{
  "name": "Create AI-Ready Vector Datasets for LLMs with Bright Data, Gemini & Pinecone",
  "nodes": [
    {
      "id": "0a468953-e348-420e-a6b3-c55fb20d3cbf",
      "name": "When clicking ‘Test workflow’",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
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      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "3725e480-246f-4f32-b0a7-b946cacbe830",
      "name": "AI Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
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        -60
      ],
      "parameters": {
        "text": "=Format the below search result\n\n{{ $json.output.search_result }}",
        "options": {},
        "promptType": "define",
        "hasOutputParser": true
      },
      "typeVersion": 1.8
    },
    {
      "id": "30a12b8e-02f5-4b2e-bf9f-20fd9658405e",
      "name": "Pinecone Vector Store",
      "type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
      "position": [
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        -10
      ],
      "parameters": {
        "mode": "insert",
        "options": {},
        "pineconeIndex": {
          "__rl": true,
          "mode": "list",
          "value": "REPLACE_WITH_RESOURCE"
        }
      },
      "typeVersion": 1.1
    },
    {
      "id": "1738dea6-fa4f-4a8d-a6fb-2f01feb1a6d5",
      "name": "Embeddings Google Gemini",
      "type": "@n8n/n8n-nodes-langchain.embeddingsGoogleGemini",
      "position": [
        1612,
        210
      ],
      "parameters": {
        "modelName": "models/text-embedding-004"
      },
      "typeVersion": 1
    },
    {
      "id": "e6443541-de71-4d26-ad58-d7c72868a190",
      "name": "Default Data Loader",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        1760,
        220
      ],
      "parameters": {
        "options": {},
        "jsonData": "={{ $('Information Extractor with Data Formatter').item.json.output.search_result }}",
        "jsonMode": "expressionData"
      },
      "typeVersion": 1
    },
    {
      "id": "09ffc8cd-096f-47fe-937d-f8ab4fb41266",
      "name": "Recursive Character Text Splitter",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "position": [
        1820,
        410
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "90cc9aa4-0931-4c52-8734-e4e0de820205",
      "name": "Google Gemini Chat Model1",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        1240,
        160
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "typeVersion": 1
    },
    {
      "id": "1090a4af-7e5d-446b-a537-3afe48cd4909",
      "name": "Google Gemini Chat Model2",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        948,
        -340
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "typeVersion": 1
    },
    {
      "id": "324c530c-0a03-411e-acb0-d82e9dc635cf",
      "name": "Google Gemini Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        948,
        160
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "typeVersion": 1
    },
    {
      "id": "3226a2d6-ade1-4d6a-95c5-0be4d787a947",
      "name": "Structured Output Parser",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        1400,
        160
      ],
      "parameters": {
        "jsonSchemaExample": "[{\n\t\"id\": \"<string>\",\n\t\"title\": \"<string>\",\n    \"summary\": \"<string>\",\n    \"keywords\": [\"\"],\n    \"topics\": [\"\"]\n}]"
      },
      "typeVersion": 1.2
    },
    {
      "id": "a739a314-900a-4ef7-9cc2-1b65374e2e05",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        40,
        -360
      ],
      "parameters": {
        "width": 480,
        "height": 220,
        "content": "## Note\nPlease make sure to set the URL for web crawling. \n\nWeb-Unlocker Product is being utilized for performing the web scrapping. \n\nThis workflow is utilizing the Basic LLM Chain, Information Extraction with the AI Agents for formatting, extracting and persisting the response in PineCone Vector Database"
      },
      "typeVersion": 1
    },
    {
      "id": "3dca6d46-c423-4fb5-a6e4-c2aa2852d51c",
      "name": "Set Fields - URL and Webhook URL",
      "type": "n8n-nodes-base.set",
      "notes": "Set the URL which you are interested to scrap the data",
      "position": [
        420,
        -710
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "1c132dd6-31e4-453b-a8cf-cad9845fe55b",
              "name": "url",
              "type": "string",
              "value": "https://news.ycombinator.com?product=unlocker&method=api"
            },
            {
              "id": "90f3272b-d13d-44e2-8b4c-0943648cfce9",
              "name": "webhook_url",
              "type": "string",
              "value": "https://webhook.site/bc804ce5-4a45-4177-a68a-99c80e5c86e6"
            }
          ]
        }
      },
      "notesInFlow": true,
      "typeVersion": 3.4
    },
    {
      "id": "216a3261-a398-484c-9bf4-ca5966b829b6",
      "name": "Make a web request",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        640,
        -260
      ],
      "parameters": {
        "url": "https://api.brightdata.com/request",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "sendHeaders": true,
        "authentication": "genericCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "zone",
              "value": "web_unlocker1"
            },
            {
              "name": "url",
              "value": "={{ $json.url }}"
            },
            {
              "name": "format",
              "value": "raw"
            }
          ]
        },
        "genericAuthType": "httpHeaderAuth",
        "headerParameters": {
          "parameters": [
            {}
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "0c74e21c-3007-4297-b6ab-8ee17f4c6436",
      "name": "Structured JSON Data Formatter",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        860,
        -560
      ],
      "parameters": {
        "text": "=Format the below response and produce a textual data. Output the response as per the below JSON schema.\n\nHere's the input: {{ $json.data }}\nHere's the JSON schema: \n\n[{\n    \"rank\": { \"type\": \"integer\" },\n    \"title\": { \"type\": \"string\" },\n    \"site\": { \"type\": \"string\" },\n    \"points\": { \"type\": \"integer\" },\n    \"user\": { \"type\": \"string\" },\n    \"age\": { \"type\": \"string\" },\n    \"comments\": { \"type\": \"string\" }\n}]",
        "messages": {
          "messageValues": [
            {
              "message": "You are an expert data formatter"
            }
          ]
        },
        "promptType": "define"
      },
      "typeVersion": 1.6
    },
    {
      "id": "012d4bb0-2b58-47cd-9cea-b4e0dced9082",
      "name": "Webhook for structured data",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1314,
        -860
      ],
      "parameters": {
