Interface: Evaluator<Input, Output, Expected, Metadata>
Type parameters
| Name | Type |
|---|---|
Input | Input |
Output | Output |
Expected | Expected |
Metadata | extends BaseMetadata = DefaultMetadataType |
Properties
baseExperimentId
• Optional baseExperimentId: string
An optional experiment id to use as a base. If specified, the new experiment will be summarized
and compared to this experiment. This takes precedence over baseExperimentName if specified.
baseExperimentName
• Optional baseExperimentName: string
An optional experiment name to use as a base. If specified, the new experiment will be summarized and compared to this experiment.
data
• data: EvalData<Input, Expected, Metadata>
A function that returns a list of inputs, expected outputs, and metadata.
experimentName
• Optional experimentName: string
An optional name for the experiment.
isPublic
• Optional isPublic: boolean
Whether the experiment should be public. Defaults to false.
maxConcurrency
• Optional maxConcurrency: number
The maximum number of tasks/scorers that will be run concurrently. Defaults to undefined, in which case there is no max concurrency.
metadata
• Optional metadata: Record<string, unknown>
Optional additional metadata for the experiment.
projectId
• Optional projectId: string
If specified, uses the given project ID instead of the evaluator's name to identify the project.
scores
• scores: EvalScorer<Input, Output, Expected, Metadata>[]
A set of functions that take an input, output, and expected value and return a score.
state
• Optional state: BraintrustState
If specified, uses the logger state to initialize Braintrust objects. If unspecified, falls back to the global state (initialized using your API key).
task
• task: EvalTask<Input, Output>
A function that takes an input and returns an output.
timeout
• Optional timeout: number
The duration, in milliseconds, after which to time out the evaluation. Defaults to undefined, in which case there is no timeout.
trialCount
• Optional trialCount: number
The number of times to run the evaluator per input. This is useful for evaluating applications that have non-deterministic behavior and gives you both a stronger aggregate measure and a sense of the variance in the results.
update
• Optional update: boolean
Whether to update an existing experiment with experiment_name if one exists. Defaults to false.