Grader Models
ModelsExpand Collapse
class EvalContentItem: A class that can be one of several variants.union A single content item: input text, output text, input image, or input audio.
A single content item: input text, output text, input image, or input audio.
class ResponseInputText:A text input to the model.
A text input to the model.
The type of the input item. Always input_text.
class LabelModelGrader:A LabelModelGrader object which uses a model to assign labels to each item
in the evaluation.
A LabelModelGrader object which uses a model to assign labels to each item in the evaluation.
List<Input> input
Content contentInputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
class ResponseInputText:A text input to the model.
A text input to the model.
The type of the input item. Always input_text.
List<EvalContentItem>
class ResponseInputText:A text input to the model.
A text input to the model.
The type of the input item. Always input_text.
class MultiGrader:A MultiGrader object combines the output of multiple graders to produce a single score.
A MultiGrader object combines the output of multiple graders to produce a single score.
Graders gradersA StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
class StringCheckGrader:A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
class TextSimilarityGrader:A TextSimilarityGrader object which grades text based on similarity metrics.
A TextSimilarityGrader object which grades text based on similarity metrics.
class ScoreModelGrader:A ScoreModelGrader object that uses a model to assign a score to the input.
A ScoreModelGrader object that uses a model to assign a score to the input.
List<Input> inputThe input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
Content contentInputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
class ResponseInputText:A text input to the model.
A text input to the model.
The type of the input item. Always input_text.
List<EvalContentItem>
class ResponseInputText:A text input to the model.
A text input to the model.
The type of the input item. Always input_text.
The object type, which is always score_model.
Optional<SamplingParams> samplingParamsThe sampling parameters for the model.
The sampling parameters for the model.
The maximum number of tokens the grader model may generate in its response.
Constrains effort on reasoning for reasoning models. Currently supported
values are none, minimal, low, medium, high, xhigh, and max.
Reducing reasoning effort can result in faster responses and fewer tokens
used on reasoning in a response. Not all reasoning models support every
value. See the
reasoning guide
for model-specific support.
class LabelModelGrader:A LabelModelGrader object which uses a model to assign labels to each item
in the evaluation.
A LabelModelGrader object which uses a model to assign labels to each item in the evaluation.
List<Input> input
Content contentInputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
class ResponseInputText:A text input to the model.
A text input to the model.
The type of the input item. Always input_text.
List<EvalContentItem>
class ResponseInputText:A text input to the model.
A text input to the model.
The type of the input item. Always input_text.
class ScoreModelGrader:A ScoreModelGrader object that uses a model to assign a score to the input.
A ScoreModelGrader object that uses a model to assign a score to the input.
List<Input> inputThe input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
Content contentInputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
class ResponseInputText:A text input to the model.
A text input to the model.
The type of the input item. Always input_text.
List<EvalContentItem>
class ResponseInputText:A text input to the model.
A text input to the model.
The type of the input item. Always input_text.
The object type, which is always score_model.
Optional<SamplingParams> samplingParamsThe sampling parameters for the model.
The sampling parameters for the model.
The maximum number of tokens the grader model may generate in its response.
Constrains effort on reasoning for reasoning models. Currently supported
values are none, minimal, low, medium, high, xhigh, and max.
Reducing reasoning effort can result in faster responses and fewer tokens
used on reasoning in a response. Not all reasoning models support every
value. See the
reasoning guide
for model-specific support.