RAG-Chatbot mit Google Drive

• •Supabase URL und API Key
• •Google Drive API-Anmeldedaten
• •OpenAI API Key
• •PostgreSQL-Datenbankverbindungsdaten

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        "content": "## 🚀 COMPLETE SETUP GUIDE - READ FIRST!\n\n### Step 1: Required Services\n1. **Google Drive** - For document storage\n2. **OpenAI Account** - For embeddings and chat (API key required)\n3. **Supabase Account** - For vector database (free tier OK)\n4. **PostgreSQL Database** - For chat memory (can use Supabase or separate)\n\n### Step 2: Supabase Vector Database Setup\nRun these SQL commands in Supabase SQL editor:\nhttps://supabase.com/docs/guides/ai/langchain?database-method=sql\n\n### Step 3: Credentials Setup\n1. **Google Drive OAuth2** - Enable Drive API, create OAuth2 credentials\n2. **OpenAI API** - Get API key from OpenAI dashboard\n3. **Supabase API** - Get URL and service role key from project settings\n4. **PostgreSQL** - Use Supabase connection string or separate DB\n\n### Step 4: Configure Workflow\n1. Update Google Drive folder IDs in both trigger nodes\n2. Ensure all credential connections are set\n3. Test with a single PDF file first\n\n### Step 5: Testing\n1. Upload a document to your Google Drive folder\n2. Check Supabase documents table for new entries\n3. Activate workflow and test chat interface\n4. Ask questions about your document content\n\n### 📋 Quick Checklist:\n☐ Supabase database and functions created\n☐ Google Drive folder IDs configured\n☐ All 4 credentials added to n8n\n☐ Test PDF uploaded to Drive folder\n☐ Workflow activated successfully\n☐ Chat interface responding correctly"
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        "content": "## Data Ingestion: Adding Google Drive PDF files to Vector DB"
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        "content": "## Conversational RAG AI agent"
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