{
  "id": "1GOrjyc9mtZCMvCr",
  "meta": {
    "instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40",
    "templateCredsSetupCompleted": true
  },
  "name": "Structured Data Extract, Data Mining with Bright Data & Google Gemini",
  "tags": [
    {
      "id": "Kujft2FOjmOVQAmJ",
      "name": "Engineering",
      "createdAt": "2025-04-09T01:31:00.558Z",
      "updatedAt": "2025-04-09T01:31:00.558Z"
    },
    {
      "id": "ddPkw7Hg5dZhQu2w",
      "name": "AI",
      "createdAt": "2025-04-13T05:38:08.053Z",
      "updatedAt": "2025-04-13T05:38:08.053Z"
    }
  ],
  "nodes": [
    {
      "id": "1e9038e6-9ebc-4460-bee2-3faea3b38f4c",
      "name": "When clicking ‘Test workflow’",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        200,
        -420
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "fd4ace46-7261-4380-8b65-1e00bb574f27",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        200,
        -780
      ],
      "parameters": {
        "width": 400,
        "height": 300,
        "content": "## Note\n\nThis workflow deals with the structured data extraction by utilizing Bright Data Web Unlocker Product.\n\nThe Basic LLM Chain, Information Extraction, are being used to demonstrate the usage of the N8N AI capabilities.\n\n**Please make sure to set the web URL of your interest within the \"Set URL and Bright Data Zone\" node and update the Webhook Notification URL**"
      },
      "typeVersion": 1
    },
    {
      "id": "1c1dd10f-beb2-4cc7-9118-77efd3172651",
      "name": "Sticky Note1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        620,
        -780
      ],
      "parameters": {
        "width": 480,
        "height": 300,
        "content": "## LLM Usages\n\nGoogle Gemini Flash Exp model is being used.\n\nBasic LLM Chain Data Extractor.\n\nInformation Extraction is being used for the handling the custom sentiment analysis with the structured response."
      },
      "typeVersion": 1
    },
    {
      "id": "9795ac80-6ded-465d-bfcf-0c6ce120452f",
      "name": "Markdown to Textual Data Extractor",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        860,
        -420
      ],
      "parameters": {
        "text": "=You need to analyze the below markdown and convert to textual data. Please do not output with your own thoughts. Make sure to output with textual data only with no links, scripts, css etc.\n\n{{ $json.data }}",
        "messages": {
          "messageValues": [
            {
              "message": "You are a markdown expert"
            }
          ]
        },
        "promptType": "define"
      },
      "typeVersion": 1.6
    },
    {
      "id": "b6a8cc64-c0c7-40dc-b7c1-0571baf3a0a9",
      "name": "Set URL and Bright Data Zone",
      "type": "n8n-nodes-base.set",
      "position": [
        420,
        -420
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "3aedba66-f447-4d7a-93c0-8158c5e795f9",
              "name": "url",
              "type": "string",
              "value": "https://www.bbc.com/news/world"
            },
            {
              "id": "4e7ee31d-da89-422f-8079-2ff2d357a0ba",
              "name": "zone",
              "type": "string",
              "value": "web_unlocker1"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "8d15dca1-3014-405f-ac35-78d64eda1d07",
      "name": "Initiate a Webhook Notification for Markdown to Textual Data Extraction",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1314,
        -720
      ],
      "parameters": {
        "url": "https://webhook.site/3c36d7d1-de1b-4171-9fd3-643ea2e4dd76",
        "options": {},
        "sendBody": true,
        "bodyParameters": {
          "parameters": [
            {
              "name": "content",
              "value": "={{ $json.text }}"
            }
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "fff9e2d1-f3e2-47c3-8c3a-f9de8dbdee6a",
      "name": "Initiate a Webhook Notification for AI Sentiment Analyzer",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1612,
        80
      ],
      "parameters": {
        "url": "https://webhook.site/3c36d7d1-de1b-4171-9fd3-643ea2e4dd76",
        "options": {},
        "sendBody": true,
        "bodyParameters": {
          "parameters": [
            {
              "name": "summary",
              "value": "={{ $json.output }}"
            }
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "40c82a76-1710-4e57-8123-9c9fbc729110",
      "name": "Google Gemini Chat Model for Data Extract",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        948,
        -200
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "0c1da174-9b9c-4067-9b2c-fa0cc8c33dc8",
      "name": "Google Gemini Chat Model for Sentiment Analyzer",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        1324,
        200
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "7fae589c-854d-429e-9e67-527a002fcabf",
      "name": "Perform Bright Data Web Request",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        640,
        -420
      ],
      "parameters": {
        "url": "https://api.brightdata.com/request",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "sendHeaders": true,
        "authentication": "genericCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "zone",
              "value": "={{ $json.zone }}"
            },
            {
              "name": "url",
              "value": "={{ $json.url }}?product=unlocker&method=api"
            },
            {
              "name": "format",
              "value": "raw"
            },
            {
              "name": "data_format",
              "value": "markdown"
            }
          ]
        },
        "genericAuthType": "httpHeaderAuth",
        "headerParameters": {
          "parameters": [
            {}
          ]
        }
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "kdbqXuxIR8qIxF7y",
          "name": "Header Auth account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "e15fb9ba-ea8f-41f0-9b99-437d14a98a7d",
      "name": "Topic Extractor with the structured response",
      "type": "@n8n/n8n-nodes-langchain.informationExtractor",
      "position": [
        1236,
        -20
      ],
      "parameters": {
        "text": "=Perform the topic analysis on the below content and output with the structured information.\n\nHere's the content:\n\n{{ $('Perform Bright Data Web Request').item.json.data }}",
        "options": {
          "systemPromptTemplate": "You are an expert data analyst."
