Saltar al contenido principal
POST
/
v1
/
chat
/
completions
curl --request POST \
  --url https://api.apimart.ai/v1/chat/completions \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "gpt-5", # Can be replaced with any supported model ID
    "messages": [
      {
        "role": "system",
        "content": "You are a professional AI assistant."
      },
      {
        "role": "user",
        "content": "Tell me about the history of artificial intelligence."
      }
    ]
  }'
import requests

url = "https://api.apimart.ai/v1/chat/completions"

payload = {
    "model": "gpt-5",  # Can be replaced with any supported model ID
    "messages": [
        {
            "role": "system",
            "content": "You are a professional AI assistant."
        },
        {
            "role": "user",
            "content": "Tell me about the history of artificial intelligence."
        }
    ]
}

headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())
const url = "https://api.apimart.ai/v1/chat/completions";

const payload = {
  model: "gpt-5",  // Can be replaced with any supported model ID
  messages: [
    {
      role: "system",
      content: "You are a professional AI assistant."
    },
    {
      role: "user",
      content: "Tell me about the history of artificial intelligence."
    }
  ]
};

const headers = {
  "Authorization": "Bearer <token>",
  "Content-Type": "application/json"
};

fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(payload)
})
  .then(response => response.json())
  .then(data => console.log(data))
  .catch(error => console.error('Error:', error));
package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
)

func main() {
    url := "https://api.apimart.ai/v1/chat/completions"

    payload := map[string]interface{}{
        "model": "gpt-5",  // Can be replaced with any supported model ID
        "messages": []map[string]string{
            {
                "role":    "system",
                "content": "You are a professional AI assistant.",
            },
            {
                "role":    "user",
                "content": "Tell me about the history of artificial intelligence.",
            },
        },
    }

    jsonData, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    req.Header.Set("Authorization", "Bearer <token>")
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    body, _ := ioutil.ReadAll(resp.Body)
    fmt.Println(string(body))
}
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;

public class Main {
    public static void main(String[] args) throws Exception {
        String url = "https://api.apimart.ai/v1/chat/completions";

        // Can be replaced with any supported model ID
        String payload = """
        {
          "model": "gpt-5",
          "messages": [
            {
              "role": "system",
              "content": "You are a professional AI assistant."
            },
            {
              "role": "user",
              "content": "Tell me about the history of artificial intelligence."
            }
          ]
        }
        """;

        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(url))
            .header("Authorization", "Bearer <token>")
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(payload))
            .build();

        HttpResponse<String> response = client.send(request,
            HttpResponse.BodyHandlers.ofString());

        System.out.println(response.body());
    }
}
<?php

$url = "https://api.apimart.ai/v1/chat/completions";

// Can be replaced with any supported model ID
$payload = [
    "model" => "gpt-5",
    "messages" => [
        [
            "role" => "system",
            "content" => "You are a professional AI assistant."
        ],
        [
            "role" => "user",
            "content" => "Tell me about the history of artificial intelligence."
        ]
    ]
];

$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
]);

$response = curl_exec($ch);
curl_close($ch);

echo $response;
?>
require 'net/http'
require 'json'
require 'uri'

url = URI("https://api.apimart.ai/v1/chat/completions")

# Can be replaced with any supported model ID
payload = {
  model: "gpt-5",
  messages: [
    {
      role: "system",
      content: "You are a professional AI assistant."
    },
    {
      role: "user",
      content: "Tell me about the history of artificial intelligence."
    }
  ]
}

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 = payload.to_json

response = http.request(request)
puts response.body
import Foundation

let url = URL(string: "https://api.apimart.ai/v1/chat/completions")!

let payload: [String: Any] = [
    "model": "gpt-5",  // Can be replaced with any supported model ID
    "messages": [
        [
            "role": "system",
            "content": "You are a professional AI assistant."
        ],
        [
            "role": "user",
            "content": "Tell me about the history of artificial intelligence."
        ]
    ]
]

var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)

let task = URLSession.shared.dataTask(with: request) { data, response, error in
    if let error = error {
        print("Error: \(error)")
        return
    }

    if let data = data, let responseString = String(data: data, encoding: .utf8) {
        print(responseString)
    }
}

task.resume()
using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

class Program
{
    static async Task Main(string[] args)
    {
        var url = "https://api.apimart.ai/v1/chat/completions";

