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

Free

Creator

Muhammad Asadullah

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