Add custom word entry + language pair support for learning units

- New UnitBuilder component with language pair selector (DE⇄EN, ES, FR, etc.)
- Manual word entry form with auto-suggest from Kaikki dictionary (6M words)
- "No results" prompt to add multi-word terms (e.g. "schottisches Hochland")
- New backend endpoint GET /vocabulary/lookup-translation (any→any via EN hub)
- Updated POST /vocabulary/units: accepts custom_words + source_lang/target_lang
- Split unit endpoints into vocabulary/unit_api.py (500 LOC budget)

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

backend-lehrer/vocabulary/api.py

@@ -22,11 +22,6 @@ from .db import (
     get_all_pos,
     VocabularyWord,
 )
-from units.learning import (
-    LearningUnitCreate,
-    create_learning_unit,
-    get_learning_unit,
-)
 
 logger = logging.getLogger(__name__)
 
@@ -239,130 +234,7 @@ async def api_tts(text: str = Query("", min_length=1), lang: str = Query("de")):
 # ---------------------------------------------------------------------------
 
 
-class CreateUnitFromWordsPayload(BaseModel):
-    title: str
-    word_ids: List[str]
-    grade: Optional[str] = None
-    language: Optional[str] = "de"
-
-
-@router.post("/units")
-async def api_create_unit_from_words(payload: CreateUnitFromWordsPayload):
-    """Create a learning unit from selected vocabulary word IDs.
-
-    Fetches full word details, creates a LearningUnit in the
-    learning_units system, and stores the vocabulary data.
-    """
-    if not payload.word_ids:
-        raise HTTPException(status_code=400, detail="Keine Woerter ausgewaehlt")
-
-    # Fetch all selected words
-    words = []
-    for wid in payload.word_ids:
-        word = await get_word(wid)
-        if word:
-            words.append(word)
-
-    if not words:
-        raise HTTPException(status_code=404, detail="Keine der Woerter gefunden")
-
-    # Create learning unit
-    lu = create_learning_unit(LearningUnitCreate(
-        title=payload.title,
-        topic="Vocabulary",
-        grade_level=payload.grade or "5-8",
-        language=payload.language or "de",
-        status="raw",
-    ))
-
-    # Save vocabulary data as analysis JSON for generators
-    import os
-    analysis_dir = os.path.expanduser("~/Arbeitsblaetter/Lerneinheiten")
-    os.makedirs(analysis_dir, exist_ok=True)
-
-    vocab_data = [w.to_dict() for w in words]
-    analysis_path = os.path.join(analysis_dir, f"{lu.id}_vocab.json")
-    with open(analysis_path, "w", encoding="utf-8") as f:
-        json.dump({"words": vocab_data, "title": payload.title}, f, ensure_ascii=False, indent=2)
-
-    # Also save as QA items for flashcards/type trainer
-    qa_items = []
-    for i, w in enumerate(words):
-        qa_items.append({
-            "id": f"qa_{i+1}",
-            "question": w.english,
-            "answer": w.german,
-            "question_type": "knowledge",
-            "key_terms": [w.english],
-            "difficulty": w.difficulty,
-            "source_hint": w.part_of_speech,
-            "leitner_box": 0,
-            "correct_count": 0,
-            "incorrect_count": 0,
-            "last_seen": None,
-            "next_review": None,
-            # Extra fields for enhanced flashcards
-            "ipa_en": w.ipa_en,
-            "ipa_de": w.ipa_de,
-            "syllables_en": w.syllables_en,
-            "syllables_de": w.syllables_de,
-            "example_en": w.example_en,
-            "example_de": w.example_de,
-            "image_url": w.image_url,
-            "audio_url_en": w.audio_url_en,
-            "audio_url_de": w.audio_url_de,
-            "part_of_speech": w.part_of_speech,
-            "translations": w.translations,
-        })
-
-    qa_path = os.path.join(analysis_dir, f"{lu.id}_qa.json")
-    with open(qa_path, "w", encoding="utf-8") as f:
-        json.dump({
-            "qa_items": qa_items,
-            "metadata": {
-                "subject": "English Vocabulary",
-                "grade_level": payload.grade or "5-8",
-                "source_title": payload.title,
-                "total_questions": len(qa_items),
-            },
-        }, f, ensure_ascii=False, indent=2)
-
-    # Auto-enrich words with images (Wikipedia + emoji fallback)
-    try:
-        from services.image_service import enrich_words_with_images
-        await enrich_words_with_images(payload.word_ids)
-    except Exception as e:
-        logger.warning(f"Image enrichment failed (non-critical): {e}")
-
-    logger.info(f"Created vocab unit {lu.id} with {len(words)} words")
-
-    return {
-        "unit_id": lu.id,
-        "title": payload.title,
-        "word_count": len(words),
-        "status": "created",
-    }
-
-
-@router.get("/units/{unit_id}")
-async def api_get_unit_words(unit_id: str):
-    """Get all words for a learning unit."""
-    import os
-    vocab_path = os.path.join(
-        os.path.expanduser("~/Arbeitsblaetter/Lerneinheiten"),
-        f"{unit_id}_vocab.json",
-    )
-    if not os.path.exists(vocab_path):
-        raise HTTPException(status_code=404, detail="Unit nicht gefunden")
-
-    with open(vocab_path, "r", encoding="utf-8") as f:
-        data = json.load(f)
-
-    return {
-        "unit_id": unit_id,
-        "title": data.get("title", ""),
-        "words": data.get("words", []),
-    }
+# Unit creation and translation lookup moved to vocabulary/unit_api.py
 
 
 # ---------------------------------------------------------------------------