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GradersGrader Models

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GraderInputs = array of string or ResponseInputText { text, type } or object { text, type } or 2 more

A list of inputs, each of which may be either an input text, output text, input image, or input audio object.

One of the following:
TextInput = string

A text input to the model.

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

OutputText = object { text, type }

A text output from the model.

text: string

The text output from the model.

type: "output_text"

The type of the output text. Always output_text.

InputImage = object { image_url, type, detail }

An image input block used within EvalItem content arrays.

image_url: string

The URL of the image input.

type: "input_image"

The type of the image input. Always input_image.

detail: optional string

The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.

ResponseInputAudio = object { input_audio, type }

An audio input to the model.

input_audio: object { data, format }
data: string

Base64-encoded audio data.

format: "mp3" or "wav"

The format of the audio data. Currently supported formats are mp3 and wav.

One of the following:
"mp3"
"wav"
type: "input_audio"

The type of the input item. Always input_audio.

LabelModelGrader = object { input, labels, model, 3 more }

A LabelModelGrader object which uses a model to assign labels to each item in the evaluation.

input: array of object { content, role, type }
content: string or ResponseInputText { text, type } or object { text, type } or 3 more

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.

One of the following:
TextInput = string

A text input to the model.

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

OutputText = object { text, type }

A text output from the model.

text: string

The text output from the model.

type: "output_text"

The type of the output text. Always output_text.

InputImage = object { image_url, type, detail }

An image input block used within EvalItem content arrays.

image_url: string

The URL of the image input.

type: "input_image"

The type of the image input. Always input_image.

detail: optional string

The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.

ResponseInputAudio = object { input_audio, type }

An audio input to the model.

input_audio: object { data, format }
data: string

Base64-encoded audio data.

format: "mp3" or "wav"

The format of the audio data. Currently supported formats are mp3 and wav.

One of the following:
"mp3"
"wav"
type: "input_audio"

The type of the input item. Always input_audio.

GraderInputs = array of string or ResponseInputText { text, type } or object { text, type } or 2 more

A list of inputs, each of which may be either an input text, output text, input image, or input audio object.

One of the following:
TextInput = string

A text input to the model.

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

OutputText = object { text, type }

A text output from the model.

text: string

The text output from the model.

type: "output_text"

The type of the output text. Always output_text.

InputImage = object { image_url, type, detail }

An image input block used within EvalItem content arrays.

image_url: string

The URL of the image input.

type: "input_image"

The type of the image input. Always input_image.

detail: optional string

The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.

ResponseInputAudio = object { input_audio, type }

An audio input to the model.

input_audio: object { data, format }
data: string

Base64-encoded audio data.

format: "mp3" or "wav"

The format of the audio data. Currently supported formats are mp3 and wav.

One of the following:
"mp3"
"wav"
type: "input_audio"

The type of the input item. Always input_audio.

role: "user" or "assistant" or "system" or "developer"

The role of the message input. One of user, assistant, system, or developer.

One of the following:
"user"
"assistant"
"system"
"developer"
type: optional "message"

The type of the message input. Always message.

labels: array of string

The labels to assign to each item in the evaluation.

model: string

The model to use for the evaluation. Must support structured outputs.

name: string

The name of the grader.

passing_labels: array of string

The labels that indicate a passing result. Must be a subset of labels.

type: "label_model"

The object type, which is always label_model.

MultiGrader = object { calculate_output, graders, name, type }

A MultiGrader object combines the output of multiple graders to produce a single score.

calculate_output: string

A formula to calculate the output based on grader results.

graders: StringCheckGrader { input, name, operation, 2 more } or TextSimilarityGrader { evaluation_metric, input, name, 2 more } or PythonGrader { name, source, type, image_tag } or 2 more

A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.

One of the following:
StringCheckGrader = object { input, name, operation, 2 more }

A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.

input: string

The input text. This may include template strings.

name: string

The name of the grader.

operation: "eq" or "ne" or "like" or "ilike"

The string check operation to perform. One of eq, ne, like, or ilike.

