OpenAI와 RAGAS 방법을 사용하여 AI 대리자 응답 정확성 평가

• •대상 API의 인증 정보가 필요할 수 있음
• •OpenAI API Key

{
  "meta": {
    "instanceId": "408f9fb9940c3cb18ffdef0e0150fe342d6e655c3a9fac21f0f644e8bedabcd9",
    "templateCredsSetupCompleted": true
  },
  "nodes": [
    {
      "id": "20985bbf-3a4f-4e7c-8c7d-4d4bee4e1eaa",
      "name": "정확성 분류기",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        340,
        -320
      ],
      "parameters": {
        "text": "=question: {{ $json.question }}\n## answers:\n{{ $json.answer.split('\\n').filter(Boolean).map(str => `* ${str.trim()}`).join('\\n') }}\n## ground truth\n{{ $json.groundTruth.map(str => `* ${str}`).join('\\n') }}",
        "batching": {},
        "messages": {
          "messageValues": [
            {
              "message": "=Given a ground truth and an answer statements, analyze each statement and classify them in one of the following categories: TP (true positive): statements that are present in answer that are also directly supported by the one or more statements in ground truth, FP (false positive): statements present in the answer but not directly supported by any statement in ground truth, FN (false negative): statements found in the ground truth but not present in answer. Each statement can only belong to one of the categories. Provide a reason for each classification."
            }
          ]
        },
        "promptType": "define",
        "hasOutputParser": true
      },
      "typeVersion": 1.7
    },
    {
      "id": "d40a51d3-6ea0-4a16-b094-7862c061904f",
      "name": "예시1",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        520,
        -140
      ],
      "parameters": {
        "jsonSchemaExample": "{\n  \"TP\": [\n    {\n      \"statement\": \"The primary function of the sun is to provide light to the solar system.\",\n      \"reason\": \"This statement is somewhat supported by the ground truth mentioning the sun providing light and its roles, though it focuses more broadly on the sun's energy.\"\n    }\n  ],\n  \"FP\": [\n    {\n      \"statement\": \"The sun is powered by nuclear fission, similar to nuclear reactors on Earth.\",\n      \"reason\": \"This statement is incorrect and contradicts the ground truth which states that the sun is powered by nuclear fusion.\"\n    }\n  ],\n  \"FN\": [\n    {\n      \"statement\": \"The sun is powered by nuclear fusion, where hydrogen atoms fuse to form helium.\",\n      \"reason\": \"This accurate description of the sun’s power source is not included in the answer.\"\n    },\n    {\n      \"statement\": \"This fusion process in the sun's core releases a tremendous amount of energy.\",\n      \"reason\": \"This process and its significance are not mentioned in the answer.\"\n    },\n    {\n      \"statement\": \"The energy from the sun provides heat and light, which are essential for life on Earth.\",\n      \"reason\": \"The answer only mentions light, omitting the essential aspects of heat and its necessity for life, which the ground truth covers.\"\n    },\n    {\n      \"statement\": \"The sun's light plays a critical role in Earth's climate system.\",\n      \"reason\": \"This broader impact of the sun’s light on Earth's climate system is not addressed in the answer.\"\n    },\n    {\n      \"statement\": \"Sunlight helps to drive the weather and ocean currents.\",\n      \"reason\": \"The effect of sunlight on weather patterns and ocean currents is omitted in the answer.\"\n    }\n  ]\n}"
      },
      "typeVersion": 1.2
    },
    {
      "id": "32195796-6f39-47e1-b531-c7583a4bfc2d",
      "name": "OpenAI 채팅 모델",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        340,
        -140
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4.1-mini",
          "cachedResultName": "gpt-4.1-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "23186242-a4e5-4e70-a010-acbfa2eafb35",
      "name": "OpenAI 채팅 모델1",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        -752,
        50
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4.1-mini",
          "cachedResultName": "gpt-4.1-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "2e6b4d45-f0e0-434a-92bb-c76bf96588ad",
      "name": "데이터셋 행 가져올 때",
      "type": "n8n-nodes-base.evaluationTrigger",
      "position": [
        -1280,
        -270
      ],
      "parameters": {
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": "gid=0",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit#gid=0",
          "cachedResultName": "Correctness"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=drivesdk",
          "cachedResultName": "96. Evaluations Test"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
          "id": "XHvC7jIRR8A2TlUl",
          "name": "Google Sheets account"
        }
      },
      "typeVersion": 4.6
    },
    {
      "id": "9d8b8b85-819a-4762-a573-4e4f50f3c2ba",
