trentuna/candle-annotator
8
0
Fork 0
Code Issues Pull requests Releases Packages Activity Actions

fix(ml): extract class labels from model when metadata is missing

Browse source 
The model info returned empty labels array because the pkl file has
no metadata dict. Now extracts labels from model.classes_ or
model.model.classes_ as fallback.
This commit is contained in:
Marko Djordjevic 2026-02-15 22:18:16 +01:00
parent be09cef098
commit f7b154f866
1 changed files with 10 additions and 1 deletions
Download patch file Download diff file Expand all files Collapse all files

11
services/ml/app/main.py
View file

@ -257,6 +257,15 @@ def load_model_from_local(model_path: str) -> tuple[Any, Dict[str, Any]]:
model = model_data
metadata = {}
# Extract labels from model if not in metadata
labels = metadata.get("labels", [])
if not labels:
# Try to get class labels from the model itself
if hasattr(model, 'classes_'):
labels = [str(c) for c in model.classes_]
elif hasattr(model, 'model') and hasattr(model.model, 'classes_'):
labels = [str(c) for c in model.model.classes_]
# Build model info
model_info = {
"model_name": model_path.stem,
@ -265,7 +274,7 @@ def load_model_from_local(model_path: str) -> tuple[Any, Dict[str, Any]]:
"trained_at": metadata.get("trained_at", None),
"dataset_version": metadata.get("dataset_version", None),
"feature_engineering_enabled": metadata.get("feature_engineering_enabled", True),
"labels": metadata.get("labels", []),
"labels": labels,
"per_class_metrics": metadata.get("per_class_metrics", [])
}