One of the following:
"eq"
"ne"
"like"
"ilike"
reference: string

The reference text. This may include template strings.

type: "string_check"

The object type, which is always string_check.

TextSimilarityGrader = object { evaluation_metric, input, name, 2 more }

A TextSimilarityGrader object which grades text based on similarity metrics.

evaluation_metric: "cosine" or "fuzzy_match" or "bleu" or 8 more

The evaluation metric to use. One of cosine, fuzzy_match, bleu, gleu, meteor, rouge_1, rouge_2, rouge_3, rouge_4, rouge_5, or rouge_l.

One of the following:
"cosine"
"fuzzy_match"
"bleu"
"gleu"
"meteor"
"rouge_1"
"rouge_2"
"rouge_3"
"rouge_4"
"rouge_5"
"rouge_l"
input: string

The text being graded.

name: string

The name of the grader.

reference: string

The text being graded against.

type: "text_similarity"

The type of grader.

PythonGrader = object { name, source, type, image_tag }

A PythonGrader object that runs a python script on the input.

name: string

The name of the grader.

source: string

The source code of the python script.

type: "python"

The object type, which is always python.

image_tag: optional string

The image tag to use for the python script.

ScoreModelGrader = object { input, model, name, 3 more }

A ScoreModelGrader object that uses a model to assign a score to the input.

input: array of object { content, role, type }

The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.

content: string or ResponseInputText { text, type } or object { text, type } or 3 more

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.

One of the following:
TextInput = string

A text input to the model.

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

OutputText = object { text, type }

A text output from the model.

text: string

The text output from the model.

type: "output_text"

The type of the output text. Always output_text.

InputImage = object { image_url, type, detail }

An image input block used within EvalItem content arrays.

image_url: string

The URL of the image input.

type: "input_image"

The type of the image input. Always input_image.

detail: optional string

The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.

ResponseInputAudio = object { input_audio, type }

An audio input to the model.

input_audio: object { data, format }
data: string

Base64-encoded audio data.

format: "mp3" or "wav"

The format of the audio data. Currently supported formats are mp3 and wav.

One of the following:
"mp3"
"wav"
type: "input_audio"

The type of the input item. Always input_audio.

GraderInputs = array of string or ResponseInputText { text, type } or object { text, type } or 2 more

A list of inputs, each of which may be either an input text, output text, input image, or input audio object.

One of the following:
TextInput = string

A text input to the model.

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

OutputText = object { text, type }

A text output from the model.

text: string

The text output from the model.

type: "output_text"

The type of the output text. Always output_text.

InputImage = object { image_url, type, detail }

An image input block used within EvalItem content arrays.

image_url: string

The URL of the image input.

type: "input_image"

The type of the image input. Always input_image.

detail: optional string

The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.

ResponseInputAudio = object { input_audio, type }

An audio input to the model.

input_audio: object { data, format }
data: string

Base64-encoded audio data.

format: "mp3" or "wav"

The format of the audio data. Currently supported formats are mp3 and wav.

One of the following:
"mp3"
"wav"
type: "input_audio"

The type of the input item. Always input_audio.

role: "user" or "assistant" or "system" or "developer"

The role of the message input. One of user, assistant, system, or developer.

One of the following:
"user"
"assistant"
"system"
"developer"
type: optional "message"

The type of the message input. Always message.

model: string

The model to use for the evaluation.

name: string

The name of the grader.

type: "score_model"

The object type, which is always score_model.

range: optional array of number

The range of the score. Defaults to [0, 1].

sampling_params: optional object { max_completions_tokens, reasoning_effort, seed, 2 more }

The sampling parameters for the model.

max_completions_tokens: optional number

The maximum number of tokens the grader model may generate in its response.

minimum1
reasoning_effort: optional ReasoningEffort

Constrains effort on reasoning for reasoning models. Currently supported values are none, minimal, low, medium, high, and xhigh. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.

