[split-required] Split final 43 files (500-668 LOC) to complete refactoring

klausur-service (11 files):
- cv_gutter_repair, ocr_pipeline_regression, upload_api
- ocr_pipeline_sessions, smart_spell, nru_worksheet_generator
- ocr_pipeline_overlays, mail/aggregator, zeugnis_api
- cv_syllable_detect, self_rag

backend-lehrer (17 files):
- classroom_engine/suggestions, generators/quiz_generator
- worksheets_api, llm_gateway/comparison, state_engine_api
- classroom/models (→ 4 submodules), services/file_processor
- alerts_agent/api/wizard+digests+routes, content_generators/pdf
- classroom/routes/sessions, llm_gateway/inference
- classroom_engine/analytics, auth/keycloak_auth
- alerts_agent/processing/rule_engine, ai_processor/print_versions

agent-core (5 files):
- brain/memory_store, brain/knowledge_graph, brain/context_manager
- orchestrator/supervisor, sessions/session_manager

admin-lehrer (5 components):
- GridOverlay, StepGridReview, DevOpsPipelineSidebar
- DataFlowDiagram, sbom/wizard/page

website (2 files):
- DependencyMap, lehrer/abitur-archiv

Other: nibis_ingestion, grid_detection_service, export-doclayout-onnx

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

klausur-service/backend/nru_worksheet_models.py

@@ -0,0 +1,70 @@
+"""
+NRU Worksheet Models — data classes and entry separation logic.
+
+Extracted from nru_worksheet_generator.py for modularity.
+"""
+
+import logging
+from typing import List, Dict, Tuple
+from dataclasses import dataclass
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class VocabEntry:
+    english: str
+    german: str
+    source_page: int = 1
+
+
+@dataclass
+class SentenceEntry:
+    german: str
+    english: str  # For solution sheet
+    source_page: int = 1
+
+
+def separate_vocab_and_sentences(entries: List[Dict]) -> Tuple[List[VocabEntry], List[SentenceEntry]]:
+    """
+    Separate vocabulary entries into single words/phrases and full sentences.
+
+    Sentences are identified by:
+    - Ending with punctuation (. ! ?)
+    - Being longer than 40 characters
+    - Containing multiple words with capital letters mid-sentence
+    """
+    vocab_list = []
+    sentence_list = []
+
+    for entry in entries:
+        english = entry.get("english", "").strip()
+        german = entry.get("german", "").strip()
+        source_page = entry.get("source_page", 1)
+
+        if not english or not german:
+            continue
+
+        # Detect if this is a sentence
+        is_sentence = (
+            english.endswith('.') or
+            english.endswith('!') or
+            english.endswith('?') or
+            len(english) > 50 or
+            (len(english.split()) > 5 and any(w[0].isupper() for w in english.split()[1:] if w))
+        )
+
+        if is_sentence:
+            sentence_list.append(SentenceEntry(
+                german=german,
+                english=english,
+                source_page=source_page
+            ))
+        else:
+            vocab_list.append(VocabEntry(
+                english=english,
+                german=german,
+                source_page=source_page
+            ))
+
+    return vocab_list, sentence_list