chore: add hf_model_commit_message to LocusToGeneStep (opentarget…

…s#905)

src/gentropy/config.py

@@ -274,6 +274,7 @@ class LocusToGeneConfig(StepConfig):
     )
     wandb_run_name: str | None = None
     hf_hub_repo_id: str | None = "opentargets/locus_to_gene"
+    hf_model_commit_message: str | None = "chore: update model"
     download_from_hub: bool = True
     _target_: str = "gentropy.l2g.LocusToGeneStep"
 
@@ -633,6 +634,7 @@ class LocusToGeneEvidenceStepConfig(StepConfig):
     locus_to_gene_threshold: float = 0.05
     _target_: str = "gentropy.l2g.LocusToGeneEvidenceStep"
 
+
 @dataclass
 class LocusToGeneAssociationsStepConfig(StepConfig):
     """Configuration of the locus to gene association step."""
@@ -643,6 +645,7 @@ class LocusToGeneAssociationsStepConfig(StepConfig):
     indirect_associations_output_path: str = MISSING
     _target_: str = "gentropy.l2g.LocusToGeneAssociationsStep"
 
+
 @dataclass
 class StudyLocusValidationStepConfig(StepConfig):
     """Configuration of the study index validation step.

src/gentropy/l2g.py

@@ -110,6 +110,7 @@ def __init__(
         gene_interactions_path: str | None = None,
         predictions_path: str | None = None,
         hf_hub_repo_id: str | None,
+        hf_model_commit_message: str | None = "chore: update model",
     ) -> None:
         """Initialise the step and run the logic based on mode.
 
@@ -128,6 +129,7 @@ def __init__(
             gene_interactions_path (str | None): Path to the gene interactions dataset
             predictions_path (str | None): Path to the L2G predictions output dataset
             hf_hub_repo_id (str | None): Hugging Face Hub repository ID. If provided, the model will be uploaded to Hugging Face.
+            hf_model_commit_message (str | None): Commit message when we upload the model to the Hugging Face Hub
 
         Raises:
             ValueError: If run_mode is not 'train' or 'predict'
@@ -146,6 +148,7 @@ def __init__(
         self.wandb_run_name = wandb_run_name
         self.hf_hub_repo_id = hf_hub_repo_id
         self.download_from_hub = download_from_hub
+        self.hf_model_commit_message = hf_model_commit_message
 
         # Load common inputs
         self.credible_set = StudyLocus.from_parquet(
@@ -219,7 +222,7 @@ def run_train(self) -> None:
             ).train(self.wandb_run_name)
             if trained_model.training_data and trained_model.model and self.model_path:
                 trained_model.save(self.model_path)
-                if self.hf_hub_repo_id:
+                if self.hf_hub_repo_id and self.hf_model_commit_message:
                     hf_hub_token = access_gcp_secret(
                         "hfhub-key", "open-targets-genetics-dev"
                     )
@@ -231,7 +234,7 @@ def run_train(self) -> None:
                             "goldStandardSet", "geneId"
                         ).toPandas(),
                         repo_id=self.hf_hub_repo_id,
-                        commit_message="chore: update model",
+                        commit_message=self.hf_model_commit_message,
                     )
 
     def _annotate_gold_standards_w_feature_matrix(self) -> L2GFeatureMatrix: