LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models

Systems that support users in the automatic creation of visualizations must address several subtasks -understand the semantics of data, enumerate relevant visualization goals and generate visualization specifications. In this work, we pose visualization generation as a multi-stage generation problem and argue that well-orchestrated pipelines based on large language models (LLMs) and image generation models (IGMs) are suitable to addressing these tasks. We present LIDA, a novel tool for generating grammar-agnostic visualizations and infographics. LIDA comprises of 4 modules -A SUMMARIZER that converts data into a rich but compact natural language summary, a GOAL EXPLORER that enumerates visualization goals given the data, a VISGENERATOR that generates, refines, executes and filters visualization code and an INFOGRAPHER module that yields data-faithful stylized graphics using IGMs. LIDA provides a python api, and a hybrid USER INTERFACE (direct manipulation and multilingual natural language) for interactive chart, infographics and data story generation. Code and demo are available at this url - https://microsoft.github.io/lida/ GOAL EXPLORER VIZ GENERATOR INFOGRAPHER SUMMARIZER Convert datasets into a rich but compact natural language representation (context). The cars dataset contains technical specifications for cars and has 9 fields -Name,