[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>
This commit is contained in:
Benjamin Admin
474
backend-lehrer/correction_endpoints.py
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474
backend-lehrer/correction_endpoints.py
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@@ -0,0 +1,474 @@
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"""
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Correction API - REST endpoint handlers.
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Workflow:
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1. Upload: Gescannte Klassenarbeit hochladen
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2. OCR: Text aus Handschrift extrahieren
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3. Analyse: Antworten analysieren und bewerten
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4. Feedback: KI-generiertes Feedback erstellen
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5. Export: Korrigierte Arbeit als PDF exportieren
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"""
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import logging
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import uuid
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import os
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from datetime import datetime
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from typing import Dict, Any, Optional
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from pathlib import Path
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from fastapi import APIRouter, HTTPException, UploadFile, File, BackgroundTasks
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from correction_models import (
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CorrectionStatus,
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AnswerEvaluation,
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CorrectionCreate,
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CorrectionUpdate,
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Correction,
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CorrectionResponse,
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AnalysisResponse,
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UPLOAD_DIR,
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)
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from correction_helpers import (
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corrections_store,
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calculate_grade,
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generate_ai_feedback,
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process_ocr,
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PDFService,
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CorrectionData,
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StudentInfo,
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)
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logger = logging.getLogger(__name__)
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router = APIRouter(
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prefix="/corrections",
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tags=["corrections"],
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)
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# ============================================================================
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# API Endpoints
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# ============================================================================
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@router.post("/", response_model=CorrectionResponse)
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async def create_correction(data: CorrectionCreate):
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"""
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Erstellt eine neue Korrektur.
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Noch ohne Datei - diese wird separat hochgeladen.
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"""
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correction_id = str(uuid.uuid4())
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now = datetime.utcnow()
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correction = Correction(
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id=correction_id,
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student_id=data.student_id,
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student_name=data.student_name,
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class_name=data.class_name,
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exam_title=data.exam_title,
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subject=data.subject,
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max_points=data.max_points,
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status=CorrectionStatus.UPLOADED,
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created_at=now,
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updated_at=now
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)
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corrections_store[correction_id] = correction
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logger.info(f"Created correction {correction_id} for {data.student_name}")
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return CorrectionResponse(success=True, correction=correction)
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@router.post("/{correction_id}/upload", response_model=CorrectionResponse)
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async def upload_exam(
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correction_id: str,
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background_tasks: BackgroundTasks,
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file: UploadFile = File(...)
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):
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"""
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Laedt gescannte Klassenarbeit hoch und startet OCR.
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Unterstuetzte Formate: PDF, PNG, JPG, JPEG
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"""
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correction = corrections_store.get(correction_id)
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if not correction:
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raise HTTPException(status_code=404, detail="Korrektur nicht gefunden")
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# Validiere Dateiformat
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allowed_extensions = {".pdf", ".png", ".jpg", ".jpeg"}
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file_ext = Path(file.filename).suffix.lower() if file.filename else ""
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if file_ext not in allowed_extensions:
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raise HTTPException(
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status_code=400,
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detail=f"Ungueltiges Dateiformat. Erlaubt: {', '.join(allowed_extensions)}"
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)
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# Speichere Datei
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file_path = UPLOAD_DIR / f"{correction_id}{file_ext}"
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try:
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content = await file.read()
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with open(file_path, "wb") as f:
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f.write(content)
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correction.file_path = str(file_path)
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correction.updated_at = datetime.utcnow()
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corrections_store[correction_id] = correction
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# Starte OCR im Hintergrund
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background_tasks.add_task(process_ocr, correction_id, str(file_path))
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logger.info(f"Uploaded file for correction {correction_id}: {file.filename}")
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return CorrectionResponse(success=True, correction=correction)
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except Exception as e:
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logger.error(f"Upload error: {e}")
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return CorrectionResponse(success=False, error=str(e))
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@router.get("/{correction_id}", response_model=CorrectionResponse)
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async def get_correction(correction_id: str):
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"""Ruft eine Korrektur ab."""
