Commit Graph
4 Commits
Author SHA1 Message Date
liambrydonandLiam Brydon 376fd65785 [Feature] ML model caching for reducing prediction overhead (#156)
The caching is now finished. The cache is created in `settings.py` giving us the most flexibility for using it in the future.

The cache is currently updated/accessed by `tasks.py/get_ml_model` which can be called from whatever task needs to access ml models in this way (currently, `predict` and `predict_simple`).

This implementation currently caches all ml models including the relative reasoning. If we don't want this and only want to cache enviFormer, i can change it to that. However, I don't think there is a harm in having the other models be cached as well.

Co-authored-by: Liam Brydon <62733830+MyCreativityOutlet@users.noreply.github.com>
Reviewed-on: enviPath/enviPy#156
Co-authored-by: liambrydon <lbry121@aucklanduni.ac.nz>
Co-committed-by: liambrydon <lbry121@aucklanduni.ac.nz>
2025-10-16 08:58:36 +13:00
liambrydonandLiam Brydon 22f0bbe10b [Feature] Eval package evaluation
`evaluate_model` in `PackageBasedModel` and `EnviFormer` now use evaluation packages if any are present instead of the random splits.

Co-authored-by: Liam Brydon <62733830+MyCreativityOutlet@users.noreply.github.com>
Reviewed-on: enviPath/enviPy#148
Co-authored-by: liambrydon <lbry121@aucklanduni.ac.nz>
Co-committed-by: liambrydon <lbry121@aucklanduni.ac.nz>
2025-10-08 19:03:21 +13:00
liambrydonandLiam Brydon d2f4fdc58a [Feature] Enviformer fine tuning and evaluation
## 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>
2025-10-07 21:14:10 +13:00
liambrydon 97d0527565 Merge pull request 'fixed calls to create MLRelativeReasoning during bootstrap.py and test_model.py' (#56) from fix/mlrr_arguments into develop
Reviewed-on: enviPath/enviPy#56
2025-08-22 11:29:02 +12:00