Description

I need an n8n workflow that automatically processes 100+ PDF files from Google Drive, analyzes them with OpenAI GPT-4, and writes structured metadata to Google Sheets.

Key Requirements
-Process 100+ academic PDF files (up to 100 pages each)
-Sequential processing (one file at a time using Split in Batches)
-Extract text from PDFs
-Analyze with GPT-4 and extract metadata (author, year, title, topic,   summary, etc.)
-Write 13 specific fields to Google Sheets
-Must work on self-hosted n8n (Hostinger)
-Easy credential setup (I add my own API keys after delivery)

Technical Stack
-n8n workflow (7-8 nodes)
-Google Drive API (list and download PDFs)
-OpenAI API (GPT-4 analysis)
-Google Sheets API (write results)
-PDF text extraction
-Loop structure with error handling

What You'll Deliver
-Ready-to-import n8n workflow JSON file
-Setup documentation (README.md)
-Configuration template
-Test results

Important Notes
-Workflow runs locally on Hostinger
-Must handle large files and long execution times (2-3 hours)
-Memory optimization essential
-No hardcoded credentials - must use n8n credential system

FULL SPECIFICATION
-Confirmation you've read the full specification PDF
-Your experience with n8n workflows
-Your approach to handling 100+ large PDFs efficiently
-If you have a better idea for the workflow architecture, please describe it
-Estimated delivery time
-Any questions or clarifications needed

Alternative Solutions Welcome
If you have experience with similar projects and can suggest a better approach than the one specified, I'm open to alternatives. Please explain:

-Why your approach would be better
-What tools/architecture you would use
-Pros and cons compared to the n8n workflow
-Budget implications if different