Evaluation metric example: Categorization

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 a category matches the expected one. The workflow takes support tickets and generates a category and priority, which is then compared with the correct answers in the dataset. We use an evaluation trigger to read in our dataset It is wired up in parallel with

Help me set up the n8n workflow "Evaluation metric example: Categorization" (https://n8n.io/workflows/4269). It uses: AI Agent, OpenAI Chat Model, Structured Output Parser, Evaluation. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.