from __future__ import annotations from src.domain import Verdict from src.i18n import t from src.schemas import Finding, Kpis, MethodScore, Span, ValidationReport def decide_verdict(report: ValidationReport, n_docs: int, leftover: int, n_review: int) -> Verdict: if not report.ok: return Verdict.INVALID if n_docs <= 0: return Verdict.INSUFFICIENT if leftover > 0 or n_review > 0: return Verdict.REVIEW return Verdict.HOLD def status_label(verdict: Verdict, lang: str) -> str: mapping = { Verdict.REVIEW: t(lang, "status_review"), Verdict.HOLD: t(lang, "status_hold"), Verdict.INSUFFICIENT: t(lang, "status_insufficient"), Verdict.INVALID: t(lang, "status_invalid"), } return mapping[verdict] def reasons(policy: MethodScore, baseline: MethodScore, lang: str) -> list[str]: return [ t(lang, "reason_policy").format(p=f"{policy.precision:.2f}", r=f"{policy.recall:.2f}"), t(lang, "reason_baseline").format(p=f"{baseline.precision:.2f}", r=f"{baseline.recall:.2f}"), t(lang, "reason_over").format(n=f"{policy.over_redaction:.3f}", base=f"{baseline.over_redaction:.3f}"), t(lang, "reason_left").format(n=policy.leftover_exports), t(lang, "reason_meta").format(n=policy.metadata_leaks), t(lang, "reason_scope"), t(lang, "reason_no_llm"), ] def narrative(kpis: Kpis, lang: str) -> str: return t(lang, "narrative").format( docs=kpis.n_docs, spans=kpis.n_spans, precision=f"{100 * kpis.policy_precision:.0f}%", recall=f"{100 * kpis.policy_recall:.0f}%", leftover=kpis.leftover_exports, ) def finding_from_span(doc_id: str, span: Span, lang: str) -> Finding: preview = span.surface if len(span.surface) <= 6 else f"{span.surface[:2]}…{span.surface[-2:]}" return Finding( finding_id=span.finding_id, doc_id=doc_id, entity_type=span.entity_type.value, start=span.start, end=span.end, surface_preview=preview, confidence=span.confidence, method=span.method, rule_id=span.rule_id, workflow=span.workflow.value, reason=span.reason, language=span.language, observed=t(lang, "observed_span").format(start=span.start, end=span.end, rule=span.rule_id), inference=span.reason, action=t(lang, "action_span").format(kind=span.entity_type.value), )