from .base import BaseLanguageAgent
from ..normalizers import normalize_it_text
from ..system_strings import build_contextual_system_vocabulary, build_system_vocabulary


class ItalianAgent(BaseLanguageAgent):
    locale = "it"
    tone = "professional and approachable"
    preferred_formality = "polite"
    vocabulary_map = {
        **build_system_vocabulary(
            "it",
            (
                "weeks_1_2",
                "without_commitment",
                "transparent_label",
                "transparent_investment",
                "customization_integrations",
                "multilingual_rollout",
            ),
        ),
    }
    _system_contextual = build_contextual_system_vocabulary("it", ("transparent_label",))
    contextual_vocabulary_map = {
        "badge": {**_system_contextual.get("badge", {})},
        "label": {**_system_contextual.get("label", {})},
        "metric": {**_system_contextual.get("metric", {})},
        "stat": {**_system_contextual.get("stat", {})},
        "rendered": {**_system_contextual.get("rendered", {})},
    }
    cta_defaults = {
        "starter": "Prenota una call iniziale",
        "business": "Pianifica la call business",
        "support": "Richiedi supporto",
        "service": "Mostra i servizi",
        "project": "Avvia il tuo progetto",
        "quote": "Richiedi una proposta",
        "contact": "Pianifica la riunione introduttiva",
    }

    def post_cleanup_text(self, text: str, field_path: str = "") -> str:
        return normalize_it_text(text, field_path=field_path)