[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>
This commit is contained in:
Benjamin Admin
@@ -16,11 +16,9 @@ Unterstützt:
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import logging
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import uuid
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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 typing import Dict
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from fastapi import APIRouter, HTTPException, UploadFile, File, Form
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from pydantic import BaseModel, Field
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from fastapi import APIRouter, HTTPException
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from generators import (
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MultipleChoiceGenerator,
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@@ -28,9 +26,22 @@ from generators import (
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MindmapGenerator,
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QuizGenerator
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)
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from generators.mc_generator import Difficulty
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from generators.cloze_generator import ClozeType
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from generators.quiz_generator import QuizType
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from worksheets_models import (
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ContentType,
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GenerateRequest,
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MCGenerateRequest,
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ClozeGenerateRequest,
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MindmapGenerateRequest,
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QuizGenerateRequest,
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BatchGenerateRequest,
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WorksheetContent,
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GenerateResponse,
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BatchGenerateResponse,
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parse_difficulty,
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parse_cloze_type,
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parse_quiz_types,
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)
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logger = logging.getLogger(__name__)
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@@ -40,89 +51,6 @@ router = APIRouter(
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)
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# ============================================================================
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# Pydantic Models
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# ============================================================================
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class ContentType(str, Enum):
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"""Verfügbare Content-Typen."""
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MULTIPLE_CHOICE = "multiple_choice"
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CLOZE = "cloze"
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MINDMAP = "mindmap"
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QUIZ = "quiz"
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class GenerateRequest(BaseModel):
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"""Basis-Request für Generierung."""
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source_text: str = Field(..., min_length=50, description="Quelltext für Generierung")
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topic: Optional[str] = Field(None, description="Thema/Titel")
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subject: Optional[str] = Field(None, description="Fach")
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grade_level: Optional[str] = Field(None, description="Klassenstufe")
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class MCGenerateRequest(GenerateRequest):
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"""Request für Multiple-Choice-Generierung."""
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num_questions: int = Field(5, ge=1, le=20, description="Anzahl Fragen")
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difficulty: str = Field("medium", description="easy, medium, hard")
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class ClozeGenerateRequest(GenerateRequest):
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"""Request für Lückentext-Generierung."""
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num_gaps: int = Field(5, ge=1, le=15, description="Anzahl Lücken")
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difficulty: str = Field("medium", description="easy, medium, hard")
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cloze_type: str = Field("fill_in", description="fill_in, drag_drop, dropdown")
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class MindmapGenerateRequest(GenerateRequest):
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"""Request für Mindmap-Generierung."""
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max_depth: int = Field(3, ge=2, le=5, description="Maximale Tiefe")
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class QuizGenerateRequest(GenerateRequest):
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"""Request für Quiz-Generierung."""
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quiz_types: List[str] = Field(
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["true_false", "matching"],
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description="Typen: true_false, matching, sorting, open_ended"
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)
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num_items: int = Field(5, ge=1, le=10, description="Items pro Typ")
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difficulty: str = Field("medium", description="easy, medium, hard")
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class BatchGenerateRequest(BaseModel):
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"""Request für Batch-Generierung mehrerer Content-Typen."""
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source_text: str = Field(..., min_length=50)
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content_types: List[str] = Field(..., description="Liste von Content-Typen")
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topic: Optional[str] = None
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subject: Optional[str] = None
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grade_level: Optional[str] = None
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difficulty: str = "medium"
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class WorksheetContent(BaseModel):
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"""Generierter Content."""
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id: str
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content_type: str
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data: Dict[str, Any]
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h5p_format: Optional[Dict[str, Any]] = None
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created_at: datetime
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topic: Optional[str] = None
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difficulty: Optional[str] = None
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class GenerateResponse(BaseModel):
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"""Response mit generiertem Content."""
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success: bool
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content: Optional[WorksheetContent] = None
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error: Optional[str] = None
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class BatchGenerateResponse(BaseModel):
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"""Response für Batch-Generierung."""
