feat: switch AI provider from Anthropic to DeepSeek
- lib/claude/client.ts: replace Anthropic SDK with openai package pointed at DeepSeek baseURL
- 4 AI routes: port tool definitions, tool_choice, and output parsing to OpenAI function-calling format
- Drop thinking:{type:'adaptive'} (no DeepSeek equivalent); model string → deepseek-chat
- settings/route.ts: add DEEPSEEK_API_KEY to ALLOWED_KEYS
- migration: seed DEEPSEEK_API_KEY placeholder row in app_settings
- tests: update 3 AI route tests to mock createDeepSeekClient + OpenAI response shape
Voyage AI embedding path untouched (DeepSeek has no embeddings endpoint).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CPf5Rc8QPx6V8KLEEgfKEQ
This commit is contained in:
@@ -2,7 +2,7 @@ export const dynamic = 'force-dynamic'
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import { NextResponse } from 'next/server'
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import { createClient } from '@/lib/supabase/server'
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import { createAnthropicClient } from '@/lib/claude/client'
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import { createDeepSeekClient } from '@/lib/claude/client'
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import { getApiKey } from '@/lib/settings'
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type ZoneAggregate = {
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@@ -92,41 +92,43 @@ export async function POST() {
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return NextResponse.json({ error: 'Rate limit: wait 60 seconds between AI requests' }, { status: 429 })
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}
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const anthropicKey = await getApiKey(supabase, 'ANTHROPIC_API_KEY')
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const anthropic = createAnthropicClient(anthropicKey)
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const deepseekKey = await getApiKey(supabase, 'DEEPSEEK_API_KEY')
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const client = createDeepSeekClient(deepseekKey)
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let message: Awaited<ReturnType<typeof anthropic.messages.create>>
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let res: Awaited<ReturnType<typeof client.chat.completions.create>>
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try {
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message = await anthropic.messages.create({
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model: 'claude-opus-4-8',
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thinking: { type: 'adaptive' },
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res = await client.chat.completions.create({
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model: 'deepseek-chat',
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max_tokens: 2048,
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tools: [{
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name: 'flag_rising_risk',
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description: 'Flag warehouse zones showing rising safety risk from 90-day incident aggregates',
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input_schema: {
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type: 'object' as const,
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properties: {
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flags: {
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type: 'array',
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items: {
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type: 'object',
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properties: {
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zone: { type: 'string' },
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site: { type: 'string' },
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risk_level: { type: 'string', enum: ['low', 'medium', 'high'] },
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rationale: { type: 'string', description: 'One or two sentences citing the numbers' },
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recommended_action: { type: 'string', description: 'One concrete preventive action' },
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type: 'function',
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function: {
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name: 'flag_rising_risk',
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description: 'Flag warehouse zones showing rising safety risk from 90-day incident aggregates',
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parameters: {
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type: 'object',
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properties: {
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flags: {
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type: 'array',
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items: {
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type: 'object',
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properties: {
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zone: { type: 'string' },
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site: { type: 'string' },
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risk_level: { type: 'string', enum: ['low', 'medium', 'high'] },
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rationale: { type: 'string', description: 'One or two sentences citing the numbers' },
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recommended_action: { type: 'string', description: 'One concrete preventive action' },
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},
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required: ['zone', 'site', 'risk_level', 'rationale', 'recommended_action'],
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},
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required: ['zone', 'site', 'risk_level', 'rationale', 'recommended_action'],
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},
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summary: { type: 'string', description: 'Two-sentence overall risk picture' },
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},
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summary: { type: 'string', description: 'Two-sentence overall risk picture' },
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required: ['flags', 'summary'],
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},
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required: ['flags', 'summary'],
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},
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}],
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tool_choice: { type: 'tool', name: 'flag_rising_risk' },
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tool_choice: { type: 'function', function: { name: 'flag_rising_risk' } },
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messages: [{
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role: 'user',
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content: `You are an HSE risk analyst for a Malaysian 3PL warehouse operator. Below are 90-day incident aggregates per zone. "first_half" is incidents in days 90-46, "second_half" is days 45-0 — a rising second_half means worsening trend. Near-miss and hazard reports are leading indicators; injuries are lagging.
