fix(fc2b): lazy-import onnxruntime in tagger (CI collection failure)

onnxruntime is in requirements-ml.txt only (deliberately kept out of the
lean web image and CI). The top-level `import onnxruntime` broke pytest
collection of test_ml_tagger / test_ml_suggestions / test_tasks_ml even
though those are pure-logic/integration-marked, because collection
imports the module.

Mirrors the embedder's lazy-torch pattern: onnxruntime is imported inside
Tagger.load(), placed AFTER the file-existence checks so
test_load_raises_when_model_missing still gets RuntimeError (not
ModuleNotFoundError) in onnxruntime-less environments. self._session
annotation dropped to a comment to avoid an eval-time ort reference.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

backend/app/services/ml/tagger.py

@@ -15,9 +15,13 @@ from dataclasses import dataclass
 from pathlib import Path
 
 import numpy as np
-import onnxruntime as ort
 from PIL import Image, ImageFile
 
+# onnxruntime lives in requirements-ml.txt only — it is NOT installed in the
+# lean web image or in CI. Imported lazily inside Tagger.load() so this module
+# imports fine without it (the suggestion service imports SURFACED_CATEGORIES
+# from here in the web container, and CI collects the pure-logic tests).
+
 # Tolerate minutely-truncated source images (same rationale as IR's wd14.py:
 # a few missing bytes at the JPEG EOI shouldn't block tagging the whole image).
 ImageFile.LOAD_TRUNCATED_IMAGES = True
@@ -43,7 +47,7 @@ class TagPrediction:
 class Tagger:
     def __init__(self, model_dir: Path | None = None):
         self._model_dir = model_dir or _MODEL_DIR
-        self._session: ort.InferenceSession | None = None
+        self._session = None  # onnxruntime.InferenceSession once load()ed
         self._tag_meta: list[dict] | None = None
         self._input_name: str | None = None
         self._output_name: str | None = None
@@ -73,6 +77,11 @@ class Tagger:
                     {"name": row["name"], "category": row["category"]}
                 )
 
+        # Lazy import — kept after the file-existence checks so the
+        # missing-model RuntimeError still fires first in environments
+        # without onnxruntime (CI / lean web image).
+        import onnxruntime as ort
+
         session = ort.InferenceSession(
             str(model_path), providers=["CPUExecutionProvider"]
         )