curl --request POST \
  --url https://{instance}.omniapp.co/api/v1/ai/eval/prompt-sets \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model_id": "880e8400-e29b-41d4-a716-446655440003",
  "name": "Orders regression",
  "slug": "orders-regression",
  "description": "Regression suite for the orders topic",
  "prompts": []
}
'

import requests

url = "https://{instance}.omniapp.co/api/v1/ai/eval/prompt-sets"

payload = {
    "model_id": "880e8400-e29b-41d4-a716-446655440003",
    "name": "Orders regression",
    "slug": "orders-regression",
    "description": "Regression suite for the orders topic",
    "prompts": []
}
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({
    model_id: '880e8400-e29b-41d4-a716-446655440003',
    name: 'Orders regression',
    slug: 'orders-regression',
    description: 'Regression suite for the orders topic',
    prompts: []
  })
};

fetch('https://{instance}.omniapp.co/api/v1/ai/eval/prompt-sets', 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://{instance}.omniapp.co/api/v1/ai/eval/prompt-sets",
  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([
    'model_id' => '880e8400-e29b-41d4-a716-446655440003',
    'name' => 'Orders regression',
    'slug' => 'orders-regression',
    'description' => 'Regression suite for the orders topic',
    'prompts' => [
        
    ]
  ]),
  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://{instance}.omniapp.co/api/v1/ai/eval/prompt-sets"

	payload := strings.NewReader("{\n  \"model_id\": \"880e8400-e29b-41d4-a716-446655440003\",\n  \"name\": \"Orders regression\",\n  \"slug\": \"orders-regression\",\n  \"description\": \"Regression suite for the orders topic\",\n  \"prompts\": []\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://{instance}.omniapp.co/api/v1/ai/eval/prompt-sets")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model_id\": \"880e8400-e29b-41d4-a716-446655440003\",\n  \"name\": \"Orders regression\",\n  \"slug\": \"orders-regression\",\n  \"description\": \"Regression suite for the orders topic\",\n  \"prompts\": []\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://{instance}.omniapp.co/api/v1/ai/eval/prompt-sets")

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  \"model_id\": \"880e8400-e29b-41d4-a716-446655440003\",\n  \"name\": \"Orders regression\",\n  \"slug\": \"orders-regression\",\n  \"description\": \"Regression suite for the orders topic\",\n  \"prompts\": []\n}"

response = http.request(request)
puts response.read_body

{
  "prompt_set": {
    "created_at": "2025-01-15T10:00:00.000Z",
    "description": "Regression suite for the orders topic",
    "id": "550e8400-e29b-41d4-a716-446655440000",
    "is_archived": false,
    "model_id": "880e8400-e29b-41d4-a716-446655440003",
    "name": "Orders regression",
    "prompts": [
      {
        "created_at": "2025-01-15T10:00:00.000Z",
        "expectation": "The top product by revenue should be Aniseed Syrup.",
        "id": "770e8400-e29b-41d4-a716-446655440002",
        "prompt_text": "What are the top 5 products by revenue?",
        "updated_at": "2025-01-15T10:00:00.000Z"
      }
    ],
    "slug": "orders-regression",
    "updated_at": "2025-01-15T10:00:00.000Z"
  }
}

{
  "detail": "Bad Request: name: Required",
  "status": 400
}

{
  "detail": "Unauthorized: Missing or invalid API key",
  "status": 401
}

{
  "detail": "AI eval requires at least Querier access on the model",
  "status": 403
}