Evaluation metric example: Correctness (judged by AI)

AI evaluation in n8n This is a template for n8n's evaluation feature. Evaluation is a technique for getting confidence that your AI workflow performs reliably, by running a test dataset containing different inputs through the workflow. By calculating a metric (score) for each input, you can see where the workflow is performing well and where it isn't. How it works This template shows how to calculate a workflow evaluation metric: whether an output matches an expected output (i.e. has the same meaning). The workflow takes questions about the causes of historical events and compares them with the reference answers in the dataset. We use an evaluation trigger to read in our dataset It is wired

Help me set up the n8n workflow "Evaluation metric example: Correctness (judged by AI)" (https://n8n.io/workflows/4271). It uses: AI Agent, OpenAI Chat Model, OpenAI, Evaluation. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.