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correction = corrections_store.get(correction_id)
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if not correction:
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raise HTTPException(status_code=404, detail="Korrektur nicht gefunden")
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return CorrectionResponse(success=True, correction=correction)
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@router.get("/", response_model=Dict[str, Any])
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async def list_corrections(
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class_name: Optional[str] = None,
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status: Optional[CorrectionStatus] = None,
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limit: int = 50
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):
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"""Listet Korrekturen auf, optional gefiltert."""
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corrections = list(corrections_store.values())
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if class_name:
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corrections = [c for c in corrections if c.class_name == class_name]
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if status:
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corrections = [c for c in corrections if c.status == status]
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# Sortiere nach Erstellungsdatum (neueste zuerst)
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corrections.sort(key=lambda x: x.created_at, reverse=True)
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return {
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"total": len(corrections),
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"corrections": [c.dict() for c in corrections[:limit]]
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}
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@router.post("/{correction_id}/analyze", response_model=AnalysisResponse)
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async def analyze_correction(
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correction_id: str,
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expected_answers: Optional[Dict[str, str]] = None
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):
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"""
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Analysiert die extrahierten Antworten.
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Optional mit Musterloesung fuer automatische Bewertung.
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"""
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correction = corrections_store.get(correction_id)
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if not correction:
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raise HTTPException(status_code=404, detail="Korrektur nicht gefunden")
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if correction.status not in [CorrectionStatus.OCR_COMPLETE, CorrectionStatus.ANALYZED]:
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raise HTTPException(
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status_code=400,
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detail=f"Korrektur im falschen Status: {correction.status}"
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)
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if not correction.extracted_text:
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raise HTTPException(status_code=400, detail="Kein extrahierter Text vorhanden")
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try:
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correction.status = CorrectionStatus.ANALYZING
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corrections_store[correction_id] = correction
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# Einfache Analyse ohne LLM
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# Teile Text in Abschnitte (simuliert Aufgabenerkennung)
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text_parts = correction.extracted_text.split('\n\n')
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evaluations = []
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for i, part in enumerate(text_parts[:10], start=1): # Max 10 Aufgaben
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if len(part.strip()) < 5:
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continue
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# Simulierte Bewertung
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# In Produktion wuerde hier LLM-basierte Analyse stattfinden
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expected = expected_answers.get(str(i), "") if expected_answers else ""
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# Einfacher Textvergleich (in Produktion: semantischer Vergleich)
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is_correct = bool(expected and expected.lower() in part.lower())
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points = correction.max_points / len(text_parts) if text_parts else 0
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evaluation = AnswerEvaluation(
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question_number=i,
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extracted_text=part[:200], # Kuerzen fuer Response
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points_possible=points,
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points_awarded=points if is_correct else points * 0.5, # Teilpunkte
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feedback=f"Antwort zu Aufgabe {i}" + (" korrekt." if is_correct else " mit Verbesserungsbedarf."),
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is_correct=is_correct,
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confidence=0.7 # Simulierte Confidence
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)
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evaluations.append(evaluation)
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# Berechne Gesamtergebnis
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total_points = sum(e.points_awarded for e in evaluations)
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percentage = (total_points / correction.max_points * 100) if correction.max_points > 0 else 0
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suggested_grade = calculate_grade(percentage)
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# Generiere Feedback
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ai_feedback = generate_ai_feedback(
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evaluations, total_points, correction.max_points, correction.subject
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)
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# Aktualisiere Korrektur
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correction.evaluations = evaluations
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correction.total_points = total_points
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correction.percentage = percentage
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correction.grade = suggested_grade
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correction.ai_feedback = ai_feedback
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correction.status = CorrectionStatus.ANALYZED
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correction.updated_at = datetime.utcnow()
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corrections_store[correction_id] = correction
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logger.info(f"Analysis complete for {correction_id}: {total_points}/{correction.max_points}")
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return AnalysisResponse(
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success=True,
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evaluations=evaluations,
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total_points=total_points,
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percentage=percentage,
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suggested_grade=suggested_grade,
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ai_feedback=ai_feedback
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)
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except Exception as e:
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logger.error(f"Analysis error: {e}")
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correction.status = CorrectionStatus.ERROR
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corrections_store[correction_id] = correction
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return AnalysisResponse(success=False, error=str(e))
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@router.put("/{correction_id}", response_model=CorrectionResponse)
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async def update_correction(correction_id: str, data: CorrectionUpdate):
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"""
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Aktualisiert eine Korrektur.
