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POST
/
metrics
/
batch
Create multiple metrics
curl --request POST \
  --url https://api.galtea.ai/metrics/batch \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "metrics": [
    {
      "id": "metric_123",
      "organizationId": "org_123",
      "userId": "user_123",
      "name": "Accuracy",
      "evaluationParams": [
        "input",
        "actualOutput",
        "expectedOutput"
      ],
      "source": "FULL_PROMPT",
      "judgePrompt": "Evaluate the accuracy of the response",
      "tags": [
        "accuracy",
        "quality"
      ],
      "description": "Measures the accuracy of responses",
      "documentationUrl": "https://docs.example.com/metrics/accuracy",
      "evaluatorModelName": "GPT-4",
      "areEvalParamsTop": true,
      "specificationIds": [
        "spec_123"
      ],
      "createdAt": "2023-11-07T05:31:56Z",
      "legacyAt": "2023-11-07T05:31:56Z",
      "disabledAt": "2023-11-07T05:31:56Z"
    }
  ]
}
'
[
  {
    "id": "metric_123",
    "organizationId": "org_123",
    "userId": "user_123",
    "name": "Accuracy",
    "evaluationParams": [
      "input",
      "actualOutput",
      "expectedOutput"
    ],
    "source": "FULL_PROMPT",
    "judgePrompt": "Evaluate the accuracy of the response",
    "tags": [
      "accuracy",
      "quality"
    ],
    "description": "Measures the accuracy of responses",
    "documentationUrl": "https://docs.example.com/metrics/accuracy",
    "evaluatorModelName": "GPT-4",
    "areEvalParamsTop": true,
    "specificationIds": [
      "spec_123"
    ],
    "createdAt": "2023-11-07T05:31:56Z",
    "legacyAt": "2023-11-07T05:31:56Z",
    "disabledAt": "2023-11-07T05:31:56Z"
  }
]

Authorizations

​
Authorization
string
header
required

API key authorization. Pass your API key in the Authorization header as a Bearer token. Both new (gsk_*) and legacy (gsk-) API keys are accepted, e.g. Authorization: Bearer gsk_... or Authorization: Bearer gsk-....

Body

application/json
​
metrics
object[]
required

Response

Metrics created successfully

​
id
string
Example:

"metric_123"

​
organizationId
string | null
Example:

"org_123"

​
userId
string | null
Example:

"user_123"

​
name
string
Example:

"Accuracy"

​
evaluationParams
string[]

Ordered list of inference-result fields the evaluator needs (e.g. input, actualOutput, expectedOutput, retrievalContext). Determines which data the evaluation engine extracts from each inference result.

Example:
["input", "actualOutput", "expectedOutput"]
​
source
enum<string> | null
Available options:
SELF_HOSTED,
FULL_PROMPT,
PARTIAL_PROMPT,
HUMAN_EVALUATION,
GEVAL,
DEEPEVAL,
DETERMINISTIC
Example:

"FULL_PROMPT"

​
judgePrompt
string | null
Example:

"Evaluate the accuracy of the response"

​
tags
string[]
Example:
["accuracy", "quality"]
​
description
string | null
Example:

"Measures the accuracy of responses"

​
documentationUrl
string | null
Example:

"https://docs.example.com/metrics/accuracy"

​
evaluatorModelName
string | null
Example:

"GPT-4"

​
areEvalParamsTop
boolean | null

When true, evaluationParams are injected at the top level of the evaluator prompt instead of nested inside the conversation context.

​
specificationIds
string[]
Example:
["spec_123"]
​
createdAt
string<date-time>
​
legacyAt
string<date-time> | null
​
disabledAt
string<date-time> | null