![generative-AI.png](kvGiCIcTKSys)

This flow zone gets the model specifications and results using a Python recipe. Then, a first Large Language Model (LLM) prompt recipe makes as many calls as there are significant covariates, using [Retrieval-Augmented Generation](https://doc.dataiku.com/dss/latest/generative-ai/rag.html), to find possible causes for the impact of each specific variable on maintenance performance.

Finally, a second LLM prompt recipe summarizes these results following a specific template that you can easily modify by double-clicking on the recipe. The result is then sent to the third panel of the dashboard to provide insights into the determinants of maintenance performance.