68일차 정답본(LAB-A·VIBE-A)과 과제 정답 answers/ 공개, Lab 03 학생 문서 갱신
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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{
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"name": "answer · 68 Lab 01 challenge (agent and missing input)",
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"nodes": [
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{
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"name": "Assistant webhook",
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"type": "n8n-nodes-base.webhook",
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"typeVersion": 2,
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"position": [
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0,
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300
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],
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"parameters": {
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"httpMethod": "POST",
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"path": "my-split",
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"responseMode": "responseNode",
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"options": {}
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}
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},
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{
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"name": "Has message?",
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"type": "n8n-nodes-base.if",
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"typeVersion": 2.2,
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"position": [
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200,
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300
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],
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"parameters": {
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"conditions": {
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"options": {
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"caseSensitive": true,
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"leftValue": "",
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"typeValidation": "strict",
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"version": 2
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},
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"conditions": [
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{
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"id": "c1",
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"leftValue": "={{ $json.body.message }}",
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"rightValue": "",
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"operator": {
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"type": "string",
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"operation": "notEmpty",
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"singleValue": true
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}
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}
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],
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"combinator": "and"
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},
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"options": {}
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}
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},
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{
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"name": "Reject empty",
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"type": "n8n-nodes-base.respondToWebhook",
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"typeVersion": 1.1,
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"position": [
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420,
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520
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],
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"parameters": {
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"respondWith": "json",
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"responseBody": "{ \"error\": \"message is required\" }",
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"options": {
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"responseCode": 400
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}
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}
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},
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{
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"name": "Split tasks",
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"type": "@n8n/n8n-nodes-langchain.agent",
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"typeVersion": 3.1,
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"position": [
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420,
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300
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],
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"parameters": {
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"promptType": "define",
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"text": "={{ $('Assistant webhook').first().json.body.message }}",
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"options": {
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"systemMessage": "You split one employee message into separate tasks. Task types: \"it\" = IT problems and IT request status (password, account, VPN, printer, mail, software, ticket ids like T-1002); \"meeting\" = organizing meeting notes or action items; \"other\" = anything else. One task per separate request. Keep each task text in Korean as the employee wrote it, and keep ticket ids. Return only JSON, no code fence: {\"tasks\": [{\"type\": \"it\", \"text\": \"...\"}]}",
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"maxIterations": 2
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}
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}
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},
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{
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"name": "OpenAI chat model",
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"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
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"typeVersion": 1.2,
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"position": [
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380,
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520
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],
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"parameters": {
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"model": {
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"__rl": true,
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"mode": "id",
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"value": "gpt-4.1-mini"
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},
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"options": {
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"temperature": 0
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}
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},
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"credentials": {
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"openAiApi": {
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"id": "openAiCourse0001",
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"name": "OpenAI (.env)"
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}
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}
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},
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{
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"name": "Parse tasks",
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"type": "n8n-nodes-base.code",
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"typeVersion": 2,
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"position": [
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680,
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300
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],
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"parameters": {
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"jsCode": "// Turn the agent text into a list of tasks, then decide in code who handles each task\n// and which input is missing (the LLM does not decide this).\nconst body = $('Assistant webhook').first().json.body;\nconst raw = String($json.output ?? '').trim().replace(/^```(json)?\\s*|```$/g, '');\nlet items = [];\ntry { const data = JSON.parse(raw); items = Array.isArray(data) ? data : (data.tasks ?? []); } catch (error) { items = []; }\nconst AGENT = { it: 'it-agent', meeting: 'meeting-agent', other: '담당자 연결' };\nconst tasks = items\n .map(item => ({ type: ['it', 'meeting', 'other'].includes(item?.type) ? item.type : 'other', text: String(item?.text ?? '').trim() }))\n .filter(task => task.text)\n .map(task => {\n const missing = [];\n if (task.type === 'meeting' && !String(body.notes ?? '').trim()) missing.push('notes');\n if (task.type === 'it' && !String(body.user ?? '').trim()) missing.push('user');\n return { ...task, agent: AGENT[task.type], missing };\n });\nreturn [{ json: { count: tasks.length, tasks } }];"
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}
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},
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{
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"name": "Send result",
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"type": "n8n-nodes-base.respondToWebhook",
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"typeVersion": 1.1,
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"position": [
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900,
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300
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],
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"parameters": {
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"respondWith": "json",
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"responseBody": "={{ $json }}",
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"options": {}
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}
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}
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],
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"connections": {
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"Assistant webhook": {
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"main": [
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[
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{
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"node": "Has message?",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"Has message?": {
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"main": [
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[
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{
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"node": "Split tasks",
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"type": "main",
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"index": 0
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}
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],
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[
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{
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"node": "Reject empty",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"OpenAI chat model": {
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"ai_languageModel": [
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[
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{
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"node": "Split tasks",
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"type": "ai_languageModel",
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"index": 0
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}
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]
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]
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},
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"Split tasks": {
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"main": [
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[
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{
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"node": "Parse tasks",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"Parse tasks": {
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"main": [
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[
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{
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"node": "Send result",
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"type": "main",
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"index": 0
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}
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]
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]
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}
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},
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"settings": {
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"executionOrder": "v1"
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}
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}
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