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@@ -142,11 +144,13 @@ ${JSON.stringify(aggregates, null, 2)}
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return NextResponse.json({ error: 'AI service unavailable' }, { status: 503 })
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}
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const toolBlock = message.content.find(b => b.type === 'tool_use')
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if (!toolBlock || toolBlock.type !== 'tool_use')
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return NextResponse.json({ error: 'AI suggestion failed' }, { status: 500 })
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const call = res.choices[0]?.message?.tool_calls?.[0]
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if (!call || call.type !== 'function') return NextResponse.json({ error: 'AI suggestion failed' }, { status: 500 })
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let input: { flags?: unknown; summary?: unknown }
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try { input = JSON.parse(call.function.arguments) }
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catch { return NextResponse.json({ error: 'AI returned unexpected structure' }, { status: 500 }) }
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const input = toolBlock.input as { flags?: unknown; summary?: unknown }
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if (!Array.isArray(input.flags) || typeof input.summary !== 'string')
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return NextResponse.json({ error: 'AI returned unexpected structure' }, { status: 500 })
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@@ -164,7 +168,7 @@ ${JSON.stringify(aggregates, null, 2)}
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p_table_name: 'incidents',
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p_record_id: user.id,
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p_action: 'ai_risk_flags',
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p_new_value: { flags, summary: input.summary, model: 'claude-opus-4-8' } as never,
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p_new_value: { flags, summary: input.summary, model: 'deepseek-chat' } as never,
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})
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return NextResponse.json({ flags, summary: input.summary })
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@@ -2,7 +2,7 @@ export const dynamic = 'force-dynamic'
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import { NextRequest, NextResponse } from 'next/server'
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import { createClient } from '@/lib/supabase/server'
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import { createAnthropicClient } from '@/lib/claude/client'
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import { createDeepSeekClient } from '@/lib/claude/client'
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import { getApiKey } from '@/lib/settings'
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export async function POST(
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@@ -28,8 +28,8 @@ export async function POST(
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if ((recentCount ?? 0) > 0)
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return NextResponse.json({ error: 'Rate limited — please wait 60 seconds' }, { status: 429 })
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const anthropicKey = await getApiKey(supabase, 'ANTHROPIC_API_KEY')
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const anthropic = createAnthropicClient(anthropicKey)
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const deepseekKey = await getApiKey(supabase, 'DEEPSEEK_API_KEY')
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const client = createDeepSeekClient(deepseekKey)
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const { data: incident } = await supabase
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.from('incidents')
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@@ -55,44 +55,46 @@ export async function POST(
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const siteName = (incident.sites as unknown as { name: string } | null)?.name ?? 'Unknown'
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const zoneName = (incident.zones as unknown as { name: string } | null)?.name ?? 'Unknown'
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let message: Awaited<ReturnType<typeof anthropic.messages.create>>
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let res: Awaited<ReturnType<typeof client.chat.completions.create>>
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try {
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message = await anthropic.messages.create({
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model: 'claude-opus-4-8',
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thinking: { type: 'adaptive' },
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res = await client.chat.completions.create({
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model: 'deepseek-chat',
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max_tokens: 2048,
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tools: [{
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name: 'draft_rca',
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description: 'Draft a 5-Why root cause analysis and CAPA suggestions for an HSE incident',
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input_schema: {
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type: 'object' as const,
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properties: {
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five_why_steps: {
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type: 'array',
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items: {
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type: 'object',
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properties: {
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why: { type: 'string', description: 'The why question' },
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answer: { type: 'string', description: 'The finding or answer' },
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type: 'function',
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function: {
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name: 'draft_rca',
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description: 'Draft a 5-Why root cause analysis and CAPA suggestions for an HSE incident',
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parameters: {
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type: 'object',
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properties: {
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five_why_steps: {
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type: 'array',
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items: {
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type: 'object',
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properties: {
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why: { type: 'string', description: 'The why question' },
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answer: { type: 'string', description: 'The finding or answer' },
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},
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required: ['why', 'answer'],
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},
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required: ['why', 'answer'],
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description: '3 to 5 why steps',
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},
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root_cause_summary: {
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type: 'string',
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description: 'One-sentence root cause statement',
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},
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capa_suggestions: {
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type: 'array',
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items: { type: 'string' },
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description: 'Up to 3 corrective/preventive action suggestions',
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},
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description: '3 to 5 why steps',
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},
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root_cause_summary: {
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type: 'string',
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description: 'One-sentence root cause statement',
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},
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capa_suggestions: {
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type: 'array',
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items: { type: 'string' },
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description: 'Up to 3 corrective/preventive action suggestions',
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},
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required: ['five_why_steps', 'root_cause_summary', 'capa_suggestions'],
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},
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required: ['five_why_steps', 'root_cause_summary', 'capa_suggestions'],
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},
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}],
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tool_choice: { type: 'tool', name: 'draft_rca' },
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tool_choice: { type: 'function', function: { name: 'draft_rca' } },
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messages: [{
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role: 'user',
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content: `You are an experienced HSE investigator for a Malaysian 3PL warehouse. Draft a 5-Why root cause analysis for this incident.
