Create test case
curl --request POST \
--url https://api.galtea.ai/testCases \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"id": "tc_123",
"testId": "test_123",
"userId": "user_123",
"input": {
"user_message": "What is the capital of France?"
},
"expectedOutput": "Paris",
"expectedTools": [
"search",
"calculator"
],
"context": {
"value": "Geography question"
},
"source": "manual",
"sourceFile": "<string>",
"confidence": 0.95,
"confidenceReason": "High quality data",
"variant": "VARIANT_1",
"strategy": "STRATEGY_1",
"languageCode": "es-MX",
"gender": "FEMALE",
"backgroundNoiseProfile": "street",
"backgroundNoiseLevel": "medium",
"userPersona": "Student",
"scenario": "Educational quiz",
"goal": "Test geographical knowledge",
"archetype": "data_grounded",
"specRelevance": "direct",
"stoppingCriterias": [
"MAX_ITERATIONS",
"GOAL_ACHIEVED"
],
"maxIterations": 10,
"isAugmented": false,
"reviewedById": "user_456",
"userScore": 5,
"userScoreReason": "Accurate and complete",
"creditsUsed": 1,
"sourceTestCaseId": "<string>",
"testCaseGroupId": "testCaseGroup_123",
"parentTestCaseId": "<string>",
"legacyAt": "2023-11-07T05:31:56Z",
"createdAt": "2023-11-07T05:31:56Z",
"deletedAt": "2023-11-07T05:31:56Z"
}
'import requests
url = "https://api.galtea.ai/testCases"
payload = {
"id": "tc_123",
"testId": "test_123",
"userId": "user_123",
"input": { "user_message": "What is the capital of France?" },
"expectedOutput": "Paris",
"expectedTools": ["search", "calculator"],
"context": { "value": "Geography question" },
"source": "manual",
"sourceFile": "<string>",
"confidence": 0.95,
"confidenceReason": "High quality data",
"variant": "VARIANT_1",
"strategy": "STRATEGY_1",
"languageCode": "es-MX",
"gender": "FEMALE",
"backgroundNoiseProfile": "street",
"backgroundNoiseLevel": "medium",
"userPersona": "Student",
"scenario": "Educational quiz",
"goal": "Test geographical knowledge",
"archetype": "data_grounded",
"specRelevance": "direct",
"stoppingCriterias": ["MAX_ITERATIONS", "GOAL_ACHIEVED"],
"maxIterations": 10,
"isAugmented": False,
"reviewedById": "user_456",
"userScore": 5,
"userScoreReason": "Accurate and complete",
"creditsUsed": 1,
"sourceTestCaseId": "<string>",
"testCaseGroupId": "testCaseGroup_123",
"parentTestCaseId": "<string>",
"legacyAt": "2023-11-07T05:31:56Z",
"createdAt": "2023-11-07T05:31:56Z",
"deletedAt": "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({
id: 'tc_123',
testId: 'test_123',
userId: 'user_123',
input: {user_message: 'What is the capital of France?'},
expectedOutput: 'Paris',
expectedTools: ['search', 'calculator'],
context: {value: 'Geography question'},
source: 'manual',
sourceFile: '<string>',
confidence: 0.95,
confidenceReason: 'High quality data',
variant: 'VARIANT_1',
strategy: 'STRATEGY_1',
languageCode: 'es-MX',
gender: 'FEMALE',
backgroundNoiseProfile: 'street',
backgroundNoiseLevel: 'medium',
userPersona: 'Student',
scenario: 'Educational quiz',
goal: 'Test geographical knowledge',
archetype: 'data_grounded',
specRelevance: 'direct',
stoppingCriterias: ['MAX_ITERATIONS', 'GOAL_ACHIEVED'],
maxIterations: 10,
isAugmented: false,
reviewedById: 'user_456',
userScore: 5,
userScoreReason: 'Accurate and complete',
creditsUsed: 1,
sourceTestCaseId: '<string>',
testCaseGroupId: 'testCaseGroup_123',
parentTestCaseId: '<string>',
legacyAt: '2023-11-07T05:31:56Z',
createdAt: '2023-11-07T05:31:56Z',
deletedAt: '2023-11-07T05:31:56Z'
})
};
fetch('https://api.galtea.ai/testCases', 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/testCases",
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([
'id' => 'tc_123',
'testId' => 'test_123',
'userId' => 'user_123',
'input' => [
'user_message' => 'What is the capital of France?'
