> ## Documentation Index
> Fetch the complete documentation index at: https://docs.galileo.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Trace input / output only

> Train a trace-style Luna metric from a single serialized field.

Use this tutorial when the trace-level signal can be represented as one serialized field, typically stored in a single text column. Many safety and security style metrics fit this simplified trace pattern.

## Dataset schema

Typical columns:

* `input`: the serialized trace or message text
* `label`: the ground-truth class for the metric

## Config shape

Set:

* `data_generation.metric.input_format: "single"`
* `data_generation.source_data.dataset.columns.features: ["input"]`
* `training.metric.type: "boolean"`

## Minimal end-to-end config

```yaml theme={null}
run_steps:
  - data_generation
  - training

pipeline_provider: "local"
metric_name: "custom"

data_generation:
  metric:
    name: "Toxicity Detection"
    type: "binary"
    input_format: "single"
    llmaj_source_prompt: "Determine whether the text is toxic or not."
  source_data:
    dataset:
      source_type: "huggingface"
      huggingface:
        name: "toxicity_dataset"
  output:
    dataset:
      repo_name: "toxicity-training-dataset"

training:
  dataset:
    name: "toxicity-training-dataset"
  prompt_template: |
    Determine whether the text is toxic or not.
    Text:
    {input}

    Respond with "true" or "false".
  output:
    model_name: "toxicity-model"
```