      "name": "입력 재매핑",
      "type": "n8n-nodes-base.set",
      "position": [
        -1060,
        -270
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "00924b90-278f-49f5-80f2-c297df0fcc97",
              "name": "chatInput",
              "type": "string",
              "value": "={{ $json.input }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "781b1a23-0359-46ab-bf8e-c86b1bcc0cf9",
      "name": "평가",
      "type": "n8n-nodes-base.evaluation",
      "position": [
        -464,
        -170
      ],
      "parameters": {
        "operation": "checkIfEvaluating"
      },
      "typeVersion": 4.6
    },
    {
      "id": "7f8623d7-4263-45f2-a2f1-dcb07dc17c90",
      "name": "입력 필드 설정",
      "type": "n8n-nodes-base.set",
      "position": [
        -244,
        -320
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "d58952c1-d346-4fbf-881e-d5c04b6781a5",
              "name": "question",
              "type": "string",
              "value": "={{ $('When fetching a dataset row').first().json.input }}"
            },
            {
              "id": "0f10a3d0-cf6e-4715-9ded-2cee54aa62ec",
              "name": "answer",
              "type": "string",
              "value": "={{ $json.output }}"
            },
            {
              "id": "edbe42ed-36a7-438a-989f-900673e61d0f",
              "name": "groundTruth",
              "type": "array",
              "value": "={{ $('When fetching a dataset row').first().json['ground truth'].split('\\n') }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "a126142b-bd50-48fb-ab3d-e20fea082dc7",
      "name": "작업 없음",
      "type": "n8n-nodes-base.noOp",
      "position": [
        -244,
        -70
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "b896a963-5fe8-4566-9f11-9c963d93e467",
      "name": "AI 에이전트",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        -840,
        -170
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 2
    },
    {
      "id": "526b0248-d81b-428f-8f02-aa69acebd05c",
      "name": "채팅 메시지 수신 시",
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "position": [
        -1060,
        -70
      ],
      "webhookId": "ba1fadeb-b566-469a-97b3-3159a99f1805",
      "parameters": {
        "options": {}
      },
      "typeVersion": 1.1
    },
    {
      "id": "acd7d0aa-00fa-4d9d-9995-f468e1f4770a",
      "name": "병합",
      "type": "n8n-nodes-base.merge",
      "position": [
        1220,
        -320
      ],
      "parameters": {
        "mode": "combine",
        "options": {},
        "combineBy": "combineByPosition"
      },
      "typeVersion": 3.1
    },
    {
      "id": "a183f7f7-0071-42ae-a17d-fc7b087f0f49",
      "name": "F1 점수 계산",
      "type": "n8n-nodes-base.code",
      "position": [
        980,
        -320
      ],
      "parameters": {
        "mode": "runOnceForEachItem",
        "jsCode": "const { TP, FP, FN } = $input.item.json.output;\n\nreturn {\n  f1Score: fbetaScore(TP.length, FP.length, FN.length)\n};\n\nfunction fbetaScore(tp, fp, fn, beta = 1.0) {\n  const precision = tp + fp === 0 ? 0 : tp / (tp + fp);\n  const recall = tp + fn === 0 ? 0 : tp / (tp + fn);\n  \n  if (precision === 0 && recall === 0) return 0.0;\n\n  const betaSquared = beta * beta;\n  const fbeta = (1 + betaSquared)\n    * (precision * recall)\n    / ((betaSquared * precision) + recall);\n\n  return fbeta;\n}"
      },
      "typeVersion": 2
    },
    {
      "id": "cd961c4b-170d-46dc-9aa2-128eb4b1ffe7",
      "name": "정확성 점수",
      "type": "n8n-nodes-base.code",
      "position": [
        1400,
        -320
      ],
      "parameters": {
        "mode": "runOnceForEachItem",
        "jsCode": "const {\n  f1Score,\n  similarityScore,\n} = $input.item.json;\n\nconst weights = [0.75, 0.25];\n\nreturn {\n  score: weightedAverage([f1Score, similarityScore], weights)\n};\n\nfunction weightedAverage(values, weights) {\n  const weightedSum = values.reduce((sum, val, i) => sum + val * weights[i], 0);\n  const totalWeight = weights.reduce((sum, w) => sum + w, 0);\n  return weightedSum / totalWeight;\n}"
      },
      "typeVersion": 2
    },
    {
      "id": "4a6f9201-8c09-4210-9322-bd14bd86d4fd",
      "name": "스티커 노트1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1352,
        -530
      ],
      "parameters": {
        "color": 7,
        "width": 840,
        "height": 720,
        "content": "## 1. Setup Your AI Workflow to Use Evaluations\n[Learn more about the Evaluations Trigger](https://docs.n8n.io/integrations/builtin/?utm_source=n8n_app&utm_medium=node_settings_modal-credential_link&utm_campaign=n8n-nodes-base.evaluationTrigger)\n\nThe Evaluations Trigger is a separate execution which does not affect your production workflow in any way. It is manually triggered and automatically pulled datasets from the assigned Google Sheet."
