Process documents with recursive chunking using Google Drive, OpenAI & Gemini RAG
1. Document Ingestion & Processing Google Drive Trigger monitors for new files → Loop Over Items processes each file → File Info extracts metadata → Google Drive downloads the actual content → Switch routes to appropriate extractors (PDF or TEXT) based on file type 2. Content Transformation & Chunking Document Data node processes extracted text → Recursive Splitter breaks content into contextual chunks → Chunk Splitting applies intelligent segmentation while preserving document contex
At a glance
Process documents with recursive chunking using Google Drive, OpenAI & Gemini RAG is a ready-made n8n workflow you import as a workflow JSON file — no build required. It connects agent, chainLlm, code, documentDefaultDataLoader. It's free to download. Follow the 5-step import below to go live in minutes.
- Platform
- n8n
- Connects
- agent, chainLlm, code, documentDefaultDataLoader, embeddingsOpenAi, extractFromFile
- Modules
- 23
- Price
- Free
- Version
- v1.0

About this workflow
1. Document Ingestion & Processing Google Drive Trigger monitors for new files → Loop Over Items processes each file → File Info extracts metadata → Google Drive downloads the actual content → Switch routes to appropriate extractors (PDF or TEXT) based on file type 2. Content Transformation & Chunking Document Data node processes extracted text → Recursive Splitter breaks content into contextual chunks → Chunk Splitting applies intelligent segmentation while preserving document context and relationships between chunks 3. Embedding & Storage Basic LLM Chain processes chunks → OpenAI Chat Model generates contextual understanding → Summarize creates document summaries → Supabase Vector Store saves embeddings with metadata → Embeddings OpenAI creates vector representations → Default Data Loader handles storage operations 4. Query Processing & Retrieval When Clicking Execute triggers user queries → OpenAI processes and understands the question → AI Agent orchestrates hybrid search (combining vector similarity + keyword matching) → Google Gemini Chat Model generates final responses using retrieved context → HTTP Request handles additional external data sources
How to import this n8n workflow
- 1
Download the workflow JSON file after purchase.
- 2
Open n8n → click the menu → Import from File.
- 3
Select the downloaded JSON and import.
- 4
Set up credentials for each node that requires them.
- 5
Click Execute Workflow to test, then activate.
Setup guide
Setup guide included
Purchase to unlock the full step-by-step guide
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- JSON blueprint — instant download
- Setup guide PDF included
- 5 downloads · valid 30 days
- Works with n8n
Need help setting this up?
Book a 3-hour live setup session with an Agility consultant.
- Configure live on Google Meet / Zoom
- Free follow-up if workflow has defects
- Platform expert assigned to you