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


class SpanishAgent(BaseLanguageAgent):
    locale = "es"
    tone = "clear and business-focused"
    preferred_formality = "formal"
    vocabulary_map = {
        **build_system_vocabulary(
            "es",
            (
                "plan_badge",
                "response_time",
                "without_commitment",
                "transparent_label",
                "transparent_investment",
            ),
        ),
    }
    _system_contextual = build_contextual_system_vocabulary("es", ("plan_badge", "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", {})},
        "title": {**_system_contextual.get("title", {})},
        "heading": {**_system_contextual.get("heading", {})},
        "rendered": {**_system_contextual.get("rendered", {})},
    }
    cta_defaults = {
        "starter": "Reservar llamada inicial",
        "business": "Reservar llamada comercial",
        "support": "Solicitar soporte",
        "service": "Mostrar los servicios",
        "project": "Inicia tu proyecto",
        "quote": "Solicitar propuesta",
        "contact": "Planificar la reunión inicial",
    }

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