],
'expectedOutput' => 'Paris',
'expectedTools' => [
'search',
'calculator'
],
'context' => [
'value' => 'Geography question'
],
'source' => 'manual',
'sourceFile' => '<string>',
'confidence' => 0.95,
'confidenceReason' => 'High quality data',
'variant' => 'VARIANT_1',
'strategy' => 'STRATEGY_1',
'languageCode' => 'es-MX',
'gender' => 'FEMALE',
'backgroundNoiseProfile' => 'street',
'backgroundNoiseLevel' => 'medium',
'userPersona' => 'Student',
'scenario' => 'Educational quiz',
'goal' => 'Test geographical knowledge',
'archetype' => 'data_grounded',
'specRelevance' => 'direct',
'stoppingCriterias' => [
'MAX_ITERATIONS',
'GOAL_ACHIEVED'
],
'maxIterations' => 10,
'isAugmented' => false,
'reviewedById' => 'user_456',
'userScore' => 5,
'userScoreReason' => 'Accurate and complete',
'creditsUsed' => 1,
'sourceTestCaseId' => '<string>',
'testCaseGroupId' => 'testCaseGroup_123',
'parentTestCaseId' => '<string>',
'legacyAt' => '2023-11-07T05:31:56Z',
'createdAt' => '2023-11-07T05:31:56Z',
'deletedAt' => '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/testCases"
payload := strings.NewReader("{\n \"id\": \"tc_123\",\n \"testId\": \"test_123\",\n \"userId\": \"user_123\",\n \"input\": {\n \"user_message\": \"What is the capital of France?\"\n },\n \"expectedOutput\": \"Paris\",\n \"expectedTools\": [\n \"search\",\n \"calculator\"\n ],\n \"context\": {\n \"value\": \"Geography question\"\n },\n \"source\": \"manual\",\n \"sourceFile\": \"<string>\",\n \"confidence\": 0.95,\n \"confidenceReason\": \"High quality data\",\n \"variant\": \"VARIANT_1\",\n \"strategy\": \"STRATEGY_1\",\n \"languageCode\": \"es-MX\",\n \"gender\": \"FEMALE\",\n \"backgroundNoiseProfile\": \"street\",\n \"backgroundNoiseLevel\": \"medium\",\n \"userPersona\": \"Student\",\n \"scenario\": \"Educational quiz\",\n \"goal\": \"Test geographical knowledge\",\n \"archetype\": \"data_grounded\",\n \"specRelevance\": \"direct\",\n \"stoppingCriterias\": [\n \"MAX_ITERATIONS\",\n \"GOAL_ACHIEVED\"\n ],\n \"maxIterations\": 10,\n \"isAugmented\": false,\n \"reviewedById\": \"user_456\",\n \"userScore\": 5,\n \"userScoreReason\": \"Accurate and complete\",\n \"creditsUsed\": 1,\n \"sourceTestCaseId\": \"<string>\",\n \"testCaseGroupId\": \"testCaseGroup_123\",\n \"parentTestCaseId\": \"<string>\",\n \"legacyAt\": \"2023-11-07T05:31:56Z\",\n \"createdAt\": \"2023-11-07T05:31:56Z\",\n \"deletedAt\": \"2023-11-07T05:31:56Z\"\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/testCases")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"id\": \"tc_123\",\n \"testId\": \"test_123\",\n \"userId\": \"user_123\",\n \"input\": {\n \"user_message\": \"What is the capital of France?\"\n },\n \"expectedOutput\": \"Paris\",\n \"expectedTools\": [\n \"search\",\n \"calculator\"\n ],\n \"context\": {\n \"value\": \"Geography question\"\n },\n \"source\": \"manual\",\n \"sourceFile\": \"<string>\",\n \"confidence\": 0.95,\n \"confidenceReason\": \"High quality data\",\n \"variant\": \"VARIANT_1\",\n \"strategy\": \"STRATEGY_1\",\n \"languageCode\": \"es-MX\",\n \"gender\": \"FEMALE\",\n \"backgroundNoiseProfile\": \"street\",\n \"backgroundNoiseLevel\": \"medium\",\n \"userPersona\": \"Student\",\n \"scenario\": \"Educational quiz\",\n \"goal\": \"Test geographical knowledge\",\n \"archetype\": \"data_grounded\",\n \"specRelevance\": \"direct\",\n \"stoppingCriterias\": [\n \"MAX_ITERATIONS\",\n \"GOAL_ACHIEVED\"\n ],\n \"maxIterations\": 10,\n \"isAugmented\": false,\n \"reviewedById\": \"user_456\",\n \"userScore\": 5,\n \"userScoreReason\": \"Accurate and complete\",\n \"creditsUsed\": 1,\n \"sourceTestCaseId\": \"<string>\",\n \"testCaseGroupId\": \"testCaseGroup_123\",\n \"parentTestCaseId\": \"<string>\",\n \"legacyAt\": \"2023-11-07T05:31:56Z\",\n \"createdAt\": \"2023-11-07T05:31:56Z\",\n \"deletedAt\": \"2023-11-07T05:31:56Z\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.galtea.ai/testCases")
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 \"id\": \"tc_123\",\n \"testId\": \"test_123\",\n \"userId\": \"user_123\",\n \"input\": {\n \"user_message\": \"What is the capital of France?\"\n },\n \"expectedOutput\": \"Paris\",\n \"expectedTools\": [\n \"search\",\n \"calculator\"\n ],\n \"context\": {\n \"value\": \"Geography question\"\n },\n \"source\": \"manual\",\n \"sourceFile\": \"<string>\",\n \"confidence\": 0.95,\n \"confidenceReason\": \"High quality data\",\n \"variant\": \"VARIANT_1\",\n \"strategy\": \"STRATEGY_1\",\n \"languageCode\": \"es-MX\",\n \"gender\": \"FEMALE\",\n \"backgroundNoiseProfile\": \"street\",\n \"backgroundNoiseLevel\": \"medium\",\n \"userPersona\": \"Student\",\n \"scenario\": \"Educational quiz\",\n \"goal\": \"Test geographical knowledge\",\n \"archetype\": \"data_grounded\",\n \"specRelevance\": \"direct\",\n \"stoppingCriterias\": [\n \"MAX_ITERATIONS\",\n \"GOAL_ACHIEVED\"\n ],\n \"maxIterations\": 10,\n \"isAugmented\": false,\n \"reviewedById\": \"user_456\",\n \"userScore\": 5,\n \"userScoreReason\": \"Accurate and complete\",\n \"creditsUsed\": 1,\n \"sourceTestCaseId\": \"<string>\",\n \"testCaseGroupId\": \"testCaseGroup_123\",\n \"parentTestCaseId\": \"<string>\",\n \"legacyAt\": \"2023-11-07T05:31:56Z\",\n \"createdAt\": \"2023-11-07T05:31:56Z\",\n \"deletedAt\": \"2023-11-07T05:31:56Z\"\n}"
response = http.request(request)
puts response.read_body{
"id": "tc_123",
"testId": "test_123",
"userId": "user_123",
"input": {
"user_message": "What is the capital of France?"
},
"expectedOutput": "Paris",
"expectedTools": [
"search",
"calculator"
],
"context": {
"value": "Geography question"
},
"source": "manual",
"sourceFile": "<string>",
"confidence": 0.95,
"confidenceReason": "High quality data",
"variant": "VARIANT_1",
"strategy": "STRATEGY_1",
"languageCode": "es-MX",
"gender": "FEMALE",
"backgroundNoiseProfile": "street",
"backgroundNoiseLevel": "medium",
"userPersona": "Student",
"scenario": "Educational quiz",
"goal": "Test geographical knowledge",
"archetype": "data_grounded",
"specRelevance": "direct",
"stoppingCriterias": [
"MAX_ITERATIONS",
"GOAL_ACHIEVED"
],
"maxIterations": 10,
"isAugmented": false,
"reviewedById": "user_456",
"userScore": 5,
"userScoreReason": "Accurate and complete",
"creditsUsed": 1,
"sourceTestCaseId": "<string>",
"testCaseGroupId": "testCaseGroup_123",
"parentTestCaseId": "<string>",
"legacyAt": "2023-11-07T05:31:56Z",
"createdAt": "2023-11-07T05:31:56Z",
"deletedAt": "2023-11-07T05:31:56Z"
}{
"error": "Error type",
"message": "Error message description"
}Create test case
Create a new test case. See Datasets.
