Build & query RAG system with Google Drive, OpenAI GPT-4o-mini, and Pinecone
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.
What this workflow does
This AI workflow has 11 nodes and runs on Google Drive events (file created) (plus 1 other trigger). Along the way it connects Google Drive, Pinecone Vector Store, Embeddings OpenAI and OpenAI Chat Model.
How it runs
Trigger: On Google Drive events (file created) (plus 1 other trigger).
- Google Drive: download
- AI Agent: runs an AI agent, with model: OpenAI Chat Model; 1 tool (Pinecone Vector Store)
- Pinecone Vector Store: stores documents in the Pinecone vector store, with embeddings: Embeddings OpenAI; document loader: Default Data Loader
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (9)
- Google Drive Trigger
n8n-nodes-base.googleDriveTrigger - Google Drive
n8n-nodes-base.googleDrive - Pinecone Vector Store
@n8n/n8n-nodes-langchain.vectorStorePinecone - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - AI Agent
@n8n/n8n-nodes-langchain.agent - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi
From the author
🔍 What This Workflow Does This RAG Pipeline in n8n automates document ingestion from Google Drive, vectorizes it using OpenAI embeddings, stores it in Pinecone, and enables chat-based retrieval using LangChain agents. Main Functions: 📂 Auto-detects new…