호출 센터 분석(DeepSeek 모델 양AI 검증)

• •HTTP Webhook 엔드포인트(n8n이 자동으로 생성)
• •대상 API의 인증 정보가 필요할 수 있음

{
  "meta": {
    "instanceId": "66ce8bb89c7868f862e0d2e755cd17c6a5aea7904e5504a5b2e292e317980443",
    "templateCredsSetupCompleted": true
  },
  "nodes": [
    {
      "id": "613422d5-05db-4163-bcb0-3fdae9de260b",
      "name": "워크플로우 '테스트' 클릭 시",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        -1120,
        60
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "9ec28d5b-6ea0-4a57-911e-9f4546b739a2",
      "name": "메모지",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -520,
        -240
      ],
      "parameters": {
        "color": 7,
        "width": 340,
        "height": 440,
        "content": "## Generate report\nUsing deepseek R1"
      },
      "typeVersion": 1
    },
    {
      "id": "cf30eb86-2aad-4d33-a5c2-737239e63636",
      "name": "메모지1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -140,
        -240
      ],
      "parameters": {
        "color": 7,
        "width": 340,
        "height": 440,
        "content": "## Double-check\nUsing deepseek V3"
      },
      "typeVersion": 1
    },
    {
      "id": "d799760f-83c5-4603-8eb8-3857807b364a",
      "name": "HTTP 요청",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        300,
        -140
      ],
      "parameters": {
        "url": "YOUR_CALL_BACK_API",
        "method": "POST",
        "options": {},
        "jsonBody": "={\n  data: \"{{$node['Report'].json.text}}\"\n}",
        "sendBody": true,
        "specifyBody": "json"
      },
      "typeVersion": 4.2
    },
    {
      "id": "bf0a8ab6-06e0-4564-96af-ddcf6795a845",
      "name": "보고서",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        -480,
        -140
      ],
      "parameters": {
        "text": "=You are a CRM data analyst assistant. Your task is to analyze the provided CRM data and generate valuable insights in Markdown format.\n\nYou will receive JSON data extracted from a CRM system that may include information about:\n- Call canter agents metrics.\n\n# ANALYSIS REQUIREMENTS\nAnalyze the data considering:\n1. Lead conversion rates and quality metrics\n2. Upsall\n3. Rank the agents with small description about every one.\n\n# OUTPUT FORMAT\nStructure your analysis in Markdown.\n\n# GUIDELINES\n- Focus on actionable insights rather than just describing the data\n- Use bullet points and tables when appropriate to improve readability\n- Include both positive findings and areas for improvement\n- Reference specific data points to support your analysis\n- Prioritize quality over quantity in your recommendations\n- Be concise yet thorough\n- If there are data quality issues or missing information, note these limitations\n- If you detect any unusual patterns or anomalies, highlight them\n\n# DATA\n```\n{{ JSON.stringify($input.first().json.body) }}\n```",
        "promptType": "define"
      },
      "typeVersion": 1.6
    },
    {
      "id": "f51d601e-898c-4dd6-894b-2e4911a334db",
      "name": "DeepSeek 추론",
      "type": "@n8n/n8n-nodes-langchain.lmChatDeepSeek",
      "position": [
        -400,
        60
      ],
      "parameters": {
        "model": "deepseek-reasoner",
        "options": {}
      },
      "credentials": {
        "deepSeekApi": {
          "id": "ltpFxb7M3kHaEBFD",
          "name": "DeepSeek account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "9393be48-aebc-4f6c-b445-014633e0e289",
      "name": "DeepSeek 채팅",
      "type": "@n8n/n8n-nodes-langchain.lmChatDeepSeek",
      "position": [
        -20,
        80
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "deepSeekApi": {
          "id": "ltpFxb7M3kHaEBFD",
          "name": "DeepSeek account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "4a8dc360-fd3f-46a5-89e1-87ece59b0bb6",
      "name": "예시 데이터",