      },
      "typeVersion": 1
    },
    {
      "id": "4be720d8-8a34-4f8d-a27a-04302542a2cc",
      "name": "스티커 노트",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -500,
        -900
      ],
      "parameters": {
        "color": 7,
        "width": 2480,
        "height": 1100,
        "content": "## 2. Answer Correctness: Is the agent getting its facts correct?\n[Learn more about the Evaluations Trigger](https://docs.n8n.io/integrations/builtin/?utm_source=n8n_app&utm_medium=node_settings_modal-credential_link&utm_campaign=n8n-nodes-base.evaluationTrigger)\n\nThis evaluation measures answer correctness compared to ground truth as a combination of factuality and semantic similarity.\nWhen the agent is without tools, this test may check for accuracy in the agent's training data. For best results, the agent's response should be verbose and conversational. "
      },
      "typeVersion": 1
    },
    {
      "id": "2b3fe36c-4af9-4dec-bf0d-e9b6fe0386fb",
      "name": "지표 업데이트",
      "type": "n8n-nodes-base.evaluation",
      "position": [
        1800,
        -320
      ],
      "parameters": {
        "metrics": {
          "assignments": [
            {
              "id": "1fd7759c-f4ef-4eda-87ad-9d9563b63e99",
              "name": "score",
              "type": "number",
              "value": "={{ $json.score }}"
            }
          ]
        },
        "operation": "setMetrics"
      },
      "typeVersion": 4.6
    },
    {
      "id": "2c3b928e-db4c-42b7-b530-34ad3f6a1a04",
      "name": "출력 업데이트",
      "type": "n8n-nodes-base.evaluation",
      "position": [
        1600,
        -320
      ],
      "parameters": {
        "outputs": {
          "values": [
            {
              "outputName": "output",
              "outputValue": "={{ $('Set Input Fields').first().json.answer }}"
            },
            {
              "outputName": "score",
              "outputValue": "={{ $json.score }}"
            }
          ]
        },
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": "gid=0",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit#gid=0",
          "cachedResultName": "Correctness"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=drivesdk",
          "cachedResultName": "96. Evaluations Test"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
          "id": "XHvC7jIRR8A2TlUl",
          "name": "Google Sheets account"
        }
      },
      "typeVersion": 4.6
    },
    {
      "id": "9de68866-994d-455e-af12-fb608a75341d",
      "name": "스티커 노트3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1840,
        -600
      ],
      "parameters": {
        "width": 440,
        "height": 800,
        "content": "## Try It Out!\n### This n8n template demonstrates how to calculate the evaluation metric \"Correctness\" which in this scenario, measures the compares and classifies the agent's response against a set of ground truths.\n\nThe scoring approach is adapted from [https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/_answer_correctness.py](https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/_answer_correctness.py)\n\n### How it works\n* This evaluation works best where the agent's response is allowed to be more verbose and conversational.\n* For our scoring, we classify the agent's response into 3 buckets: True Positive (in answer and ground truth), False Positive (in answer but not ground truth) and False Negative (not in answer but in ground truth).\n* We also calculate an average similarity score on the agent's response against all ground truths.\n* The classification and the similarity score is then averaged to give the final score. \n* A high score indicates the agent is accurate whereas a low score could indicate the agent has incorrect training data or is not providing a comprehensive enough answer.\n\n### Requirements\n* n8n version 1.94+\n* Check out this Google Sheet for a sample data [https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing](https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing)\n\n\n### Need Help?\nJoin the [Discord](https://discord.com/invite/XPKeKXeB7d) or ask in the [Forum](https://community.n8n.io/)!\n\nHappy Hacking!"
