Google Drive to Supabase contextual vector database sync for RAG applications
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
Nodes used (27)
- AI Agent
@n8n/n8n-nodes-langchain.agent - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Google Drive
n8n-nodes-base.googleDrive - Supabase
n8n-nodes-base.supabase - Switch
n8n-nodes-base.switch - Crypto
n8n-nodes-base.crypto - Aggregate
n8n-nodes-base.aggregate - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - Extract from File
n8n-nodes-base.extractFromFile - Edit Fields (Set)
n8n-nodes-base.set - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches - If
n8n-nodes-base.if - Google Drive Trigger
n8n-nodes-base.googleDriveTrigger - Execute Workflow Trigger
n8n-nodes-base.executeWorkflowTrigger - Call n8n Workflow Tool
@n8n/n8n-nodes-langchain.toolWorkflow - HTTP Request
n8n-nodes-base.httpRequest - Execute Sub-workflow
n8n-nodes-base.executeWorkflow - Supabase Vector Store
@n8n/n8n-nodes-langchain.vectorStoreSupabase - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - Code
n8n-nodes-base.code - Split Out
n8n-nodes-base.splitOut - Wait
n8n-nodes-base.wait
What it does
Workflow Summary This automation keeps your Supabase vector database synchronized with documents stored in Google Drive, while also making the data contextual and vector based for better retrieval. When a file is added or modified, the workflow extracts its text, splits it into smaller chunks, and enriches each chunk with contextual metadata (such as summaries and document details). It then generates embeddings using OpenAI and stores both the vector data and metadata in Supabase. If a file changes, the old records are replaced with updated, contextualized content. The result is a continuously updated and context-aware vector database, enabling highly accurate hybrid search and retrieval. To setup 1. Connect Google Drive • Create a Google Drive folder to watch. • Connect your Google Drive account in n8n and authorize access. • Point the Google Drive Trigger node to this folder (new/modified files trigger the flow). 2. Configure Supabase • Please refer to the Setting Up Supabase Sticky Note. 3. Connect OpenAI (or your embedding model) • Add your OpenAI API key in n8n credentials.