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success: bool
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contents: List[WorksheetContent] = []
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errors: List[str] = []
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# ============================================================================
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# In-Memory Storage (später durch DB ersetzen)
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# ============================================================================
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@@ -134,49 +62,12 @@ _generated_content: Dict[str, WorksheetContent] = {}
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# Generator Instances
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# ============================================================================
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# Generatoren ohne LLM-Client (automatische Generierung)
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# In Produktion würde hier der LLM-Client injiziert
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mc_generator = MultipleChoiceGenerator()
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cloze_generator = ClozeGenerator()
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mindmap_generator = MindmapGenerator()
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quiz_generator = QuizGenerator()
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# ============================================================================
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# Helper Functions
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# ============================================================================
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def _parse_difficulty(difficulty_str: str) -> Difficulty:
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"""Konvertiert String zu Difficulty Enum."""
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mapping = {
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"easy": Difficulty.EASY,
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"medium": Difficulty.MEDIUM,
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"hard": Difficulty.HARD
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}
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return mapping.get(difficulty_str.lower(), Difficulty.MEDIUM)
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def _parse_cloze_type(type_str: str) -> ClozeType:
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"""Konvertiert String zu ClozeType Enum."""
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mapping = {
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"fill_in": ClozeType.FILL_IN,
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"drag_drop": ClozeType.DRAG_DROP,
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"dropdown": ClozeType.DROPDOWN
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}
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return mapping.get(type_str.lower(), ClozeType.FILL_IN)
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def _parse_quiz_types(type_strs: List[str]) -> List[QuizType]:
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"""Konvertiert String-Liste zu QuizType Enums."""
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mapping = {
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"true_false": QuizType.TRUE_FALSE,
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"matching": QuizType.MATCHING,
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"sorting": QuizType.SORTING,
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"open_ended": QuizType.OPEN_ENDED
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}
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return [mapping.get(t.lower(), QuizType.TRUE_FALSE) for t in type_strs]
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def _store_content(content: WorksheetContent) -> None:
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"""Speichert generierten Content."""
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_generated_content[content.id] = content
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@@ -188,15 +79,9 @@ def _store_content(content: WorksheetContent) -> None:
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@router.post("/generate/multiple-choice", response_model=GenerateResponse)
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async def generate_multiple_choice(request: MCGenerateRequest):
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"""
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Generiert Multiple-Choice-Fragen aus Quelltext.
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- **source_text**: Text mit mind. 50 Zeichen
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- **num_questions**: Anzahl Fragen (1-20)
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- **difficulty**: easy, medium, hard
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"""
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"""Generiert Multiple-Choice-Fragen aus Quelltext."""
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try:
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difficulty = _parse_difficulty(request.difficulty)
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difficulty = parse_difficulty(request.difficulty)
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questions = mc_generator.generate(
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source_text=request.source_text,
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@@ -212,7 +97,6 @@ async def generate_multiple_choice(request: MCGenerateRequest):
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error="Keine Fragen generiert. Text möglicherweise zu kurz."
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)
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# Konvertiere zu Dict
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questions_dict = mc_generator.to_dict(questions)
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h5p_format = mc_generator.to_h5p_format(questions)
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@@ -227,7 +111,6 @@ async def generate_multiple_choice(request: MCGenerateRequest):
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)
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_store_content(content)
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return GenerateResponse(success=True, content=content)
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except Exception as e:
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@@ -237,15 +120,9 @@ async def generate_multiple_choice(request: MCGenerateRequest):
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@router.post("/generate/cloze", response_model=GenerateResponse)
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async def generate_cloze(request: ClozeGenerateRequest):
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"""
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Generiert Lückentext aus Quelltext.
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- **source_text**: Text mit mind. 50 Zeichen
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- **num_gaps**: Anzahl Lücken (1-15)
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- **cloze_type**: fill_in, drag_drop, dropdown
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"""
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"""Generiert Lückentext aus Quelltext."""
