forked from enviPath/enviPy
liambrydon
d2f4fdc58a
## Changes - I have finished the backend integration of EnviFormer (#19), this includes, dataset building, model finetuning, model evaluation and model prediction with the finetuned model. - `PackageBasedModel` has been adjusted to be more abstract, this includes making the `_save_model` method and making `compute_averages` a static class function. - I had to bump the python-version in `pyproject.toml` to >=3.12 from >=3.11 otherwise uv failed to install EnviFormer. - The default EnviFormer loading during `settings.py` has been removed. ## Future Fix I noticed you have a little bit of code in `PackageBasedModel` -> `evaluate_model` for using the `eval_packages` during evaluation instead of train/test splits on `data_packages`. It doesn't seem finished, I presume we want this for all models, so I will take care of that in a new branch/pullrequest after this request is merged. Also, I haven't done anything for a POST request to finetune the model, I'm not sure if that is something we want now. Co-authored-by: Liam Brydon <62733830+MyCreativityOutlet@users.noreply.github.com> Reviewed-on: enviPath/enviPy#141 Reviewed-by: jebus <lorsbach@envipath.com> Co-authored-by: liambrydon <lbry121@aucklanduni.ac.nz> Co-committed-by: liambrydon <lbry121@aucklanduni.ac.nz>