Files
ims/app/api/incidents/ai/quality-check/route.ts
T
adminandClaude Sonnet 4.6 b9ab94c9da feat: API key settings page — store ANTHROPIC/VOYAGE keys in DB with admin UI
- Migration: app_settings table with admin-only RLS (ANTHROPIC_API_KEY, VOYAGE_API_KEY)
- lib/settings.ts: getApiKey() reads DB first, falls back to env var
- lib/claude/client.ts: factory createAnthropicClient(apiKey) replaces singleton
- lib/claude/embed.ts: optional apiKey param, falls back to env
- 3 Claude AI routes + similar route: fetch key from settings before calling AI
- incidents/route.ts: fire-and-forget embed reads VOYAGE key from settings
- GET/POST /api/settings: admin-only masked key management endpoint
- /hse/settings page + ApiKeyForm client component

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01FFDuBhMKvoWjrWT3ZnGmmr
2026-07-11 17:46:40 +08:00

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TypeScript
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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) {
const supabase = await createClient()
const { data: { user }, error: authError } = await supabase.auth.getUser()
if (authError || !user) return NextResponse.json({ error: 'Unauthorized' }, { status: 401 })
const anthropicKey = await getApiKey(supabase, 'ANTHROPIC_API_KEY')
const anthropic = createAnthropicClient(anthropicKey)
let body: { description?: string; incident_type?: string }
try {
body = await request.json()
} catch {
return NextResponse.json({ error: 'Invalid JSON body' }, { status: 400 })
}
if (!body.description || !body.incident_type) {
return NextResponse.json({ error: 'description and incident_type required' }, { status: 422 })
}
let message: Awaited<ReturnType<typeof anthropic.messages.create>>
try {
message = await anthropic.messages.create({
model: 'claude-opus-4-8',
thinking: { type: 'adaptive' },
max_tokens: 1024,
tools: [{
name: 'assess_quality',
description: 'Assess HSE incident report description quality',
input_schema: {
type: 'object' as const,
properties: {
score: { type: 'number', description: '1-10 quality score' },
passes: { type: 'boolean', description: 'True when score is 6 or above' },
feedback: { type: 'string', description: 'One-sentence quality summary' },
suggestions: {
type: 'array',
items: { type: 'string' },
description: 'Up to 3 concrete suggestions to improve the description',
},
},
required: ['score', 'passes', 'feedback', 'suggestions'],
},
}],
tool_choice: { type: 'tool', name: 'assess_quality' },
messages: [{
role: 'user',
content: `You are an HSE reporting assistant for a Malaysian 3PL warehouse. Assess this incident report description.
Incident type: ${body.incident_type}
Description: ${body.description}
Score 110 based on: specificity (location, time, persons involved), completeness (what happened + immediate actions), and clarity. Score 6 or above passes. If score is below 6, give up to 3 actionable suggestions.`,
}],
})
} 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 assessment failed' }, { status: 500 })
}
const input = toolBlock.input as {
score?: unknown
passes?: unknown
feedback?: unknown
suggestions?: unknown
}
if (
typeof input.score !== 'number' ||
typeof input.passes !== 'boolean' ||
typeof input.feedback !== 'string' ||
!Array.isArray(input.suggestions)
) {
return NextResponse.json({ error: 'AI returned unexpected structure' }, { status: 500 })
}
return NextResponse.json(input)
}