        // Can be replaced with any supported model ID
        var payload = @"{
            ""model"": ""gpt-5"",
            ""messages"": [
                {
                    ""role"": ""system"",
                    ""content"": ""You are a professional AI assistant.""
                },
                {
                    ""role"": ""user"",
                    ""content"": ""Tell me about the history of artificial intelligence.""
                }
            ]
        }";

        using var client = new HttpClient();
        client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");

        var content = new StringContent(payload, Encoding.UTF8, "application/json");
        var response = await client.PostAsync(url, content);
        var result = await response.Content.ReadAsStringAsync();

        Console.WriteLine(result);
    }
}
#include <stdio.h>
#include <curl/curl.h>

int main(void) {
    CURL *curl;
    CURLcode res;

    curl_global_init(CURL_GLOBAL_DEFAULT);
    curl = curl_easy_init();

    if(curl) {
        const char *url = "https://api.apimart.ai/v1/chat/completions";
        // Can be replaced with any supported model ID
        const char *payload = "{"
            "\"model\":\"gpt-5\","
            "\"messages\":[{\"role\":\"system\",\"content\":\"You are a professional AI assistant.\"},{\"role\":\"user\",\"content\":\"Tell me about the history of artificial intelligence.\"}]"
        "}";

        struct curl_slist *headers = NULL;
        headers = curl_slist_append(headers, "Authorization: Bearer <token>");
        headers = curl_slist_append(headers, "Content-Type: application/json");

        curl_easy_setopt(curl, CURLOPT_URL, url);
        curl_easy_setopt(curl, CURLOPT_POSTFIELDS, payload);
        curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers);

        res = curl_easy_perform(curl);

        if(res != CURLE_OK) {
            fprintf(stderr, "curl_easy_perform() failed: %s\n",
                    curl_easy_strerror(res));
        }

        curl_slist_free_all(headers);
        curl_easy_cleanup(curl);
    }

    curl_global_cleanup();
    return 0;
}
#import <Foundation/Foundation.h>

int main(int argc, const char * argv[]) {
    @autoreleasepool {
        NSURL *url = [NSURL URLWithString:@"https://api.apimart.ai/v1/chat/completions"];

        NSDictionary *payload = @{
            @"model": @"gpt-5",  // Can be replaced with any supported model ID
            @"messages": @[
                @{
                    @"role": @"system",
                    @"content": @"You are a professional AI assistant."
                },
                @{
                    @"role": @"user",
                    @"content": @"Tell me about the history of artificial intelligence."
                }
            ]
        };

        NSError *error;
        NSData *jsonData = [NSJSONSerialization dataWithJSONObject:payload
                                                          options:0
                                                            error:&error];

        NSMutableURLRequest *request = [NSMutableURLRequest requestWithURL:url];
        [request setHTTPMethod:@"POST"];
        [request setValue:@"Bearer <token>" forHTTPHeaderField:@"Authorization"];
        [request setValue:@"application/json" forHTTPHeaderField:@"Content-Type"];
        [request setHTTPBody:jsonData];

        NSURLSessionDataTask *task = [[NSURLSession sharedSession]
            dataTaskWithRequest:request
            completionHandler:^(NSData *data, NSURLResponse *response, NSError *error) {
                if (error) {
                    NSLog(@"Error: %@", error);
                    return;
                }
                NSString *result = [[NSString alloc] initWithData:data
                                                        encoding:NSUTF8StringEncoding];
                NSLog(@"%@", result);
            }];

        [task resume];
        [[NSRunLoop mainRunLoop] run];
    }
    return 0;
}
(* Requires cohttp and yojson libraries *)
open Lwt
open Cohttp
open Cohttp_lwt_unix

let url = "https://api.apimart.ai/v1/chat/completions"

(* Can be replaced with any supported model ID *)
let payload = {|{
  "model": "gpt-5",
  "messages": [
    {
      "role": "system",
      "content": "You are a professional AI assistant."
    },
    {
      "role": "user",
      "content": "Tell me about the history of artificial intelligence."
    }
  ]
}|}

let () =
  let headers = Header.init ()
    |> fun h -> Header.add h "Authorization" "Bearer <token>"
    |> fun h -> Header.add h "Content-Type" "application/json"
  in
  let body = Cohttp_lwt.Body.of_string payload in

  let response = Client.post ~headers ~body (Uri.of_string url) >>= fun (resp, body) ->
    body |> Cohttp_lwt.Body.to_string >|= fun body_str ->
    print_endline body_str
  in
  Lwt_main.run response
import 'dart:convert';
import 'package:http/http.dart' as http;

void main() async {
  final url = Uri.parse('https://api.apimart.ai/v1/chat/completions');

