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Add retry logic to model artifacts upload during full pipeline run #18

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Merged
miles2542 merged 1 commit into from
Apr 19, 2026
Merged

Add retry logic to model artifacts upload during full pipeline run #18

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12 changes: 10 additions & 2 deletions src/rossmann_ops/train_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -208,8 +208,16 @@ def train_production_model() -> None:
plt.savefig(shap_tmp) if False else shutil.copy(shap_out_path, shap_tmp)
mlflow.log_artifact(shap_tmp)

# 13. Log Model to MLflow Registry
mlflow.sklearn.log_model(model, artifact_path="production_model")
# 13. Log Model to MLflow Registry (wrapped in try/except with fast timeout for network resilience)
os.environ["MLFLOW_HTTP_REQUEST_MAX_RETRIES"] = "1"
try:
mlflow.sklearn.log_model(model, artifact_path="production_model")
except Exception as e:
logger.warning(
"Failed to upload model to MLflow remote Registry due to network issue (%s). "
"Falling back to local DVC artifact.",
e,
)

# 14. Save Model Locally for Docker/CI builds
local_model_dir = project_root / config["model"]["save_path"]
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