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

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

backend-lehrer/learning_units_api.py

@@ -1,376 +1,4 @@
-from typing import List, Dict, Any, Optional
-from datetime import datetime
-from pathlib import Path
-import json
-import os
-import logging
-
-from fastapi import APIRouter, HTTPException
-from pydantic import BaseModel
-
-from learning_units import (
-    LearningUnit,
-    LearningUnitCreate,
-    LearningUnitUpdate,
-    list_learning_units,
-    get_learning_unit,
-    create_learning_unit,
-    update_learning_unit,
-    delete_learning_unit,
-)
-
-logger = logging.getLogger(__name__)
-
-
-router = APIRouter(
-    prefix="/learning-units",
-    tags=["learning-units"],
-)
-
-
-# ---------- Payload-Modelle für das Frontend ----------
-
-
-class LearningUnitCreatePayload(BaseModel):
-    """
-    Payload so, wie er aus dem Frontend kommt:
-    {
-      "student": "...",
-      "subject": "...",
-      "title": "...",
-      "grade": "7a"
-    }
-    """
-    student: Optional[str] = None
-    subject: Optional[str] = None
-    title: Optional[str] = None
-    grade: Optional[str] = None
-
-
-class AttachWorksheetsPayload(BaseModel):
-    worksheet_files: List[str]
-
-
-class RemoveWorksheetPayload(BaseModel):
-    worksheet_file: str
-
-
-class GenerateFromAnalysisPayload(BaseModel):
-    analysis_data: Dict[str, Any]
-    num_questions: int = 8
-
-
-# ---------- Hilfsfunktion: Backend-Modell -> Frontend-Objekt ----------
-
-
-def unit_to_frontend_dict(lu: LearningUnit) -> Dict[str, Any]:
-    """
-    Wandelt eine LearningUnit in das Format um, das das Frontend erwartet.
-    Wichtig sind:
-    - id
-    - label  (sichtbarer Name)
-    - meta   (Untertitelzeile)
-    - worksheet_files (Liste von Dateinamen)
-    """
-    label = lu.title or "Lerneinheit"
-
-    # Meta-Text: z.B. "Thema: Auge · Klasse: 7a · angelegt am 10.12.2025"
-    meta_parts: List[str] = []
-    if lu.topic:
-        meta_parts.append(f"Thema: {lu.topic}")
-    if lu.grade_level:
-        meta_parts.append(f"Klasse: {lu.grade_level}")
-    created_str = lu.created_at.strftime("%d.%m.%Y")
-    meta_parts.append(f"angelegt am {created_str}")
-
-    meta = " · ".join(meta_parts)
-
-    return {
-        "id": lu.id,
-        "label": label,
-        "meta": meta,
-        "title": lu.title,
-        "topic": lu.topic,
-        "grade_level": lu.grade_level,
-        "language": lu.language,
-        "status": lu.status,
-        "worksheet_files": lu.worksheet_files,
-        "created_at": lu.created_at.isoformat(),
-        "updated_at": lu.updated_at.isoformat(),
-    }
-
-
-# ---------- Endpunkte ----------
-
-
-@router.get("/", response_model=List[Dict[str, Any]])
-def api_list_learning_units():
-    """Alle Lerneinheiten für das Frontend auflisten."""
-    units = list_learning_units()
-    return [unit_to_frontend_dict(u) for u in units]
-
-
-@router.post("/", response_model=Dict[str, Any])
-def api_create_learning_unit(payload: LearningUnitCreatePayload):
-    """
-    Neue Lerneinheit anlegen.
-    Mapped das Frontend-Payload (student/subject/title/grade)
-    auf das generische LearningUnit-Modell.
-    """
-
-    # Mindestens eines der Felder muss gesetzt sein
-    if not (payload.student or payload.subject or payload.title):
-        raise HTTPException(
-            status_code=400,
-            detail="Bitte mindestens Schüler/in, Fach oder Thema angeben.",
-        )
-
-    # Titel/Topic bestimmen
-    # sichtbarer Titel: bevorzugt Thema (title), sonst Kombination
-    if payload.title:
-        title = payload.title
-    else:
-        parts = []
-        if payload.subject:
-            parts.append(payload.subject)
-        if payload.student:
-            parts.append(payload.student)
-        title = " – ".join(parts) if parts else "Lerneinheit"
-
-    topic = payload.title or payload.subject or None
-    grade_level = payload.grade or None
-
-    lu_create = LearningUnitCreate(
-        title=title,
-        description=None,
-        topic=topic,
-        grade_level=grade_level,
-        language="de",
-        worksheet_files=[],
-        status="raw",
-    )
-
-    lu = create_learning_unit(lu_create)
-    return unit_to_frontend_dict(lu)
-
-
-@router.post("/{unit_id}/attach-worksheets", response_model=Dict[str, Any])
-def api_attach_worksheets(unit_id: str, payload: AttachWorksheetsPayload):
-    """
-    Fügt der Lerneinheit eine oder mehrere Arbeitsblätter hinzu.