      "type": "n8n-nodes-base.code",
      "position": [
        -860,
        60
      ],
      "parameters": {
        "jsCode": "return {\n  \"body\": \n    // You can use any data as JSON\n    // this is just example\n    // data start here\n    [\n      {\n        \"user\": {\n          \"id\": 15,\n          \"full_name\": \"lisa confirmation\",\n        },\n        \"productivity\": 44.67,\n        \"total_leads\": 465,\n        \"total_confirmed\": 291,\n        \"total_delivred\": 130,\n        \"total_in_proccess\": 119,\n        \"total_cancled\": 0,\n        \"total_returned\": 13,\n        \"total_assign\": 495,\n        \"total_need_confirmation\": 0,\n        \"total_recheck\": 22,\n        \"upsell\": 59,\n        \"upsell_delivered\": 27,\n        \"confirmation_rate\": 62.58\n      },\n      {\n        \"user\": {\n          \"id\": 1346,\n          \"full_name\": \"Sallam Confirmation\",\n        },\n        \"productivity\": 42.29,\n        \"total_leads\": 374,\n        \"total_confirmed\": 253,\n        \"total_delivred\": 107,\n        \"total_in_proccess\": 96,\n        \"total_cancled\": 0,\n        \"total_returned\": 21,\n        \"total_assign\": 459,\n        \"total_need_confirmation\": 1,\n        \"total_recheck\": 1,\n        \"upsell\": 62,\n        \"upsell_delivered\": 31,\n        \"confirmation_rate\": 67.65\n      }\n    ]\n    // data end here\n}"
      },
      "typeVersion": 2
    },
    {
      "id": "41e36370-fa7a-4f6e-a439-15127dfc432d",
      "name": "메모지2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1160,
        -20
      ],
      "parameters": {
        "width": 480,
        "height": 240,
        "content": "## Test Workflow\nClick this button to test the workflow with example data"
      },
      "typeVersion": 1
    },
    {
      "id": "e0d473e8-7a2e-4473-9af7-5f2f835990db",
      "name": "메모지8",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1160,
        240
      ],
      "parameters": {
        "width": 480,
        "height": 80,
        "content": "## Just to test"
      },
      "typeVersion": 1
    },
    {
      "id": "b0c31c3b-1fd0-485e-a54b-9a3045bcf09e",
      "name": "메모지7",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1160,
        400
      ],
      "parameters": {
        "color": 4,
        "width": 1540,
        "height": 100,
        "content": "## Do you need more help or have any suggestions?\nContact me at mediaplus.ma@gmail.com"
      },
      "typeVersion": 1
    },
    {
      "id": "9a1f03ee-167f-44e3-ae12-61ab8d3789f2",
      "name": "메모지6",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -520,
        -360
      ],
      "parameters": {
        "color": 7,
        "width": 720,
        "height": 80,
        "content": "## Change here\nYou can edit/add details about your goal by changing the AI promps.\n"
      },
      "typeVersion": 1
    },
    {
      "id": "d91de9c8-835b-4232-a76b-e27554ad595d",
      "name": "Webhook",
      "type": "n8n-nodes-base.webhook",
      "position": [
        -980,
        -300
      ],
      "webhookId": "b408defb-315d-4676-b4c4-1dcebe81ffc0",
      "parameters": {
        "path": "b408defb-315d-4676-b4c4-1dcebe81ffc0",
        "options": {},
        "httpMethod": [
          "POST",
          "GET"
        ],
        "multipleMethods": true
      },
      "typeVersion": 2
    },
    {
      "id": "04c2da18-10c9-44df-8084-52b5901ecc18",
      "name": "메모지9",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1020,
        -380
      ],
      "parameters": {
        "color": 4,
        "width": 200,
        "height": 240,
        "content": "## Production"
      },
      "typeVersion": 1
    },
    {
      "id": "a1fb1cbc-391c-4918-b48f-8b44116921b8",
      "name": "재확인",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        -100,
