Get an output item of an eval run

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

Get an evaluation run output item by ID.

Path ParametersExpand Collapse

eval_id: string

run_id: string

output_item_id: string

ReturnsExpand Collapse

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.

code: string

The error code.

message: string

The error message.

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.

Get an output item of an eval run

curl https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a/runs/evalrun_67abd54d60ec8190832b46859da808f7/output_items/outputitem_67abd55eb6548190bb580745d5644a33 \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json"

{
  "object": "eval.run.output_item",
  "id": "outputitem_67e5796c28e081909917bf79f6e6214d",
  "created_at": 1743092076,
  "run_id": "evalrun_67abd54d60ec8190832b46859da808f7",
  "eval_id": "eval_67abd54d9b0081909a86353f6fb9317a",
  "status": "pass",
  "datasource_item_id": 5,
  "datasource_item": {
    "input": "Stock Markets Rally After Positive Economic Data Released",
    "ground_truth": "Markets"
  },
  "results": [
    {
      "name": "String check-a2486074-d803-4445-b431-ad2262e85d47",
      "sample": null,
      "passed": true,
      "score": 1.0
    }
  ],
  "sample": {
    "input": [
      {
        "role": "developer",
        "content": "Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\"  \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\"  \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\"  \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\"  \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\"  \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n",
        "tool_call_id": null,
        "tool_calls": null,
        "function_call": null
      },
      {
        "role": "user",
        "content": "Stock Markets Rally After Positive Economic Data Released",
        "tool_call_id": null,
        "tool_calls": null,
        "function_call": null
      }
    ],
    "output": [
      {
        "role": "assistant",
        "content": "Markets",
        "tool_call_id": null,
        "tool_calls": null,
        "function_call": null
      }
    ],
    "finish_reason": "stop",
    "model": "gpt-4o-mini-2024-07-18",
    "usage": {
      "total_tokens": 325,
      "completion_tokens": 2,
      "prompt_tokens": 323,
      "cached_tokens": 0
    },
    "error": null,
    "temperature": 1.0,
    "max_completion_tokens": 2048,
    "top_p": 1.0,
    "seed": 42
  }
}

Returns Examples

{
  "object": "eval.run.output_item",
  "id": "outputitem_67e5796c28e081909917bf79f6e6214d",
  "created_at": 1743092076,
  "run_id": "evalrun_67abd54d60ec8190832b46859da808f7",
  "eval_id": "eval_67abd54d9b0081909a86353f6fb9317a",
  "status": "pass",
  "datasource_item_id": 5,
  "datasource_item": {
    "input": "Stock Markets Rally After Positive Economic Data Released",
    "ground_truth": "Markets"
  },
  "results": [
    {
      "name": "String check-a2486074-d803-4445-b431-ad2262e85d47",
      "sample": null,
      "passed": true,
      "score": 1.0
    }
  ],
  "sample": {
    "input": [
      {
        "role": "developer",
        "content": "Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\"  \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\"  \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\"  \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\"  \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\"  \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n",
        "tool_call_id": null,
        "tool_calls": null,
        "function_call": null
      },
      {
        "role": "user",
        "content": "Stock Markets Rally After Positive Economic Data Released",
        "tool_call_id": null,
        "tool_calls": null,
        "function_call": null
      }
    ],
    "output": [
      {
        "role": "assistant",
        "content": "Markets",
        "tool_call_id": null,
        "tool_calls": null,
        "function_call": null
      }
    ],
    "finish_reason": "stop",
    "model": "gpt-4o-mini-2024-07-18",
    "usage": {
      "total_tokens": 325,
      "completion_tokens": 2,
      "prompt_tokens": 323,
      "cached_tokens": 0
    },
    "error": null,
    "temperature": 1.0,
    "max_completion_tokens": 2048,
    "top_p": 1.0,
    "seed": 42
  }
}