Créer une base de données vectorielle RAG à partir de documents Google Drive avec Gemini et Supabase

• •Informations de connexion à la base de données PostgreSQL
• •Informations d'identification Google Drive API
• •URL et Clé API Supabase

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        "content": "# 📁 Drive to Supabase Vector Store for Study RAG\n\nProcesses Google Drive folder files into Supabase vector embeddings for RAG applications.\n\n**Flow:** Drive URL → Parse ID → Init DB → Fetch Files → Loop → Download → Embed → Store\n\n**Requirements:**\n- Google Drive OAuth2\n- Supabase + Postgres credentials\n- Google Gemini API key\n\n**Input:** `{\"Drive_Folder_link\": \"your_drive_url\"}`\n**Output:** Vector embeddings in Supabase documents table\n"
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