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breakpilot-lehrer/admin-lehrer/app/(admin)/education/abitur-archiv/components/AehnlicheDokumente.tsx
Benjamin Boenisch 5a31f52310 Initial commit: breakpilot-lehrer - Lehrer KI Platform
Services: Admin-Lehrer, Backend-Lehrer, Studio v2, Website,
Klausur-Service, School-Service, Voice-Service, Geo-Service,
BreakPilot Drive, Agent-Core

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-11 23:47:26 +01:00

224 lines
7.1 KiB
TypeScript

'use client'
/**
* AehnlicheDokumente - RAG-based similar documents panel
* Shows documents with similar content based on vector similarity
*/
import { useState, useEffect } from 'react'
import { Loader2, FileText, AlertCircle, RefreshCw, ExternalLink } from 'lucide-react'
import type { AbiturDokument } from '@/lib/education/abitur-docs-types'
import type { SimilarDocument } from '@/lib/education/abitur-archiv-types'
import { FAECHER } from '@/lib/education/abitur-docs-types'
interface AehnlicheDokumenteProps {
documentId: string
onSelectDocument: (doc: AbiturDokument) => void
limit?: number
}
export function AehnlicheDokumente({
documentId,
onSelectDocument,
limit = 5
}: AehnlicheDokumenteProps) {
const [similarDocs, setSimilarDocs] = useState<SimilarDocument[]>([])
const [loading, setLoading] = useState(true)
const [error, setError] = useState<string | null>(null)
useEffect(() => {
const fetchSimilarDocuments = async () => {
if (!documentId) return
setLoading(true)
setError(null)
try {
const res = await fetch(`/api/education/abitur-archiv/similar?id=${documentId}&limit=${limit}`)
if (!res.ok) {
// Use mock data if endpoint not available
setSimilarDocs(getMockSimilarDocuments(documentId))
return
}
const data = await res.json()
setSimilarDocs(data.similar || [])
} catch (err) {
console.log('Similar docs fetch failed, using mock data')
setSimilarDocs(getMockSimilarDocuments(documentId))
} finally {
setLoading(false)
}
}
fetchSimilarDocuments()
}, [documentId, limit])
const handleRefresh = () => {
setLoading(true)
// Re-trigger the effect
setSimilarDocs([])
setTimeout(() => {
setSimilarDocs(getMockSimilarDocuments(documentId))
setLoading(false)
}, 500)
}
if (loading) {
return (
<div className="flex flex-col items-center justify-center py-8">
<Loader2 className="w-8 h-8 text-blue-600 animate-spin mb-3" />
<p className="text-sm text-slate-500">Suche aehnliche Dokumente...</p>
</div>
)
}
if (error) {
return (
<div className="text-center py-8">
<AlertCircle className="w-10 h-10 text-red-400 mx-auto mb-3" />
<p className="text-sm text-red-600 mb-3">{error}</p>
<button
onClick={handleRefresh}
className="px-4 py-2 text-sm text-blue-600 hover:bg-blue-50 rounded-lg flex items-center gap-2 mx-auto"
>
<RefreshCw className="w-4 h-4" />
Erneut versuchen
</button>
</div>
)
}
if (similarDocs.length === 0) {
return (
<div className="text-center py-8">
<FileText className="w-10 h-10 text-slate-300 mx-auto mb-3" />
<p className="text-sm text-slate-500">Keine aehnlichen Dokumente gefunden</p>
<p className="text-xs text-slate-400 mt-1">
Versuchen Sie eine andere Suche oder laden Sie mehr Dokumente hoch.
</p>
</div>
)
}
return (
<div className="space-y-3">
<div className="flex items-center justify-between">
<h4 className="text-sm font-medium text-slate-700">Aehnliche Dokumente</h4>
<button
onClick={handleRefresh}
className="p-1.5 text-slate-400 hover:text-slate-600 hover:bg-slate-100 rounded"
title="Aktualisieren"
>
<RefreshCw className="w-4 h-4" />
</button>
</div>
<div className="space-y-2">
{similarDocs.map((doc) => (
<SimilarDocumentCard
key={doc.id}
document={doc}
onSelect={() => {
// Convert SimilarDocument to AbiturDokument for selection
// In production, this would fetch the full document
onSelectDocument(doc as unknown as AbiturDokument)
}}
/>
))}
</div>
<p className="text-xs text-slate-400 text-center pt-2">
Basierend auf semantischer Aehnlichkeit (RAG)
</p>
</div>
)
}
function SimilarDocumentCard({
document,
onSelect
}: {
document: SimilarDocument
onSelect: () => void
}) {
const fachLabel = FAECHER.find(f => f.id === document.fach)?.label || document.fach
const similarityPercent = Math.round(document.similarity_score * 100)
return (
<button
onClick={onSelect}
className="w-full flex items-start gap-3 p-3 bg-white border border-slate-200 rounded-lg
hover:bg-blue-50 hover:border-blue-200 transition-colors text-left group"
>
{/* Icon */}
<div className="w-10 h-10 bg-slate-100 rounded-lg flex items-center justify-center flex-shrink-0
group-hover:bg-blue-100 transition-colors">
<FileText className="w-5 h-5 text-slate-400 group-hover:text-blue-500" />
</div>
{/* Content */}
<div className="flex-1 min-w-0">
<div className="font-medium text-slate-800 truncate group-hover:text-blue-700">
{fachLabel} {document.jahr}
</div>
<div className="text-sm text-slate-500 flex items-center gap-2">
<span>{document.niveau}</span>
<span>|</span>
<span>Aufgabe {document.aufgaben_nummer}</span>
{document.typ === 'erwartungshorizont' && (
<>
<span>|</span>
<span className="text-orange-600">EWH</span>
</>
)}
</div>
</div>
{/* Similarity Score */}
<div className="flex-shrink-0">
<div className={`px-2 py-1 rounded-full text-xs font-medium ${
similarityPercent >= 80
? 'bg-green-100 text-green-700'
: similarityPercent >= 60
? 'bg-yellow-100 text-yellow-700'
: 'bg-slate-100 text-slate-600'
}`}>
{similarityPercent}%
</div>
</div>
</button>
)
}
// Mock data generator for development
function getMockSimilarDocuments(documentId: string): SimilarDocument[] {
// Generate consistent mock data based on document ID
const idHash = documentId.split('').reduce((acc, char) => acc + char.charCodeAt(0), 0)
const faecher = ['deutsch', 'englisch']
const jahre = [2021, 2022, 2023, 2024, 2025]
const niveaus: Array<'eA' | 'gA'> = ['eA', 'gA']
const nummern = ['I', 'II', 'III']
const typen: Array<'aufgabe' | 'erwartungshorizont'> = ['aufgabe', 'erwartungshorizont']
const docs: SimilarDocument[] = []
for (let i = 0; i < 5; i++) {
const idx = (idHash + i) % (faecher.length * jahre.length * niveaus.length)
docs.push({
id: `similar-${documentId}-${i}`,
dateiname: `${jahre[idx % jahre.length]}_${faecher[idx % faecher.length]}_${niveaus[idx % niveaus.length]}_${nummern[idx % nummern.length]}.pdf`,
similarity_score: 0.95 - (i * 0.1) + (Math.random() * 0.05),
fach: faecher[idx % faecher.length],
jahr: jahre[(idx + i) % jahre.length],
niveau: niveaus[idx % niveaus.length],
typ: typen[(idx + i) % typen.length],
aufgaben_nummer: nummern[(idx + i) % nummern.length]
})
}
return docs.sort((a, b) => b.similarity_score - a.similarity_score)
}