become a better data scientist and help you stand out in your career? I’ll show you inside my free chatgpt for data scientists workshop.

Price: Does Free sound good?

How To Join: 👉 Register Here


R-Tips Weekly

This article is part of R-Tips Weekly, a weekly video tutorial that shows you step-by-step how to do common R coding tasks. Pretty cool, right?

Here are the links to get set up. 👇

What is chattr

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 provides integration to many common models including OpenAI’s GPT models, Llama, and GitHub Copilot:

Once set up, you can use an LLM widget inside of RStudio IDE:

Benefits of using Chattr: Knowledge of Your RStudio Environment

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.

Tutorial: How to get ChatGPT inside of RStudio

It takes about 1 minute to get chattr set up so you can start using ChatGPT inside of Rstudio. All the tutorial code shown is available in the R-Tips Newsletter folder for R-Tip 080.

Here’s how to set up Chattr:

Follow these 5 steps:

  1. Install: chattr is not on CRAN as of this article. But you can install from GitHub.
  2. Load: Load chattr
  3. API Key: Set up your OpenAI API Key.
  4. Select a Model: For this demo I’m using gpt-3.5-turbo, denoted “gpt35”. But you can use gpt-4-turbo as well with “gpt4”.
  5. Run Chattr: This fires up a chattr_app() as a background job.

Success: A ChatBot Just Appeared inside Rstudio

Once successful you’ll see a dialog open in the RStudio Viewer window. You can begin asking questions like how to read the data from the chattr folder.

Chattr Background job

One thing I want to mention is why it makes sense to run Chattr as a background job. Running as a background job frees up your Console so you can continue to work.

Make a quick Shiny App with chattr

One of the things I love LLM’s for is building shiny apps. So I’ll share a quick dialog I had with chattr to make one. The chattr shiny app is in the test_shiny_app.R file.

One of the things I wanted to do was explore a Marketing Campaign dataset that I have inside the R-Tip 80 folder marketing_campaign.csv.

So I asked it howt to make a minimal shiny app to explore the data?

And it made this for me (shiny app is in the R-Tip 80 Folder):

Conclusions:

This is exciting! Chattr is making it easier and more productive for me to use LLM’s in my R workflow. I look forward to seeing how chattr progresses as LLM’s become a bigger part of my data science process.

There you have it. How to get ChatGPT into R. But, the next problem is that you’ll need to solve business problems with data science and R.

If you would like to grow your Business Data Science skills, then please read on…

Need to advance your business data science skills?

I’ve helped 6,107+ students learn data science for business from an elite business consultant’s perspective.

I’ve worked with Fortune 500 companies like S&P Global, Apple, MRM McCann, and more.

And I built a training program that gets my students life-changing data science careers (don’t believe me? see my testimonials here):

6-Figure Data Science Job at CVS Health ($125K)
Senior VP Of Analytics At JP Morgan ($200K)
50%+ Raises & Promotions ($150K)
Lead Data Scientist at Northwestern Mutual ($175K)
2X-ed Salary (From $60K to $120K)
2 Competing ML Job Offers ($150K)
Promotion to Lead Data Scientist ($175K)
Data Scientist Job at Verizon ($125K+)
Data Scientist Job at CitiBank ($100K + Bonus)

Whenever you are ready, here’s the system they are taking:

Here’s the system that has gotten aspiring data scientists, career transitioners, and life long learners data science jobs and promotions…

Join My 5-Course R-Track Program Now!
(And Become The Data Scientist You Were Meant To Be…)

P.S. – Samantha landed her NEW Data Science R Developer job at CVS Health (Fortune 500). This could be you.

To leave a comment for the author, please follow the link and comment on their blog: business-science.io.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Exit mobile version