Templates / Evaluation metric example: Correctness (judged by AI)

Evaluation metric example: Correctness (judged by AI)

Needs changes

by David Roberts ✓ · 2,120 views · created 2025-05-21 · Engineering, AI Summarization

Needs changes. This template uses 1 thing(s) that n8n 3.0 removes: AI Agent v1 (old agent modes). 1 breaking item(s) found. Static check, last run 2026-10-19.

What this workflow does

This AI workflow has 9 nodes and runs when a chat message arrives (plus 1 other trigger). Along the way it connects OpenAI Chat Model, Evaluation and OpenAI.

How it runs

Trigger: When a chat message arrives (plus 1 other trigger).

  1. AI Agent: runs an AI agent, with model: OpenAI Chat Model
  2. Match chat format (Edit Fields (Set)): sets 1 field: chatInput
  3. Evaluating? (Evaluation): check if evaluating
  4. Calculate correctness metric (OpenAI): uses OpenAI
  5. Set metrics (Evaluation): set metrics

Services it uses

OpenAI Chat ModelEvaluationOpenAI

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 (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 3.0Replace with
AI Agent v1 (old agent modes)
AI Agent (v1.9)
Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.

Nodes used (8)

From the author

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…

Excerpt from David Roberts's description on n8n.io.

View the original on n8n.io → Check your own copy

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