POST
/
testCases
Create test case
curl --request POST \
--url https://api.galtea.ai/testCases \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"id": "tc_123",
"testId": "test_123",
"userId": "user_123",
"input": {
"user_message": "What is the capital of France?"
},
"expectedOutput": "Paris",
"expectedTools": [
"search",
"calculator"
],
"context": {
"value": "Geography question"
},
"source": "manual",
"sourceFile": "<string>",
"confidence": 0.95,
"confidenceReason": "High quality data",
"variant": "VARIANT_1",
"strategy": "STRATEGY_1",
"languageCode": "es-MX",
"gender": "FEMALE",
"backgroundNoiseProfile": "street",
"backgroundNoiseLevel": "medium",
"userPersona": "Student",
"scenario": "Educational quiz",
"goal": "Test geographical knowledge",
"archetype": "data_grounded",
"specRelevance": "direct",
"stoppingCriterias": [
"MAX_ITERATIONS",
"GOAL_ACHIEVED"
],
"maxIterations": 10,
"isAugmented": false,
"reviewedById": "user_456",
"userScore": 5,
"userScoreReason": "Accurate and complete",
"creditsUsed": 1,
"sourceTestCaseId": "<string>",
"testCaseGroupId": "testCaseGroup_123",
"parentTestCaseId": "<string>",
"legacyAt": "2023-11-07T05:31:56Z",
"createdAt": "2023-11-07T05:31:56Z",
"deletedAt": "2023-11-07T05:31:56Z"
}
'import requests
url = "https://api.galtea.ai/testCases"
payload = {
"id": "tc_123",
"testId": "test_123",
"userId": "user_123",
"input": { "user_message": "What is the capital of France?" },
"expectedOutput": "Paris",
"expectedTools": ["search", "calculator"],
"context": { "value": "Geography question" },
"source": "manual",
"sourceFile": "<string>",
"confidence": 0.95,
"confidenceReason": "High quality data",
"variant": "VARIANT_1",
"strategy": "STRATEGY_1",
"languageCode": "es-MX",
"gender": "FEMALE",
"backgroundNoiseProfile": "street",
"backgroundNoiseLevel": "medium",
"userPersona": "Student",
"scenario": "Educational quiz",
"goal": "Test geographical knowledge",
"archetype": "data_grounded",
"specRelevance": "direct",
"stoppingCriterias": ["MAX_ITERATIONS", "GOAL_ACHIEVED"],
"maxIterations": 10,
"isAugmented": False,
"reviewedById": "user_456",
"userScore": 5,
"userScoreReason": "Accurate and complete",
"creditsUsed": 1,
"sourceTestCaseId": "<string>",
"testCaseGroupId": "testCaseGroup_123",
"parentTestCaseId": "<string>",
"legacyAt": "2023-11-07T05:31:56Z",
"createdAt": "2023-11-07T05:31:56Z",
"deletedAt": "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({
id: 'tc_123',
testId: 'test_123',
userId: 'user_123',
input: {user_message: 'What is the capital of France?'},
expectedOutput: 'Paris',
expectedTools: ['search', 'calculator'],
context: {value: 'Geography question'},
source: 'manual',
sourceFile: '<string>',
confidence: 0.95,
confidenceReason: 'High quality data',
variant: 'VARIANT_1',
strategy: 'STRATEGY_1',
languageCode: 'es-MX',
gender: 'FEMALE',
backgroundNoiseProfile: 'street',
backgroundNoiseLevel: 'medium',
userPersona: 'Student',
scenario: 'Educational quiz',
goal: 'Test geographical knowledge',
archetype: 'data_grounded',
specRelevance: 'direct',
stoppingCriterias: ['MAX_ITERATIONS', 'GOAL_ACHIEVED'],
maxIterations: 10,
isAugmented: false,
reviewedById: 'user_456',
userScore: 5,
userScoreReason: 'Accurate and complete',
creditsUsed: 1,
sourceTestCaseId: '<string>',
testCaseGroupId: 'testCaseGroup_123',
parentTestCaseId: '<string>',
legacyAt: '2023-11-07T05:31:56Z',
createdAt: '2023-11-07T05:31:56Z',
deletedAt: '2023-11-07T05:31:56Z'
})
};
fetch('https://api.galtea.ai/testCases', 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/testCases",
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([
'id' => 'tc_123',
'testId' => 'test_123',
'userId' => 'user_123',
'input' => [
'user_message' => 'What is the capital of France?'
