[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>

backend-lehrer/correction_models.py

@@ -0,0 +1,111 @@
+"""
+Correction API - Pydantic models and enums.
+"""
+
+from datetime import datetime
+from typing import List, Dict, Any, Optional
+from enum import Enum
+from pathlib import Path
+
+from pydantic import BaseModel, Field
+
+
+# Upload directory
+UPLOAD_DIR = Path("/tmp/corrections")
+UPLOAD_DIR.mkdir(parents=True, exist_ok=True)
+
+
+# ============================================================================
+# Enums and Models
+# ============================================================================
+
+class CorrectionStatus(str, Enum):
+    """Status einer Korrektur."""
+    UPLOADED = "uploaded"           # Datei hochgeladen
+    PROCESSING = "processing"       # OCR laeuft
+    OCR_COMPLETE = "ocr_complete"   # OCR abgeschlossen
+    ANALYZING = "analyzing"         # Analyse laeuft
+    ANALYZED = "analyzed"           # Analyse abgeschlossen
+    REVIEWING = "reviewing"         # Lehrkraft prueft
+    COMPLETED = "completed"         # Korrektur abgeschlossen
+    ERROR = "error"                 # Fehler aufgetreten
+
+
+class AnswerEvaluation(BaseModel):
+    """Bewertung einer einzelnen Antwort."""
+    question_number: int
+    extracted_text: str
+    points_possible: float
+    points_awarded: float
+    feedback: str
+    is_correct: bool
+    confidence: float  # 0-1, wie sicher die OCR/Analyse ist
+
+
+class CorrectionCreate(BaseModel):
+    """Request zum Erstellen einer neuen Korrektur."""
+    student_id: str
+    student_name: str
+    class_name: str
+    exam_title: str
+    subject: str
+    max_points: float = Field(default=100.0, ge=0)
+    expected_answers: Optional[Dict[str, str]] = None  # Musterloesung
+
+
+class CorrectionUpdate(BaseModel):
+    """Request zum Aktualisieren einer Korrektur."""
+    evaluations: Optional[List[AnswerEvaluation]] = None
+    total_points: Optional[float] = None
+    grade: Optional[str] = None
+    teacher_notes: Optional[str] = None
+    status: Optional[CorrectionStatus] = None
+
+
+class Correction(BaseModel):
+    """Eine Korrektur."""
+    id: str
+    student_id: str
+    student_name: str
+    class_name: str
+    exam_title: str
+    subject: str
+    max_points: float
+    total_points: float = 0.0
+    percentage: float = 0.0
+    grade: Optional[str] = None
+    status: CorrectionStatus
+    file_path: Optional[str] = None
+    extracted_text: Optional[str] = None
+    evaluations: List[AnswerEvaluation] = []
+    teacher_notes: Optional[str] = None
+    ai_feedback: Optional[str] = None
+    created_at: datetime
+    updated_at: datetime
+
+
+class CorrectionResponse(BaseModel):
+    """Response fuer eine Korrektur."""
+    success: bool
+    correction: Optional[Correction] = None
+    error: Optional[str] = None
+
+
+class OCRResponse(BaseModel):
+    """Response fuer OCR-Ergebnis."""
+    success: bool
+    extracted_text: Optional[str] = None
+    regions: List[Dict[str, Any]] = []
+    confidence: float = 0.0
+    error: Optional[str] = None
+
+
+class AnalysisResponse(BaseModel):
+    """Response fuer Analyse-Ergebnis."""
+    success: bool
+    evaluations: List[AnswerEvaluation] = []
+    total_points: float = 0.0
+    percentage: float = 0.0
+    suggested_grade: Optional[str] = None
+    ai_feedback: Optional[str] = None
+    error: Optional[str] = None