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43 lines
1.5 KiB
Python

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)