],
'expectedOutput' => 'Paris',
'expectedTools' => [
'search',
'calculator'
],
'context' => [
'value' => 'Geography question'
],
'source' => 'manual',
'sourceFile' => '<string>',
'confidence' => 0.95,
'confidenceReason' => 'High quality data',
'variant' => 'VARIANT_1',
'strategy' => 'STRATEGY_1',
'languageCode' => 'es-MX',
'gender' => 'FEMALE',
'backgroundNoiseProfile' => 'street',
'backgroundNoiseLevel' => 'medium',
'userPersona' => 'Student',
'scenario' => 'Educational quiz',
'goal' => 'Test geographical knowledge',
'archetype' => 'data_grounded',
'specRelevance' => 'direct',
'stoppingCriterias' => [
'MAX_ITERATIONS',
'GOAL_ACHIEVED'
],
'maxIterations' => 10,
'isAugmented' => false,
'reviewedById' => 'user_456',
'userScore' => 5,
'userScoreReason' => 'Accurate and complete',
'creditsUsed' => 1,
'sourceTestCaseId' => '<string>',
'testCaseGroupId' => 'testCaseGroup_123',
'parentTestCaseId' => '<string>',
'legacyAt' => '2023-11-07T05:31:56Z',
'createdAt' => '2023-11-07T05:31:56Z',
'deletedAt' => '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/testCases"
payload := strings.NewReader("{\n \"id\": \"tc_123\",\n \"testId\": \"test_123\",\n \"userId\": \"user_123\",\n \"input\": {\n \"user_message\": \"What is the capital of France?\"\n },\n \"expectedOutput\": \"Paris\",\n \"expectedTools\": [\n \"search\",\n \"calculator\"\n ],\n \"context\": {\n \"value\": \"Geography question\"\n },\n \"source\": \"manual\",\n \"sourceFile\": \"<string>\",\n \"confidence\": 0.95,\n \"confidenceReason\": \"High quality data\",\n \"variant\": \"VARIANT_1\",\n \"strategy\": \"STRATEGY_1\",\n \"languageCode\": \"es-MX\",\n \"gender\": \"FEMALE\",\n \"backgroundNoiseProfile\": \"street\",\n \"backgroundNoiseLevel\": \"medium\",\n \"userPersona\": \"Student\",\n \"scenario\": \"Educational quiz\",\n \"goal\": \"Test geographical knowledge\",\n \"archetype\": \"data_grounded\",\n \"specRelevance\": \"direct\",\n \"stoppingCriterias\": [\n \"MAX_ITERATIONS\",\n \"GOAL_ACHIEVED\"\n ],\n \"maxIterations\": 10,\n \"isAugmented\": false,\n \"reviewedById\": \"user_456\",\n \"userScore\": 5,\n \"userScoreReason\": \"Accurate and complete\",\n \"creditsUsed\": 1,\n \"sourceTestCaseId\": \"<string>\",\n \"testCaseGroupId\": \"testCaseGroup_123\",\n \"parentTestCaseId\": \"<string>\",\n \"legacyAt\": \"2023-11-07T05:31:56Z\",\n \"createdAt\": \"2023-11-07T05:31:56Z\",\n \"deletedAt\": \"2023-11-07T05:31:56Z\"\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/testCases")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"id\": \"tc_123\",\n \"testId\": \"test_123\",\n \"userId\": \"user_123\",\n \"input\": {\n \"user_message\": \"What is the capital of France?\"\n },\n \"expectedOutput\": \"Paris\",\n \"expectedTools\": [\n \"search\",\n \"calculator\"\n ],\n \"context\": {\n \"value\": \"Geography question\"\n },\n \"source\": \"manual\",\n \"sourceFile\": \"<string>\",\n \"confidence\": 0.95,\n \"confidenceReason\": \"High quality data\",\n \"variant\": \"VARIANT_1\",\n \"strategy\": \"STRATEGY_1\",\n \"languageCode\": \"es-MX\",\n \"gender\": \"FEMALE\",\n \"backgroundNoiseProfile\": \"street\",\n \"backgroundNoiseLevel\": \"medium\",\n \"userPersona\": \"Student\",\n \"scenario\": \"Educational quiz\",\n \"goal\": \"Test