How to run an R data visualization chatbot you can talk to
Briefly

How to run an R data visualization chatbot you can talk to
"Typing questions into a chatbot is nice, but speaking often feels more natural. In fact, some experts encourage people to talk to generative AI instead of typing, in part to get out of the habit of using them as glorified search engines. "If you haven't tried voice chatting with an AI model to see the appeal, you should," advises University of Pennsylvania professor Ethan Mollick, who studies innovation and artificial intelligence. "Anthropomorphism is the future, in ways good and bad.""
"Speech is a \"very fast and fluid interaction,\" Posit Chief Scientist Hadley Wickham said in his conference keynote, which included a brief ggbot2 demo. \"My goal has always been for the code to get out of the way, and for you to express your ideas so you can interact with the data as quickly as possible.\" Tell ggbot2 what you want in a spoken conversation, and it will generate plots and ggplot2 R code from your data."
"ggbot2 relies on the shinyrealtime package, which integrates OpenAI's Realtime API with Shiny apps written in either R or Python. shinyrealtime apps can also generate data visualization code in either language. All ggbot2 and shinyrealtime applications use OpenAI's Realtime API for conversational voice chats, which Posit CTO Joe Cheng told me he found particularly well suited for this type of work. OpenAI says its Realtime API was designed for low latency, elegant handling of user interruptions, and tool calling. So,"
ggbot2 is a voice assistant that generates ggplot2 visualizations and ggplot2 R code from spoken user instructions. Speech provides a fast, fluid interaction that helps users express ideas without letting code get in the way. The ggbot2 R package is available for local use and was showcased around posit::conf(2025). ggbot2 relies on the shinyrealtime package, which integrates OpenAI's Realtime API with Shiny apps in R or Python and can produce data-visualization code. The OpenAI Realtime API emphasizes low latency, smooth interruption handling, and tool calling, making it suitable for conversational voice-based plotting workflows.
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