      },
      "typeVersion": 1
    },
    {
      "id": "5d3cbd9f-7cd9-4ff9-851c-e0b5b352302e",
      "name": "임베딩 가져오기",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        180,
        -500
      ],
      "parameters": {
        "url": "https://api.openai.com/v1/embeddings",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "authentication": "predefinedCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "input",
              "value": "={{ $json.groundTruth }}"
            },
            {
              "name": "model",
              "value": "text-embedding-3-small"
            },
            {
              "name": "encoding_format",
              "value": "float"
            }
          ]
        },
        "nodeCredentialType": "openAiApi"
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "1da5f360-0e0f-4643-8236-8f55cc343655",
      "name": "GroundTruth를 항목으로 변환",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        -20,
        -500
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "groundTruth"
      },
      "typeVersion": 1
    },
    {
      "id": "e3c0673d-e80a-4f6f-a061-a9d92bfbb082",
      "name": "임베딩 가져오기1",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        180,
        -680
      ],
      "parameters": {
        "url": "https://api.openai.com/v1/embeddings",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "authentication": "predefinedCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "input",
              "value": "={{ $json.answer }}"
            },
            {
              "name": "model",
              "value": "text-embedding-3-small"
            },
            {
              "name": "encoding_format",
              "value": "float"
            }
          ]
        },
        "nodeCredentialType": "openAiApi"
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "70688754-a777-464c-8b3b-f216018438e9",
      "name": "집계",
      "type": "n8n-nodes-base.aggregate",
      "position": [
        580,
        -500
      ],
      "parameters": {
        "options": {},
        "aggregate": "aggregateAllItemData",
        "destinationFieldName": "groundTruth"
      },
      "typeVersion": 1
    },
    {
      "id": "1b91219c-0e7a-4843-8f37-ee0160af2d2d",
      "name": "임베딩 재매핑",
      "type": "n8n-nodes-base.set",
      "position": [
        380,
        -680
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "3db07c98-f926-46e0-85f2-ed1eb137f842",
              "name": "answer",
              "type": "array",
              "value": "={{ $json.data[0].embedding }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "d6844754-380d-4610-984e-a16042a9e239",
      "name": "임베딩 재매핑1",
      "type": "n8n-nodes-base.set",
      "position": [
        380,
        -500
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "3db07c98-f926-46e0-85f2-ed1eb137f842",
              "name": "data",
              "type": "array",
              "value": "={{ $json.data[0].embedding }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "8759c3ab-4d72-46f9-b969-339aba79b34f",
      "name": "임베딩 결과 생성",
      "type": "n8n-nodes-base.merge",
      "position": [
        780,
        -500
      ],
      "parameters": {
        "mode": "combine",
        "options": {},
        "combineBy": "combineByPosition"
      },
      "typeVersion": 3.1
    },
    {
      "id": "3acb5098-2703-4474-86da-d96f76350936",
      "name": "유사도 점수 계산",
      "type": "n8n-nodes-base.code",
      "position": [
        980,
        -500
      ],
      "parameters": {
        "jsCode": "const { answer, groundTruth = [] } = $input.item.json;\n\nconst scores = await Promise.all(groundTruth.map(truth =>\n  cosineSimilarity(answer, truth.data)\n));\n\nconst scoreAvg = scores.reduce((acc,score) => acc + score, 0) / scores.length;\n\nreturn { json: { similarityScore: scoreAvg } }\n\nfunction cosineSimilarity(a, b) {  \n  let dotProduct = normA = normB = 0;\n  for (let i = 0; i < a.length; i++) {\n    dotProduct += a[i] * b[i];\n    normA += a[i] ** 2;\n    normB += b[i] ** 2;\n  }\n  return dotProduct / (Math.sqrt(normA) * Math.sqrt(normB));\n}"
      },
      "typeVersion": 2
    }
  ],
  "pinData": {},
  "connections": {
    "acd7d0aa-00fa-4d9d-9995-f468e1f4770a": {
      "main": [
        [
          {
            "node": "cd961c4b-170d-46dc-9aa2-128eb4b1ffe7",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "b896a963-5fe8-4566-9f11-9c963d93e467": {
      "main": [
        [
          {