  // Can be replaced with any supported model ID
  final payload = {
    'model': 'gpt-5',
    'messages': [
      {
        'role': 'system',
        'content': 'You are a professional AI assistant.'
      },
      {
        'role': 'user',
        'content': 'Tell me about the history of artificial intelligence.'
      }
    ]
  };

  final response = await http.post(
    url,
    headers: {
      'Authorization': 'Bearer <token>',
      'Content-Type': 'application/json',
    },
    body: jsonEncode(payload),
  );

  print(response.body);
}
library(httr)
library(jsonlite)

url <- "https://api.apimart.ai/v1/chat/completions"

# Can be replaced with any supported model ID
payload <- list(
  model = "gpt-5",
  messages = list(
    list(
      role = "system",
      content = "You are a professional AI assistant."
    ),
    list(
      role = "user",
      content = "Tell me about the history of artificial intelligence."
    )
  )
)

response <- POST(
  url,
  add_headers(
    Authorization = "Bearer <token>",
    `Content-Type` = "application/json"
  ),
  body = toJSON(payload, auto_unbox = TRUE),
  encode = "raw"
)

cat(content(response, "text"))
{
  "code": 200,
  "data": {
    "id": "chatcmpl-9876543210",
    "object": "chat.completion",
    "created": 1677652288,
    "model": "gpt-5",
    "choices": [
      {
        "index": 0,
        "message": {
          "role": "assistant",
          "content": "The history of artificial intelligence (AI) dates back to the 1950s...\n\n1. **Early Period (1950s-1960s)**: The proposal of the Turing Test marked the beginning of AI research...\n\n2. **Expert Systems Era (1970s-1980s)**: Rule-based systems began to be applied in medical diagnosis, financial analysis, and other fields...\n\n3. **Rise of Machine Learning (1990s-2000s)**: Statistical learning methods gradually became mainstream...\n\n4. **Deep Learning Revolution (2010s-Present)**: Breakthroughs in neural network technology brought explosive growth to AI..."
        },
        "finish_reason": "stop"
      }
    ],
    "usage": {
      "prompt_tokens": 28,
      "completion_tokens": 320,
      "total_tokens": 348
    }
  }
}
{
  "error": {
    "code": 400,
    "message": "Invalid request parameters",
    "type": "invalid_request_error"
  }
}
{
  "error": {
    "code": 401,
    "message": "Authentication failed, please check your API key",
    "type": "authentication_error"
  }
}
{
  "error": {
    "code": 402,
    "message": "Insufficient account balance, please recharge",
    "type": "payment_required"
  }
}
{
  "error": {
    "code": 403,
    "message": "Access forbidden, you don't have permission to access this resource",
    "type": "permission_error"
  }
}
{
  "error": {
    "code": 429,
    "message": "Too many requests, please try again later",
    "type": "rate_limit_error"
  }
}
{
  "error": {
    "code": 500,
    "message": "Internal server error, please try again later",
    "type": "server_error"
  }
}
{
  "error": {
    "code": 502,
    "message": "Bad gateway, service temporarily unavailable",
    "type": "bad_gateway"
  }
}
curl --request POST \
  --url https://api.apimart.ai/v1/chat/completions \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "gpt-5", # Can be replaced with any supported model ID
    "messages": [
      {
        "role": "system",
        "content": "You are a professional AI assistant."
      },
      {
        "role": "user",
        "content": "Tell me about the history of artificial intelligence."
      }
    ]
  }'
import requests

url = "https://api.apimart.ai/v1/chat/completions"

payload = {
    "model": "gpt-5",  # Can be replaced with any supported model ID
    "messages": [
        {
            "role": "system",
            "content": "You are a professional AI assistant."
        },
        {
            "role": "user",
            "content": "Tell me about the history of artificial intelligence."
        }
    ]
}

headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())
const url = "https://api.apimart.ai/v1/chat/completions";

const payload = {
  model: "gpt-5",  // Can be replaced with any supported model ID
  messages: [
    {
      role: "system",
      content: "You are a professional AI assistant."
    },
    {
      role: "user",
      content: "Tell me about the history of artificial intelligence."
    }
  ]
};

