{
  "workflow": {
    "id": 3542,
    "name": "Create AI-ready vector datasets for LLMs with Bright Data, Gemini & Pinecone",
    "views": 2385,
    "recentViews": 0,
    "totalViews": 2385,
    "createdAt": "2025-04-13T14:26:13.036Z",
    "description": "### Who this is for?\nThis workflow enables automated, scalable collection of high-quality, AI-ready data from websites using Bright Data’s Web Unlocker, with a focus on preparing that data for LLM training. Leveraging LLM Chains and AI agents, the system formats and extracts key information, then stores the structured embeddings in a Pinecone vector database.\n\nThis workflow is tailored for:​\n\n- ML Engineers & Researchers building or fine-tuning domain-specific LLMs.\n\n- AI Startups needing clean, structured content for product training.\n\n- Data Teams preparing knowledge bases for enterprise-grade AI apps.\n\n- LLM-as-a-Service Providers sourcing dynamic web content across niches.\n\n### What problem is this workflow solving?\n\nTraining a large language model (LLM) requires vast amounts of clean, relevant, and structured data. Manual collection is slow, error-prone, and lacks scalability. \n\nThis workflow:\n\n- Automatically extracts web data from specified URLs.\n\n- Bypasses anti-bot measures using Bright Data’s Web Unlocker.\n\n- Formats, cleans, and transforms raw content using LLM agents.\n\n- Stores semantically searchable vectors in Pinecone.\n\n- Makes datasets AI-ready for fine-tuning, RAG, or domain-specific training.\n\n### What this workflow does\n\nThis workflow automates the process of collecting, cleaning, and vectorizing web content to create structured, high-quality datasets that are ready to be used for LLM (Large Language Model) training or retrieval-augmented generation (RAG).\n\n1. Web Crawling with Bright Data Web Unlocker.\n2. AI Information Extraction and Data Formatting.\n3. AI Data Formatting to produce a JSON structured data.\n3. Persistence in Pinecone Vector DB.\n4. Handle Webhook notification of structured data.\n\n### Setup\n\n- Sign up at [Bright Data](https://brightdata.com/).\n- Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions.\n- In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication).\n![Header Authentication.png](fileId:1235)\nThe Value field should be set with the\n**Bearer XXXXXXXXXXXXXX**. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token.\n- A Google Gemini API key (or access through Vertex AI or proxy).\n- Update the LinkedIn URL by navigating to the **Set LinkedIn URL** node.\n- Update the **Set Fields - URL and Webhook URL** node with the URL for web data extraction and the Webhook notification URL.\n\n### How to customize this workflow to your needs\n\n1. Set Your Target URLs. Target sites that are high-quality, domain-specific, and relevant to your LLM's purpose.\n2. Adjust Bright Data Web Unlocker Settings. Geo-location, Headers / User-Agent strings, Retry rules and proxies.\n3. Modify the Information Extraction Logic. Change prompts to extract specific attributes. Use structured templates or few-shot examples in prompts.\n4. Swap the Embedding Model. Use OpenAI, Hugging Face or other your own hosted embedding model API.\n4. Customize Pinecone Metadata Fields. Store extra fields in Pinecone for better filtering & semantic querying.\n5. Add Data Validation or Deduplication. Skip duplicates or low-quality content.",
    "workflow": {
      "id": "3Lih0LVosR8dZbla",
      "meta": {
        "instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40",
        "templateCredsSetupCompleted": true
      },
      "name": "Create AI-Ready Vector Datasets for LLMs with Bright Data, Gemini & Pinecone",
      "tags": [
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          "id": "Kujft2FOjmOVQAmJ",
          "name": "Engineering",
          "createdAt": "2025-04-09T01:31:00.558Z",
          "updatedAt": "2025-04-09T01:31:00.558Z"
        },
        {
          "id": "ZOwtAMLepQaGW76t",
          "name": "Building Blocks",
          "createdAt": "2025-04-13T15:23:40.462Z",
          "updatedAt": "2025-04-13T15:23:40.462Z"
        },
        {
          "id": "ddPkw7Hg5dZhQu2w",
          "name": "AI",
          "createdAt": "2025-04-13T05:38:08.053Z",
          "updatedAt": "2025-04-13T05:38:08.053Z"
        }
      ],
      "nodes": [
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          "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": [
            1236,
            -60
          ],
          "parameters": {
            "text": "=Format the below search result\n\n{{ $json.output.search_result }}",
            "options": {},
            "promptType": "define",
            "hasOutputParser": true
          },
          "typeVersion": 1.8
        },
        {
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          "name": "Pinecone Vector Store",
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            "mode": "insert",
            "options": {},
            "pineconeIndex": {
              "__rl": true,
              "mode": "list",
              "value": "hacker-news",
              "cachedResultName": "hacker-news"
            }
          },
          "credentials": {
            "pineconeApi": {
              "id": "credential-id",
              "name": "pineconeApi Credential"
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          ],
          "parameters": {
            "modelName": "models/text-embedding-004"
          },
          "credentials": {
            "googlePalmApi": {
              "id": "credential-id",
              "name": "googlePalmApi Credential"
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          },
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          "name": "Default Data Loader",
          "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
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            220
          ],
          "parameters": {
            "options": {},
            "jsonData": "={{ $('Information Extractor with Data Formatter').item.json.output.search_result }}",
            "jsonMode": "expressionData"
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        },
        {
