The cost of the task can be calculated on the Pricing page.
Live ChatGPT LLM Responses
Live ChatGPT LLM Responses endpoint allows you to retrieve structured responses from a specific ChatGPT AI model, based on the input parameters.
Live ChatGPT LLM Responses endpoint allows you to retrieve structured responses from a specific ChatGPT AI model, based on the input parameters.
The cost of the task can be calculated on the Pricing page.
All POST data should be sent in the JSON format (UTF-8 encoding). The task setting is done using the POST method. When setting a task, you should send all task parameters in the task array of the generic POST array. You can send up to 2000 API calls per minute, each Live ChatGPT LLM Responses call can contain only one task.
The number of concurrent Live tasks is currently limited to 30 per account for each platform in the LLM Responses.
Execution time for tasks set with the Live ChatGPT LLM Responses endpoint is currently up to 120 seconds.
Below you will find a detailed description of the fields you can use for setting a task.
Description of the fields for setting a task:
| Field name | Type | Description |
|---|---|---|
user_prompt | string | prompt for the AI model |
model_name | string | name of the AI model |
max_output_tokens | integer | maximum number of tokens in the AI response |
temperature | float | randomness of the AI response |
top_p | float | |
web_search | boolean | enable web search |
force_web_search | boolean | force AI agent to use web search |
web_search_country_iso_code | string | ISO country code of the location |
web_search_city | string | city name of the location |
system_message | string | instructions for the AI behaviour |
message_chain | array | conversation history |
tag | string | user-defined task identifier |
tasks array with the information specific to the set tasks.| Field name | Type | Description |
|---|---|---|
version | string | the current version of the API |
status_code | integer | general status code |
status_message | string | general informational message |
time | string | execution time, seconds |
cost | float | total tasks cost, USD |
tasks_count | integer | the number of tasks in the |
tasks_error | integer | the number of tasks in the |
tasks | array | array of tasks |
id | string | task identifier |
status_code | integer | status code of the task |
status_message | string | informational message of the task |
time | string | execution time, seconds |
cost | float | cost of the task, USD |
result_count | integer | number of elements in the |
path | array | URL path |
data | object | contains the same parameters that you specified in the POST request |
result | array | array of results |
model_name | string | name of the AI model used |
input_tokens | integer | number of tokens in the input |
output_tokens | integer | number of tokens in the output |
reasoning_tokens | integer | number of reasoning tokens |
web_search | boolean | indicates if web search was used |
money_spent | float | cost of AI tokens, USD |
datetime | string | date and time when the result was received |
items | array | array of response items |
reasoning | object | element in the response |
type | string | type of the element = 'reasoning' |
sections | array | reasoning chain sections |
type | string | type of element='summary_text' |
text | string | text of the reasoning chain section |
message | object | element in the response |
type | string | type of the element = 'message' |
sections | array | array of content sections |
type | string | type of element='text' |
text | string | AI-generated text content |
annotations | array | array of references used to generate the response |
title | string | the domain name or title of the quoted source |
url | string | URL of the quoted source |
fan_out_queries | array | array of fan-out queries |
Instead of ‘login’ and ‘password’ use your credentials from https://app.dataforseo.com/api-access
# Instead of 'login' and 'password' use your credentials from https://app.dataforseo.com/api-access
login="login"
password="password"
cred="$(printf ${login}:${password} | base64)"
curl --location --request POST "https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/live"
--header "Authorization: Basic ${cred}"
--header "Content-Type: application/json"
--data-raw '[
{
"system_message": "communicate as if we are in a business meeting",
"message_chain": [
{
"role": "user",
"message": "Hello, what’s up?"
},
{
"role": "ai",
"message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?"
}
],
"max_output_tokens": 200,
"temperature": 0.3,
"top_p": 0.5,
"model_name": "gpt-4.1-mini",
"web_search": true,
"web_search_country_iso_code": "FR",
"web_search_city": "Paris",
"user_prompt": "provide information on how relevant the amusement park business is in France now"
}
]'<?php
// You can download this file from here https://cdn.dataforseo.com/v3/examples/php/php_RestClient.zip
require('RestClient.php');
$api_url = 'https://api.dataforseo.com/';
try {
// Instead of 'login' and 'password' use your credentials from https://app.dataforseo.com/api-access
$client = new RestClient($api_url, null, 'login', 'password');
} catch (RestClientException $e) {
echo "n";
print "HTTP code: {$e->getHttpCode()}n";
print "Error code: {$e->getCode()}n";
print "Message: {$e->getMessage()}n";
print $e->getTraceAsString();
echo "n";
exit();
}
$post_array = array();
// You can set only one task at a time
$post_array[] = array(
"system_message" => "communicate as if we are in a business meeting",
"message_chain" => [
[
"role" => "user",
"message" => "Hello, what’s up?"
],
[
"role" => "ai",
"message" => "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?"
