Chart Generation

Chart generation turns data and a question into a finished visualization — the model picks a chart type, maps columns to axes, and produces either a rendered image or, more usefully, chart code (Vega-Lite, matplotlib, or a config for your front-end library) that your app renders. It's the visual half of "chat with your data," often paired with text-to-SQL: one step fetches the rows, the next decides how to show them. For SaaS builders, embedding it lets users ask "show revenue by region as a bar chart" and get a dashboard tile without touching a chart builder. Practical note: let the model emit a chart spec, not a bitmap — specs are interactive, restyleable to your brand, and inspectable, whereas an AI-drawn PNG can mislabel axes or invent values you can't correct. Guard against bad chart choices (pie charts for time series) by constraining the allowed types, and always validate the spec against the real data.