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Ermoeglicht manuelle Anpassungen durch die Lehrkraft.
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"""
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correction = corrections_store.get(correction_id)
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if not correction:
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raise HTTPException(status_code=404, detail="Korrektur nicht gefunden")
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if data.evaluations is not None:
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correction.evaluations = data.evaluations
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correction.total_points = sum(e.points_awarded for e in data.evaluations)
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correction.percentage = (
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correction.total_points / correction.max_points * 100
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) if correction.max_points > 0 else 0
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if data.total_points is not None:
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correction.total_points = data.total_points
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correction.percentage = (
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data.total_points / correction.max_points * 100
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) if correction.max_points > 0 else 0
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if data.grade is not None:
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correction.grade = data.grade
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if data.teacher_notes is not None:
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correction.teacher_notes = data.teacher_notes
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if data.status is not None:
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correction.status = data.status
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correction.updated_at = datetime.utcnow()
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corrections_store[correction_id] = correction
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return CorrectionResponse(success=True, correction=correction)
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@router.post("/{correction_id}/complete", response_model=CorrectionResponse)
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async def complete_correction(correction_id: str):
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"""Markiert Korrektur als abgeschlossen."""
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correction = corrections_store.get(correction_id)
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if not correction:
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raise HTTPException(status_code=404, detail="Korrektur nicht gefunden")
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correction.status = CorrectionStatus.COMPLETED
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correction.updated_at = datetime.utcnow()
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corrections_store[correction_id] = correction
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logger.info(f"Correction {correction_id} completed: {correction.grade}")
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return CorrectionResponse(success=True, correction=correction)
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@router.get("/{correction_id}/export-pdf")
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async def export_correction_pdf(correction_id: str):
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"""
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Exportiert korrigierte Arbeit als PDF.
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Enthaelt:
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- Originalscan
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- Bewertungen
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- Feedback
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- Gesamtergebnis
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"""
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correction = corrections_store.get(correction_id)
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if not correction:
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raise HTTPException(status_code=404, detail="Korrektur nicht gefunden")
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try:
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pdf_service = PDFService()
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# Erstelle CorrectionData
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correction_data = CorrectionData(
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student=StudentInfo(
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student_id=correction.student_id,
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name=correction.student_name,
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class_name=correction.class_name
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),
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exam_title=correction.exam_title,
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subject=correction.subject,
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date=correction.created_at.strftime("%d.%m.%Y"),
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max_points=correction.max_points,
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achieved_points=correction.total_points,
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grade=correction.grade or "",
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percentage=correction.percentage,
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corrections=[
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{
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"question": f"Aufgabe {e.question_number}",
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"answer": e.extracted_text,
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"points": f"{e.points_awarded}/{e.points_possible}",
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"feedback": e.feedback
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}
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for e in correction.evaluations
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],
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teacher_notes=correction.teacher_notes or "",
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ai_feedback=correction.ai_feedback or ""
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)
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# Generiere PDF
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pdf_bytes = pdf_service.generate_correction_pdf(correction_data)
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from fastapi.responses import Response
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return Response(
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content=pdf_bytes,
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media_type="application/pdf",
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headers={
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"Content-Disposition": f'attachment; filename="korrektur_{correction.student_name}_{correction.exam_title}.pdf"'
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}
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)
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except Exception as e:
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logger.error(f"PDF export error: {e}")
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raise HTTPException(status_code=500, detail=f"PDF-Export fehlgeschlagen: {str(e)}")
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@router.delete("/{correction_id}")
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async def delete_correction(correction_id: str):
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"""Loescht eine Korrektur."""
