Automate LLM testing with GPT-4 judge & Google Sheets tracking
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.
Nodes used (10)
- Merge
n8n-nodes-base.merge - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - Google Sheets
n8n-nodes-base.googleSheets - Limit
n8n-nodes-base.limit - Edit Fields (Set)
n8n-nodes-base.set - HTTP Request
n8n-nodes-base.httpRequest - Webhook
n8n-nodes-base.webhook - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - OpenRouter Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenRouter - Manual Trigger
n8n-nodes-base.manualTrigger
What it does
How it works - The workflow loads a list of test cases from a Google Sheet (previous results stored from an LLM) - For each test case, we execute a call to an LLM judge in parallel (using HTTP Request + Webhook nodes) - The judge uses the Input, Output, and Reference Answer fields from the spreadsheet to mark each LLM response as Pass/Fail - The results are logged into a separate sheet in the same Sheets file. Set up steps: - Add your credentials for Google Sheets and OpenRouter (or replace the OpenRouter node with your favourite chat model). - Make a copy of the example Sheet to populate it with you own test data. - Run the workflow with the Execute Workflow button next to the Manual Trigger node.