# Metrics

A Metric is a mapping from [Columns](/v0.26.x/configuration/data-pipeline.md#columns) into meaningful numeric values representing cost, quality, performance, or other behavioral characteristics. Metrics are computed for every ingested log or trace as part of the [DBNL Data Pipeline](/v0.26.x/configuration/data-pipeline.md) and show up in the [Logs](/v0.26.x/workflow/logs.md) view, [Explorer](/v0.26.x/workflow/explorer.md) pages, and [Metrics Dashboard](/v0.26.x/workflow/dashboards.md#metrics-dashboard).

DBNL comes with many built in metrics and templates that can be customized. Fundamentally, Metrics are one of two types:

* [**LLM-as-judge Metrics**](#llm-as-judge-metrics): Evals and judges that require an LLM to compute a score or classification based on a prompt.
* [**Standard Metrics**](#standard-metrics): Functions that can be computed using non-LLM methods like traditional Natural Language Processing (NLP) metrics, statistical operations, and other common mapping [functions](/v0.26.x/reference/query-language/functions.md).

### Default Metrics

Every product contains the following metrics by default, computed using the required `input` and `output` fields of the [DBNL Semantic Convention](/v0.26.x/configuration/dbnl-semantic-convention.md) and the default [Model Connection](/v0.26.x/configuration/model-connections.md) for the [Project](/v0.26.x/workflow/projects.md):

* `answer_relevancy`: Determines if the `input` is relevant to the `output`. See [template](/v0.26.x/workflow/metrics/llm-as-judge-metric-templates.md#llm_answer_relevancy).
* `user_frustration`: Assesses the level of frustration of the `input` based on tone, word choice, and other properties. See [template](/v0.26.x/workflow/metrics/llm-as-judge-metric-templates.md#llm_text_frustration).
* `topic`: Classifies the conversation into a topic based on the `input` and `output`. This Metric is created after topics are automatically generated from the first 7 days of ingested data. Topics can be manually adjusted by editing the [template](/v0.26.x/workflow/metrics/llm-as-judge-metric-templates.md#topic).
* `conversation_summary` (immutable): A summary of the `input` and `output`, used as part of `topic` generation.
* `summary_embedding` (immutable): An embedding of the `conversation_summary`, used as part of `topic` generation.

### Creating a Metric

Metrics can be created by clicking on the "+ Create New Metric" button on the Metrics page.

<figure><img src="/files/zNneK6P87NM3nAdiXQRi" alt=""><figcaption></figcaption></figure>

### LLM-as-Judge Metrics

LLM-as-Judge Metrics can be customized from the built in [LLM-as-Judge Metric Templates](/v0.26.x/workflow/metrics/llm-as-judge-metric-templates.md). Each of these Metrics is one of two types:

* Classifier Metric: Outputs a categorical value equal to one of a predefined set of classes. Example: [`llm_answer_groundedness`](/v0.26.x/workflow/metrics/llm-as-judge-metric-templates.md#llm_answer_groundedness).
* Scorer Metric: Outputs an integer in the range `[1, 2, 3, 4, 5]`. Example: [`llm_text_frustration`](/v0.26.x/workflow/metrics/llm-as-judge-metric-templates.md#llm_text_frustration).

### Standard Metrics

Standard Metrics are functions that can be computed using non-LLM methods. They can be built using the [Functions](/v0.26.x/reference/query-language/functions.md) available in the [DBNL Query Language](/v0.26.x/reference/query-language.md).


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.dbnl.com/v0.26.x/workflow/metrics.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.