        },
        "schemaType": "manual",
        "inputSchema": "{\n  \"$schema\": \"http://json-schema.org/draft-07/schema#\",\n  \"title\": \"TopicModelingResponseArray\",\n  \"type\": \"array\",\n  \"items\": {\n    \"type\": \"object\",\n    \"properties\": {\n      \"topic\": {\n        \"type\": \"string\",\n        \"description\": \"The identified topic or theme derived from the input text.\"\n      },\n      \"score\": {\n        \"type\": \"number\",\n        \"minimum\": 0,\n        \"maximum\": 1,\n        \"description\": \"Confidence score representing how strongly this topic is reflected in the content.\"\n      },\n      \"summary\": {\n        \"type\": \"string\",\n        \"description\": \"Brief explanation of the topic’s context within the text.\"\n      },\n      \"keywords\": {\n        \"type\": \"array\",\n        \"description\": \"List of keywords associated with the topic.\",\n        \"items\": {\n          \"type\": \"string\"\n        }\n      }\n    },\n    \"required\": [\"topic\", \"score\", \"summary\", \"keywords\"],\n    \"additionalProperties\": false\n  }\n}\n"
      },
      "typeVersion": 1
    },
    {
      "id": "e7f2b2c5-89ba-45c4-b7a4-297a159f8b39",
      "name": "Trends by location and category with the structured response",
      "type": "@n8n/n8n-nodes-langchain.informationExtractor",
      "position": [
        1236,
        -520
      ],
      "parameters": {
        "text": "=Perform the data analysis on the below content and output with the structured information by clustering the emerging trends by location and category\n\nHere's the content:\n\n{{ $('Perform Bright Data Web Request').item.json.data }}",
        "options": {
          "systemPromptTemplate": "You are an expert data analyst."
        },
        "schemaType": "manual",
        "inputSchema": "{\n  \"$schema\": \"http://json-schema.org/draft-07/schema#\",\n  \"title\": \"EmergingTrendsClusteredByLocationAndCategory\",\n  \"type\": \"array\",\n  \"items\": {\n    \"type\": \"object\",\n    \"properties\": {\n      \"location\": {\n        \"type\": \"string\",\n        \"description\": \"Geographical region or city where the trend is observed.\"\n      },\n      \"category\": {\n        \"type\": \"string\",\n        \"description\": \"Domain or industry related to the trend (e.g., Technology, Finance, Healthcare).\"\n      },\n      \"trends\": {\n        \"type\": \"array\",\n        \"items\": {\n          \"type\": \"object\",\n          \"properties\": {\n            \"trend\": {\n              \"type\": \"string\",\n              \"description\": \"A concise label for the emerging trend.\"\n            },\n            \"score\": {\n              \"type\": \"number\",\n              \"minimum\": 0,\n              \"maximum\": 1,\n              \"description\": \"Confidence or prominence score of the trend.\"\n            },\n            \"summary\": {\n              \"type\": \"string\",\n              \"description\": \"Short explanation describing the context and impact of the trend.\"\n            },\n            \"mentions\": {\n              \"type\": \"array\",\n              \"items\": {\n                \"type\": \"string\"\n              },\n              \"description\": \"Keywords or phrases that commonly co-occur with the trend.\"\n            }\n          },\n          \"required\": [\"trend\", \"score\", \"summary\", \"mentions\"],\n          \"additionalProperties\": false\n        }\n      }\n    },\n    \"required\": [\"location\", \"category\", \"trends\"],\n    \"additionalProperties\": false\n  }\n}\n"
      },
      "typeVersion": 1
    },
    {
      "id": "92203e9f-cf13-435e-bf78-3c39a6e1e6f6",
      "name": "Google Gemini Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        1324,
        -300
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "1a252b74-6768-41a6-99dd-090e35c47065",
      "name": "Initiate a Webhook Notification for trends by location and category",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1612,
        -320
      ],
      "parameters": {
        "url": "https://webhook.site/3c36d7d1-de1b-4171-9fd3-643ea2e4dd76",
        "options": {},
        "sendBody": true,
        "bodyParameters": {
          "parameters": [
            {
              "name": "summary",
              "value": "={{ $json.output }}"
            }
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "c952ab41-66af-4b41-b04e-407816074c87",
