Batch Create

POSThttps://api.confident-ai.com/v2/metrics-batch

Creates several GEVAL metrics at once and returns the ones created. Metrics whose name already exists in the project are skipped. DAG metrics must be created one at a time.

POST/v2/metrics-batch

curl -X POST "https://api.confident-ai.com/v2/metrics-batch" \
  -H "CONFIDENT_API_KEY: <PROJECT-API-KEY>" \
  -H "Content-Type: application/json" \
  -d '{
  "metrics": [
    {
      "name": "Correctness",
      "multiTurn": false,
      "criteria": "Determine if the actual output is correct based on the expected output.",
      "evaluationSteps": [
        "Compare the actual output with the expected output.",
        "Penalise any factual contradiction."
      ],
      "evaluationParams": [
        "actualOutput",
        "expectedOutput"
      ],
      "rubric": [
        {
          "scoreRange": [
            8,
            10
          ],
          "expectedOutcome": "The answer is factually correct and complete."
        }
      ],
      "algorithm": "DEFAULT",
      "dag": {
        "nodes": {
          "root": {
            "type": "BinaryJudgementNode",
            "criteria": "Does the actual output answer the input?",
            "evaluation_params": [
              "input",
              "actual_output"
            ],
            "children": [
              "pass",
              "fail"
            ]
          },
          "pass": {
            "type": "VerdictNode",
            "verdict": true,
            "score": 10
          },
          "fail": {
            "type": "VerdictNode",
            "verdict": false,
            "score": 0
          }
        }
      }
    }
  ]
}'

200

{
  "success": true,
  "data": {
    "metrics": [
      {
        "id": "<METRIC-ID>",
        "name": "Correctness",
        "algorithm": "DEFAULT",
        "criteria": "Determine if the actual output is correct based on the expected output.",
        "evaluationSteps": null,
        "rubric": [
          {
            "scoreRange": [
              8,
              10
            ],
            "expectedOutcome": "The answer is factually correct and complete."
          }
        ],
        "dag": {
          "nodes": {
            "root": {
              "type": "BinaryJudgementNode",
              "criteria": "Does the actual output answer the input?",
              "evaluation_params": [
                "input",
                "actual_output"
              ],
              "children": [
                "pass",
                "fail"
              ]
            },
            "pass": {
              "type": "VerdictNode",
              "verdict": true,
              "score": 10
            },
            "fail": {
              "type": "VerdictNode",
              "verdict": false,
              "score": 0
            }
          }
        },
        "multiTurn": false,
        "requiredParameters": [
          "actualOutput",
          "expectedOutput"
        ]
      }
    ]
  },
  "deprecated": false
}

Headers

CONFIDENT_API_KEYstringRequired
The API key of your Confident AI project.

Request body

metricslist of objectsRequired
The metrics to create. Names must be unique within the batch for the same multiTurn, and DAG metrics are not accepted here.
Show 8 propertiesHide 8 properties
- namestringRequired
  The name of the metric, unique within your project.
- multiTurnboolean
  This is true when the metric evaluates conversations rather than single test cases. It decides which evaluationParams are valid and cannot be changed later.
- criteriastring
  The criteria the metric scores against. A GEVAL metric needs criteria or evaluationSteps.
- evaluationStepslist of strings
  The steps the metric follows to score, as an alternative to criteria.
- evaluationParamslist of enums
  The test case fields the metric evaluates. A single-turn metric needs at least one, and every field must match multiTurn.
  Show 14 enum valuesHide 14 enum values
  - input
  - actualOutput
  - expectedOutput
  - context
  - expectedTools
  - content
  - role
  - scenario
  - expectedOutcome
  - turns
  - toolsCalled
  - retrievalContext
  - metadata
  - tags
- rubriclist of objects
  Score ranges that anchor how the metric scores.
  Show 2 propertiesHide 2 properties
  - scoreRangelist of anyRequired
    The inclusive start and end of the score range this outcome describes, each between 0 and 10, with the start no greater than the end.
  - expectedOutcomestringRequired
    What a response scoring in this range looks like.
- algorithmenum
  The algorithm the metric is evaluated with. GEVAL scores against criteria or evaluation steps, DAG walks a decision graph, CODE runs your own code, and DEFAULT is a built-in metric.
  Show 4 enum valuesHide 4 enum values
  - DEFAULT
  - DAG
  - GEVAL
  - CODE
- dagobject
  The decision graph of a DAG metric. It is validated on write, and metric references are resolved against the metrics in your project.
  Show 1 propertyHide 1 property
  - nodesobjectRequired
    The graph's nodes keyed by node id, as serialized by deepeval's DAG metric. Judgement nodes list their children by id; verdict nodes carry a verdict and a score, or point at another metric by metric_name.

Response

Batch Create succeeded.

successboolean
Indicates if the request was successful.
dataobject
Show 1 propertyHide 1 property
- metricslist of objects
  This is the list of metrics.
  Show 9 propertiesHide 9 properties
  - idstring
    This is the unique id of the metric.
  - namestring
    This is the name of the metric, unique within your project.
  - algorithmenum | null
    The algorithm the metric is evaluated with. GEVAL scores against criteria or evaluation steps, DAG walks a decision graph, CODE runs your own code, and DEFAULT is a built-in metric.
    Show 4 enum valuesHide 4 enum values
    DEFAULT
    DAG
    GEVAL
    CODE
  - criteriastring | null
    This is the criteria the metric scores against, or null when it uses evaluation steps.
  - evaluationStepsarray | null
    These are the steps the metric follows to score, or null when it uses criteria.
  - rubricarray | null
    These are the score ranges that anchor how the metric scores, or null.
    Show 2 propertiesHide 2 properties
    scoreRangelist of any
    The inclusive start and end of the score range this outcome describes, each between 0 and 10, with the start no greater than the end.
    expectedOutcomestring
    What a response scoring in this range looks like.
  - dagobject | null
    The decision graph of a DAG metric. It is validated on write, and metric references are resolved against the metrics in your project.
    Show 1 propertyHide 1 property
    nodesobject
    The graph's nodes keyed by node id, as serialized by deepeval's DAG metric. Judgement nodes list their children by id; verdict nodes carry a verdict and a score, or point at another metric by metric_name.
  - multiTurnboolean
    This is true when the metric evaluates conversations rather than single test cases.
  - requiredParameterslist of enums
    The test case fields the metric needs to run.
    Show 14 enum valuesHide 14 enum values
    input
    actualOutput
    expectedOutput
    context
    expectedTools
    content
    role
    scenario
    expectedOutcome
    turns
    toolsCalled
    retrievalContext
    metadata
    tags
deprecatedboolean
Indicates if this endpoint is deprecated.

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