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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",
      "parentMetricId": "metric_122",
      "organizationId": "org_123",
      "userId": "user_123",
      "name": "Accuracy",
      "evaluationParams": [
        "input",
        "actualOutput",
        "expectedOutput"
      ],
      "source": "PARTIAL_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"
      ],
      "userGroupIds": [
        "ug_123"
      ],
      "createdAt": "2023-11-07T05:31:56Z",
      "legacyAt": "2023-11-07T05:31:56Z",
      "disabledAt": "2023-11-07T05:31:56Z"
    }
  ]
}
'
import requests

url = "https://api.galtea.ai/metrics/batch"

payload = { "metrics": [
        {
            "id": "metric_123",
            "parentMetricId": "metric_122",
            "organizationId": "org_123",
            "userId": "user_123",
            "name": "Accuracy",
            "evaluationParams": ["input", "actualOutput", "expectedOutput"],
            "source": "PARTIAL_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"],
            "userGroupIds": ["ug_123"],
            "createdAt": "2023-11-07T05:31:56Z",
            "legacyAt": "2023-11-07T05:31:56Z",
            "disabledAt": "2023-11-07T05:31:56Z"
        }
    ] }
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)
const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    metrics: [
      {
        id: 'metric_123',
        parentMetricId: 'metric_122',
        organizationId: 'org_123',
        userId: 'user_123',
        name: 'Accuracy',
        evaluationParams: ['input', 'actualOutput', 'expectedOutput'],
        source: 'PARTIAL_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'],
        userGroupIds: ['ug_123'],
        createdAt: '2023-11-07T05:31:56Z',
        legacyAt: '2023-11-07T05:31:56Z',
        disabledAt: '2023-11-07T05:31:56Z'
      }
    ]
  })
};

fetch('https://api.galtea.ai/metrics/batch', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));
<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.galtea.ai/metrics/batch",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'metrics' => [
        [
                'id' => 'metric_123',
                'parentMetricId' => 'metric_122',
                'organizationId' => 'org_123',
                'userId' => 'user_123',
                'name' => 'Accuracy',
                'evaluationParams' => [
                                'input',
                                'actualOutput',
                                'expectedOutput'
                ],
                'source' => 'PARTIAL_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'
                ],
                'userGroupIds' => [
                                'ug_123'
                ],
                'createdAt' => '2023-11-07T05:31:56Z',
                'legacyAt' => '2023-11-07T05:31:56Z',
                'disabledAt' => '2023-11-07T05:31:56Z'
        ]
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}
package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.galtea.ai/metrics/batch"

	payload := strings.NewReader("{\n  \"metrics\": [\n    {\n      \"id\": \"metric_123\",\n      \"parentMetricId\": \"metric_122\",\n      \"organizationId\": \"org_123\",\n      \"userId\": \"user_123\",\n      \"name\": \"Accuracy\",\n      \"evaluationParams\": [\n        \"input\",\n        \"actualOutput\",\n        \"expectedOutput\"\n      ],\n      \"source\": \"PARTIAL_PROMPT\",\n      \"judgePrompt\": \"Evaluate the accuracy of the response\",\n      \"tags\": [\n        \"accuracy\",\n        \"quality\"\n      ],\n      \"description\": \"Measures the accuracy of responses\",\n      \"documentationUrl\": \"https://docs.example.com/metrics/accuracy\",\n      \"evaluatorModelName\": \"GPT-4\",\n      \"areEvalParamsTop\": true,\n      \"specificationIds\": [\n        \"spec_123\"\n      ],\n      \"userGroupIds\": [\n        \"ug_123\"\n      ],\n      \"createdAt\": \"2023-11-07T05:31:56Z\",\n      \"legacyAt\": \"2023-11-07T05:31:56Z\",\n      \"disabledAt\": \"2023-11-07T05:31:56Z\"\n    }\n  ]\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}
HttpResponse<String> response = Unirest.post("https://api.galtea.ai/metrics/batch")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"metrics\": [\n    {\n      \"id\": \"metric_123\",\n      \"parentMetricId\": \"metric_122\",\n      \"organizationId\": \"org_123\",\n      \"userId\": \"user_123\",\n      \"name\": \"Accuracy\",\n      \"evaluationParams\": [\n        \"input\",\n        \"actualOutput\",\n        \"expectedOutput\"\n      ],\n      \"source\": \"PARTIAL_PROMPT\",\n      \"judgePrompt\": \"Evaluate the accuracy of the response\",\n      \"tags\": [\n        \"accuracy\",\n        \"quality\"\n      ],\n      \"description\": \"Measures the accuracy of responses\",\n      \"documentationUrl\": \"https://docs.example.com/metrics/accuracy\",\n      \"evaluatorModelName\": \"GPT-4\",\n      \"areEvalParamsTop\": true,\n      \"specificationIds\": [\n        \"spec_123\"\n      ],\n      \"userGroupIds\": [\n        \"ug_123\"\n      ],\n      \"createdAt\": \"2023-11-07T05:31:56Z\",\n      \"legacyAt\": \"2023-11-07T05:31:56Z\",\n      \"disabledAt\": \"2023-11-07T05:31:56Z\"\n    }\n  ]\n}")
  .asString();
require 'uri'
require 'net/http'