geographical knowledge\",\n \"archetype\": \"data_grounded\",\n \"specRelevance\": \"direct\",\n \"stoppingCriterias\": [\n \"MAX_ITERATIONS\",\n \"GOAL_ACHIEVED\"\n ],\n \"maxIterations\": 10,\n \"isAugmented\": false,\n \"reviewedById\": \"user_456\",\n \"userScore\": 5,\n \"userScoreReason\": \"Accurate and complete\",\n \"creditsUsed\": 1,\n \"sourceTestCaseId\": \"<string>\",\n \"testCaseGroupId\": \"testCaseGroup_123\",\n \"parentTestCaseId\": \"<string>\",\n \"legacyAt\": \"2023-11-07T05:31:56Z\",\n \"createdAt\": \"2023-11-07T05:31:56Z\",\n \"deletedAt\": \"2023-11-07T05:31:56Z\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.galtea.ai/testCases")
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 \"id\": \"tc_123\",\n \"testId\": \"test_123\",\n \"userId\": \"user_123\",\n \"input\": {\n \"user_message\": \"What is the capital of France?\"\n },\n \"expectedOutput\": \"Paris\",\n \"expectedTools\": [\n \"search\",\n \"calculator\"\n ],\n \"context\": {\n \"value\": \"Geography question\"\n },\n \"source\": \"manual\",\n \"sourceFile\": \"<string>\",\n \"confidence\": 0.95,\n \"confidenceReason\": \"High quality data\",\n \"variant\": \"VARIANT_1\",\n \"strategy\": \"STRATEGY_1\",\n \"languageCode\": \"es-MX\",\n \"gender\": \"FEMALE\",\n \"backgroundNoiseProfile\": \"street\",\n \"backgroundNoiseLevel\": \"medium\",\n \"userPersona\": \"Student\",\n \"scenario\": \"Educational quiz\",\n \"goal\": \"Test geographical knowledge\",\n \"archetype\": \"data_grounded\",\n \"specRelevance\": \"direct\",\n \"stoppingCriterias\": [\n \"MAX_ITERATIONS\",\n \"GOAL_ACHIEVED\"\n ],\n \"maxIterations\": 10,\n \"isAugmented\": false,\n \"reviewedById\": \"user_456\",\n \"userScore\": 5,\n \"userScoreReason\": \"Accurate and complete\",\n \"creditsUsed\": 1,\n \"sourceTestCaseId\": \"<string>\",\n \"testCaseGroupId\": \"testCaseGroup_123\",\n \"parentTestCaseId\": \"<string>\",\n \"legacyAt\": \"2023-11-07T05:31:56Z\",\n \"createdAt\": \"2023-11-07T05:31:56Z\",\n \"deletedAt\": \"2023-11-07T05:31:56Z\"\n}"
response = http.request(request)
puts response.read_body{
"id": "tc_123",
"testId": "test_123",
"userId": "user_123",
"input": {
"user_message": "What is the capital of France?"
},
"expectedOutput": "Paris",
"expectedTools": [
"search",
"calculator"
],
"context": {
"value": "Geography question"
},
"source": "manual",
"sourceFile": "<string>",
"confidence": 0.95,
"confidenceReason": "High quality data",
"variant": "VARIANT_1",
"strategy": "STRATEGY_1",
"languageCode": "es-MX",
"gender": "FEMALE",
"backgroundNoiseProfile": "street",
"backgroundNoiseLevel": "medium",
"userPersona": "Student",
"scenario": "Educational quiz",
"goal": "Test geographical knowledge",
"archetype": "data_grounded",
"specRelevance": "direct",
"stoppingCriterias": [
"MAX_ITERATIONS",
"GOAL_ACHIEVED"
],
"maxIterations": 10,
"isAugmented": false,
"reviewedById": "user_456",
"userScore": 5,
"userScoreReason": "Accurate and complete",
"creditsUsed": 1,
"sourceTestCaseId": "<string>",
"testCaseGroupId": "testCaseGroup_123",
"parentTestCaseId": "<string>",
"legacyAt": "2023-11-07T05:31:56Z",
"createdAt": "2023-11-07T05:31:56Z",
"deletedAt": "2023-11-07T05:31:56Z"
}{
"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-....