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@@ -114,15 +116,12 @@ Provide 3–5 Why steps drilling from immediate cause to root cause. Give a one-
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return NextResponse.json({ error: 'AI service unavailable' }, { status: 503 })
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}
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const toolBlock = message.content.find(b => b.type === 'tool_use')
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if (!toolBlock || toolBlock.type !== 'tool_use')
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return NextResponse.json({ error: 'AI draft failed' }, { status: 500 })
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const call = res.choices[0]?.message?.tool_calls?.[0]
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if (!call || call.type !== 'function') return NextResponse.json({ error: 'AI draft failed' }, { status: 500 })
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const draft = toolBlock.input as {
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five_why_steps?: unknown
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root_cause_summary?: unknown
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capa_suggestions?: unknown
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}
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let draft: { five_why_steps?: unknown; root_cause_summary?: unknown; capa_suggestions?: unknown }
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try { draft = JSON.parse(call.function.arguments) }
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catch { return NextResponse.json({ error: 'AI returned unexpected structure' }, { status: 500 }) }
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if (
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!Array.isArray(draft.five_why_steps) ||
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@@ -138,7 +137,7 @@ Provide 3–5 Why steps drilling from immediate cause to root cause. Give a one-
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p_action: 'ai_rca_draft',
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p_new_value: {
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root_cause_summary: draft.root_cause_summary,
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model: 'claude-opus-4-8',
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model: 'deepseek-chat',
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} as never,
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})
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@@ -2,7 +2,7 @@ export const dynamic = 'force-dynamic'
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import { NextRequest, NextResponse } from 'next/server'
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import { createClient } from '@/lib/supabase/server'
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import { createAnthropicClient } from '@/lib/claude/client'
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import { createDeepSeekClient } from '@/lib/claude/client'
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import { getApiKey } from '@/lib/settings'
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export async function POST(
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@@ -28,8 +28,8 @@ export async function POST(
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if ((recentCount ?? 0) > 0)
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return NextResponse.json({ error: 'Rate limited — please wait 60 seconds' }, { status: 429 })
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const anthropicKey = await getApiKey(supabase, 'ANTHROPIC_API_KEY')
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const anthropic = createAnthropicClient(anthropicKey)
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const deepseekKey = await getApiKey(supabase, 'DEEPSEEK_API_KEY')
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const client = createDeepSeekClient(deepseekKey)
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const { data: incident } = await supabase
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.from('incidents')
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@@ -46,32 +46,34 @@ export async function POST(
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medical_status: string | null
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}
