ims/app/api/incidents/[id]/similar/route.ts

export const dynamic = 'force-dynamic'

import { NextRequest, NextResponse } from 'next/server'
import { createClient } from '@/lib/supabase/server'
import { embedText } from '@/lib/claude/embed'
import { getApiKey } from '@/lib/settings'

export async function GET(
  _request: NextRequest,
  { params }: { params: Promise<{ id: string }> }
) {
  const { id } = await params
  const supabase = await createClient()
  const { data: { user }, error: authError } = await supabase.auth.getUser()
  if (authError || !user) return NextResponse.json({ error: 'Unauthorized' }, { status: 401 })

  const { data: profile } = await supabase.from('users').select('role').eq('id', user.id).single()
  if (!profile || !['hse', 'admin'].includes(profile.role))
    return NextResponse.json({ error: 'Forbidden' }, { status: 403 })

  const googleAiKey = await getApiKey(supabase, 'GOOGLE_AI_API_KEY')

  const { data: incident } = await supabase
    .from('incidents')
    .select('id, description, embedding, status')
    .eq('id', id)
    .single()
  if (!incident) return NextResponse.json({ error: 'Not found' }, { status: 404 })

  const inc = incident as { id: string; description: string; embedding: string | null; status: string }

  let embeddingVec: number[]
  try {
    if (inc.embedding) {
      embeddingVec = JSON.parse(inc.embedding) as number[]
    } else {
      embeddingVec = await embedText(inc.description, googleAiKey)
      // Closed incidents are locked at the DB level — the trigger would reject
      // this backfill. The vector still serves the similarity query below.
      if (inc.status !== 'closed') {
        const { error: persistError } = await supabase.from('incidents').update({
          embedding: `[${embeddingVec.join(',')}]` as unknown as string,
        }).eq('id', id)
        if (persistError) console.error('embedding backfill error:', persistError)
      }
    }
  } catch {
    return NextResponse.json({ error: 'Embedding service unavailable' }, { status: 503 })
  }

  const { data: similar } = await supabase.rpc('match_incidents', {
    query_embedding: `[${embeddingVec.join(',')}]`,
    exclude_id: id,
    match_count: 5,
  })

  return NextResponse.json(similar ?? [])
}