  • gpt-5.1 defaults to none, which does not perform reasoning. The supported reasoning values for gpt-5.1 are none, low, medium, and high. Tool calls are supported for all reasoning values in gpt-5.1.
  • All models before gpt-5.1 default to medium reasoning effort, and do not support none.
  • The gpt-5-pro model defaults to (and only supports) high reasoning effort.
  • xhigh is supported for all models after gpt-5.1-codex-max.
seed: optional number

A seed value to initialize the randomness, during sampling.

temperature: optional number

A higher temperature increases randomness in the outputs.

top_p: optional number

An alternative to temperature for nucleus sampling; 1.0 includes all tokens.

LabelModelGrader = object { input, labels, model, 3 more }

A LabelModelGrader object which uses a model to assign labels to each item in the evaluation.

input: array of object { content, role, type }
content: string or ResponseInputText { text, type } or object { text, type } or 3 more

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.

One of the following:
TextInput = string

A text input to the model.

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

OutputText = object { text, type }

A text output from the model.

text: string

The text output from the model.

type: "output_text"

The type of the output text. Always output_text.

InputImage = object { image_url, type, detail }

An image input block used within EvalItem content arrays.

image_url: string

The URL of the image input.

type: "input_image"

The type of the image input. Always input_image.

detail: optional string

The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.

ResponseInputAudio = object { input_audio, type }

An audio input to the model.

input_audio: object { data, format }
data: string

Base64-encoded audio data.

format: "mp3" or "wav"

The format of the audio data. Currently supported formats are mp3 and wav.

One of the following:
"mp3"
"wav"
type: "input_audio"

The type of the input item. Always input_audio.

GraderInputs = array of string or ResponseInputText { text, type } or object { text, type } or 2 more

A list of inputs, each of which may be either an input text, output text, input image, or input audio object.

One of the following:
TextInput = string

A text input to the model.

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

OutputText = object { text, type }

A text output from the model.

text: string

The text output from the model.

type: "output_text"

The type of the output text. Always output_text.

InputImage = object { image_url, type, detail }

An image input block used within EvalItem content arrays.

image_url: string

The URL of the image input.

type: "input_image"

The type of the image input. Always input_image.

detail: optional string

The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.

ResponseInputAudio = object { input_audio, type }

An audio input to the model.

input_audio: object { data, format }
data: string

Base64-encoded audio data.

format: "mp3" or "wav"

The format of the audio data. Currently supported formats are mp3 and wav.

One of the following:
"mp3"
"wav"
type: "input_audio"

The type of the input item. Always input_audio.

role: "user" or "assistant" or "system" or "developer"

The role of the message input. One of user, assistant, system, or developer.

One of the following:
"user"
"assistant"
"system"
"developer"
type: optional "message"

The type of the message input. Always message.

labels: array of string

The labels to assign to each item in the evaluation.

model: string

The model to use for the evaluation. Must support structured outputs.

name: string

The name of the grader.

passing_labels: array of string

The labels that indicate a passing result. Must be a subset of labels.

type: "label_model"

The object type, which is always label_model.

name: string

The name of the grader.

type: "multi"

The object type, which is always multi.

PythonGrader = object { name, source, type, image_tag }

A PythonGrader object that runs a python script on the input.

name: string

The name of the grader.

source: string

The source code of the python script.

type: "python"

The object type, which is always python.

image_tag: optional string

The image tag to use for the python script.

ScoreModelGrader = object { input, model, name, 3 more }

A ScoreModelGrader object that uses a model to assign a score to the input.

input: array of object { content, role, type }

The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.

content: string or ResponseInputText { text, type } or object { text, type } or 3 more

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.

One of the following:
TextInput = string

A text input to the model.

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

OutputText = object { text, type }

A text output from the model.

text: string

The text output from the model.

type: "output_text"

The type of the output text. Always output_text.

InputImage = object { image_url, type, detail }

An image input block used within EvalItem content arrays.

image_url: string

The URL of the image input.

type: "input_image"

The type of the image input. Always input_image.

detail: optional string

The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.

