40 lines
1.6 KiB
Python
40 lines
1.6 KiB
Python
from .base import BaseLanguageAgent
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from ..normalizers import normalize_ru_text
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from ..system_strings import build_contextual_system_vocabulary, build_system_vocabulary
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class RussianAgent(BaseLanguageAgent):
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locale = "ru"
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tone = "professional and confident"
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preferred_formality = "neutral polite"
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vocabulary_map = {
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**build_system_vocabulary(
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"ru",
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(
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"customization_integrations",
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"detailed_page_structure",
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"without_commitment",
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),
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),
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}
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_system_contextual = build_contextual_system_vocabulary("ru", ("plan_badge", "transparent_label"))
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contextual_vocabulary_map = {
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"badge": {**_system_contextual.get("badge", {})},
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"label": {**_system_contextual.get("label", {})},
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"metric": {**_system_contextual.get("metric", {})},
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"stat": {**_system_contextual.get("stat", {})},
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"rendered": {**_system_contextual.get("rendered", {})},
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}
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cta_defaults = {
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"starter": "Запланировать стартовую консультацию",
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"business": "Обсудить бизнес-проект",
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"support": "Посмотреть поддержку",
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"service": "Посмотреть услуги",
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"project": "Запустить свой проект",
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"contact": "Отправить запрос",
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"quote": "Получить предложение",
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}
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def post_cleanup_text(self, text: str, field_path: str = "") -> str:
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return normalize_ru_text(text, field_path=field_path)
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