]
],
"max_output_tokens" => 200,
"temperature" => 0.3,
"top_p" => 0.5,
"model_name" => "gpt-4.1-mini",
"web_search" => true,
"web_search_country_iso_code" => "FR",
"web_search_city" => "Paris",
"user_prompt" => "provide information on how relevant the amusement park business is in France now"
);
if (count($post_array) > 0) {
try {
// POST /v3/serp/google/ai_mode/live/advanced
// in addition to 'google' and 'ai_mode' you can also set other search engine and type parameters
// the full list of possible parameters is available in documentation
$result = $client->post('/v3/ai_optimization/chat_gpt/llm_responses/live', $post_array);
print_r($result);
// do something with post result
} catch (RestClientException $e) {
echo "n";
print "HTTP code: {$e->getHttpCode()}n";
print "Error code: {$e->getCode()}n";
print "Message: {$e->getMessage()}n";
print $e->getTraceAsString();
echo "n";
}
$client = null;
?>const axios = require('axios');
axios({
method: 'post',
url: 'https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/live',
auth: {
username: 'login',
password: 'password'
},
data: [{
system_message: encodeURI("communicate as if we are in a business meeting"),
message_chain: [
{
role: "user",
message: "Hello, what’s up?"
},
{
role: "ai",
message: encodeURI("Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?")
}
],
max_output_tokens: 200,
temperature: 0.3,
top_p: 0.5,
model_name: "gpt-4.1-mini",
web_search: true,
web_search_country_iso_code: "FR",
web_search_city: "Paris",
user_prompt: encodeURI("provide information on how relevant the amusement park business is in France now")
}],
headers: {
'content-type': 'application/json'
}
}).then(function (response) {
var result = response['data']['tasks'];
// Result data
console.log(result);
}).catch(function (error) {
console.log(error);
});"""
Method: POST
Endpoint: https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/live
@see https://docs.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/live
"""
import sys
import os
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '../../../../../')))
from lib.client import RestClient
from lib.config import username, password
client = RestClient(username, password)
post_data = []
post_data.append({
'system_message': 'communicate as if we are in a business meeting',
'message_chain': [
{
'role': 'user',
'message': 'Hello, what's up?'
},
{
'role': 'ai',
'message': 'Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?'
}
],
'max_output_tokens': 200,
'web_search_country_iso_code': 'FR',
'web_search_city': 'Paris',
'model_name': 'gpt-4o',
'web_search': True,
'user_prompt': 'provide information on how relevant the amusement park business is in France now'
})
try:
response = client.post('/v3/ai_optimization/chat_gpt/llm_responses/live', post_data)
print(response)
# do something with post result
except Exception as e:
print(f'An error occurred: {e}')using System;
using System.Linq;
using System.Net.Http;
using System.Net.Http.Headers;
using System.Text;
using System.Collections.Generic;
using System.Threading.Tasks;
using Newtonsoft.Json;
namespace DataForSeoSdk;
public class AiOptimization
{
private static readonly HttpClient _httpClient;
static AiOptimization()
{
_httpClient = new HttpClient
{
BaseAddress = new Uri("https://api.dataforseo.com/")
};
_httpClient.DefaultRequestHeaders.Authorization =
new AuthenticationHeaderValue("Basic", ApiConfig.Base64Auth);
}
/// <summary>
/// Method: POST
/// Endpoint: https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/live
/// </summary>
/// <see href="https://docs.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/live"/>
public static async Task ChatGptLlmResponsesLive()
{
var postData = new List<object>();
// a simple way to set a task, the full list of possible parameters is available in documentation
postData.Add(new
{
system_message = "communicate as if we are in a business meeting",
message_chain = new object[]
{
new
{
role = "user",
message = "Hello, what's up?"
},
new
{
role = "ai",
message = "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?"
}
},
max_output_tokens = 200,
web_search_country_iso_code = "FR",
web_search_city = "Paris",
model_name = "gpt-4o",
web_search = true,
user_prompt = "provide information on how relevant the amusement park business is in France now"
});
var content = new StringContent(JsonConvert.SerializeObject(postData), Encoding.UTF8, "application/json");
using var response = await _httpClient.PostAsync("/v3/ai_optimization/chat_gpt/llm_responses/live", content);
var result = JsonConvert.DeserializeObject<dynamic>(await response.Content.ReadAsStringAsync());
// you can find the full list of the response codes here https://docs.dataforseo.com/v3/appendix/errors
if (result.status_code == 20000)
{
// do something with result
Console.WriteLine(result);
}
else
Console.WriteLine($"error. Code: {result.status_code} Message: {result.status_message}");
}The above command returns JSON structured like this:
{
"version":"0.1.20251208",
"status_code":20000,
"status_message":"Ok.",
"time":"4.7042 sec.",
"cost":0.0296424,
"tasks_count":1,
"tasks_error":0,
"tasks":[
{
"id":"12111224-1535-0612-0000-0362a4b8fdb4",
"status_code":20000,
"status_message":"Ok.",
"time":"4.6134 sec.",
"cost":0.0296424,
"result_count":1,
"path":[
"v3",
"ai_optimization",
"chat_gpt",
"llm_responses",
"live"
],
"data":{
"api":"ai_optimization",
"function":"llm_responses",
"se":"chat_gpt",
"system_message":"communicate as if we are in a business meeting",
"message_chain":[
{
"role":"user",
"message":"Hello, what's up?"
