API Reference

Evals

Runs

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Output Items

Manage and run evals in the OpenAI platform.

Get eval run output items

GET/evals/{eval_id}/runs/{run_id}/output_items

Get an output item of an eval run

GET/evals/{eval_id}/runs/{run_id}/output_items/{output_item_id}

ModelsExpand Collapse

OutputItemListResponse object { id, created_at, datasource_item, 7 more }

A schema representing an evaluation run output item.

id: string

Unique identifier for the evaluation run output item.

created_at: number

Unix timestamp (in seconds) when the evaluation run was created.

datasource_item: map[unknown]

Details of the input data source item.

datasource_item_id: number

The identifier for the data source item.

eval_id: string

The identifier of the evaluation group.

object: "eval.run.output_item"

The type of the object. Always “eval.run.output_item”.

results: array of object { name, passed, score, 2 more }

A list of grader results for this output item.

name: string

The name of the grader.

passed: boolean

Whether the grader considered the output a pass.

score: number

The numeric score produced by the grader.

sample: optional map[unknown]

Optional sample or intermediate data produced by the grader.

type: optional string

The grader type (for example, “string-check-grader”).

run_id: string

The identifier of the evaluation run associated with this output item.

sample: object { error, finish_reason, input, 7 more }

A sample containing the input and output of the evaluation run.

error: EvalAPIError { code, message }

An object representing an error response from the Eval API.

finish_reason: string

The reason why the sample generation was finished.

input: array of object { content, role }

An array of input messages.

content: string

The content of the message.

role: string

The role of the message sender (e.g., system, user, developer).

max_completion_tokens: number

The maximum number of tokens allowed for completion.

model: string

The model used for generating the sample.

output: array of object { content, role }

An array of output messages.

content: optional string

The content of the message.

role: optional string

The role of the message (e.g. “system”, “assistant”, “user”).

seed: number

The seed used for generating the sample.

temperature: number

The sampling temperature used.

top_p: number

The top_p value used for sampling.

usage: object { cached_tokens, completion_tokens, prompt_tokens, total_tokens }

Token usage details for the sample.

cached_tokens: number

The number of tokens retrieved from cache.

completion_tokens: number

The number of completion tokens generated.

prompt_tokens: number

The number of prompt tokens used.

total_tokens: number

The total number of tokens used.

status: string

The status of the evaluation run.

OutputItemRetrieveResponse object { id, created_at, datasource_item, 7 more }

A schema representing an evaluation run output item.

id: string

Unique identifier for the evaluation run output item.

created_at: number

Unix timestamp (in seconds) when the evaluation run was created.

datasource_item: map[unknown]

Details of the input data source item.

datasource_item_id: number

The identifier for the data source item.

eval_id: string

The identifier of the evaluation group.

object: "eval.run.output_item"

The type of the object. Always “eval.run.output_item”.

results: array of object { name, passed, score, 2 more }

A list of grader results for this output item.

name: string

The name of the grader.

passed: boolean

Whether the grader considered the output a pass.

score: number

The numeric score produced by the grader.

sample: optional map[unknown]

Optional sample or intermediate data produced by the grader.

type: optional string

The grader type (for example, “string-check-grader”).

run_id: string

The identifier of the evaluation run associated with this output item.

sample: object { error, finish_reason, input, 7 more }

A sample containing the input and output of the evaluation run.

error: EvalAPIError { code, message }

An object representing an error response from the Eval API.

finish_reason: string

The reason why the sample generation was finished.

input: array of object { content, role }

An array of input messages.

content: string

The content of the message.

role: string

The role of the message sender (e.g., system, user, developer).

max_completion_tokens: number

The maximum number of tokens allowed for completion.

model: string

The model used for generating the sample.

output: array of object { content, role }

An array of output messages.

content: optional string

The content of the message.

role: optional string

The role of the message (e.g. “system”, “assistant”, “user”).

seed: number

The seed used for generating the sample.

temperature: number

The sampling temperature used.

top_p: number

The top_p value used for sampling.

usage: object { cached_tokens, completion_tokens, prompt_tokens, total_tokens }

Token usage details for the sample.

cached_tokens: number

The number of tokens retrieved from cache.

completion_tokens: number

The number of completion tokens generated.

prompt_tokens: number

The number of prompt tokens used.

total_tokens: number

The total number of tokens used.

status: string

The status of the evaluation run.