# 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/task_post" 
--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?"
      }
    ],
    "model_name": "gpt-4.1-mini",
    "user_prompt": "provide information on how relevant the amusement park business is in France now"
  }
]"

<?php

/**
 * Method: POST
 * Endpoint: https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/task_post
 * @see https://docs.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/task_post
 */

require_once __DIR__ . '/../../../../../lib/RestClient.php';
$config = require __DIR__ . '/../../../../../lib/config.php';

$client = new RestClient($config['base_url'], null, $config['login'], $config['password']);

$data = [
    [
        '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?',
            ],
        ],
        'model_name' => 'gpt-4.1-mini',
        'user_prompt' => 'provide information on how relevant the amusement park business is in France now',
    ],
];
try {
    $result = $client->post('/v3/ai_optimization/chat_gpt/llm_responses/task_post', $data);
    print_r($result);
    // do something with post result
} catch (RestClientException $e) {
    printf(
        "HTTP code: %dnError code: %dnMessage: %snTrace: %sn",
        $e->getHttpCode(),
        $e->getCode(),
        $e->getMessage(),
        $e->getTraceAsString()
    );
}
?>

const post_array = [];

post_array.push({
  "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?"
      }
    ],
    "model_name": "gpt-4.1-mini",
    "user_prompt": "provide information on how relevant the amusement park business is in France now"
});

const axios = require('axios');

axios({
  method: 'post',
  url: 'https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/task_post',
  auth: {
    username: 'login',
    password: 'password'
  },
  data: post_array,
  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/task_post
@see https://docs.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/task_post
"""

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?'
            }
        ],
        'model_name': 'gpt-4.1-mini',
        '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/task_post', 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/task_post
    /// </summary>
    /// <see href="https://docs.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/task_post"/>
    
    public static async Task ChatGPTLlmResponsesTaskPost()
    {
        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 = 1024,
            temperature = 0.3,
            top_p = 0.5,
            model_name = "gpt-4.1-mini",
            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/task_post", 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}");
    }