Evaluate a support ticket classifier with OpenAI GPT-4o-mini and n8n evaluations
Needs changesWhat this workflow does
This AI workflow has 10 nodes and runs on Evaluation events (plus 1 other trigger). Along the way it connects Evaluation and OpenAI Chat Model.
How it runs
Trigger: On Evaluation events (plus 1 other trigger).
- Format ticket input (Code): runs custom JavaScript code
- AI Agent: runs an AI agent, with model: OpenAI Chat Model
- Evaluating? (Evaluation): check if evaluating
- Compare Classification (Code): runs custom JavaScript code
- Respond to Webhook: sends the response back to the webhook caller
- Evaluation: uses Evaluation
- Set Metrics (Evaluation): set metrics
Services it uses
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in AI Agent - Classify Ticket (v1.9): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) AI Agent - Classify Ticket (v1.9) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (7)
- Webhook
n8n-nodes-base.webhook - Evaluation Trigger
n8n-nodes-base.evaluationTrigger - Code
n8n-nodes-base.code - AI Agent
@n8n/n8n-nodes-langchain.agent - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Evaluation
n8n-nodes-base.evaluation - Respond to Webhook
n8n-nodes-base.respondToWebhook
From the author
Measure how well your AI classifier actually performs. This template shows how to evaluate a support ticket classifier using n8n's built-in evaluation system, comparing AI predictions against expected labels with exact match scoring. What you'll do Open the…