RAG-Chatbot für Ihre Website mit Supabase erstellen

• •Möglicherweise sind Ziel-API-Anmeldedaten erforderlich
• •OpenAI API Key
• •PostgreSQL-Datenbankverbindungsdaten
• •Supabase URL und API Key

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  "meta": {
    "instanceId": "fcb622cbd5234c565b9b78babeaf0ea2455df9d2aad0d1adff7c1ef99583e685",
    "templateCredsSetupCompleted": true
  },
  "name": "Build RAG Chatbot for Your Website Using Supabase",
  "tags": [],
  "nodes": [
    {
      "id": "c2c34da8-27e8-4881-a3fd-3b5f6987e0bf",
      "name": "Wenn Chat-Nachricht empfangen",
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "position": [
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      ],
      "webhookId": "dec328cc-f47e-4727-b1c5-7370be86a958",
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        "mode": "webhook",
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    {
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      "name": "HTML-Extraktion",
      "type": "n8n-nodes-base.htmlExtract",
      "position": [
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      ],
      "parameters": {
        "options": {},
        "extractionValues": {
          "values": [
            {
              "key": "title",
              "cssSelector": "title, h1"
            },
            {
              "key": "content",
              "cssSelector": "p, article, .content, .post-content, main"
            },
            {
              "key": "meta_description",
              "attribute": "content",
              "cssSelector": "meta[name='description']",
              "returnValue": "attribute"
            },
            {
              "key": "links",
              "attribute": "href",
              "cssSelector": "a[href]",
              "returnValue": "attribute"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
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      "name": "Standard-Datenlader",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
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      ],
      "parameters": {
        "loader": "jsonLoader",
        "options": {
          "metadata": {
            "metadataValues": [
              {
                "name": "website_url",
                "value": "={{ $('Enter Website Url').item.json['Website Url'] }}"
              }
            ]
          }
        },
        "dataType": "binary"
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      "typeVersion": 1
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      "parameters": {
        "options": {},
        "chunkSize": 3000,
        "chunkOverlap": 500
      },
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    },
    {
      "id": "b7541584-131f-4868-b8dd-053ab509ab1b",
      "name": "Supabase Vektorspeicher",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreSupabase",
      "position": [
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      ],
      "parameters": {
        "mode": "insert",
        "options": {},
        "tableName": {
          "__rl": true,
          "mode": "list",
          "value": "documents",
          "cachedResultName": "documents"
        },
        "embeddingBatchSize": 100
      },
      "credentials": {
        "supabaseApi": {
          "id": "E3H0gensGX1OYVwU",
          "name": "Supabase account"
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    },
    {
      "id": "7b923d0f-c803-4b3c-afd8-ee680793c955",
      "name": "Website-URL eingeben",
      "type": "n8n-nodes-base.formTrigger",
      "position": [
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      ],
      "webhookId": "b02a5096-11b0-4677-acfa-fcac5722498c",
      "parameters": {
        "options": {},
        "formTitle": "Form",
        "formFields": {
          "values": [
            {
              "fieldLabel": "Website Url",
              "placeholder": "Enter Website Url"
            }
          ]
        },
        "formDescription": "Enter Website Url"
      },
      "typeVersion": 2.2
    },
    {
      "id": "9e961fc5-b937-4f0e-b9f5-8ada4f3598f5",
      "name": "Kurznotiz 1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -180,
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      ],
      "parameters": {
        "color": 3,
        "width": 520,
        "height": 100,
        "content": "## Generating Embeddings from Website Content"
      },
      "typeVersion": 1
    },
    {
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      "name": "Kurznotiz 2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      ],
      "parameters": {
        "width": 300,
        "height": 80,
        "content": "## User-Initiated Question"
      },
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    },
    {
      "id": "1c11199e-d217-4f2d-8afe-913f902ef47c",
      "name": "Kurznotiz 3",
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      "parameters": {
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        "width": 540,
        "height": 80,
        "content": "## Vector-Based Answer Retrieval"
      },
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    },
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      "name": "Kurznotiz",
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      "parameters": {
        "width": 640,
        "height": 100,
        "content": "## Website Data Extraction\n\n"
      },
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    },
    {
      "id": "eeffcae9-2e9c-48f2-ad13-2b75b7218fe2",
      "name": "Website-Daten-Scraping",
      "type": "n8n-nodes-base.httpRequest",
      "maxTries": 3,
      "position": [
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      ],
      "parameters": {
        "url": "={{ $json['Website Url'] }}",
        "options": {
          "timeout": 30000,
          "redirect": {
            "redirect": {
              "maxRedirects": 5
            }
          }
        }
      },
      "retryOnFail": true,
      "typeVersion": 4.1
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    {
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      "name": "In Datei konvertieren",
      "type": "n8n-nodes-base.convertToFile",
      "position": [
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      ],
      "parameters": {
        "options": {},
        "operation": "toJson"
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      "typeVersion": 1.1
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      "name": "Einbettungen Cohere",
      "type": "@n8n/n8n-nodes-langchain.embeddingsCohere",
      "position": [
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      ],
      "parameters": {},
      "credentials": {
        "cohereApi": {
          "id": "5VhbvbDzLliD5nO9",
          "name": "CohereApi account"
        }
      },
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    {
      "id": "d8d3a79a-1ac2-42dd-b383-e39bbcbded75",
      "name": "Frage & Antwort Abruf",
      "type": "@n8n/n8n-nodes-langchain.agent",
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      ],
      "parameters": {
        "options": {
          "systemMessage": "=# Overview  \nYou are an AI agent that responds strictly using information from stored document embeddings in a supabase vector store.  \n\n## Context  \n- The agent is designed to provide accurate, document-based answers.  \n- It must avoid using external knowledge or assumptions.  \n\n## Instructions  \n1. Analyze the user's question.  \n2. Retrieve relevant content from the document embeddings using supabase.  \n3. Construct a response only from the matching document chunks.\n## Tools  \n- Vector store containing embedded documents\n- Embeddings Cohere  \n\n## SOP (Standard Operating Procedure)  \n1. Receive user query.  \n2. Search the vector store for relevant document chunks.  \n3. Extract and synthesize an answer using only that content.  \n4. If no matches, issue fallback message.  \n\n## Final Notes  \n- Do not rely on prior training or external facts.  \n- The response must remain strictly grounded in the documents.  "
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    },
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      "name": "Daten aus Supabase Vektorspeicher",
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      ],
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        "mode": "retrieve-as-tool",
        "topK": null,
        "options": {},
        "toolName": "documents_knowledge_base",
        "tableName": {
          "__rl": true,
          "mode": "list",
          "value": "documents",
          "cachedResultName": "documents"
        },
        "toolDescription": "work with documents data in Supabase vector store",
        "includeDocumentMetadata": false
      },
      "credentials": {
        "supabaseApi": {
          "id": "E3H0gensGX1OYVwU",
          "name": "Supabase account"
        }
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      "credentials": {
        "cohereApi": {
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          "name": "CohereApi account"
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      },
      "typeVersion": 1
    },
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      "name": "Chat-Speicher",
      "type": "@n8n/n8n-nodes-langchain.memoryPostgresChat",
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        "tableName": "chat_memory",
        "contextWindowLength": 3
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        "postgres": {
          "id": "lf7D6rk7s95k7I12",
          "name": "Postgres account 2"
        }
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      "typeVersion": 1.3
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      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "FWzCPYhm2kVkOjE5",
          "name": "OpenAi account 7"
        }
      },
      "typeVersion": 1.2
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
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            "node": "Supabase Vector Store",
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    "Embeddings Cohere": {
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    },
    "Embeddings mit Cohere": {
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