      "name": "Create a binary file for topics",
      "type": "n8n-nodes-base.function",
      "position": [
        1612,
        -120
      ],
      "parameters": {
        "functionCode": "items[0].binary = {\n  data: {\n    data: new Buffer(JSON.stringify(items[0].json, null, 2)).toString('base64')\n  }\n};\nreturn items;"
      },
      "typeVersion": 1
    },
    {
      "id": "2cf80339-0927-4f48-a13a-c610eaf4edca",
      "name": "Write the topics file to disk",
      "type": "n8n-nodes-base.readWriteFile",
      "position": [
        1820,
        -120
      ],
      "parameters": {
        "options": {},
        "fileName": "d:\\topics.json",
        "operation": "write"
      },
      "typeVersion": 1
    },
    {
      "id": "cf1da0ee-bb78-4ea7-bb2d-f2f82f728b12",
      "name": "Write the trends file to disk",
      "type": "n8n-nodes-base.readWriteFile",
      "position": [
        1832,
        -520
      ],
      "parameters": {
        "options": {},
        "fileName": "d:\\trends.json",
        "operation": "write"
      },
      "typeVersion": 1
    },
    {
      "id": "d38ca005-6ba3-4105-9fcd-058602ba16ce",
      "name": "Create a binary data for tends",
      "type": "n8n-nodes-base.function",
      "position": [
        1612,
        -520
      ],
      "parameters": {
        "functionCode": "items[0].binary = {\n  data: {\n    data: new Buffer(JSON.stringify(items[0].json, null, 2)).toString('base64')\n  }\n};\nreturn items;"
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "6a81579d-1f3b-4ea2-821b-fff07b32ee7d",
  "connections": {
    "Google Gemini Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "Trends by location and category with the structured response",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Set URL and Bright Data Zone": {
      "main": [
        [
          {
            "node": "Perform Bright Data Web Request",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Write the trends file to disk": {
      "main": [
        []
      ]
    },
    "Create a binary data for tends": {
      "main": [
        [
          {
            "node": "Write the trends file to disk",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Create a binary file for topics": {
      "main": [
        [
          {
            "node": "Write the topics file to disk",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Perform Bright Data Web Request": {
      "main": [
        [
          {
            "node": "Markdown to Textual Data Extractor",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "When clicking ‘Test workflow’": {
      "main": [
        [
          {
            "node": "Set URL and Bright Data Zone",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Markdown to Textual Data Extractor": {
      "main": [
        [
          {
            "node": "Topic Extractor with the structured response",
            "type": "main",
            "index": 0
          },
          {
            "node": "Initiate a Webhook Notification for Markdown to Textual Data Extraction",
            "type": "main",
            "index": 0
          },
          {
            "node": "Trends by location and category with the structured response",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model for Data Extract": {
      "ai_languageModel": [
        [
          {
            "node": "Markdown to Textual Data Extractor",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Topic Extractor with the structured response": {
      "main": [
        [
          {
            "node": "Initiate a Webhook Notification for AI Sentiment Analyzer",
            "type": "main",
            "index": 0
          },
          {
            "node": "Create a binary file for topics",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model for Sentiment Analyzer": {
      "ai_languageModel": [
        [
          {
            "node": "Topic Extractor with the structured response",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Trends by location and category with the structured response": {
      "main": [
        [
          {
            "node": "Initiate a Webhook Notification for trends by location and category",
            "type": "main",
            "index": 0
          },
          {
            "node": "Create a binary data for tends",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}