Body
application/json
Example:
"tc_123"
Example:
"test_123"
Example:
"user_123"
Structured input data. For plain text input, format is { user_message: "..." }
Example:
{
"user_message": "What is the capital of France?"
}
Example:
"Paris"
Example:
["search", "calculator"]
Structured context data. For plain text context, format is { value: "..." }
Example:
{ "value": "Geography question" }
Example:
"manual"
Example:
0.95
Example:
"High quality data"
Example:
"VARIANT_1"
Example:
"STRATEGY_1"
BCP-47 language tag (e.g. en, es-MX). The region subtag selects the regional variety in simulated user messages and voice synthesis; generated test text keeps the base language. The value is stored as the full tag.
Example:
"es-MX"
Persona-derived gender ("MALE"/"FEMALE") for the male/female synthesized caller voice in phone (voice) evaluations. Stored only for now (not consumed yet). Ignored by text evaluations.
Available options:
MALE, FEMALE Example:
"FEMALE"
Background noise mixed into the simulated caller audio during a voice test. Clip-backed (office, street, car) or synthetic (white, pink). Null means off; set together with backgroundNoiseLevel.
Available options:
office, street, car, white, pink Example:
"street"
How loud the background noise is relative to the caller speech. Null means off; set together with backgroundNoiseProfile.
Available options:
light, medium, heavy Example:
"medium"
Example:
"Student"
Example:
"Educational quiz"
Example:
"Test geographical knowledge"
Example:
"data_grounded"
Example:
"direct"
Example:
["MAX_ITERATIONS", "GOAL_ACHIEVED"]
Example:
10
Example:
false
Example:
"user_456"
Example:
5
Example:
"Accurate and complete"
Example:
1
Revision family key shared by every revision of this test case.
Example:
"testCaseGroup_123"
The revision this row was forked from; null for a family root.
Set when this revision was superseded by a newer one; null for the active head.
Response
Test case created successfully
Example:
"tc_123"
Example:
"test_123"
Example:
"user_123"
Structured input data. For plain text input, format is { user_message: "..." }
Example:
{
"user_message": "What is the capital of France?"
}
Example:
"Paris"
Example:
["search", "calculator"]
Structured context data. For plain text context, format is { value: "..." }
Example:
{ "value": "Geography question" }
Example:
"manual"
Example:
0.95
Example:
"High quality data"
Example:
"VARIANT_1"
Example:
"STRATEGY_1"
BCP-47 language tag (e.g. en, es-MX). The region subtag selects the regional variety in simulated user messages and voice synthesis; generated test text keeps the base language. The value is stored as the full tag.
Example:
"es-MX"
Persona-derived gender ("MALE"/"FEMALE") for the male/female synthesized caller voice in phone (voice) evaluations. Stored only for now (not consumed yet). Ignored by text evaluations.
Available options:
MALE, FEMALE Example:
"FEMALE"
Background noise mixed into the simulated caller audio during a voice test. Clip-backed (office, street, car) or synthetic (white, pink). Null means off; set together with backgroundNoiseLevel.
Available options:
office, street, car, white, pink Example:
"street"
How loud the background noise is relative to the caller speech. Null means off; set together with backgroundNoiseProfile.
Available options:
light, medium, heavy Example:
"medium"
Example:
"Student"
Example:
"Educational quiz"
Example:
"Test geographical knowledge"
Example:
"data_grounded"
Example:
"direct"
Example:
["MAX_ITERATIONS", "GOAL_ACHIEVED"]
Example:
10
Example:
false
Example:
"user_456"
Example:
5
Example:
"Accurate and complete"
Example:
1
Revision family key shared by every revision of this test case.
Example:
"testCaseGroup_123"
The revision this row was forked from; null for a family root.
Set when this revision was superseded by a newer one; null for the active head.