From Computational to Conversational Notebooks

TL;DR

This paper explores the integration of large language models into computational notebooks, proposing various support levels from inline code completion to conversationally generated executable code, aiming to enhance user productivity and interface design.

Contribution

It introduces a spectrum of LLM-supported notebook features and presents five concrete UI design examples to inspire future development.

Findings

Proposed a range of LLM integration levels in notebooks

Presented five example UI designs for LLM-supported notebooks

Discussed benefits and drawbacks of different support levels

Abstract

Today, we see a drastic increase in LLM-based user interfaces to support users in various tasks. Also, in programming, we witness a productivity boost with features like LLM-supported code completion and conversational agents to generate code. In this work, we look at the future of computational notebooks by enriching them with LLM support. We propose a spectrum of support, from simple inline code completion to executable code that was the output of a conversation. We showcase five concrete examples for potential user interface designs and discuss their benefits and drawbacks. With this, we hope to inspire the future development of LLM-supported computational notebooks.