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try:
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cloze_type = _parse_cloze_type(request.cloze_type)
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cloze_type = parse_cloze_type(request.cloze_type)
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cloze = cloze_generator.generate(
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source_text=request.source_text,
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@@ -275,7 +152,6 @@ async def generate_cloze(request: ClozeGenerateRequest):
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)
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_store_content(content)
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return GenerateResponse(success=True, content=content)
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except Exception as e:
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@@ -285,12 +161,7 @@ async def generate_cloze(request: ClozeGenerateRequest):
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@router.post("/generate/mindmap", response_model=GenerateResponse)
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async def generate_mindmap(request: MindmapGenerateRequest):
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"""
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Generiert Mindmap aus Quelltext.
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- **source_text**: Text mit mind. 50 Zeichen
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- **max_depth**: Maximale Tiefe (2-5)
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"""
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"""Generiert Mindmap aus Quelltext."""
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try:
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mindmap = mindmap_generator.generate(
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source_text=request.source_text,
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@@ -317,14 +188,13 @@ async def generate_mindmap(request: MindmapGenerateRequest):
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"mermaid": mermaid,
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"json_tree": json_tree
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},
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h5p_format=None, # Mindmaps haben kein H5P-Format
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h5p_format=None,
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created_at=datetime.utcnow(),
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topic=request.topic,
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difficulty=None
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)
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_store_content(content)
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return GenerateResponse(success=True, content=content)
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except Exception as e:
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@@ -334,17 +204,10 @@ async def generate_mindmap(request: MindmapGenerateRequest):
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@router.post("/generate/quiz", response_model=GenerateResponse)
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async def generate_quiz(request: QuizGenerateRequest):
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"""
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Generiert Quiz mit verschiedenen Fragetypen.
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- **source_text**: Text mit mind. 50 Zeichen
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- **quiz_types**: Liste von true_false, matching, sorting, open_ended
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- **num_items**: Items pro Typ (1-10)
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"""
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"""Generiert Quiz mit verschiedenen Fragetypen."""
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try:
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quiz_types = _parse_quiz_types(request.quiz_types)
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quiz_types = parse_quiz_types(request.quiz_types)
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# Generate quiz for each type and combine results
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all_questions = []
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quizzes = []
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@@ -365,7 +228,6 @@ async def generate_quiz(request: QuizGenerateRequest):
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error="Quiz konnte nicht generiert werden. Text möglicherweise zu kurz."
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)
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# Combine all quizzes into a single dict
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combined_quiz_dict = {
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"quiz_types": [qt.value for qt in quiz_types],
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"title": f"Combined Quiz - {request.topic or 'Various Topics'}",
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@@ -374,12 +236,10 @@ async def generate_quiz(request: QuizGenerateRequest):
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"questions": []
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}
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# Add questions from each quiz
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for quiz in quizzes:
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quiz_dict = quiz_generator.to_dict(quiz)
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combined_quiz_dict["questions"].extend(quiz_dict.get("questions", []))
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# Use first quiz's H5P format as base (or empty if none)
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h5p_format = quiz_generator.to_h5p_format(quizzes[0]) if quizzes else {}
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content = WorksheetContent(
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@@ -393,7 +253,6 @@ async def generate_quiz(request: QuizGenerateRequest):
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)
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_store_content(content)
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return GenerateResponse(success=True, content=content)
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except Exception as e:
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@@ -403,22 +262,10 @@ async def generate_quiz(request: QuizGenerateRequest):
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@router.post("/generate/batch", response_model=BatchGenerateResponse)
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async def generate_batch(request: BatchGenerateRequest):
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"""
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Generiert mehrere Content-Typen aus einem Quelltext.
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Ideal für die Erstellung kompletter Arbeitsblätter mit
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verschiedenen Übungstypen.
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"""
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"""Generiert mehrere Content-Typen aus einem Quelltext."""
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contents = []
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errors = []
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type_mapping = {
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"multiple_choice": MCGenerateRequest,
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"cloze": ClozeGenerateRequest,
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"mindmap": MindmapGenerateRequest,
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"quiz": QuizGenerateRequest
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}
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for content_type in request.content_types:
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try:
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if content_type == "multiple_choice":
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