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Créer un ensemble de données vectoriel prêt pour l'IA pour les LLM à l'aide de Bright Data, Gemini et Pinecone

Avancé

Ceci est unBuilding Blocks, AIworkflow d'automatisation du domainecontenant 21 nœuds.Utilise principalement des nœuds comme Set, HttpRequest, ManualTrigger, Agent, ChainLlm, combinant la technologie d'intelligence artificielle pour une automatisation intelligente. Créer des jeux de données vectoriels prêts pour l'IA pour les LLM avec Bright Data, Gemini et Pinecone

Prérequis
  • •Peut nécessiter les informations d'identification d'authentification de l'API cible
  • •Clé API Google Gemini
  • •Clé API Pinecone

Nœuds utilisés (21)

Set
StickyNote
HttpRequest
ManualTrigger
Agent
ChainLlm
LmChatGoogleGemini
VectorStorePinecone
InformationExtractor
EmbeddingsGoogleGemini
OutputParserStructured
DocumentDefaultDataLoader
TextSplitterRecursiveCharacterTextSplitter

Catégorie

Blocs de construction
Intelligence Artificielle
Aperçu du workflow
Visualisation des connexions entre les nœuds, avec support du zoom et du déplacement
React Flow
Exporter le workflow
Copiez la configuration JSON suivante dans n8n pour importer et utiliser ce workflow
{
  "id": "3Lih0LVosR8dZbla",
  "meta": {
    "instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40",
    "templateCredsSetupCompleted": true
  },
  "name": "Create AI-Ready Vector Datasets for LLMs with Bright Data, Gemini & Pinecone",
  "tags": [
    {
      "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": [
    {
      "id": "0a468953-e348-420e-a6b3-c55fb20d3cbf",
      "name": "Lors du clic sur 'Tester le workflow'",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        200,
        -710
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "3725e480-246f-4f32-b0a7-b946cacbe830",
      "name": "Agent IA",
      "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
    },
    {
      "id": "30a12b8e-02f5-4b2e-bf9f-20fd9658405e",
      "name": "Magasin vectoriel Pinecone",
      "type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
      "position": [
        1628,
        -10
      ],
      "parameters": {
        "mode": "insert",
        "options": {},
        "pineconeIndex": {
          "__rl": true,
          "mode": "list",
          "value": "hacker-news",
          "cachedResultName": "hacker-news"
        }
      },
      "credentials": {
        "pineconeApi": {
          "id": "wdfRQ6NE8yjCDFhY",
          "name": "PineconeApi account"
        }
      },
      "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"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "e6443541-de71-4d26-ad58-d7c72868a190",
      "name": "Chargeur de données par défaut",
      "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": "Séparateur de texte récursif",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "position": [
        1820,
        410
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "90cc9aa4-0931-4c52-8734-e4e0de820205",
      "name": "Modèle de chat Google Gemini 1",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        1240,
        160
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "1090a4af-7e5d-446b-a537-3afe48cd4909",
      "name": "Modèle de chat Google Gemini 2",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        948,
        -340
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "324c530c-0a03-411e-acb0-d82e9dc635cf",
      "name": "Modèle de chat Google Gemini",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        948,
        160
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "3226a2d6-ade1-4d6a-95c5-0be4d787a947",
      "name": "Analyseur de sortie structurée",
      "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": "Note autocollante",
      "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": "Définir les champs - URL et 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 une requête web",
      "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": "kdbqXuxIR8qIxF7y",
          "name": "Header Auth account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "0c74e21c-3007-4297-b6ab-8ee17f4c6436",
      "name": "Formateur de données structurées JSON",
      "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 pour données structurées",
      "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 pour réponse d'agent IA structurée",
      "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": "Note autocollante 1",
      "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": "Note autocollante 2",
      "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": "Note autocollante 3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1260,
        -920
      ],
      "parameters": {
        "color": 3,
        "width": 680,
        "height": 440,
        "content": "## Webhook Notification Handler\n"
      },
      "typeVersion": 1
    },
    {
      "id": "37ab5c0f-d36e-4131-844d-20a22d3f2861",
      "name": "Extracteur d'informations avec formateur de données",
      "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": "Note autocollante 4",
      "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
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "799fb406-600d-45a5-b926-24b8844f33a5",
  "connections": {
    "3725e480-246f-4f32-b0a7-b946cacbe830": {
      "main": [
        [
          {
            "node": "30a12b8e-02f5-4b2e-bf9f-20fd9658405e",
            "type": "main",
            "index": 0
          },
          {
            "node": "93b35e5e-6f52-4aeb-8f1b-39cc495beefe",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "216a3261-a398-484c-9bf4-ca5966b829b6": {
      "main": [
        [
          {
            "node": "0c74e21c-3007-4297-b6ab-8ee17f4c6436",
            "type": "main",
            "index": 0
          },
          {
            "node": "37ab5c0f-d36e-4131-844d-20a22d3f2861",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "e6443541-de71-4d26-ad58-d7c72868a190": {
      "ai_document": [
        [
          {
            "node": "30a12b8e-02f5-4b2e-bf9f-20fd9658405e",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "30a12b8e-02f5-4b2e-bf9f-20fd9658405e": {
      "ai_tool": [
        []
      ]
    },
    "1738dea6-fa4f-4a8d-a6fb-2f01feb1a6d5": {
      "ai_embedding": [
        [
          {
            "node": "30a12b8e-02f5-4b2e-bf9f-20fd9658405e",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "324c530c-0a03-411e-acb0-d82e9dc635cf": {
      "ai_languageModel": [
        [
          {
            "node": "37ab5c0f-d36e-4131-844d-20a22d3f2861",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "3226a2d6-ade1-4d6a-95c5-0be4d787a947": {
      "ai_outputParser": [
        [
          {
            "node": "3725e480-246f-4f32-b0a7-b946cacbe830",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "90cc9aa4-0931-4c52-8734-e4e0de820205": {
      "ai_languageModel": [
        [
          {
            "node": "3725e480-246f-4f32-b0a7-b946cacbe830",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "1090a4af-7e5d-446b-a537-3afe48cd4909": {
      "ai_languageModel": [
        [
          {
            "node": "0c74e21c-3007-4297-b6ab-8ee17f4c6436",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "0c74e21c-3007-4297-b6ab-8ee17f4c6436": {
      "main": [
        [
          {
            "node": "012d4bb0-2b58-47cd-9cea-b4e0dced9082",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "3dca6d46-c423-4fb5-a6e4-c2aa2852d51c": {
      "main": [
        [
          {
            "node": "216a3261-a398-484c-9bf4-ca5966b829b6",
            "type": "main",
            "index": 0
          },
          {
            "node": "012d4bb0-2b58-47cd-9cea-b4e0dced9082",
            "type": "main",
            "index": 0
          },
          {
            "node": "93b35e5e-6f52-4aeb-8f1b-39cc495beefe",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "09ffc8cd-096f-47fe-937d-f8ab4fb41266": {
      "ai_textSplitter": [
        [
          {
            "node": "e6443541-de71-4d26-ad58-d7c72868a190",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
      ]
    },
    "0a468953-e348-420e-a6b3-c55fb20d3cbf": {
      "main": [
        [
          {
            "node": "3dca6d46-c423-4fb5-a6e4-c2aa2852d51c",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "37ab5c0f-d36e-4131-844d-20a22d3f2861": {
      "main": [
        [
          {
            "node": "3725e480-246f-4f32-b0a7-b946cacbe830",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}
Foire aux questions

