Google Drive to Pinecone Vector Storage Workflow

# Document Chat Bot with Automated RAG System This workflow creates a conversational assistant that can answer questions based on your Google Drive documents. It automatically processes various file types and uses Retrieval-Augmented Generation (RAG) to provide accurate answers based on your document content. ## How It Works 1. **Monitors Google Drive for New Documents**: Automatically detects when files are created or updated in designated folders. 2. **Processes Multiple File Types**: Handles PDFs, Excel spreadsheets, and Google Docs. 3. **Builds a Knowledge Base**: Converts documents into searchable vector embeddings stored in Supabase. 4. **Provides Chat Interface**: Users can ask questions about their documents through a web interface. 5. **Retrieves Relevant Information**: Uses advanced RAG techniques to find and present the most relevant information. ## Setup Steps (Estimated time: 25-30 minutes) 1. **API Credentials**: Connect your OpenAI API key for text processing and embeddings. 2. **Google Drive Integration**: Set up Google Drive triggers to monitor specific folders. 3. **Supabase Configuration**: Configure Supabase vector database for document storage. 4. **Chat Interface Setup**: Deploy the web-based chat interface using the provided webhook. The workflow automatically chunks documents into manageable segments, generates embeddings, and stores them in a vector database for efficient retrieval. When users ask questions, the system finds the most relevant document sections and uses them to generate accurate, contextual responses.

Platform

n8n

Category

AI

Price

$24.99

Creator

Muhammad Asadullah

• set
• code
• wait
• switch
• webhook
• splitOut
• supabase
• summarize
• stickyNote
• googleDrive