},
{
"role":"ai",
"message":"Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?"
}
],
"temperature":0.3,
"top_p":0.5,
"web_search_country_iso_code":"FR",
"web_search_city":"Paris",
"model_name":"gpt-4.1-mini",
"web_search":true,
"user_prompt":"provide information on how relevant the amusement park business is in France now"
},
"result":[
{
"model_name":"gpt-4.1-mini-2025-04-14",
"input_tokens":8174,
"output_tokens":483,
"reasoning_tokens":576,
"web_search":true,
"money_spent":0.0290424,
"datetime":"2025-12-11 12:24:51 +00:00",
"items":[
{
"type":"reasoning",
"sections":[
{
"type":"summary_text",
"text":"**Exploring a riddle**nnThis likely refers to a riddle or joke. The classic answer seems to be a cup that's closed at the top and bottom, making it essentially useless. Or, is it a trophy cup or even a cupcake? I need to think through this riddle: I have a cup with no bottom and a closed top. How can I drink from it? The punchline might simply be that you can't drink from it. Hm, I wonder if there might be other interpretations too!"
},
{
"type":"summary_text",
"text":"**Pondering a riddle’s meaning**nnI’m considering if this cup could also mean something like hiccup — closed at the top and bottom? But if there’s no bottom, anything liquid just falls out. A closed top means you can’t pour anything in. So it may not be a traditional drinking cup. Maybe it’s an acorn cup, although it has an open top. The joke could suggest inverting it, but that still leaves it open. I’m not sure how it all ties back to drinking from it!"
},
{
"type":"summary_text",
"text":"**Clarifying the riddle’s punchline**nnSo, the answer seems to be that you're meant to drink from the rim, but since there’s no bottom and the top is closed, it's impossible to do that. The correct response points to a thimble instead, which has an open bottom. The punchline is clear: You can't drink; it's a thimble. The riddle plays on the expectation of a witty response. To keep it light, I could say, You don't! That's a thimble! and add a playful tone."
}
]
},
{
"type":"message",
"sections":[
{
"type":"text",
"text":"The amusement park industry in France remains a significant and growing sector within the country's tourism and entertainment landscape. In 2024, the French amusement parks market generated approximately USD 3.25 billion in revenue and is projected to reach USD 4.27 billion by 2030, reflecting a compound annual growth rate (CAGR) of 4.4% from 2025 to 2030. ([grandviewresearch.com](https://www.grandviewresearch.com/horizon/outlook/amusement-parks-market/france?utm_source=openai))nnFrance's contribution to the European amusement parks market is notable, accounting for 26.6% of the total revenue in 2024. ([grandviewresearch.com](https://www.grandviewresearch.com/horizon/outlook/amusement-parks-market/europe?utm_source=openai)) This underscores the country's prominence in the regional market.nnMajor parks such as Disneyland Paris and Parc Astérix continue to attract millions of visitors annually. In 2023, Parc Astérix welcomed over 2.8 million visitors, making it the second most visited park in France after Disneyland Paris. ([en.wikipedia.org](https://en.wikipedia.org/wiki/Parc_Ast%C3%A9rix?utm_source=openai)) Additionally, the Compagnie des Alpes, a leading operator in the sector, reported a revenue of €525.9 million in the 2022/2023 financial year, with over 10.6 million visitors across its parks. ([compagniedesalpes.com](https://www.compagniedesalpes.com/sites/default/files/documents/2024-02/CDA_DEU_2023_EN.pdf?utm_source=openai))nnThe industry is also witnessing a trend towards immersive and personalized attractions, catering to visitors seeking unique experiences. This shift includes the development of themed areas and interactive installations that appeal to various age groups, ensuring an inclusive environment for families. ([statista.com](https://www.statista.com/outlook/amo/entertainment/amusement-parks/france?utm_source=openai))nnIn summary, the amusement park business in France is not only relevant but also experiencing growth and innovation, solidifying its position as a key component of the country's entertainment and tourism sectors. ",
"annotations":[
{
"title":"France Amusement Parks Market Size & Outlook, 2030",
"url":"https://www.grandviewresearch.com/horizon/outlook/amusement-parks-market/france?utm_source=openai"
},
{
"title":"Europe Amusement Parks Market Size & Outlook, 2030",
"url":"https://www.grandviewresearch.com/horizon/outlook/amusement-parks-market/europe?utm_source=openai"
},
{
"title":"Parc Astérix",
"url":"https://en.wikipedia.org/wiki/Parc_Ast%C3%A9rix?utm_source=openai"
},
{
"title":"2023 UNIVERSAL",
"url":"https://www.compagniedesalpes.com/sites/default/files/documents/2024-02/CDA_DEU_2023_EN.pdf?utm_source=openai"
},
{
"title":"Amusement Parks - France | Statista Market Forecast",
"url":"https://www.statista.com/outlook/amo/entertainment/amusement-parks/france?utm_source=openai"
}
]
}
]
}
],
"fan_out_queries":[
"current relevance of amusement park business in France 2024"
]
}
]
}
]
}