Comment utiliser ce workflow ?

Copiez le code de configuration JSON ci-dessus, créez un nouveau workflow dans votre instance n8n et sélectionnez "Importer depuis le JSON", collez la configuration et modifiez les paramètres d'authentification selon vos besoins.

Dans quelles scénarios ce workflow est-il adapté ?

Avancé - Blocs de construction, Intelligence Artificielle

Est-ce payant ?

Ce workflow est entièrement gratuit et peut être utilisé directement. Veuillez noter que les services tiers utilisés dans le workflow (comme l'API OpenAI) peuvent nécessiter un paiement de votre part.

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Nombre de nœuds21
Catégorie2
Types de nœuds13
Description de la difficulté

Adapté aux utilisateurs avancés, avec des workflows complexes contenant 16+ nœuds

Auteur
Ranjan Dailata

Ranjan Dailata

@ranjancse
Liens externes
Voir sur n8n.io →

Partager ce workflow

Catégories

IA Multimodale
1540
Intelligence Artificielle
1108
Création de contenu
695
Résumé IA
516
Marketing
419
Chatbot IA
251
Ingénierie
241
Étude de marché
203
Divers
193
Autres
176
Ventes
162
Opérations IT
156
Extraction de documents
147
RAG IA
146
Blocs de construction
144
Réseaux sociaux
137
Génération de leads
125
Productivité personnelle
117
DevOps
111
Ressources Humaines
101
Support
97
Nurturing de leads
87
CRM
82
Finance
81
Produit
77
Chatbot de support
76
Design
70
Gestion des tickets
67
Opérations de sécurité
57
Traitement des factures
53
Trading crypto
49
Gestion de fichiers
39
Gestion de projet
35
Wiki interne
32

Catégories: 34