-    """
-    lu = get_learning_unit(unit_id)
-    if not lu:
-        raise HTTPException(status_code=404, detail="Lerneinheit nicht gefunden.")
-
-    files_to_add = [f for f in payload.worksheet_files if f not in lu.worksheet_files]
-    if files_to_add:
-        new_list = lu.worksheet_files + files_to_add
-        update = LearningUnitUpdate(worksheet_files=new_list)
-        lu = update_learning_unit(unit_id, update)
-        if not lu:
-            raise HTTPException(status_code=500, detail="Lerneinheit konnte nicht aktualisiert werden.")
-
-    return unit_to_frontend_dict(lu)
-
-
-@router.post("/{unit_id}/remove-worksheet", response_model=Dict[str, Any])
-def api_remove_worksheet(unit_id: str, payload: RemoveWorksheetPayload):
-    """
-    Entfernt genau ein Arbeitsblatt aus der Lerneinheit.
-    """
-    lu = get_learning_unit(unit_id)
-    if not lu:
-        raise HTTPException(status_code=404, detail="Lerneinheit nicht gefunden.")
-
-    if payload.worksheet_file not in lu.worksheet_files:
-        # Nichts zu tun, aber kein Fehler – einfach unverändert zurückgeben
-        return unit_to_frontend_dict(lu)
-
-    new_list = [f for f in lu.worksheet_files if f != payload.worksheet_file]
-    update = LearningUnitUpdate(worksheet_files=new_list)
-    lu = update_learning_unit(unit_id, update)
-    if not lu:
-        raise HTTPException(status_code=500, detail="Lerneinheit konnte nicht aktualisiert werden.")
-
-    return unit_to_frontend_dict(lu)
-
-
-@router.delete("/{unit_id}")
-def api_delete_learning_unit(unit_id: str):
-    """
-    Lerneinheit komplett löschen (aktuell vom Frontend noch nicht verwendet).
-    """
-    ok = delete_learning_unit(unit_id)
-    if not ok:
-        raise HTTPException(status_code=404, detail="Lerneinheit nicht gefunden.")
-    return {"status": "deleted", "id": unit_id}
-
-
-# ---------- Generator-Endpunkte ----------
-
-LERNEINHEITEN_DIR = os.path.expanduser("~/Arbeitsblaetter/Lerneinheiten")
-
-
-def _save_analysis_and_get_path(unit_id: str, analysis_data: Dict[str, Any]) -> Path:
-    """Save analysis_data to disk and return the path."""
-    os.makedirs(LERNEINHEITEN_DIR, exist_ok=True)
-    path = Path(LERNEINHEITEN_DIR) / f"{unit_id}_analyse.json"
-    with open(path, "w", encoding="utf-8") as f:
-        json.dump(analysis_data, f, ensure_ascii=False, indent=2)
-    return path
-
-
-@router.post("/{unit_id}/generate-qa")
-def api_generate_qa(unit_id: str, payload: GenerateFromAnalysisPayload):
-    """Generate Q&A items with Leitner fields from analysis data."""
-    lu = get_learning_unit(unit_id)
-    if not lu:
-        raise HTTPException(status_code=404, detail="Lerneinheit nicht gefunden.")
-
-    analysis_path = _save_analysis_and_get_path(unit_id, payload.analysis_data)
-
-    try:
-        from ai_processing.qa_generator import generate_qa_from_analysis
-        qa_path = generate_qa_from_analysis(analysis_path, num_questions=payload.num_questions)
-        with open(qa_path, "r", encoding="utf-8") as f:
-            qa_data = json.load(f)
-
-        # Update unit status
-        update_learning_unit(unit_id, LearningUnitUpdate(status="qa_generated"))
-        logger.info(f"Generated QA for unit {unit_id}: {len(qa_data.get('qa_items', []))} items")
-        return qa_data
-    except Exception as e:
-        logger.error(f"QA generation failed for {unit_id}: {e}")
-        raise HTTPException(status_code=500, detail=f"QA-Generierung fehlgeschlagen: {e}")
-
-
-@router.post("/{unit_id}/generate-mc")
-def api_generate_mc(unit_id: str, payload: GenerateFromAnalysisPayload):
-    """Generate multiple choice questions from analysis data."""
-    lu = get_learning_unit(unit_id)
-    if not lu:
-        raise HTTPException(status_code=404, detail="Lerneinheit nicht gefunden.")
-
-    analysis_path = _save_analysis_and_get_path(unit_id, payload.analysis_data)
-
-    try:
-        from ai_processing.mc_generator import generate_mc_from_analysis
-        mc_path = generate_mc_from_analysis(analysis_path, num_questions=payload.num_questions)
-        with open(mc_path, "r", encoding="utf-8") as f:
-            mc_data = json.load(f)
-
-        update_learning_unit(unit_id, LearningUnitUpdate(status="mc_generated"))
-        logger.info(f"Generated MC for unit {unit_id}: {len(mc_data.get('questions', []))} questions")
-        return mc_data
-    except Exception as e:
-        logger.error(f"MC generation failed for {unit_id}: {e}")
-        raise HTTPException(status_code=500, detail=f"MC-Generierung fehlgeschlagen: {e}")
-
-
-@router.post("/{unit_id}/generate-cloze")
-def api_generate_cloze(unit_id: str, payload: GenerateFromAnalysisPayload):
-    """Generate cloze (fill-in-the-blank) items from analysis data."""
