Evaluation Metric Example: String Similarity

## AI Evaluation in n8n This is a template for n8n's [evaluation feature](https://docs.n8n.io/advanced-ai/evaluations/overview). 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](https://docs.n8n.io/advanced-ai/evaluations/tips-and-common-issues/#combining-multiple-triggers) - 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.