aio-01d4-stu/Last3Mon/68/answers/68-lab01-challenge-split.json

{
  "name": "answer · 68 Lab 01 challenge (agent and missing input)",
  "nodes": [
    {
      "name": "Assistant webhook",
      "type": "n8n-nodes-base.webhook",
      "typeVersion": 2,
      "position": [
        0,
        300
      ],
      "parameters": {
        "httpMethod": "POST",
        "path": "my-split",
        "responseMode": "responseNode",
        "options": {}
      }
    },
    {
      "name": "Has message?",
      "type": "n8n-nodes-base.if",
      "typeVersion": 2.2,
      "position": [
        200,
        300
      ],
      "parameters": {
        "conditions": {
          "options": {
            "caseSensitive": true,
            "leftValue": "",
            "typeValidation": "strict",
            "version": 2
          },
          "conditions": [
            {
              "id": "c1",
              "leftValue": "={{ $json.body.message }}",
              "rightValue": "",
              "operator": {
                "type": "string",
                "operation": "notEmpty",
                "singleValue": true
              }
            }
          ],
          "combinator": "and"
        },
        "options": {}
      }
    },
    {
      "name": "Reject empty",
      "type": "n8n-nodes-base.respondToWebhook",
      "typeVersion": 1.1,
      "position": [
        420,
        520
      ],
      "parameters": {
        "respondWith": "json",
        "responseBody": "{ \"error\": \"message is required\" }",
        "options": {
          "responseCode": 400
        }
      }
    },
    {
      "name": "Split tasks",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 3.1,
      "position": [
        420,
        300
      ],
      "parameters": {
        "promptType": "define",
        "text": "={{ $('Assistant webhook').first().json.body.message }}",
        "options": {
          "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\": \"...\"}]}",
          "maxIterations": 2
        }
      }
    },
    {
      "name": "OpenAI chat model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "typeVersion": 1.2,
      "position": [
        380,
        520
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "id",
          "value": "gpt-4.1-mini"
        },
        "options": {
          "temperature": 0
        }
      },
      "credentials": {
        "openAiApi": {
          "id": "openAiCourse0001",
          "name": "OpenAI (.env)"
        }
      }
    },
    {
      "name": "Parse tasks",
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        680,
        300
      ],
      "parameters": {
        "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 } }];"
      }
    },
    {
      "name": "Send result",
      "type": "n8n-nodes-base.respondToWebhook",
      "typeVersion": 1.1,
      "position": [
        900,
        300
      ],
      "parameters": {
        "respondWith": "json",
        "responseBody": "={{ $json }}",
        "options": {}
      }
    }
  ],
  "connections": {
    "Assistant webhook": {
      "main": [
        [
          {
            "node": "Has message?",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Has message?": {
      "main": [
        [
          {
            "node": "Split tasks",
            "type": "main",
            "index": 0
          }
        ],
        [
          {
            "node": "Reject empty",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI chat model": {
      "ai_languageModel": [
        [
          {
            "node": "Split tasks",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Split tasks": {
      "main": [
        [
          {
            "node": "Parse tasks",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Parse tasks": {
      "main": [
        [
          {
            "node": "Send result",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "settings": {
    "executionOrder": "v1"
  }
}