-    lu = get_learning_unit(unit_id)
-    if not lu:
-        raise HTTPException(status_code=404, detail="Lerneinheit nicht gefunden.")
-
-    analysis_path = _save_analysis_and_get_path(unit_id, payload.analysis_data)
-
-    try:
-        from ai_processing.cloze_generator import generate_cloze_from_analysis
-        cloze_path = generate_cloze_from_analysis(analysis_path)
-        with open(cloze_path, "r", encoding="utf-8") as f:
-            cloze_data = json.load(f)
-
-        update_learning_unit(unit_id, LearningUnitUpdate(status="cloze_generated"))
-        logger.info(f"Generated Cloze for unit {unit_id}: {len(cloze_data.get('cloze_items', []))} items")
-        return cloze_data
-    except Exception as e:
-        logger.error(f"Cloze generation failed for {unit_id}: {e}")
-        raise HTTPException(status_code=500, detail=f"Cloze-Generierung fehlgeschlagen: {e}")
-
-
-@router.get("/{unit_id}/qa")
-def api_get_qa(unit_id: str):
-    """Get generated QA items for a unit."""
-    qa_path = Path(LERNEINHEITEN_DIR) / f"{unit_id}_qa.json"
-    if not qa_path.exists():
-        raise HTTPException(status_code=404, detail="Keine QA-Daten gefunden.")
-    with open(qa_path, "r", encoding="utf-8") as f:
-        return json.load(f)
-
-
-@router.get("/{unit_id}/mc")
-def api_get_mc(unit_id: str):
-    """Get generated MC questions for a unit."""
-    mc_path = Path(LERNEINHEITEN_DIR) / f"{unit_id}_mc.json"
-    if not mc_path.exists():
-        raise HTTPException(status_code=404, detail="Keine MC-Daten gefunden.")
-    with open(mc_path, "r", encoding="utf-8") as f:
-        return json.load(f)
-
-
-@router.get("/{unit_id}/cloze")
-def api_get_cloze(unit_id: str):
-    """Get generated cloze items for a unit."""
-    cloze_path = Path(LERNEINHEITEN_DIR) / f"{unit_id}_cloze.json"
-    if not cloze_path.exists():
-        raise HTTPException(status_code=404, detail="Keine Cloze-Daten gefunden.")
-    with open(cloze_path, "r", encoding="utf-8") as f:
-        return json.load(f)
-
-
-@router.post("/{unit_id}/leitner/update")
-def api_update_leitner(unit_id: str, item_id: str, correct: bool):
-    """Update Leitner progress for a QA item."""
-    qa_path = Path(LERNEINHEITEN_DIR) / f"{unit_id}_qa.json"
-    if not qa_path.exists():
-        raise HTTPException(status_code=404, detail="Keine QA-Daten gefunden.")
-    try:
-        from ai_processing.qa_generator import update_leitner_progress
-        result = update_leitner_progress(qa_path, item_id, correct)
-        return result
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-
-@router.get("/{unit_id}/leitner/next")
-def api_get_next_review(unit_id: str, limit: int = 5):
-    """Get next Leitner review items."""
-    qa_path = Path(LERNEINHEITEN_DIR) / f"{unit_id}_qa.json"
-    if not qa_path.exists():
-        raise HTTPException(status_code=404, detail="Keine QA-Daten gefunden.")
-    try:
-        from ai_processing.qa_generator import get_next_review_items
-        items = get_next_review_items(qa_path, limit=limit)
-        return {"items": items, "count": len(items)}
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-
-class StoryGeneratePayload(BaseModel):
-    vocabulary: List[Dict[str, Any]]
-    language: str = "en"
-    grade_level: str = "5-8"
-
-
-@router.post("/{unit_id}/generate-story")
-def api_generate_story(unit_id: str, payload: StoryGeneratePayload):
-    """Generate a short story using vocabulary words."""
-    lu = get_learning_unit(unit_id)
-    if not lu:
-        raise HTTPException(status_code=404, detail="Lerneinheit nicht gefunden.")
-
-    try:
-        from story_generator import generate_story
-        result = generate_story(
-            vocabulary=payload.vocabulary,
-            language=payload.language,
-            grade_level=payload.grade_level,
-        )
-        return result
-    except Exception as e:
-        logger.error(f"Story generation failed for {unit_id}: {e}")
-        raise HTTPException(status_code=500, detail=f"Story-Generierung fehlgeschlagen: {e}")
-
+# Backward-compat shim -- module moved to units/learning_api.py
+import importlib as _importlib
+import sys as _sys
+_sys.modules[__name__] = _importlib.import_module("units.learning_api")