input: List[Input]

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

content: InputContent

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:
str

A text input to the model.

class ResponseInputText: …

A text input to the model.

text: str

The text input to the model.

type: Literal["input_text"]

The type of the input item. Always input_text.

prompt_cache_breakpoint: Optional[PromptCacheBreakpoint]

Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request’s prompt_cache_options.ttl; the boundary is not rounded to a token block.

mode: Literal["explicit"]

The breakpoint mode. Always explicit.

class InputContentOutputText: …

A text output from the model.

text: str

The text output from the model.

type: Literal["output_text"]

The type of the output text. Always output_text.

class InputContentInputImage: …

An image input block used within EvalItem content arrays.

image_url: str

The URL of the image input.

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type: Literal["input_image"]

The type of the image input. Always input_image.

detail: Optional[str]

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

class ResponseInputAudio: …

An audio input to the model.

input_audio: InputAudio
data: str

Base64-encoded audio data.

format: Literal["mp3", "wav"]

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

One of the following:
"mp3"
"wav"
type: Literal["input_audio"]

The type of the input item. Always input_audio.

List[GraderInputItem]
One of the following:
str

A text input to the model.

class ResponseInputText: …

A text input to the model.

text: str

The text input to the model.

type: Literal["input_text"]

The type of the input item. Always input_text.

prompt_cache_breakpoint: Optional[PromptCacheBreakpoint]

Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request’s prompt_cache_options.ttl; the boundary is not rounded to a token block.

mode: Literal["explicit"]

The breakpoint mode. Always explicit.

class GraderInputItemOutputText: …

A text output from the model.

text: str

The text output from the model.

type: Literal["output_text"]

The type of the output text. Always output_text.

class GraderInputItemInputImage: …

An image input block used within EvalItem content arrays.

image_url: str

The URL of the image input.

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type: Literal["input_image"]

The type of the image input. Always input_image.

detail: Optional[str]

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

class ResponseInputAudio: …

An audio input to the model.

input_audio: InputAudio
data: str

Base64-encoded audio data.

format: Literal["mp3", "wav"]

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

One of the following:
"mp3"
"wav"
type: Literal["input_audio"]

The type of the input item. Always input_audio.

role: Literal["user", "assistant", "system", "developer"]

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

One of the following:
"user"
"assistant"
"system"
"developer"
type: Optional[Literal["message"]]

The type of the message input. Always message.

model: str

The model to use for the evaluation.

name: str

The name of the grader.

type: Literal["score_model"]

The object type, which is always score_model.

range: Optional[List[float]]

The service requires two numbers for the score range. Defaults to [0, 1].

sampling_params: Optional[SamplingParams]

The sampling parameters for the model.

max_completions_tokens: Optional[int]

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

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reasoning_effort: Optional[ReasoningEffort]

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.

One of the following:
"none"
"minimal"
"low"
"medium"
"high"
"xhigh"
"max"
seed: Optional[int]

A seed value to initialize the randomness, during sampling.

temperature: Optional[float]

A higher temperature increases randomness in the outputs.

top_p: Optional[float]

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