[split-required] Split 500-850 LOC files (batch 2)

backend-lehrer (10 files):
- game/database.py (785 → 5), correction_api.py (683 → 4)
- classroom_engine/antizipation.py (676 → 5)
- llm_gateway schools/edu_search already done in prior batch

klausur-service (12 files):
- orientation_crop_api.py (694 → 5), pdf_export.py (677 → 4)
- zeugnis_crawler.py (676 → 5), grid_editor_api.py (671 → 5)
- eh_templates.py (658 → 5), mail/api.py (651 → 5)
- qdrant_service.py (638 → 5), training_api.py (625 → 4)

website (6 pages):
- middleware (696 → 8), mail (733 → 6), consent (628 → 8)
- compliance/risks (622 → 5), export (502 → 5), brandbook (629 → 7)

studio-v2 (3 components):
- B2BMigrationWizard (848 → 3), CleanupPanel (765 → 2)
- dashboard-experimental (739 → 2)

admin-lehrer (4 files):
- uebersetzungen (769 → 4), manager (670 → 2)
- ChunkBrowserQA (675 → 6), dsfa/page (674 → 5)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

klausur-service/backend/orientation_crop_helpers.py

@@ -0,0 +1,86 @@
+"""
+Orientation & Crop shared helpers - cache management and pipeline logging.
+"""
+
+import logging
+from typing import Any, Dict
+
+import cv2
+import numpy as np
+from fastapi import HTTPException
+
+from ocr_pipeline_session_store import (
+    get_session_db,
+    get_session_image,
+    update_session_db,
+)
+
+logger = logging.getLogger(__name__)
+
+
+# Reference to the shared cache from ocr_pipeline_api (set in main.py)
+_cache: Dict[str, Dict[str, Any]] = {}
+
+
+def set_cache_ref(cache: Dict[str, Dict[str, Any]]):
+    """Set reference to the shared cache from ocr_pipeline_api."""
+    global _cache
+    _cache = cache
+
+
+def get_cache_ref() -> Dict[str, Dict[str, Any]]:
+    """Get reference to the shared cache."""
+    return _cache
+
+
+async def ensure_cached(session_id: str) -> Dict[str, Any]:
+    """Ensure session is in cache, loading from DB if needed."""
+    if session_id in _cache:
+        return _cache[session_id]
+
+    session = await get_session_db(session_id)
+    if not session:
+        raise HTTPException(status_code=404, detail=f"Session {session_id} not found")
+
+    cache_entry: Dict[str, Any] = {
+        "id": session_id,
+        **session,
+        "original_bgr": None,
+        "oriented_bgr": None,
+        "cropped_bgr": None,
+        "deskewed_bgr": None,
+        "dewarped_bgr": None,
+    }
+
+    for img_type, bgr_key in [
+        ("original", "original_bgr"),
+        ("oriented", "oriented_bgr"),
+        ("cropped", "cropped_bgr"),
+        ("deskewed", "deskewed_bgr"),
+        ("dewarped", "dewarped_bgr"),
+    ]:
+        png_data = await get_session_image(session_id, img_type)
+        if png_data:
+            arr = np.frombuffer(png_data, dtype=np.uint8)
+            bgr = cv2.imdecode(arr, cv2.IMREAD_COLOR)
+            cache_entry[bgr_key] = bgr
+
+    _cache[session_id] = cache_entry
+    return cache_entry
+
+
+async def append_pipeline_log(session_id: str, step: str, metrics: dict, duration_ms: int):
+    """Append a step entry to the pipeline log."""
+    from datetime import datetime
+    session = await get_session_db(session_id)
+    if not session:
+        return
+    pipeline_log = session.get("pipeline_log") or {"steps": []}
+    pipeline_log["steps"].append({
+        "step": step,
+        "completed_at": datetime.utcnow().isoformat(),
+        "success": True,
+        "duration_ms": duration_ms,
+        "metrics": metrics,
+    })
+    await update_session_db(session_id, pipeline_log=pipeline_log)