We require an experienced n8n developer to build, test, and deliver a robust, memory-efficient workflow for processing and analyzing a large batch of academic PDF files using GPT-4 and Google services.
Project Goal
Automate the end-to-end extraction and metadata creation for 100+ academic PDF files (up to 100 pages each) from Google Drive and write the structured results to Google Sheets.
Essential Deliverables
Ready-to-Import n8n Workflow JSON File: Tested and verified on a self-hosted instance.
Detailed Configuration Template: A simple document outlining the exact column names required in Google Sheets and the parameters for the Google Drive node (Folder ID).
Adding Google Drive, Google Sheets, and OpenAI API credentials (must use the n8n credential system).
Initial setup and execution.
Test Results: Proof of a successful end-to-end run on at least 3 sample PDF files.
Critical Constraints
Memory Optimization: The workflow must be designed to be highly memory-efficient, handling large files sequentially to avoid crashing on a shared or resource-constrained Hostinger environment.
Host Environment: Workflow must be stable for long execution times (2-3 hours to process 100+ files).
No Hardcoding: All API keys and credentials must be set up using n8n's Credential system, not hardcoded in the nodes.
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