curl --request POST \
--url https://api.galtea.ai/metrics/{id}/optimize \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{}'import requests
url = "https://api.galtea.ai/metrics/{id}/optimize"
payload = {}
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({})
};
fetch('https://api.galtea.ai/metrics/{id}/optimize', 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/{id}/optimize",
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([
]),
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/{id}/optimize"
payload := strings.NewReader("{}")
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/{id}/optimize")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.galtea.ai/metrics/{id}/optimize")
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 = "{}"
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",
"actual_output",
"expected_output"
],
"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,
"optimizationStatus": "READY_FOR_REVIEW",
"judgeGenerationSettings": {
"temperature": 0.3,
"topP": 0.9,
"maxOutputTokens": 512,
"reasoningEffort": "low"
},
"classifierQuestion": {
"type": "yes_no",
"instructions": "<string>",
"goodAnswer": "yes",
"criteria": {
"yes": "<string>",
"no": "<string>"
},
"levels": [
{
"description": "<string>",
"score": 123
}
],
"doesNotApply": "<string>"
},
"optimizationValidation": {
"used": true,
"heldOutEvaluationIds": [
"evaluation_123"
],
"results": {
"optimization": {
"rowsScored": 25,
"rowsTotal": 25,
"source": {
"correct": 20,
"alignment": 0.71
},
"candidate": {
"correct": 20,
"alignment": 0.71
}
},
"validation": {
"rowsScored": 25,
"rowsTotal": 25,
"source": {
"correct": 20,
"alignment": 0.71
},
"candidate": {
"correct": 20,
"alignment": 0.71
}
}
},
"rows": [
{
"evaluationId": "evaluation_123",
"humanScore": 1,
"sourceScore": 0,
"candidateScore": 1
}
]
},
"optimizationRun": {
"strategies": [
"ADD_RUBRIC",
"SIMPLIFY"
],
"maxSteps": 6,
"stepsUsed": 4
},
"specificationIds": [
"spec_123"
],
"userGroupIds": [
"ug_123"
],
"createdAt": "2023-11-07T05:31:56Z",
"legacyAt": "2023-11-07T05:31:56Z",
"disabledAt": "2023-11-07T05:31:56Z",
"excludedFromAnalyticsAt": "2023-11-07T05:31:56Z",
"excludedByUserId": "<string>"
}{
"error": "Error type",
"message": "Error message description"
}{
"error": "Error type",
"message": "Error message description"
}{
"error": "Error type",
"message": "Error message description"
}{
"error": "Error type",
"message": "Error message description"
}Optimize metric
Starts an optimization run that sends the metric’s human-annotated evaluations to the metrics-generator service, which uses the gap between AI and human scores to produce a candidate judge prompt. Only PARTIAL_PROMPT metrics owned by an organization can be optimized, and the source must be its family’s active revision with no candidate already awaiting review. Rejected with 400 unless the metric has at least minAnnotations evaluations annotated by a human AND minDisagreements of those disagree with the AI score; both thresholds are returned by GET /metrics/{id}/human-annotation-count (defaults 10 and 5, configurable via the OPTIMIZE_MIN_ANNOTATIONS_HARD / OPTIMIZE_MIN_DISAGREEMENTS_HARD env vars). From 30 annotated evaluations the run holds out a validation set (one third of them, at least 10, chosen by session) that the optimizer only scores after its search and never searches on. Sessions kept from earlier attempts of the metric stay held out. The split, and the validation results once the run finishes, are on optimizationValidation of the metric. Returns a placeholder metric with isBeingOptimized=true; once the run finishes, the source is untouched and the result is a candidate to review with POST /metrics/{id}/activate-optimization or POST /metrics/{id}/decline-optimization. See Metrics.
