Evaluation metric example: String similarity

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

AI evaluation in n8n This is a template for n8n's evaluation feature. Evaluation is a technique for getting confidence that your AI workflow ...

Best for

Engineering automation workflows
AI Summarization automation workflows
intermediate n8n builders looking for reusable templates

Tools used

n8n-nodes-base.stickynote, n8n-nodes-base.set, n8n-nodes-base.webhook, n8n-nodes-base.evaluationtrigger, n8n-nodes-base.respondtowebhook, n8n-nodes-base.evaluation, @n8n/n8n-nodes-langchain.openai, n8n-nodes-base.code

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by David Roberts.

Original n8n.io source

1.1 Workflow description

Title: Evaluation metric example: String similarity
Workflow name: Evaluation metric example: String similarity

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: text similarity, measured character-by-character.

The workflow takes images of hand-written codes, extracts the code and compares it with the expected answer from the dataset.

The images look like this:

The workflow works as follows:

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
We download the image and use AI to extract the code
If we’re evaluating (i.e. the execution started from the evaluation trigger), we calculate the string distance metric
We pass this information back to n8n as a metric

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 2 - Sticky Note3

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 3 - Sticky Note4

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 4 - Match webhook format

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 5 - Webhook

Type / Role: n8n-nodes-base.webhook - webhook
Config choices: Version 2

Block 6 - When fetching a dataset row

Type / Role: n8n-nodes-base.evaluationTrigger - evaluationTrigger
Config choices: Version 4.6

Block 7 - Respond to Webhook

Type / Role: n8n-nodes-base.respondToWebhook - respondToWebhook
Config choices: Version 1.3

Block 8 - Evaluating?

Type / Role: n8n-nodes-base.evaluation - evaluation
Config choices: Version 4.6

Block 9 - Set metrics

Type / Role: n8n-nodes-base.evaluation - evaluation
Config choices: Version 4.6

Block 10 - Extract code from image

Type / Role: @n8n/n8n-nodes-langchain.openAi - openAi
Config choices: Version 1.8

Block 11 - Calc string distance

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 12 - Download image

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

3. Summary Table

Workflow	Evaluation metric example: String similarity
Complexity	intermediate
Nodes	12
Categories	Engineering, AI Summarization
Author	David Roberts
Published	21 May 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/4274/4274.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Engineering workflows AI Summarization workflows

Frequently asked questions

What does Evaluation metric example: String similarity do?

AI evaluation in n8n This is a template for n8n's evaluation feature. Evaluation is a technique for getting confidence that your AI workflow ...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Engineering, AI Summarization use case.

David Roberts

18 workflows

Nodes

n8n-nodes-base.stickynote n8n-nodes-base.set n8n-nodes-base.webhook n8n-nodes-base.evaluationtrigger n8n-nodes-base.respondtowebhook n8n-nodes-base.evaluation @n8n/n8n-nodes-langchain.openai n8n-nodes-base.code

Complexity

intermediate

Published 21 May 2025

Likes 0

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Install path: /data/workflows/4274/4274.json

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Evaluation metric example: String similarity

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

AI evaluation in n8n

How it works

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Sticky Note1

Block 2 - Sticky Note3

Block 3 - Sticky Note4

Block 4 - Match webhook format

Block 5 - Webhook

Block 6 - When fetching a dataset row

Block 7 - Respond to Webhook

Block 8 - Evaluating?

Block 9 - Set metrics

Block 10 - Extract code from image

Block 11 - Calc string distance

Block 12 - Download image

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions