feat: multiple translations with context, improved task examples

- Add WordTranslation model for storing multiple translations per word
- AI generates translations with example sentences and their translations
- Show example usage after answering tasks (learning + interface language)
- Save translations to word_translations table when adding words from tasks
- Improve word exclusion in new_words mode (stronger prompt + client filtering)
- Add migration for word_translations table

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

bot/handlers/vocabulary.py

@@ -69,33 +69,47 @@ async def process_word_addition(message: Message, state: FSMContext, word: str):
     lang = (user.language_interface if user else 'ru') or 'ru'
     processing_msg = await message.answer(t(lang, 'add.searching'))
 
-    # Получаем перевод через AI
+    # Получаем перевод через AI (с несколькими значениями)
     async with async_session_maker() as session:
         user = await UserService.get_user_by_telegram_id(session, message.from_user.id)
     source_lang = user.learning_language if user else 'en'
     ui_lang = user.language_interface if user else 'ru'
-    word_data = await ai_service.translate_word(word, source_lang=source_lang, translation_lang=ui_lang)
+    word_data = await ai_service.translate_word_with_contexts(
+        word, source_lang=source_lang, translation_lang=ui_lang, max_translations=3
+    )
 
     # Удаляем сообщение о загрузке
     await processing_msg.delete()
 
-    # Формируем примеры
-    examples_text = ""
-    if word_data.get("examples"):
-        examples_text = "\n\n" + t(lang, 'add.examples_header') + "\n"
-        for idx, example in enumerate(word_data["examples"][:2], 1):
-            src = example.get(source_lang) or example.get('en') or example.get('ru') or ''
-            tr = example.get(ui_lang) or example.get('ru') or example.get('en') or ''
-            examples_text += f"{idx}. {src}\n   <i>{tr}</i>\n"
+    # Формируем текст с переводами
+    translations = word_data.get("translations", [])
+    translations_text = ""
+
+    if translations:
+        # Основной перевод для backward compatibility
+        primary = next((tr for tr in translations if tr.get('is_primary')), translations[0])
+        word_data['translation'] = primary.get('translation', '')
+
+        translations_text = "\n\n" + t(lang, 'add.translations_header') + "\n"
+        for idx, tr in enumerate(translations, 1):
+            marker = "★ " if tr.get('is_primary') else ""
+            translations_text += f"{idx}. {marker}<b>{tr.get('translation', '')}</b>\n"
+            if tr.get('context'):
+                translations_text += f"   <i>«{tr.get('context', '')}»</i>\n"
+                if tr.get('context_translation'):
+                    translations_text += f"   <i>({tr.get('context_translation', '')})</i>\n"
+            translations_text += "\n"
+    else:
+        # Fallback если нет переводов
+        word_data['translation'] = 'Ошибка перевода'
 
     # Отправляем карточку слова
     card_text = (
         f"📝 <b>{word_data['word']}</b>\n"
         f"🔊 [{word_data.get('transcription', '')}]\n\n"
-        f"{t(lang, 'add.translation_label')}: {word_data['translation']}\n"
         f"{t(lang, 'add.category_label')}: {word_data.get('category', '')}\n"
         f"{t(lang, 'add.level_label')}: {word_data.get('difficulty', 'A1')}"
-        f"{examples_text}\n\n"
+        f"{translations_text}"
         f"{t(lang, 'add.confirm_question')}"
     )
 
@@ -130,7 +144,7 @@ async def confirm_add_word(callback: CallbackQuery, state: FSMContext):
         ui_lang = user.language_interface if user else 'ru'
 
         # Добавляем слово в базу
-        await VocabularyService.add_word(
+        new_word = await VocabularyService.add_word(
             session,
             user_id=user_id,
             word_original=word_data["word"],
@@ -138,12 +152,20 @@ async def confirm_add_word(callback: CallbackQuery, state: FSMContext):
             source_lang=source_lang,
             translation_lang=ui_lang,
             transcription=word_data.get("transcription"),
-            examples={"examples": word_data.get("examples", [])},
             category=word_data.get("category"),
             difficulty_level=word_data.get("difficulty"),
             source=WordSource.MANUAL
         )
 
+        # Сохраняем переводы с контекстами в отдельную таблицу
+        translations = word_data.get("translations", [])
+        if translations:
+            await VocabularyService.add_translations_bulk(
+                session,
+                vocabulary_id=new_word.id,
+                translations=translations
+            )
+
         # Получаем общее количество слов
         words_count = await VocabularyService.get_words_count(session, user_id, learning_lang=user.learning_language)
         lang = ui_lang or 'ru'