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let message: Awaited<ReturnType<typeof anthropic.messages.create>>
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let res: Awaited<ReturnType<typeof client.chat.completions.create>>
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try {
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message = await anthropic.messages.create({
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model: 'claude-opus-4-8',
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thinking: { type: 'adaptive' },
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res = await client.chat.completions.create({
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model: 'deepseek-chat',
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max_tokens: 1024,
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tools: [{
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name: 'suggest_triage',
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description: 'Suggest severity rating and NADOPOD 2004 DOSH classification for a warehouse incident',
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input_schema: {
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type: 'object' as const,
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properties: {
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severity: { type: 'number', description: '1=minor, 2=low, 3=moderate, 4=serious, 5=critical/fatality' },
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is_fatality: { type: 'boolean' },
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is_serious_bodily_injury: { type: 'boolean', description: 'Fracture, amputation, blindness, serious burn, or similar' },
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is_dangerous_occurrence: { type: 'boolean', description: 'Structural collapse, explosion, fire, scaffold collapse, etc.' },
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is_occupational_disease: { type: 'boolean', description: 'Disease arising from workplace exposure' },
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rationale: { type: 'string', description: 'One-sentence rationale citing NADOPOD 2004 where applicable' },
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type: 'function',
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function: {
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name: 'suggest_triage',
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description: 'Suggest severity rating and NADOPOD 2004 DOSH classification for a warehouse incident',
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parameters: {
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type: 'object',
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properties: {
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severity: { type: 'number', description: '1=minor, 2=low, 3=moderate, 4=serious, 5=critical/fatality' },
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is_fatality: { type: 'boolean' },
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is_serious_bodily_injury: { type: 'boolean', description: 'Fracture, amputation, blindness, serious burn, or similar' },
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is_dangerous_occurrence: { type: 'boolean', description: 'Structural collapse, explosion, fire, scaffold collapse, etc.' },
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is_occupational_disease: { type: 'boolean', description: 'Disease arising from workplace exposure' },
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rationale: { type: 'string', description: 'One-sentence rationale citing NADOPOD 2004 where applicable' },
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},
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required: [
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'severity', 'is_fatality', 'is_serious_bodily_injury',
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'is_dangerous_occurrence', 'is_occupational_disease', 'rationale',
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],
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},
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required: [
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'severity', 'is_fatality', 'is_serious_bodily_injury',
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'is_dangerous_occurrence', 'is_occupational_disease', 'rationale',
