{
  "name": "answer · 71 Lab 01 challenge (index with section)",
  "nodes": [
    {
      "name": "Index webhook",
      "type": "n8n-nodes-base.webhook",
      "typeVersion": 2,
      "position": [
        0,
        300
      ],
      "parameters": {
        "httpMethod": "POST",
        "path": "my-index",
        "responseMode": "responseNode",
        "options": {}
      }
    },
    {
      "name": "List docs",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4.2,
      "position": [
        200,
        300
      ],
      "parameters": {
        "url": "http://data-api:8800/docs",
        "options": {}
      }
    },
    {
      "name": "One item per doc",
      "type": "n8n-nodes-base.splitOut",
      "typeVersion": 1,
      "position": [
        400,
        300
      ],
      "parameters": {
        "fieldToSplitOut": "docs",
        "options": {}
      }
    },
    {
      "name": "Get doc",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4.2,
      "position": [
        600,
        300
      ],
      "parameters": {
        "url": "=http://data-api:8800/docs/{{ $json.name }}",
        "options": {}
      }
    },
    {
      "name": "Make chunks",
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        800,
        300
      ],
      "parameters": {
        "jsCode": "// Split each policy document into chunks. Body \"chunking\": \"section\" (one chunk per ## section, default) or a number of characters.\nconst body = $('Index webhook').first().json.body ?? {};\nconst CHUNKING = body.chunking ?? 'section';\nconst chunks = [];\nfor (const item of $input.all()) {\n  const { name, title, text } = item.json;\n  const content = text.split('\\n').slice(1).join('\\n').trim();\n  let pieces;\n  if (CHUNKING === 'section') {\n    pieces = content.split(/\\n(?=## )/).map(part => part.trim()).filter(Boolean);\n  } else {\n    const size = Number(CHUNKING), step = size - Math.floor(size / 5);\n    pieces = [];\n    for (let i = 0; i < content.length; i += step) pieces.push(content.slice(i, i + size));\n  }\n  pieces.forEach((piece, i) => {\n    const section = (piece.match(/^## (.+)$/m) ?? [])[1] ?? '';\n    chunks.push({ json: { source: name, title, chunk: i + 1, section, text: `${title}\\n${piece}` } });\n  });\n}\nreturn chunks;"
      }
    },
    {
      "name": "Store chunks",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreInMemory",
      "typeVersion": 1.3,
      "position": [
        1020,
        300
      ],
      "parameters": {
        "mode": "insert",
        "memoryKey": {
          "__rl": true,
          "mode": "list",
          "value": "my_policy_docs",
          "cachedResultName": "my_policy_docs"
        },
        "clearStore": true
      }
    },
    {
      "name": "Embeddings",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "typeVersion": 1.2,
      "position": [
        960,
        520
      ],
      "parameters": {
        "model": "text-embedding-3-large",
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "openAiCourse0001",
          "name": "OpenAI (.env)"
        }
      }
    },
    {
      "name": "Chunk loader",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "typeVersion": 1.1,
      "position": [
        1120,
        520
      ],
      "parameters": {
        "jsonMode": "expressionData",
        "jsonData": "={{ $json.text }}",
        "textSplittingMode": "simple",
        "options": {
          "metadata": {
            "metadataValues": [
              {
                "name": "source",
                "value": "={{ $json.source }}"
              },
              {
                "name": "title",
                "value": "={{ $json.title }}"
              },
              {
                "name": "chunk",
                "value": "={{ $json.chunk }}"
              },
              {
                "name": "section",
                "value": "={{ $json.section }}"
              }
            ]
          }
        }
      }
    },
    {
      "name": "Count",
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        1260,
        300
      ],
      "parameters": {
        "jsCode": "// One summary item after all chunks are stored.\nreturn [{ json: { indexed_chunks: $('Make chunks').all().length, chunking: ($('Index webhook').first().json.body ?? {}).chunking ?? 'section' } }];"
      }
    },
    {
      "name": "Send result",
      "type": "n8n-nodes-base.respondToWebhook",
      "typeVersion": 1.1,
      "position": [
        1460,
        300
      ],
      "parameters": {
        "respondWith": "json",
        "responseBody": "={{ $json }}",
        "options": {}
      }
    }
  ],
  "connections": {
    "Index webhook": {
      "main": [
        [
          {
            "node": "List docs",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "List docs": {
      "main": [
        [
          {
            "node": "One item per doc",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "One item per doc": {
      "main": [
        [
          {
            "node": "Get doc",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Get doc": {
      "main": [
        [
          {
            "node": "Make chunks",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Make chunks": {
      "main": [
        [
          {
            "node": "Store chunks",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Store chunks": {
      "main": [
        [
          {
            "node": "Count",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Count": {
      "main": [
        [
          {
            "node": "Send result",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings": {
      "ai_embedding": [
        [
          {
            "node": "Store chunks",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "Chunk loader": {
      "ai_document": [
        [
          {
            "node": "Store chunks",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    }
  },
  "settings": {
    "executionOrder": "v1"
  }
}