        -140
      ],
      "parameters": {
        "text": "=You are a Data Analysis Verification Expert. Your task is to evaluate whether an AI-generated report accurately and completely analyzes the provided CRM data. You will assess the report quality and determine if it's compatible with the original input.\n\n# INPUT\nYou will receive:\n1. The original call center agent metrics data (JSON)\n2. The AI-generated analysis report in Markdown\n\n# VERIFICATION REQUIREMENTS\nEvaluate the report for:\n1. Factual accuracy - Do all numbers, rankings, and statements accurately reflect the data?\n2. Comprehensiveness - Does the report cover all required areas? (Lead conversion, Upsell, Agent ranking)\n3. Insight quality - Does the report provide meaningful insights beyond basic data description?\n4. Completeness - Are all agents included in the analysis?\n5. Format compliance - Is the report properly formatted in Markdown with appropriate sections?\n\n# OUTPUT FORMAT\nReturn a JSON object with the following structure:\n```json\n{\n  \"verified\": true/false,\n  \"score\": 1-10,\n  \"quality_assessment\": \"Brief 2-4 sentence evaluation of report quality\",\n  \"missing_elements\": [\"List any required elements missing from the report\"],\n  \"inaccuracies\": [\"List any factual errors or misinterpretations\"],\n  \"improvement_suggestions\": [\"Specific suggestions for report improvement\"]\n}\n```\n\n# EVALUATION CRITERIA\n- \"verified\": Set to true ONLY if the report is factually accurate, includes all agents, covers all required areas, and provides meaningful insights.\n- \"score\": Rate from 1-10 where:\n  * 1-3: Poor report with major inaccuracies or missing elements\n  * 4-6: Adequate report with some issues\n  * 7-8: Good report with minor issues\n  * 9-10: Excellent report with comprehensive analysis\n\n# GUIDELINES\n- Be thorough and precise in your verification\n- Check all numerical claims against the original data\n- Verify that all agents are properly ranked and described\n- Check that lead conversion rates and upsell metrics are accurately analyzed\n- Assess whether the insights are actionable and valuable\n- Maintain a balanced perspective, noting both strengths and weaknesses\n\n# ORIGINAL DATA\n{{ JSON.stringify($node[\"Example data\"].json.chatInput) }}\n\n# AI-GENERATED REPORT\n{{ $json.text }}",
        "promptType": "define"
      },
      "typeVersion": 1.6
    }
  ],
  "pinData": {},
  "connections": {
    "bf0a8ab6-06e0-4564-96af-ddcf6795a845": {
      "main": [
        [
          {
            "node": "a1fb1cbc-391c-4918-b48f-8b44116921b8",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "a1fb1cbc-391c-4918-b48f-8b44116921b8": {
      "main": [
        [
          {
            "node": "d799760f-83c5-4603-8eb8-3857807b364a",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "d91de9c8-835b-4232-a76b-e27554ad595d": {
      "main": [
        [
          {
            "node": "bf0a8ab6-06e0-4564-96af-ddcf6795a845",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "4a8dc360-fd3f-46a5-89e1-87ece59b0bb6": {
      "main": [
        [
          {
            "node": "bf0a8ab6-06e0-4564-96af-ddcf6795a845",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "9393be48-aebc-4f6c-b445-014633e0e289": {
      "ai_languageModel": [
        [
          {
            "node": "a1fb1cbc-391c-4918-b48f-8b44116921b8",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "f51d601e-898c-4dd6-894b-2e4911a334db": {
      "ai_languageModel": [
        [
          {
            "node": "bf0a8ab6-06e0-4564-96af-ddcf6795a845",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "613422d5-05db-4163-bcb0-3fdae9de260b": {
      "main": [
        [
          {
            "node": "4a8dc360-fd3f-46a5-89e1-87ece59b0bb6",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}