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],
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},
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}],
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tool_choice: { type: 'tool', name: 'suggest_triage' },
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tool_choice: { type: 'function', function: { name: 'suggest_triage' } },
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messages: [{
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role: 'user',
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content: `You are an HSE triage specialist for a Malaysian 3PL warehouse. Assess this incident under NADOPOD 2004.
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@@ -89,11 +91,10 @@ Suggest severity (1–5) and tick the appropriate NADOPOD 2004 flags. Give a one
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return NextResponse.json({ error: 'AI service unavailable' }, { status: 503 })
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}
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const toolBlock = message.content.find(b => b.type === 'tool_use')
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if (!toolBlock || toolBlock.type !== 'tool_use')
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return NextResponse.json({ error: 'AI suggestion failed' }, { status: 500 })
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const call = res.choices[0]?.message?.tool_calls?.[0]
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if (!call || call.type !== 'function') return NextResponse.json({ error: 'AI suggestion failed' }, { status: 500 })
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const input = toolBlock.input as {
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let input: {
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severity?: unknown
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is_fatality?: unknown
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is_serious_bodily_injury?: unknown
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@@ -101,6 +102,8 @@ Suggest severity (1–5) and tick the appropriate NADOPOD 2004 flags. Give a one
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is_occupational_disease?: unknown
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rationale?: unknown
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}
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try { input = JSON.parse(call.function.arguments) }
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catch { return NextResponse.json({ error: 'AI returned unexpected structure' }, { status: 500 }) }
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if (
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typeof input.severity !== 'number' ||
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@@ -117,8 +120,8 @@ Suggest severity (1–5) and tick the appropriate NADOPOD 2004 flags. Give a one
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p_table_name: 'incidents',
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p_record_id: id,
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p_action: 'ai_triage_suggest',
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p_new_value: { suggestion: toolBlock.input, model: 'claude-opus-4-8' } as never,
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p_new_value: { suggestion: input, model: 'deepseek-chat' } as never,
|
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})
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return NextResponse.json(toolBlock.input)
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return NextResponse.json(input)
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}
|
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|
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@@ -2,7 +2,7 @@ export const dynamic = 'force-dynamic'
|
||||
|
||||
import { NextRequest, NextResponse } from 'next/server'
|
||||
import { createClient } from '@/lib/supabase/server'
|
||||
import { createAnthropicClient } from '@/lib/claude/client'
|
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import { createDeepSeekClient } from '@/lib/claude/client'
|
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import { getApiKey } from '@/lib/settings'
|
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|