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          "name": "Recursive Character Text Splitter",
          "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
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          ],
          "parameters": {
            "options": {}
          },
          "typeVersion": 1
        },
        {
          "id": "90cc9aa4-0931-4c52-8734-e4e0de820205",
          "name": "Google Gemini Chat Model1",
          "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
          "position": [
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            160
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          "parameters": {
            "options": {},
            "modelName": "models/gemini-2.0-flash-exp"
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          "credentials": {
            "googlePalmApi": {
              "id": "credential-id",
              "name": "googlePalmApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
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          "name": "Google Gemini Chat Model2",
          "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
          "position": [
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            -340
          ],
          "parameters": {
            "options": {},
            "modelName": "models/gemini-2.0-flash-exp"
          },
          "credentials": {
            "googlePalmApi": {
              "id": "credential-id",
              "name": "googlePalmApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
          "id": "324c530c-0a03-411e-acb0-d82e9dc635cf",
          "name": "Google Gemini Chat Model",
          "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
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            160
          ],
          "parameters": {
            "options": {},
            "modelName": "models/gemini-2.0-flash-exp"
          },
          "credentials": {
            "googlePalmApi": {
              "id": "credential-id",
              "name": "googlePalmApi Credential"
            }
          },
          "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": [
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          ],
          "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": [
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          ],
          "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": [
                {}
              ]
            }
          },
          "credentials": {
            "httpHeaderAuth": {
              "id": "credential-id",
              "name": "httpHeaderAuth Credential"
            }
          },
          "typeVersion": 4.2
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          "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
        },
        {
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          "name": "Sticky Note3",
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            "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": [
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          ],
          "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
        },
        {
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            "color": 5,
            "width": 720,
            "height": 720,
            "content": "## Data Extraction/Formatting with the AI Agent\n"
          },
          "typeVersion": 1
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      ],
      "active": false,
      "pinData": {},
      "settings": {
        "executionOrder": "v1"
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      "connections": {
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            [
              {
                "node": "Pinecone Vector Store",
                "type": "main",
                "index": 0
              },
              {
                "node": "Webhook for structured AI agent response",
                "type": "main",
                "index": 0
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            ]
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        "Make a web request": {
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                "node": "Structured JSON Data Formatter",
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              },
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                "node": "Information Extractor with Data Formatter",
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        "Default Data Loader": {
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                "type": "ai_document",
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        "Embeddings Google Gemini": {
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        "Google Gemini Chat Model": {
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                "node": "Information Extractor with Data Formatter",
                "type": "ai_languageModel",
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                "node": "AI Agent",
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        "Google Gemini Chat Model1": {
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                "node": "AI Agent",
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        "Google Gemini Chat Model2": {
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      }
    },
    "status": "published",
    "user": {
      "name": "Ranjan Dailata",
      "username": "ranjancse",
      "bio": "A Professional based out of India specialized in handling AI-powered automations. Contact me at ranjancse@gmail.com ",
      "verified": true,
      "links": [
        "https://www.linkedin.com/in/ranjan-dailata/"
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        "codex": {
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            "resources": {
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                  "icon": "🧬",
                  "label": "Why business process automation with n8n can change your daily life"
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                  "label": "Learn how to automatically cross-post your content with n8n"
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