            "node": "781b1a23-0359-46ab-bf8e-c86b1bcc0cf9",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "70688754-a777-464c-8b3b-f216018438e9": {
      "main": [
        [
          {
            "node": "8759c3ab-4d72-46f9-b969-339aba79b34f",
            "type": "main",
            "index": 1
          }
        ]
      ]
    },
    "d40a51d3-6ea0-4a16-b094-7862c061904f": {
      "ai_outputParser": [
        [
          {
            "node": "20985bbf-3a4f-4e7c-8c7d-4d4bee4e1eaa",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "781b1a23-0359-46ab-bf8e-c86b1bcc0cf9": {
      "main": [
        [
          {
            "node": "7f8623d7-4263-45f2-a2f1-dcb07dc17c90",
            "type": "main",
            "index": 0
          }
        ],
        [
          {
            "node": "a126142b-bd50-48fb-ab3d-e20fea082dc7",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "9d8b8b85-819a-4762-a573-4e4f50f3c2ba": {
      "main": [
        [
          {
            "node": "b896a963-5fe8-4566-9f11-9c963d93e467",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "5d3cbd9f-7cd9-4ff9-851c-e0b5b352302e": {
      "main": [
        [
          {
            "node": "d6844754-380d-4610-984e-a16042a9e239",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "2c3b928e-db4c-42b7-b530-34ad3f6a1a04": {
      "main": [
        [
          {
            "node": "2b3fe36c-4af9-4dec-bf0d-e9b6fe0386fb",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "e3c0673d-e80a-4f6f-a061-a9d92bfbb082": {
      "main": [
        [
          {
            "node": "1b91219c-0e7a-4843-8f37-ee0160af2d2d",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "1b91219c-0e7a-4843-8f37-ee0160af2d2d": {
      "main": [
        [
          {
            "node": "8759c3ab-4d72-46f9-b969-339aba79b34f",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "7f8623d7-4263-45f2-a2f1-dcb07dc17c90": {
      "main": [
        [
          {
            "node": "20985bbf-3a4f-4e7c-8c7d-4d4bee4e1eaa",
            "type": "main",
            "index": 0
          },
          {
            "node": "e3c0673d-e80a-4f6f-a061-a9d92bfbb082",
            "type": "main",
            "index": 0
          },
          {
            "node": "1da5f360-0e0f-4643-8236-8f55cc343655",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "cd961c4b-170d-46dc-9aa2-128eb4b1ffe7": {
      "main": [
        [
          {
            "node": "2c3b928e-db4c-42b7-b530-34ad3f6a1a04",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "32195796-6f39-47e1-b531-c7583a4bfc2d": {
      "ai_languageModel": [
        [
          {
            "node": "20985bbf-3a4f-4e7c-8c7d-4d4bee4e1eaa",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "d6844754-380d-4610-984e-a16042a9e239": {
      "main": [
        [
          {
            "node": "70688754-a777-464c-8b3b-f216018438e9",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "a183f7f7-0071-42ae-a17d-fc7b087f0f49": {
      "main": [
        [
          {
            "node": "acd7d0aa-00fa-4d9d-9995-f468e1f4770a",
            "type": "main",
            "index": 1
          }
        ]
      ]
    },
    "23186242-a4e5-4e70-a010-acbfa2eafb35": {
      "ai_languageModel": [
        [
          {
            "node": "b896a963-5fe8-4566-9f11-9c963d93e467",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "1da5f360-0e0f-4643-8236-8f55cc343655": {
      "main": [
        [
          {
            "node": "5d3cbd9f-7cd9-4ff9-851c-e0b5b352302e",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "20985bbf-3a4f-4e7c-8c7d-4d4bee4e1eaa": {
      "main": [
        [
          {
            "node": "a183f7f7-0071-42ae-a17d-fc7b087f0f49",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "8759c3ab-4d72-46f9-b969-339aba79b34f": {
      "main": [
        [
          {
            "node": "3acb5098-2703-4474-86da-d96f76350936",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "3acb5098-2703-4474-86da-d96f76350936": {
      "main": [
        [
          {
            "node": "acd7d0aa-00fa-4d9d-9995-f468e1f4770a",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "526b0248-d81b-428f-8f02-aa69acebd05c": {
      "main": [
        [
          {
            "node": "b896a963-5fe8-4566-9f11-9c963d93e467",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "2e6b4d45-f0e0-434a-92bb-c76bf96588ad": {
      "main": [
        [
          {
            "node": "9d8b8b85-819a-4762-a573-4e4f50f3c2ba",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}