@<1523701205467926528:profile|AgitatedDove14> About the proposed ways for fixing this issue, I've got my hands a little dirty with the code, and I think maybe adding another option to include some other files in the clearml-serving model add command would be beneficial here. Please suppose that I have the current directory for now:

├── common
│   ├── common.py
└── yolo8
    ├── 1
    │   ├── model_NVIDIA_GeForce_RTX_3080.plan
    │   └── model_Tesla_T4.plan
    ├── config.pbtxt
    └── preprocess.py
└── yolo7
    ├── 1
    │   ├── model_NVIDIA_GeForce_RTX_3080.plan
    │   └── model_Tesla_T4.plan
    ├── config.pbtxt
    └── preprocess.py

And now, I want to have the same code across these two models. If I want to add the entire directory here, as you can see, it will be complicated, or if possible, it might have some flaws. Regarding the second option to add preprocessing as Python packages and install them alongside other things at build time, I think it might have a syncing issue because that code will change a lot and would be an issue to install that package everytime.

If it can be handled in such a way that the preprocessing code is managed, it would be much cleaner, right? Also, I've come up with some sort of uploading preprocessing code as an artifact and then getting all of the tasks and then find the most updated common code and get a local copy from it and it is working for me. But I'm thinking maybe adding such capability into ClearML itself would be great, and I was wondering what your thoughts are on this. Is it okay to fork the repo and implement another option in here which will get a list of source codes and upload it into ClearML storage and then fetch it again in a way that preprocessing is handled? Should I do that and create a PR, or is it not necessary?