'use client'

import { FileText, Hash, Image as ImageIcon, Library } from 'lucide-react'
import type { AdvisorEvidenceMeta } from '@/lib/sdk/advisor/evidence'
import { resolveRegulation } from '@/lib/sdk/advisor/regulation-display'

function Card({
  icon,
  value,
  label,
  dim,
}: {
  icon: React.ReactNode
  value: number
  label: string
  dim?: boolean
}) {
  return (
    <div
      className={`flex items-center gap-2 rounded-lg border px-2.5 py-1.5 ${
        dim ? 'border-gray-100 bg-gray-50' : 'border-gray-200 bg-white'
      }`}
    >
      <span className={dim ? 'text-gray-300' : 'text-indigo-500'}>{icon}</span>
      <span>
        <span className={`text-sm font-bold ${dim ? 'text-gray-400' : 'text-gray-900'}`}>{value}</span>{' '}
        <span className="text-[11px] text-gray-500">{label}</span>
      </span>
    </div>
  )
}

/**
 * "Antwort basiert auf" — honest, meaningful counts (not bare badges). Regelwerke = distinct
 * document FAMILIES (via resolveRegulation), so multi-part works like the DSK SDM count once.
 * No fabricated trust score — a real trust signal needs a defined basis (bindingness/coverage).
 */
export function EvidenceSummary({ meta }: { meta: AdvisorEvidenceMeta }) {
  const families = new Set(meta.sources.map((s) => resolveRegulation(s.regulation).familyKey)).size
  const cls = 'h-4 w-4'
  return (
    <div>
      <div className="mb-1.5 text-[10px] font-semibold uppercase tracking-wide text-gray-400">
        Antwort basiert auf
      </div>
      <div className="grid grid-cols-2 gap-1.5">
        <Card icon={<Library className={cls} />} value={families} label="Regelwerke" />
        <Card icon={<FileText className={cls} />} value={meta.sources.length} label="Evidence Units" />
        <Card icon={<ImageIcon className={cls} />} value={meta.figures.length} label="Abbildungen" dim={meta.figures.length === 0} />
        <Card icon={<Hash className={cls} />} value={meta.footnotes.length} label="Fußnoten" dim={meta.footnotes.length === 0} />
      </div>
    </div>
  )
}