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

# Create Metric

> Create a metric for evaluating your products.

## Returns

Returns a [Metric](/concepts/metric) object for the given parameters, or `None` if an error occurs.

## Examples

<Tabs>
  <Tab title="AI Evaluation">
    ```python theme={"system"}
    metric = galtea.metrics.create(
        name="accuracy_v1_" + run_identifier,
        evaluator_model_name="GPT-4.1",
        source="partial_prompt",
        judge_prompt="Determine whether the actual output is equivalent to the expected output",
        evaluation_params=["input", "actual_output", "expected_output"],
        tags=["custom", "accuracy"],
        description="A custom accuracy metric.",
    )
    ```
  </Tab>

  <Tab title="Human Evaluation">
    ```python theme={"system"}
    metric = galtea.metrics.create(
        name="human_eval_v1_" + run_identifier,
        source="human_evaluation",
        judge_prompt="Review the actual output and score it based on helpfulness, accuracy, and tone. Score 1 if the response is helpful and accurate. Score 0 if it is unhelpful or incorrect.",
        evaluation_params=["input", "actual_output", "expected_output"],
        user_group_ids=[user_group_id],
        tags=["human", "quality"],
        description="A human evaluation metric scored by QA annotators.",
    )
    ```
  </Tab>

  <Tab title="Self-Hosted">
    ```python theme={"system"}
    metric = galtea.metrics.create(
        name="accuracy_v1_self_" + run_identifier,
        source="self_hosted",
        tags=["custom", "accuracy"],
        description="A custom accuracy metric calculated by our custom score function.",
    )
    ```
  </Tab>
</Tabs>

## Parameters

<ResponseField name="name" type="string" required>
  The name of the metric.
</ResponseField>

<ResponseField name="test_type" type="string" optional>
  <Warning>
    **Deprecated.** This parameter is ignored and will be removed in a future release.
  </Warning>
</ResponseField>

<ResponseField name="evaluator_model_name" type="string" optional>
  The name of the model used to evaluate the metric. Required for metrics using `judge_prompt`.

  **Available models:**

  * `"Claude-Sonnet-4.5"`
  * `"Claude-Sonnet-3.7"`
  * `"GPT-4.1-mini"`
  * `"Gemini-2.5-Flash-Lite"`
  * `"Gemini-2.5-Flash"`
  * `"Gemini-2.0-flash"`
  * `"GPT-4o"`
  * `"GPT-4.1"`

  <Note>
    It should not be provided if the metric is "self hosted" (has no `judge_prompt`) since it does not require a model for evaluation.
  </Note>
</ResponseField>

<ResponseField name="judge_prompt" type="string" optional>
  A custom prompt that defines the evaluation logic for the metric. For AI Evaluation metrics, write the evaluation criteria and scoring rubric — Galtea will prepend the selected `evaluation_params` automatically. For Human Evaluation metrics, this serves as the annotation rubric. If omitted, the metric is considered a deterministic "Custom Score" metric.
</ResponseField>

<ResponseField name="source" type="string" optional>
  The evaluation method for the metric. Possible values:

  * `"partial_prompt"` — [AI Evaluation](/concepts/metric#creating-custom-metrics-via-ai-evaluation): You provide the core evaluation criteria and rubric. Galtea dynamically constructs the final prompt by prepending selected evaluation parameters to your criteria.
  * `"human_evaluation"` — **Human Evaluation**: Human annotators manually review and score evaluations using the annotation criteria you define. Evaluations enter a `PENDING_HUMAN` status and are completed when an annotator submits a score.
  * `"self_hosted"` — [Self-Hosted](/concepts/metric#self-hosted): For deterministic metrics scored locally using the SDK's `CustomScoreEvaluationMetric`. Your custom logic runs on your infrastructure, and the resulting score is uploaded to the platform.

  Other string values are sent to the API unchanged, so values added in newer API versions can be used; the API rejects invalid ones.
</ResponseField>

<ResponseField name="evaluation_params" type="list[string]" optional>
  Evaluation parameters to include in the judge prompt. These parameters are prepended to the judge prompt to construct the final evaluation prompt.
  To check the available evaluation parameters, see the [Evaluation Parameters](/concepts/metric#param-evaluation-parameters) section.

  <Note>
    Only applicable for AI Evaluation and Human Evaluation metrics.
  </Note>
</ResponseField>

<ResponseField name="user_group_ids" type="list[string]" optional>
  A list of [user group](/concepts/user-group) IDs to associate with this metric. Only applicable when `source` is `human_evaluation`.

  * If user group IDs are specified, only users in those groups can annotate evaluations for this metric.
  * If no user group IDs are specified, any user in the organization can annotate.
</ResponseField>

<ResponseField name="tags" type="list[string]" optional>
  Tags to categorize the metric.
</ResponseField>

<ResponseField name="description" type="string" optional>
  A brief description of what the metric evaluates.
</ResponseField>

<ResponseField name="documentation_url" type="string" optional>
  A URL pointing to more detailed documentation about the metric.
</ResponseField>