Index Documents from Google Drive to Pinecone with OpenAI Embeddings for RAG
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 8 nodes and runs on Google Drive events (file created). Along the way it connects Google Drive, Pinecone Vector Store and Embeddings OpenAI.
How it runs
Trigger: On Google Drive events (file created).
- Google Drive: work with file folder
- Get Docs (Google Drive): download
- Loop Over Items (Loop Over Items (Split in Batches)): loops over the items in batches
- 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 (7)
- Google Drive
n8n-nodes-base.googleDrive - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches - 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 - Google Drive Trigger
n8n-nodes-base.googleDriveTrigger
From the author
🧠 Google Drive Upload Trigger → Pinecone Vector Upsert for Document Indexing Category: AI & LLM / Document Indexing Level: Intermediate Tags: Google Drive, Pinecone, OpenAI, Embeddings, Vector Store, LangChain, RAG 📄 What This Workflow Does This workflow…