Hey there 
I’d like to use the opportunity to showcase a piece we have done regarding interactive “data-story” notebooks using GAMS.
An Introduction to operations research in Observables
The Observable notebook is reactive. Just like in a spreadsheet, updating a cell updates all referenced cells automatically. This facilitates faster iterations of different visualisation options, and makes it easier for starters to observe the effect of changes to the codebase. Observables do not require any installation or login, which makes them a valuable resource for teaching or providing interactive, supplementary model code for research articles.
This is made possible by the neos-js package, which allows for solving GAMS models right from the browser on the neos-server, as well as gams2js, which parses the GAMS results and makes them accesible in Javascript (for use in visualisation libraries such as d3,Mapbox,Vega,etc., or websites in general).
For further examples showing what can be done with Observables see the following:
https://observablehq.com/@chrispahm/crop-gross-margins-in-germany
https://observablehq.com/explore
Further reading:
Observables are not a solution for every type of model and scenario.
Therefore, please also have a look at the wonderful GAMS examples for using Jupyter Notebooks with GAMS
https://nbviewer.jupyter.org/url/www.gams.com/external/jupyter_examples/Introduction.ipynb
and obviously GAMS MIRO for deploying interactive web applications of a GAMS model
https://miro.gams.com/gallery/endpoint/4485f4e1-dbd5-456c-8cae-3feaa5ed2cda/