export const dynamic = 'force-dynamic' import { NextRequest, NextResponse } from 'next/server' import { createClient } from '@/lib/supabase/server' import { createAnthropicClient } from '@/lib/claude/client' import { getApiKey } from '@/lib/settings' export async function POST( _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 since = new Date(Date.now() - 60_000).toISOString() const { count: recentCount } = await supabase .from('audit_log') .select('id', { count: 'exact', head: true }) .eq('changed_by', user.id) .eq('action', 'ai_rca_draft') .gte('changed_at', since) if ((recentCount ?? 0) > 0) return NextResponse.json({ error: 'Rate limited — please wait 60 seconds' }, { status: 429 }) const anthropicKey = await getApiKey(supabase, 'ANTHROPIC_API_KEY') const anthropic = createAnthropicClient(anthropicKey) const { data: incident } = await supabase .from('incidents') .select(` id, incident_type, description, severity, injury_involved, medical_status, is_fatality, is_serious_bodily_injury, triage_notes, sites (name), zones (name) `) .eq('id', id) .single() if (!incident) return NextResponse.json({ error: 'Not found' }, { status: 404 }) const inc = incident as { incident_type: string description: string severity: number | null injury_involved: boolean medical_status: string | null is_fatality: boolean is_serious_bodily_injury: boolean triage_notes: string | null } const siteName = (incident.sites as unknown as { name: string } | null)?.name ?? 'Unknown' const zoneName = (incident.zones as unknown as { name: string } | null)?.name ?? 'Unknown' let message: Awaited> try { message = await anthropic.messages.create({ model: 'claude-opus-4-8', thinking: { type: 'adaptive' }, max_tokens: 2048, tools: [{ name: 'draft_rca', description: 'Draft a 5-Why root cause analysis and CAPA suggestions for an HSE incident', input_schema: { type: 'object' as const, properties: { five_why_steps: { type: 'array', items: { type: 'object', properties: { why: { type: 'string', description: 'The why question' }, answer: { type: 'string', description: 'The finding or answer' }, }, required: ['why', 'answer'], }, description: '3 to 5 why steps', }, root_cause_summary: { type: 'string', description: 'One-sentence root cause statement', }, capa_suggestions: { type: 'array', items: { type: 'string' }, description: 'Up to 3 corrective/preventive action suggestions', }, }, required: ['five_why_steps', 'root_cause_summary', 'capa_suggestions'], }, }], tool_choice: { type: 'tool', name: 'draft_rca' }, messages: [{ role: 'user', content: `You are an experienced HSE investigator for a Malaysian 3PL warehouse. Draft a 5-Why root cause analysis for this incident. Site: ${siteName} Zone: ${zoneName} Incident type: ${inc.incident_type} Description: ${inc.description} Severity: ${inc.severity ?? 'not yet assigned'}/5 Injury involved: ${inc.injury_involved ? `yes — ${inc.medical_status}` : 'no'} Fatality: ${inc.is_fatality ? 'yes' : 'no'} Serious bodily injury: ${inc.is_serious_bodily_injury ? 'yes' : 'no'} Triage notes: ${inc.triage_notes ?? 'none'} Provide 3–5 Why steps drilling from immediate cause to root cause. Give a one-sentence root cause statement. Suggest 3 corrective/preventive actions appropriate for a Malaysian warehouse context.`, }], }) } catch { return NextResponse.json({ error: 'AI service unavailable' }, { status: 503 }) } const toolBlock = message.content.find(b => b.type === 'tool_use') if (!toolBlock || toolBlock.type !== 'tool_use') return NextResponse.json({ error: 'AI draft failed' }, { status: 500 }) const draft = toolBlock.input as { five_why_steps?: unknown root_cause_summary?: unknown capa_suggestions?: unknown } if ( !Array.isArray(draft.five_why_steps) || typeof draft.root_cause_summary !== 'string' || !Array.isArray(draft.capa_suggestions) ) { return NextResponse.json({ error: 'AI returned unexpected structure' }, { status: 500 }) } await supabase.rpc('write_audit_log', { p_table_name: 'incidents', p_record_id: id, p_action: 'ai_rca_draft', p_new_value: { root_cause_summary: draft.root_cause_summary, model: 'claude-opus-4-8', } as never, }) return NextResponse.json(draft) }