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if correction_id not in corrections_store:
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raise HTTPException(status_code=404, detail="Korrektur nicht gefunden")
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correction = corrections_store[correction_id]
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# Loesche auch die hochgeladene Datei
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if correction.file_path and os.path.exists(correction.file_path):
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try:
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os.remove(correction.file_path)
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except Exception as e:
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logger.warning(f"Could not delete file {correction.file_path}: {e}")
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del corrections_store[correction_id]
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logger.info(f"Deleted correction {correction_id}")
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return {"status": "deleted", "id": correction_id}
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@router.get("/class/{class_name}/summary")
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async def get_class_summary(class_name: str):
|
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"""
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Gibt Zusammenfassung fuer eine Klasse zurueck.
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Enthaelt Statistiken ueber alle Korrekturen der Klasse.
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"""
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class_corrections = [
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c for c in corrections_store.values()
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if c.class_name == class_name and c.status == CorrectionStatus.COMPLETED
|
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]
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if not class_corrections:
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return {
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"class_name": class_name,
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"total_students": 0,
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"average_percentage": 0,
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"grade_distribution": {},
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||||
"corrections": []
|
||||
}
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# Berechne Statistiken
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percentages = [c.percentage for c in class_corrections]
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average_percentage = sum(percentages) / len(percentages) if percentages else 0
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|
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# Notenverteilung
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grade_distribution = {}
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for c in class_corrections:
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grade = c.grade or "?"
|
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grade_distribution[grade] = grade_distribution.get(grade, 0) + 1
|
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|
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return {
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"class_name": class_name,
|
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"total_students": len(class_corrections),
|
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"average_percentage": round(average_percentage, 1),
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"average_points": round(
|
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sum(c.total_points for c in class_corrections) / len(class_corrections), 1
|
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),
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"grade_distribution": grade_distribution,
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"corrections": [
|
||||
{
|
||||
"id": c.id,
|
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"student_name": c.student_name,
|
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"total_points": c.total_points,
|
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"percentage": c.percentage,
|
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"grade": c.grade
|
||||
}
|
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for c in sorted(class_corrections, key=lambda x: x.student_name)
|
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]
|
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}
|
||||
|
||||
|
||||
@router.post("/{correction_id}/ocr/retry", response_model=CorrectionResponse)
|
||||
async def retry_ocr(correction_id: str, background_tasks: BackgroundTasks):
|
||||
"""
|
||||
Wiederholt OCR-Verarbeitung.
|
||||
|
||||
Nuetzlich wenn erste Verarbeitung fehlgeschlagen ist.
|
||||
"""
|
||||
correction = corrections_store.get(correction_id)
|
||||
if not correction:
|
||||
raise HTTPException(status_code=404, detail="Korrektur nicht gefunden")
|
||||
|
||||
if not correction.file_path:
|
||||
raise HTTPException(status_code=400, detail="Keine Datei vorhanden")
|
||||
|
||||
if not os.path.exists(correction.file_path):
|
||||
raise HTTPException(status_code=400, detail="Datei nicht mehr vorhanden")
|
||||
|
||||
# Starte OCR erneut
|
||||
correction.status = CorrectionStatus.UPLOADED
|
||||
correction.extracted_text = None
|
||||
correction.updated_at = datetime.utcnow()
|
||||
corrections_store[correction_id] = correction
|
||||
|
||||
background_tasks.add_task(process_ocr, correction_id, correction.file_path)
|
||||
|
||||
return CorrectionResponse(success=True, correction=correction)
|
||||
Reference in New Issue
Block a user