curl --request POST \
--url https://api.galtea.ai/metrics/{id}/optimize \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{}'import requests
url = "https://api.galtea.ai/metrics/{id}/optimize"
payload = {}
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({})
};
fetch('https://api.galtea.ai/metrics/{id}/optimize', 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/{id}/optimize",
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([
]),
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/{id}/optimize"
payload := strings.NewReader("{}")
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/{id}/optimize")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.galtea.ai/metrics/{id}/optimize")
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 = "{}"
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",
"actual_output",
"expected_output"
],
"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,
"optimizationStatus": "READY_FOR_REVIEW",
"judgeGenerationSettings": {
"temperature": 0.3,
"topP": 0.9,
"maxOutputTokens": 512,
"reasoningEffort": "low"
},
"classifierQuestion": {
"type": "yes_no",
"instructions": "<string>",
"goodAnswer": "yes",
"criteria": {
"yes": "<string>",
"no": "<string>"
},
"levels": [
{
"description": "<string>",
"score": 123
}
],
"doesNotApply": "<string>"
},
"optimizationValidation": {
"used": true,
"heldOutEvaluationIds": [
"evaluation_123"
],
"results": {
"optimization": {
"rowsScored": 25,
"rowsTotal": 25,
"source": {
"correct": 20,
"alignment": 0.71
},
"candidate": {
"correct": 20,
"alignment": 0.71
}
},
"validation": {
"rowsScored": 25,
"rowsTotal": 25,
"source": {
"correct": 20,
"alignment": 0.71
},
"candidate": {
"correct": 20,
"alignment": 0.71
}
}
},
"rows": [
{
"evaluationId": "evaluation_123",
"humanScore": 1,
"sourceScore": 0,
"candidateScore": 1
}
]
},
"optimizationRun": {
"strategies": [
"ADD_RUBRIC",
"SIMPLIFY"
],
"maxSteps": 6,
"stepsUsed": 4
},
"specificationIds": [
"spec_123"
],
"userGroupIds": [
"ug_123"
],
"createdAt": "2023-11-07T05:31:56Z",
"legacyAt": "2023-11-07T05:31:56Z",
"disabledAt": "2023-11-07T05:31:56Z",
"excludedFromAnalyticsAt": "2023-11-07T05:31:56Z",
"excludedByUserId": "<string>"
}{
"error": "Error type",
"message": "Error message description"
}{
"error": "Error type",
"message": "Error message description"
}{
"error": "Error type",
"message": "Error message description"
}{
"error": "Error type",
"message": "Error message description"
}Authorizations
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-....
Path Parameters
Source Metric ID
"metric_123"
Body
The body is of type object.
Response
Optimized metric placeholder created successfully
"metric_123"
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.
"metric_123"
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).
"metric_122"
"org_123"
"user_123"
"Accuracy"
Ordered list of trace fields the evaluator needs, written in snake_case (e.g. input, actual_output, expected_output, retrieval_context). Determines which data the evaluation engine extracts from each trace. Full list of accepted values: https://docs.galtea.ai/concepts/metric/evaluation-parameters
["input", "actual_output", "expected_output"]
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. CLASSIFIER is the Classifier (Jev) judge, accepted only where the deployment enables it.
SELF_HOSTED, FULL_PROMPT, PARTIAL_PROMPT, HUMAN_EVALUATION, GEVAL, DEEPEVAL, DETERMINISTIC, CLASSIFIER "PARTIAL_PROMPT"
"Evaluate the accuracy of the response"
["accuracy", "quality"]
"Measures the accuracy of responses"
"https://docs.example.com/metrics/accuracy"
"GPT-4"
When true, evaluationParams are injected at the top level of the evaluator prompt instead of nested inside the conversation context.
Whether the metric is currently being optimized.
Where an optimization attempt stands. Null for a metric that did not come from an optimization. A candidate waiting for review is legacy until it is activated.
OPTIMIZING, READY_FOR_REVIEW, FAILED, NO_IMPROVEMENT, DECLINED, ACTIVATED "READY_FOR_REVIEW"
The generation settings this metric's judge runs with. Null runs the platform defaults. Immutable: changing one creates a revision.
Show child attributes
Show child attributes
The one question of a CLASSIFIER metric; null for every other source.
Show child attributes
Show child attributes
How an optimization attempt was validated: the held-out evaluations and, once the optimizer reported, both prompts scored on the search rows and on the held-out rows. Set on an optimization attempt only, and null for any other metric, for an attempt that predates it, and for an attempt copied from another organization.
Show child attributes
Show child attributes
What an optimization attempt ran: the strategies, the step budget and the steps used. Null while the attempt runs, and when it was not reported: an attempt from before the report existed, one run by an older optimizer, a failed run, an attempt copied from another organization, or a metric that is not an optimization attempt. Null never means a run of 0 steps.
Show child attributes
Show child attributes
["spec_123"]
["ug_123"]
Earliest non-null of this metric's own legacy date and its evaluator model's unselectableAt, so a model no longer selectable makes every metric linked to it report as legacy even though the metric row itself is untouched. Present only once that date has passed: a scheduled future cutoff reports null, because the metric is still active until then. Unlike disabledAt, this field never carries a future date.
Earliest non-null of this metric's own disabled date and its evaluator model's disabledAt — a disabled model makes every metric linked to it report as disabled even though the metric row itself is untouched.
When set, results produced by this metric revision do not feed analytics.
User who last excluded this metric revision from analytics.