        "url": "={{ $json.webhook_url }}",
        "options": {},
        "sendBody": true,
        "bodyParameters": {
          "parameters": [
            {
              "name": "response",
              "value": "={{ $json.text }}"
            }
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "93b35e5e-6f52-4aeb-8f1b-39cc495beefe",
      "name": "Webhook for structured AI agent response",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1750,
        -660
      ],
      "parameters": {
        "url": "={{ $json.webhook_url }}",
        "options": {},
        "sendBody": true,
        "bodyParameters": {
          "parameters": [
            {
              "name": "response",
              "value": "={{ $json.output }}"
            }
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "251b4251-255c-48c6-999b-02227fa2de9b",
      "name": "Sticky Note1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        800,
        -620
      ],
      "parameters": {
        "width": 360,
        "height": 420,
        "content": "## AI Data Formatter\n"
      },
      "typeVersion": 1
    },
    {
      "id": "f62463cd-6be3-4942-a636-de980a3154b4",
      "name": "Sticky Note2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1560,
        -160
      ],
      "parameters": {
        "color": 4,
        "width": 520,
        "height": 720,
        "content": "## Vector Database Persistence\n"
      },
      "typeVersion": 1
    },
    {
      "id": "ad20cc91-766a-4a57-be54-6f0d09a784eb",
      "name": "Sticky Note3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1260,
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      ],
      "parameters": {
        "color": 3,
        "width": 680,
        "height": 440,
        "content": "## Webhook Notification Handler\n"
      },
      "typeVersion": 1
    },
    {
      "id": "37ab5c0f-d36e-4131-844d-20a22d3f2861",
      "name": "Information Extractor with Data Formatter",
      "type": "@n8n/n8n-nodes-langchain.informationExtractor",
      "position": [
        860,
        -60
      ],
      "parameters": {
        "text": "={{ $json.data }}",
        "options": {
          "systemPromptTemplate": "You are an expert HTML extractor. Your job is to analyze the search result and extract the content as a collection on items"
        },
        "attributes": {
          "attributes": [
            {
              "name": "search_result",
              "description": "Search Response"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "id": "e04e189a-8ba9-4ef4-9a49-fc13daf00828",
      "name": "Sticky Note4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        800,
        -160
      ],
      "parameters": {
        "color": 5,
        "width": 720,
        "height": 720,
        "content": "## Data Extraction/Formatting with the AI Agent\n"
      },
      "typeVersion": 1
    },
    {
      "id": "46b96099-a9ac-56ef-b9ba-217b845e0584",
      "name": "Publication · Overview and setup",
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
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      ],
      "parameters": {
        "content": "# Create AI-Ready Vector Datasets for LLMs with Bright Data, Gemini & Pinecone\n\n## Purpose and structure\nThis folder contains the **Create AI-Ready Vector Datasets for LLMs with Bright Data, Gemini & Pinecone** workflow. Its executable nodes use `agent`, `chainLlm`, `documentDefaultDataLoader`, `embeddingsGoogleGemini`, `httpRequest`, `informationExtractor`, `lmChatGoogleGemini`, `manualTrigger`, `outputParserStructured`, `set`, `textSplitterRecursiveCharacterTextSplitter`, `vectorStorePinecone`. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.\n\n## Setup\nImport inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.\n\n## Entry points\nWhen clicking ‘Test workflow’\n\n## Verification\nSanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.\n\n## Attribution\nhttps://github.com/Zie619/n8n-workflows/blob/94007c1445d9258a7da116646b79473e7c7c3282/workflows/Manual/0933_Manual_Stickynote_Create_Webhook.json\nMIT; preserve source notices.",
        "width": 700,
        "height": 800,
        "color": 1
      }
    }
  ],
  "active": false,
  "settings": {
    "executionOrder": "v1"
  },
  "connections": {
    "AI Agent": {
      "main": [
        [
          {
            "node": "Pinecone Vector Store",
            "type": "main",
            "index": 0
          },
          {
            "node": "Webhook for structured AI agent response",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Make a web request": {
      "main": [
        [
          {
            "node": "Structured JSON Data Formatter",
            "type": "main",
            "index": 0
          },
          {
            "node": "Information Extractor with Data Formatter",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Default Data Loader": {
      "ai_document": [
        [
          {
            "node": "Pinecone Vector Store",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "Pinecone Vector Store": {
      "ai_tool": [
        []
      ]
    },
    "Embeddings Google Gemini": {
      "ai_embedding": [
        [
          {
            "node": "Pinecone Vector Store",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "Information Extractor with Data Formatter",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Structured Output Parser": {
      "ai_outputParser": [
        [
          {
            "node": "AI Agent",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model1": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model2": {
      "ai_languageModel": [
        [
          {
            "node": "Structured JSON Data Formatter",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Structured JSON Data Formatter": {
      "main": [
        [
          {
            "node": "Webhook for structured data",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Set Fields - URL and Webhook URL": {
      "main": [
        [
          {
            "node": "Make a web request",
            "type": "main",
            "index": 0
          },
          {
            "node": "Webhook for structured data",
            "type": "main",
            "index": 0
          },
          {
            "node": "Webhook for structured AI agent response",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Recursive Character Text Splitter": {
      "ai_textSplitter": [
        [
          {
            "node": "Default Data Loader",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
      ]
    },
    "When clicking ‘Test workflow’": {
      "main": [
        [
          {
            "node": "Set Fields - URL and Webhook URL",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Information Extractor with Data Formatter": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}