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export async function POST(request: NextRequest) {
|
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@@ -20,8 +20,8 @@ export async function POST(request: NextRequest) {
|
||||
if ((recentCount ?? 0) > 0)
|
||||
return NextResponse.json({ error: 'Rate limited — please wait 60 seconds' }, { status: 429 })
|
||||
|
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const anthropicKey = await getApiKey(supabase, 'ANTHROPIC_API_KEY')
|
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const anthropic = createAnthropicClient(anthropicKey)
|
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const deepseekKey = await getApiKey(supabase, 'DEEPSEEK_API_KEY')
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const client = createDeepSeekClient(deepseekKey)
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let body: { description?: string; incident_type?: string }
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try {
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@@ -33,31 +33,33 @@ export async function POST(request: NextRequest) {
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return NextResponse.json({ error: 'description and incident_type required' }, { status: 422 })
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}
|
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|
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let message: Awaited<ReturnType<typeof anthropic.messages.create>>
|
||||
let res: Awaited<ReturnType<typeof client.chat.completions.create>>
|
||||
try {
|
||||
message = await anthropic.messages.create({
|
||||
model: 'claude-opus-4-8',
|
||||
thinking: { type: 'adaptive' },
|
||||
res = await client.chat.completions.create({
|
||||
model: 'deepseek-chat',
|
||||
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: {
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||||
type: 'array',
|
||||
items: { type: 'string' },
|
||||
description: 'Up to 3 concrete suggestions to improve the description',
|
||||
type: 'function',
|
||||
function: {
|
||||
name: 'assess_quality',
|
||||
description: 'Assess HSE incident report description quality',
|
||||
parameters: {
|
||||
type: 'object',
|
||||
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'],
|
||||
},
|
||||
required: ['score', 'passes', 'feedback', 'suggestions'],
|
||||
},
|
||||
}],
|
||||
tool_choice: { type: 'tool', name: 'assess_quality' },
|
||||
tool_choice: { type: 'function', function: { name: 'assess_quality' } },
|
||||
messages: [{
|
||||
role: 'user',
|
||||
content: `You are an HSE reporting assistant for a Malaysian 3PL warehouse. Assess this incident report description.
|
||||
@@ -72,17 +74,13 @@ Score 1–10 based on: specificity (location, time, persons involved), completen
|
||||
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 call = res.choices[0]?.message?.tool_calls?.[0]
|
||||
if (!call || call.type !== 'function') return NextResponse.json({ error: 'AI assessment failed' }, { status: 500 })
|
||||
|
||||
let input: { score?: unknown; passes?: unknown; feedback?: unknown; suggestions?: unknown }
|
||||
try { input = JSON.parse(call.function.arguments) }
|
||||
catch { return NextResponse.json({ error: 'AI returned unexpected structure' }, { status: 500 }) }
|
||||
|
||||
const input = toolBlock.input as {
|
||||
score?: unknown
|
||||
passes?: unknown
|
||||
feedback?: unknown
|
||||
suggestions?: unknown
|
||||
}
|
||||
if (
|
||||
typeof input.score !== 'number' ||
|
||||
typeof input.passes !== 'boolean' ||
|
||||
@@ -96,7 +94,7 @@ Score 1–10 based on: specificity (location, time, persons involved), completen
|
||||
p_table_name: 'incidents',
|
||||
p_record_id: user.id,
|
||||
p_action: 'ai_quality_check',
|
||||
p_new_value: { score: input.score, passes: input.passes, model: 'claude-opus-4-8' } as never,
|
||||
p_new_value: { score: input.score, passes: input.passes, model: 'deepseek-chat' } as never,
|
||||
})
|
||||
|
||||
return NextResponse.json(input)
|
||||
|
||||
@@ -5,6 +5,7 @@ import { createClient } from '@/lib/supabase/server'
|
||||
|
||||
const ALLOWED_KEYS = [
|
||||
'ANTHROPIC_API_KEY',
|
||||
'DEEPSEEK_API_KEY',
|
||||
'VOYAGE_API_KEY',
|
||||
'META_WHATSAPP_PHONE_NUMBER_ID',
|
||||
'META_WHATSAPP_ACCESS_TOKEN',
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
import Anthropic from '@anthropic-ai/sdk'
|
||||
import OpenAI from 'openai'
|
||||
|
||||
export function createAnthropicClient(apiKey: string): Anthropic {
