⚒️ Evaluation metric example: categorization
⚡ 1,544 views · ⚒️ Engineering
Description
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 the regular trigger so that the workflow can be started from either one. More info
- Once the category is generated by the agent, we check whether it matches the expected one in the dataset
- Finally we pass this information back to n8n as a metric
🔗 Nodes Used
Webhook, AI Agent, OpenAI Chat Model, Structured Output Parser, Evaluation Trigger, Evaluation
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File