Simple Eval for Legal Benchmarking

This workflow demonstrates a simple way to run evals on a set of test cases stored in a Google Sheet. The example we are using comes from an info extraction task dataset, where we tested 6 different LLMs on 18 different test cases. You can see our sample data in this spreadsheet here to get started. Once you have this working for our dataset, you can plug in your own test cases matching different LLMs to see how it works with your own data. How it works: It loads test cases from Google Sheets. For each row in our Google Sheet, it grabs the source document, converting it to text. Our "LLM judge" passes the input/output of each LLM to GPT-4.1 to evaluate each test case (Pass/Fail + Reason). It

Help me set up the n8n workflow "Simple Eval for Legal Benchmarking" (https://n8n.io/workflows/4712). It uses: Google Sheets, Google Drive, Basic LLM Chain, Structured Output Parser, OpenRouter Chat Model. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.