|
||||
return new Anthropic({ apiKey })
|
||||
export function createDeepSeekClient(apiKey: string): OpenAI {
|
||||
return new OpenAI({ apiKey, baseURL: 'https://api.deepseek.com' })
|
||||
}
|
||||
|
||||
Generated
+31
@@ -13,6 +13,7 @@
|
||||
"@supabase/supabase-js": "^2.110.2",
|
||||
"idb": "^8.0.3",
|
||||
"next": "^15.5.20",
|
||||
"openai": "^6.46.0",
|
||||
"pdf-lib": "^1.17.1",
|
||||
"react": "^19.2.7",
|
||||
"react-dom": "^19.2.7",
|
||||
@@ -7287,6 +7288,36 @@
|
||||
"node": ">=12.20.0"
|
||||
}
|
||||
},
|
||||
"node_modules/openai": {
|
||||
"version": "6.46.0",
|
||||
"resolved": "https://registry.npmjs.org/openai/-/openai-6.46.0.tgz",
|
||||
"integrity": "sha512-DFg6jEPT2RO+oAyXtddeUJU8zkGy1OQ1AjGzNIJUMQG03TTqvCpy9tBpQ+2VVVnvrl3E56F8GEin2JYtWpITtA==",
|
||||
"license": "Apache-2.0",
|
||||
"peerDependencies": {
|
||||
"@aws-sdk/credential-provider-node": ">=3.972.0 <4",
|
||||
"@smithy/hash-node": ">=4.3.0 <5",
|
||||
"@smithy/signature-v4": ">=5.4.0 <6",
|
||||
"ws": "^8.18.0",
|
||||
"zod": "^3.25 || ^4.0"
|
||||
},
|
||||
"peerDependenciesMeta": {
|
||||
"@aws-sdk/credential-provider-node": {
|
||||
"optional": true
|
||||
},
|
||||
"@smithy/hash-node": {
|
||||
"optional": true
|
||||
},
|
||||
"@smithy/signature-v4": {
|
||||
"optional": true
|
||||
},
|
||||
"ws": {
|
||||
"optional": true
|
||||
},
|
||||
"zod": {
|
||||
"optional": true
|
||||
}
|
||||
}
|
||||
},
|
||||
"node_modules/optionator": {
|
||||
"version": "0.9.4",
|
||||
"resolved": "https://registry.npmjs.org/optionator/-/optionator-0.9.4.tgz",
|
||||
|
||||
@@ -17,6 +17,7 @@
|
||||
"@supabase/supabase-js": "^2.110.2",
|
||||
"idb": "^8.0.3",
|
||||
"next": "^15.5.20",
|
||||
"openai": "^6.46.0",
|
||||
"pdf-lib": "^1.17.1",
|
||||
"react": "^19.2.7",
|
||||
"react-dom": "^19.2.7",
|
||||
|
||||
@@ -0,0 +1,4 @@
|
||||
-- Add DEEPSEEK_API_KEY placeholder to app_settings
|
||||
insert into app_settings (key, value) values
|
||||
('DEEPSEEK_API_KEY', '')
|
||||
on conflict (key) do nothing;
|
||||
@@ -1,23 +1,39 @@
|
||||
import { describe, it, expect, vi } from 'vitest'
|
||||
|
||||
const qualityOutput = { score: 8, passes: true, feedback: 'Clear description.', suggestions: [] }
|
||||
|
||||
vi.mock('@/lib/supabase/server', () => ({
|
||||
createClient: vi.fn().mockResolvedValue({
|
||||
auth: {
|
||||
getUser: vi.fn().mockResolvedValue({ data: { user: { id: 'user-1' } }, error: null }),
|
||||
},
|
||||
from: vi.fn().mockReturnValue({
|
||||
select: vi.fn().mockReturnThis(),
|
||||
eq: vi.fn().mockReturnThis(),
|
||||
gte: vi.fn().mockResolvedValue({ count: 0 }),
|
||||
}),
|
||||
rpc: vi.fn().mockResolvedValue({ error: null }),
|
||||
}),
|
||||
}))
|
||||
|
||||
vi.mock('@/lib/claude/client', () => ({
|
||||
createAnthropicClient: vi.fn().mockReturnValue({
|
||||
messages: {
|
||||
create: vi.fn().mockResolvedValue({
|
||||
content: [{
|
||||
type: 'tool_use',
|
||||
name: 'assess_quality',
|
||||
input: { score: 8, passes: true, feedback: 'Clear description.', suggestions: [] },
|
||||
}],
|
||||
}),
|
||||
createDeepSeekClient: vi.fn().mockReturnValue({
|
||||
chat: {
|
||||
completions: {
|
||||
create: vi.fn().mockResolvedValue({
|
||||
choices: [{
|
||||
message: {
|
||||
tool_calls: [{
|
||||
type: 'function',
|
||||
function: {
|
||||
name: 'assess_quality',
|
||||
arguments: JSON.stringify(qualityOutput),
|
||||
},
|
||||
}],
|
||||
},
|
||||
}],
|
||||
}),
|
||||
},
|
||||
},
|
||||
}),
|
||||
}))
|
||||
@@ -38,7 +54,7 @@ describe('POST /api/incidents/ai/quality-check', () => {
|
||||
expect(res.status).toBe(422)
|
||||
})
|
||||
|
||||
it('returns quality assessment from Claude', async () => {
|
||||
it('returns quality assessment from DeepSeek', async () => {
|
||||
const { POST } = await import('@/app/api/incidents/ai/quality-check/route')
|
||||
const req = new Request('http://localhost/api/incidents/ai/quality-check', {
|
||||
method: 'POST',
|
||||
|
||||
@@ -14,6 +14,20 @@ const mockIncident = {
|
||||
zones: { name: 'Zone B' },
|
||||
}
|
||||
|
||||
const rcaOutput = {
|
||||
five_why_steps: [
|
||||
{ why: 'Why did the incident happen?', answer: 'Forklift entered zone B without checking for pedestrians.' },
|
||||
{ why: 'Why was there no check?', answer: 'No pedestrian exclusion zone marked at zone B entrance.' },
|
||||
{ why: 'Why was it not marked?', answer: 'Site hazard assessment did not include zone B forklift route.' },
|
||||
],
|
||||
