b4613e26f3
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>
112 lines
3.1 KiB
Python
112 lines
3.1 KiB
Python
"""
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Correction API - Pydantic models and enums.
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"""
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from datetime import datetime
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from typing import List, Dict, Any, Optional
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from enum import Enum
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from pathlib import Path
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from pydantic import BaseModel, Field
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# Upload directory
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UPLOAD_DIR = Path("/tmp/corrections")
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UPLOAD_DIR.mkdir(parents=True, exist_ok=True)
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# ============================================================================
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# Enums and Models
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# ============================================================================
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class CorrectionStatus(str, Enum):
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"""Status einer Korrektur."""
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UPLOADED = "uploaded" # Datei hochgeladen
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PROCESSING = "processing" # OCR laeuft
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OCR_COMPLETE = "ocr_complete" # OCR abgeschlossen
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ANALYZING = "analyzing" # Analyse laeuft
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ANALYZED = "analyzed" # Analyse abgeschlossen
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REVIEWING = "reviewing" # Lehrkraft prueft
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COMPLETED = "completed" # Korrektur abgeschlossen
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ERROR = "error" # Fehler aufgetreten
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class AnswerEvaluation(BaseModel):
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"""Bewertung einer einzelnen Antwort."""
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question_number: int
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extracted_text: str
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points_possible: float
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points_awarded: float
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feedback: str
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is_correct: bool
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confidence: float # 0-1, wie sicher die OCR/Analyse ist
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class CorrectionCreate(BaseModel):
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"""Request zum Erstellen einer neuen Korrektur."""
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student_id: str
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student_name: str
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class_name: str
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exam_title: str
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subject: str
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max_points: float = Field(default=100.0, ge=0)
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expected_answers: Optional[Dict[str, str]] = None # Musterloesung
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class CorrectionUpdate(BaseModel):
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"""Request zum Aktualisieren einer Korrektur."""
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evaluations: Optional[List[AnswerEvaluation]] = None
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total_points: Optional[float] = None
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grade: Optional[str] = None
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teacher_notes: Optional[str] = None
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status: Optional[CorrectionStatus] = None
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class Correction(BaseModel):
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"""Eine Korrektur."""
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id: str
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student_id: str
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student_name: str
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class_name: str
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exam_title: str
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subject: str
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max_points: float
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total_points: float = 0.0
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percentage: float = 0.0
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grade: Optional[str] = None
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status: CorrectionStatus
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file_path: Optional[str] = None
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extracted_text: Optional[str] = None
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evaluations: List[AnswerEvaluation] = []
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teacher_notes: Optional[str] = None
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ai_feedback: Optional[str] = None
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created_at: datetime
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updated_at: datetime
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class CorrectionResponse(BaseModel):
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"""Response fuer eine Korrektur."""
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success: bool
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correction: Optional[Correction] = None
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error: Optional[str] = None
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class OCRResponse(BaseModel):
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"""Response fuer OCR-Ergebnis."""
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success: bool
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extracted_text: Optional[str] = None
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regions: List[Dict[str, Any]] = []
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confidence: float = 0.0
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error: Optional[str] = None
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class AnalysisResponse(BaseModel):
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"""Response fuer Analyse-Ergebnis."""
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success: bool
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evaluations: List[AnswerEvaluation] = []
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total_points: float = 0.0
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percentage: float = 0.0
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suggested_grade: Optional[str] = None
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ai_feedback: Optional[str] = None
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error: Optional[str] = None
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