url = URI("https://api.galtea.ai/metrics/batch")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"metrics\": [\n    {\n      \"id\": \"metric_123\",\n      \"parentMetricId\": \"metric_122\",\n      \"organizationId\": \"org_123\",\n      \"userId\": \"user_123\",\n      \"name\": \"Accuracy\",\n      \"evaluationParams\": [\n        \"input\",\n        \"actualOutput\",\n        \"expectedOutput\"\n      ],\n      \"source\": \"PARTIAL_PROMPT\",\n      \"judgePrompt\": \"Evaluate the accuracy of the response\",\n      \"tags\": [\n        \"accuracy\",\n        \"quality\"\n      ],\n      \"description\": \"Measures the accuracy of responses\",\n      \"documentationUrl\": \"https://docs.example.com/metrics/accuracy\",\n      \"evaluatorModelName\": \"GPT-4\",\n      \"areEvalParamsTop\": true,\n      \"specificationIds\": [\n        \"spec_123\"\n      ],\n      \"userGroupIds\": [\n        \"ug_123\"\n      ],\n      \"createdAt\": \"2023-11-07T05:31:56Z\",\n      \"legacyAt\": \"2023-11-07T05:31:56Z\",\n      \"disabledAt\": \"2023-11-07T05:31:56Z\"\n    }\n  ]\n}"

response = http.request(request)
puts response.read_body
[
  {
    "id": "metric_123",
    "metricGroupId": "metric_123",
    "parentMetricId": "metric_122",
    "organizationId": "org_123",
    "userId": "user_123",
    "name": "Accuracy",
    "evaluationParams": [
      "input",
      "actualOutput",
      "expectedOutput"
    ],
    "source": "PARTIAL_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,
    "isBeingOptimized": true,
    "specificationIds": [
      "spec_123"
    ],
    "userGroupIds": [
      "ug_123"
    ],
    "createdAt": "2023-11-07T05:31:56Z",
    "legacyAt": "2023-11-07T05:31:56Z",
    "disabledAt": "2023-11-07T05:31:56Z"
  }
]
{
  "error": "Error type",
  "message": "Error message description"
}
{
  "error": "Error type",
  "message": "Error message description"
}

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"

​
metricGroupId
string
read-only

Identifier shared by every metric in the same revision family. Server-managed — derived from parentMetricId on create (or generated for roots). Cannot be set by the caller.

Example:

"metric_123"

​
parentMetricId
string | null

Id of the direct parent metric. On create, providing this value turns the new metric into a revision: it joins the parent's family and (if the parent is active) flips the parent to legacy. Omit or null to create a root metric in a fresh group. On responses, this is the recorded parent edge (null for roots).

Example:

"metric_122"

​
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

Evaluation method for the metric. FULL_PROMPT is deprecated for creation — POST /metrics rejects it with a 400. Use PARTIAL_PROMPT for new AI Evaluation metrics. The value remains in the enum because existing FULL_PROMPT metrics are still returned by reads and filters.

Available options:
SELF_HOSTED,
FULL_PROMPT,
PARTIAL_PROMPT,
HUMAN_EVALUATION,
GEVAL,
DEEPEVAL,
DETERMINISTIC
Example:

"PARTIAL_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.

​
isBeingOptimized
boolean
read-only

Whether the metric is currently being optimized.

​
specificationIds
string[]
Example:
["spec_123"]
​
userGroupIds
string[]
Example:
["ug_123"]
​
createdAt
string<date-time>
​
legacyAt
string<date-time> | null
​
disabledAt
string<date-time> | null