Construire un chatbot RAG pour votre site avec Supabase

• •Peut nécessiter les informations d'identification d'authentification de l'API cible
• •Clé API OpenAI
• •Informations de connexion à la base de données PostgreSQL
• •URL et Clé API Supabase

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  },
  "name": "Build RAG Chatbot for Your Website Using Supabase",
  "tags": [],
  "nodes": [
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              "cssSelector": "title, h1"
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            {
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      "parameters": {
        "loader": "jsonLoader",
        "options": {
          "metadata": {
            "metadataValues": [
              {
                "name": "website_url",
                "value": "={{ $('Enter Website Url').item.json['Website Url'] }}"
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    {
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      "name": "Magasin vectoriel Supabase",
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      "name": "Saisir l'URL du site web",
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        "formTitle": "Form",
        "formFields": {
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            {
              "fieldLabel": "Website Url",
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          ]
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        "formDescription": "Enter Website Url"
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    },
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      "name": "Note adhésive 1",
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      "parameters": {
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        "width": 520,
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        "content": "## Generating Embeddings from Website Content"
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        "content": "## User-Initiated Question"
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        "content": "## Vector-Based Answer Retrieval"
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        "content": "## Website Data Extraction\n\n"
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        "options": {
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          "redirect": {
            "redirect": {
              "maxRedirects": 5
            }
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      "name": "Convertir en fichier",
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      "credentials": {
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      "name": "Récupérer question & réponse",
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          "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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