Optional
customCustom evaluators to apply to a dataset run. Each evaluator is provided with a run trace containing the model outputs, as well as an "example" object representing a record in the dataset.
Optional
evalThe language model specification for evaluators that require one.
Optional
evaluators?: (T | EvalConfig)[]LangChain evaluators to apply to a dataset run. You can optionally specify these by name, or by configuring them with an EvalConfig object.
Optional
formatConvert the evaluation data into a format that can be used by the evaluator. By default, we pass the first value of the run.inputs, run.outputs (predictions), and references (example.outputs)
The prepared data.
RunEvalConfig in LangSmith is a configuration class for running evaluations on datasets. Its primary purpose is to define the parameters and evaluators that will be applied during the evaluation of a dataset. This configuration can include various evaluators, custom evaluators, and different keys for inputs, predictions, and references.
T - The type of evaluators.
U - The type of custom evaluators.
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Configuration class for running evaluations on datasets.