ResponseInputAudio = object { input_audio, type }

An audio input to the model.

input_audio: object { data, format }
data: string

Base64-encoded audio data.

format: "mp3" or "wav"

The format of the audio data. Currently supported formats are mp3 and wav.

One of the following:
"mp3"
"wav"
type: "input_audio"

The type of the input item. Always input_audio.

GraderInputs = array of string or ResponseInputText { text, type } or object { text, type } or 2 more

A list of inputs, each of which may be either an input text, output text, input image, or input audio object.

One of the following:
TextInput = string

A text input to the model.

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

OutputText = object { text, type }

A text output from the model.

text: string

The text output from the model.

type: "output_text"

The type of the output text. Always output_text.

InputImage = object { image_url, type, detail }

An image input block used within EvalItem content arrays.

image_url: string

The URL of the image input.

type: "input_image"

The type of the image input. Always input_image.

detail: optional string

The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.

ResponseInputAudio = object { input_audio, type }

An audio input to the model.

input_audio: object { data, format }
data: string

Base64-encoded audio data.

format: "mp3" or "wav"

The format of the audio data. Currently supported formats are mp3 and wav.

One of the following:
"mp3"
"wav"
type: "input_audio"

The type of the input item. Always input_audio.

role: "user" or "assistant" or "system" or "developer"

The role of the message input. One of user, assistant, system, or developer.

One of the following:
"user"
"assistant"
"system"
"developer"
type: optional "message"

The type of the message input. Always message.

model: string

The model to use for the evaluation.

name: string

The name of the grader.

type: "score_model"

The object type, which is always score_model.

range: optional array of number

The range of the score. Defaults to [0, 1].

sampling_params: optional object { max_completions_tokens, reasoning_effort, seed, 2 more }

The sampling parameters for the model.

max_completions_tokens: optional number

The maximum number of tokens the grader model may generate in its response.

minimum1
reasoning_effort: optional ReasoningEffort

Constrains effort on reasoning for reasoning models. Currently supported values are none, minimal, low, medium, high, and xhigh. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.

  • gpt-5.1 defaults to none, which does not perform reasoning. The supported reasoning values for gpt-5.1 are none, low, medium, and high. Tool calls are supported for all reasoning values in gpt-5.1.
  • All models before gpt-5.1 default to medium reasoning effort, and do not support none.
  • The gpt-5-pro model defaults to (and only supports) high reasoning effort.
  • xhigh is supported for all models after gpt-5.1-codex-max.
seed: optional number

A seed value to initialize the randomness, during sampling.

temperature: optional number

A higher temperature increases randomness in the outputs.

top_p: optional number

An alternative to temperature for nucleus sampling; 1.0 includes all tokens.

StringCheckGrader = object { input, name, operation, 2 more }

A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.

input: string

The input text. This may include template strings.

name: string

The name of the grader.

operation: "eq" or "ne" or "like" or "ilike"

The string check operation to perform. One of eq, ne, like, or ilike.

One of the following:
"eq"
"ne"
"like"
"ilike"
reference: string

The reference text. This may include template strings.

type: "string_check"

The object type, which is always string_check.

TextSimilarityGrader = object { evaluation_metric, input, name, 2 more }

A TextSimilarityGrader object which grades text based on similarity metrics.

evaluation_metric: "cosine" or "fuzzy_match" or "bleu" or 8 more

The evaluation metric to use. One of cosine, fuzzy_match, bleu, gleu, meteor, rouge_1, rouge_2, rouge_3, rouge_4, rouge_5, or rouge_l.

One of the following:
"cosine"
"fuzzy_match"
"bleu"
"gleu"
"meteor"
"rouge_1"
"rouge_2"
"rouge_3"
"rouge_4"
"rouge_5"
"rouge_l"
input: string

The text being graded.

name: string

The name of the grader.

reference: string

The text being graded against.

type: "text_similarity"

The type of grader.