---
title: "Live ChatGPT LLM Responses"
url: "https://docs.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/live/"
date: "2026-06-06"
---
## 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.
 POST https://api.dataforseo.com/v3/ai\_optimization/chat\_gpt/llm\_responses/live
Pricing
The cost of the task can be calculated on the [Pricing page](https://dataforseo.com/pricing/ai-optimization/llm-responses).
All POST data should be sent in the [JSON](https://en.wikipedia.org/wiki/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* **required field** the question or task you want to send to the AI model; you can specify **up to 500 characters** in the `user_prompt` field |
| `model_name` | string | *name of the AI model* **required field** `model_name`consists of the actual model name and version name; if the basic model name is specified, its latest version will be set by default; for example, if `gpt-4.1` is specified, the `gpt-4.1-2025-04-14` will be set as `model_name` automatically; you can receive the list of available LLM models by making a separate request to the `https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/models` |
| `max_output_tokens` | integer | *maximum number of tokens in the AI response* optional field minimum value for reasoning models (e.g., `reasoning` is `true` in the [Models endpoint](https://docs.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/models.md)): `1024`; minimum value for non-reasoning models: `16`; maximum value: `4096`; default value: `2048` **Note:** if `web_search` is set to `true` or the reasoning model is specified in the request, the output token count may exceed the specified `max_output_tokens` limit |
| `temperature` | float | *randomness of the AI response* optional field higher values make output more diverse; lower values make output more focused; minimum value: `0` maximum value: `2` default value: `0.94` **Note:** not supported in reasoning models |
| `top_p` | float | *diversity of the AI response* optional field controls diversity of the response by limiting token selection; minimum value: `0` maximum value: `1` default value: `0.92` **Note:** `top_p` cannot be used together with `temperature` in the same request |
| `web_search` | boolean | *enable web search* optional field when enabled, the AI model can access and cite current web information; default value: `false`; **Note:** refer to the [Models endpoint](https://docs.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/models.md) for a list of models that support `web_search`; |
| `force_web_search` | boolean | *force AI agent to use web search* optional field to enable this parameter, `web_search` must also be enabled; when enabled, the AI model is forced to access and cite current web information; default value: `false`; **Note:** even if the parameter is set to `true`, there is no guarantee web sources will be cited in the response **Note #2:** not supported in reasoning models |
| `web_search_country_iso_code` | string | *ISO country code of the location* optional field to enable this parameter, `web_search` must also be enabled; when enabled, the AI model will search the web from the country you specify; **Note:** not supported in `o3-mini`, `o1-pro`, `o1` models |
| `web_search_city` | string | *city name of the location* optional field **Note:** not supported in `o3-mini`, `o1-pro`, `o1` models |
| `system_message` | string | *instructions for the AI behaviour* optional field defines the AI's role, tone, or specific behavior you can specify **up to 500 characters** in the `system_message` field |
| `message_chain` | array | *conversation history* optional field array of message objects representing previous conversation turns; each object must contain `role` and `message` parameters: `role` string with either `user` or `ai` role; `message` string with message content (max 500 characters); you can specify **the maximum of 10 message objects** in the array; example: `"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?"}]` |
| `tag` | string | *user-defined task identifier* optional field *the character limit is 255* you can use this parameter to identify the task and match it with the result you will find the specified `tag` value in the `data` object of the response |
As a response of the API server, you will receive [JSON](https://en.wikipedia.org/wiki/JSON)-encoded data containing a `tasks` array with the information specific to the set tasks.
**Description of the fields in the results array:**
| Field name | Type | Description |
|---|---|---|
| `version` | string | *the current version of the API* |
| `status_code` | integer | *general status code* you can find the full list of the response codes [here](https://docs.dataforseo.com/v3/appendix/errors.md) **Note:** we strongly recommend designing a necessary system for handling related exceptional or error conditions |
| `status_message` | string | *general informational message* you can find the full list of general informational messages [here](https://docs.dataforseo.com/v3/appendix/errors.md) |
| `time` | string | *execution time, seconds* |
| `cost` | float | *total tasks cost, USD* |
| `tasks_count` | integer | *the number of tasks in the **`tasks`** array* |
| `tasks_error` | integer | *the number of tasks in the **`tasks`** array returned with an error* |
| **`tasks`** | array | *array of tasks* |
| `id` | string | *task identifier* **unique task identifier in our system in the [UUID](https://en.wikipedia.org/wiki/Universally_unique_identifier) format** |
| `status_code` | integer | *status code of the task* generated by DataForSEO; can be within the following range: 10000-60000 you can find the full list of the response codes [here](https://docs.dataforseo.com/v3/appendix/errors.md) |
| `status_message` | string | *informational message of the task* you can find the full list of general informational messages [here](https://docs.dataforseo.com/v3/appendix/errors.md) |
| `time` | string | *execution time, seconds* |
| `cost` | float | *cost of the task, USD* includes the base task price plus the `money_spent` value |
| `result_count` | integer | *number of elements in the `result` array* |
| `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* total count of tokens processed |
| `output_tokens` | integer | *number of tokens in the output* total count of tokens generated in the AI response |
| `reasoning_tokens` | integer | *number of reasoning tokens* total count of tokens used to generate reasoning content |
| `web_search` | boolean | *indicates if web search was used* |
| `money_spent` | float | *cost of AI tokens, USD* the price charged by the third-party AI model provider for according to its [Pricing](https://platform.openai.com/docs/pricing) |
| `datetime` | string | *date and time when the result was received* in the UTC format: “yyyy-mm-dd hh-mm-ss +00:00” example: `2019-11-15 12:57:46 +00:00` |
| **`items`** | array | *array of response items* contains structured AI response data |
| **`reasoning`** | object | *element in the response* |
| `type` | string | *type of the element = **'reasoning'*** **Note:** this element is supported only in reasoning models and is not guaranteed to be returned |
| **`sections`** | array | *reasoning chain sections* array of objects containing the reasoning chain sections generated by the LLM |
| `type` | string | *type of element*=***'summary\_text'*** |
| `text` | string | *text of the reasoning chain section* text of the reasoning chain section summarizing the model's thought process |
| **`message`** | object | *element in the response* |
| `type` | string | *type of the element = **'message'*** |
| **`sections`** | array | *array of content sections* contains different parts of the AI response |
| `type` | string | *type of element*=***'text'*** |
| `text` | string | *AI-generated text content* |
| **`annotations`** | array | *array of references used to generate the response* equals `null` if the `web_search` parameter is not set to `true` **Note:** `annotations` may return empty even when `web_search` is `true`, as the AI will attempt to retrieve web information but may not find relevant results |
| `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* contains related search queries derived from the main query to provide a more comprehensive response |
> 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 ${cred}"
--header "Content-Type: application/json"
--data-raw '[
{
"system_message": "communicate as if we are in a business meeting",
"message_chain": [
{
"role": "user",
"message": "Hello, what’s up?"
},
{
"role": "ai",
"message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?"
}
],
"max_output_tokens": 200,
"temperature": 0.3,
"top_p": 0.5,
"model_name": "gpt-4.1-mini",
"web_search": true,
"web_search_country_iso_code": "FR",
"web_search_city": "Paris",
"user_prompt": "provide information on how relevant the amusement park business is in France now"
}
]'
```
```php
getHttpCode()}n";
print "Error code: {$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;
?>
```
```js
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}')
```
```csharp
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);
}
///
/// Method: POST
/// Endpoint: https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/live
///
///
public static async Task ChatGptLlmResponsesLive()
{
var postData = new List