Files
familienarchiv/ocr-service/ensure_blla_model.py
Marcel 74c9046745 fix(ocr): narrow exception handling and add unit tests for ensure_blla_model
- _model_is_loadable: narrow bare except to (RuntimeError, OSError, ValueError)
  with DEBUG-level fallback for unexpected exceptions — prevents silent masking
  of missing kraken install or AttributeError on vgsl
- _run_segtrain: replace bare except:pass with log.warning so height-check
  fallback is visible in container logs
- New test_ensure_blla_model.py: covers model-OK early return, incompatible
  model rename+replace, and missing model download paths

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-14 21:17:53 +02:00

81 lines
2.4 KiB
Python

"""Validates the blla segmentation base model and downloads it if needed.
Run at container startup before uvicorn. ketos 7 requires the model in
CoreML protobuf or safetensors format — legacy PyTorch ZIP archives
(torch.save output from kraken <4) are not loadable and will be replaced.
Exits non-zero on failure so Docker marks the container unhealthy rather
than silently starting with a broken model.
"""
import glob
import logging
import os
import shutil
import subprocess
import sys
logging.basicConfig(
level=logging.INFO,
format="%(levelname)s:ensure_blla_model:%(message)s",
)
log = logging.getLogger(__name__)
BLLA_MODEL_PATH = os.environ.get("BLLA_MODEL_PATH", "/app/models/blla.mlmodel")
# DOI for "General segmentation model for print and handwriting" — ketos 7 compatible.
BLLA_MODEL_DOI = "10.5281/zenodo.14602569"
HTRMOPO_DIR = os.path.expanduser("~/.local/share/htrmopo")
def _model_is_loadable(path: str) -> bool:
try:
from kraken.lib import vgsl
vgsl.TorchVGSLModel.load_model(path)
return True
except (RuntimeError, OSError, ValueError) as e:
log.warning("Model at %s failed to load: %s", path, e)
return False
except Exception:
log.debug("Unexpected error loading model at %s", path, exc_info=True)
return False
def _download_blla() -> str:
log.info("Downloading blla model (DOI %s) ...", BLLA_MODEL_DOI)
result = subprocess.run(
["kraken", "get", BLLA_MODEL_DOI],
capture_output=True,
text=True,
)
if result.returncode != 0:
log.error("kraken get failed: %s", result.stderr)
sys.exit(1)
candidates = sorted(glob.glob(os.path.join(HTRMOPO_DIR, "*/blla.mlmodel")))
if not candidates:
log.error("Downloaded blla.mlmodel not found under %s", HTRMOPO_DIR)
sys.exit(1)
return candidates[-1]
def main() -> None:
if os.path.exists(BLLA_MODEL_PATH):
if _model_is_loadable(BLLA_MODEL_PATH):
log.info("blla model OK: %s", BLLA_MODEL_PATH)
return
log.warning(
"blla model at %s is in an incompatible format — replacing", BLLA_MODEL_PATH
)
os.rename(BLLA_MODEL_PATH, BLLA_MODEL_PATH + ".incompatible")
os.makedirs(os.path.dirname(BLLA_MODEL_PATH), exist_ok=True)
downloaded = _download_blla()
shutil.copy2(downloaded, BLLA_MODEL_PATH)
log.info("Installed blla model at %s", BLLA_MODEL_PATH)
if __name__ == "__main__":
main()