root_cause_summary: 'Absence of pedestrian exclusion zone and forklift route hazard assessment in zone B.',
|
||||
capa_suggestions: [
|
||||
'Mark pedestrian exclusion zones at all forklift routes in zone B within 7 days.',
|
||||
'Update site hazard assessment to include forklift routes in all zones.',
|
||||
'Conduct forklift safety refresher for all operators within 30 days.',
|
||||
],
|
||||
}
|
||||
|
||||
vi.mock('@/lib/supabase/server', () => ({
|
||||
createClient: vi.fn().mockResolvedValue({
|
||||
auth: {
|
||||
@@ -22,6 +36,7 @@ vi.mock('@/lib/supabase/server', () => ({
|
||||
from: vi.fn().mockReturnValue({
|
||||
select: vi.fn().mockReturnThis(),
|
||||
eq: vi.fn().mockReturnThis(),
|
||||
gte: vi.fn().mockResolvedValue({ count: 0 }),
|
||||
single: vi.fn()
|
||||
.mockResolvedValueOnce({ data: { role: 'hse' } }) // profile
|
||||
.mockResolvedValueOnce({ data: mockIncident }), // incident
|
||||
@@ -31,27 +46,23 @@ vi.mock('@/lib/supabase/server', () => ({
|
||||
}))
|
||||
|
||||
vi.mock('@/lib/claude/client', () => ({
|
||||
createAnthropicClient: vi.fn().mockReturnValue({
|
||||
messages: {
|
||||
create: vi.fn().mockResolvedValue({
|
||||
content: [{
|
||||
type: 'tool_use',
|
||||
name: 'draft_rca',
|
||||
input: {
|
||||
five_why_steps: [
|
||||
{ why: 'Why did the incident happen?', answer: 'Forklift entered zone B without checking for pedestrians.' },
|
||||
{ why: 'Why was there no check?', answer: 'No pedestrian exclusion zone marked at zone B entrance.' },
|
||||
{ why: 'Why was it not marked?', answer: 'Site hazard assessment did not include zone B forklift route.' },
|
||||
],
|
||||
root_cause_summary: 'Absence of pedestrian exclusion zone and forklift route hazard assessment in zone B.',
|
||||
capa_suggestions: [
|
||||
'Mark pedestrian exclusion zones at all forklift routes in zone B within 7 days.',
|
||||
'Update site hazard assessment to include forklift routes in all zones.',
|
||||
'Conduct forklift safety refresher for all operators within 30 days.',
|
||||
],
|
||||
},
|
||||
}],
|
||||
}),
|
||||
createDeepSeekClient: vi.fn().mockReturnValue({
|
||||
chat: {
|
||||
completions: {
|
||||
create: vi.fn().mockResolvedValue({
|
||||
choices: [{
|
||||
message: {
|
||||
tool_calls: [{
|
||||
type: 'function',
|
||||
function: {
|
||||
name: 'draft_rca',
|
||||
arguments: JSON.stringify(rcaOutput),
|
||||
},
|
||||
}],
|
||||
},
|
||||
}],
|
||||
}),
|
||||
},
|
||||
},
|
||||
}),
|
||||
}))
|
||||
|
||||
@@ -9,6 +9,15 @@ const mockIncident = {
|
||||
medical_status: 'medical_treatment',
|
||||
}
|
||||
|
||||
const triageOutput = {
|
||||
severity: 3,
|
||||
is_fatality: false,
|
||||
is_serious_bodily_injury: true,
|
||||
is_dangerous_occurrence: false,
|
||||
is_occupational_disease: false,
|
||||
rationale: 'Fracture constitutes serious bodily injury under NADOPOD 2004.',
|
||||
}
|
||||
|
||||
vi.mock('@/lib/supabase/server', () => ({
|
||||
createClient: vi.fn().mockResolvedValue({
|
||||
auth: {
|
||||
@@ -17,6 +26,7 @@ vi.mock('@/lib/supabase/server', () => ({
|
||||
from: vi.fn().mockReturnValue({
|
||||
select: vi.fn().mockReturnThis(),
|
||||
eq: vi.fn().mockReturnThis(),
|
||||
gte: vi.fn().mockResolvedValue({ count: 0 }),
|
||||
single: vi.fn()
|
||||
.mockResolvedValueOnce({ data: { role: 'hse' } }) // profile
|
||||
.mockResolvedValueOnce({ data: mockIncident }), // incident
|
||||
@@ -26,22 +36,23 @@ vi.mock('@/lib/supabase/server', () => ({
|
||||
}))
|
||||
|
||||
vi.mock('@/lib/claude/client', () => ({
|
||||
createAnthropicClient: vi.fn().mockReturnValue({
|
||||
messages: {
|
||||
create: vi.fn().mockResolvedValue({
|
||||
content: [{
|
||||
type: 'tool_use',
|
||||
name: 'suggest_triage',
|
||||
input: {
|
||||
severity: 3,
|
||||
is_fatality: false,
|
||||
is_serious_bodily_injury: true,
|
||||
is_dangerous_occurrence: false,
|
||||
is_occupational_disease: false,
|
||||
rationale: 'Fracture constitutes serious bodily injury under NADOPOD 2004.',
|
||||
},
|
||||
}],
|
||||
}),
|
||||
createDeepSeekClient: vi.fn().mockReturnValue({
|
||||
chat: {
|
||||
completions: {
|
||||
create: vi.fn().mockResolvedValue({
|
||||
choices: [{
|
||||
message: {
|
||||
tool_calls: [{
|
||||
type: 'function',
|
||||
function: {
|
||||
name: 'suggest_triage',
|
||||
arguments: JSON.stringify(triageOutput),
|
||||
},
|
||||
}],
|
||||
},
|
||||
}],
|
||||
}),
|
||||
},
|
||||
},
|
||||
}),
|
||||
}))
|
||||
|
||||
Reference in New Issue
Block a user