This project allows to use a VLM for anomaly identification. The deployment of the VLM is explained in here. And the way to communicate with the model here, given CONVINCE use cases. For now only UC1, vacuum cleaner, and UC2, assembly robot. The last section explains how to custom the communication.

The tests have been done only on LINUX, but the use of docker should make it exploitable on all OSs.

Refer to sit-aw-api documentation to learn how to get started and use it.