Restructure: Move 43 files into 8 domain packages (backend-lehrer)

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

backend-lehrer/correction_models.py

@@ -1,111 +1,4 @@
-"""
-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
+# Backward-compat shim -- module moved to correction/models.py
+import importlib as _importlib
+import sys as _sys
+_sys.modules[__name__] = _importlib.import_module("correction.models")