const headers = {
  "Authorization": "Bearer <token>",
  "Content-Type": "application/json"
};

fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(payload)
})
  .then(response => response.json())
  .then(data => console.log(data))
  .catch(error => console.error('Error:', error));
package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
)

func main() {
    url := "https://api.apimart.ai/v1/chat/completions"

    payload := map[string]interface{}{
        "model": "gpt-5",  // Can be replaced with any supported model ID
        "messages": []map[string]string{
            {
                "role":    "system",
                "content": "You are a professional AI assistant.",
            },
            {
                "role":    "user",
                "content": "Tell me about the history of artificial intelligence.",
            },
        },
    }

    jsonData, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    req.Header.Set("Authorization", "Bearer <token>")
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    body, _ := ioutil.ReadAll(resp.Body)
    fmt.Println(string(body))
}
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;

public class Main {
    public static void main(String[] args) throws Exception {
        String url = "https://api.apimart.ai/v1/chat/completions";

        // Can be replaced with any supported model ID
        String payload = """
        {
          "model": "gpt-5",
          "messages": [
            {
              "role": "system",
              "content": "You are a professional AI assistant."
            },
            {
              "role": "user",
              "content": "Tell me about the history of artificial intelligence."
            }
          ]
        }
        """;

        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(url))
            .header("Authorization", "Bearer <token>")
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(payload))
            .build();

        HttpResponse<String> response = client.send(request,
            HttpResponse.BodyHandlers.ofString());

        System.out.println(response.body());
    }
}
<?php

$url = "https://api.apimart.ai/v1/chat/completions";

// Can be replaced with any supported model ID
$payload = [
    "model" => "gpt-5",
    "messages" => [
        [
            "role" => "system",
            "content" => "You are a professional AI assistant."
        ],
        [
            "role" => "user",
            "content" => "Tell me about the history of artificial intelligence."
        ]
    ]
];

$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
]);

$response = curl_exec($ch);
curl_close($ch);

echo $response;
?>
require 'net/http'
require 'json'
require 'uri'

url = URI("https://api.apimart.ai/v1/chat/completions")

# Can be replaced with any supported model ID
payload = {
  model: "gpt-5",
  messages: [
    {
      role: "system",
      content: "You are a professional AI assistant."
    },
    {
      role: "user",
      content: "Tell me about the history of artificial intelligence."
    }
  ]
}

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 = payload.to_json

response = http.request(request)
puts response.body
import Foundation

let url = URL(string: "https://api.apimart.ai/v1/chat/completions")!

let payload: [String: Any] = [
    "model": "gpt-5",  // Can be replaced with any supported model ID
    "messages": [
        [
            "role": "system",
            "content": "You are a professional AI assistant."
        ],
        [
            "role": "user",
            "content": "Tell me about the history of artificial intelligence."
        ]
    ]
]

var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)

let task = URLSession.shared.dataTask(with: request) { data, response, error in
    if let error = error {
        print("Error: \(error)")
        return
    }

    if let data = data, let responseString = String(data: data, encoding: .utf8) {
        print(responseString)
    }
}

task.resume()
using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

class Program
{
    static async Task Main(string[] args)
    {
        var url = "https://api.apimart.ai/v1/chat/completions";

        // Can be replaced with any supported model ID
        var payload = @"{
            ""model"": ""gpt-5"",
            ""messages"": [
                {
                    ""role"": ""system"",
                    ""content"": ""You are a professional AI assistant.""
                },
                {
                    ""role"": ""user"",
                    ""content"": ""Tell me about the history of artificial intelligence.""
                }
            ]
        }";

        using var client = new HttpClient();
        client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");

        var content = new StringContent(payload, Encoding.UTF8, "application/json");
        var response = await client.PostAsync(url, content);
        var result = await response.Content.ReadAsStringAsync();

        Console.WriteLine(result);
    }
}
#include <stdio.h>
#include <curl/curl.h>

int main(void) {
    CURL *curl;
    CURLcode res;

    curl_global_init(CURL_GLOBAL_DEFAULT);
    curl = curl_easy_init();

    if(curl) {
        const char *url = "https://api.apimart.ai/v1/chat/completions";
        // Can be replaced with any supported model ID
        const char *payload = "{"
            "\"model\":\"gpt-5\","
            "\"messages\":[{\"role\":\"system\",\"content\":\"You are a professional AI assistant.\"},{\"role\":\"user\",\"content\":\"Tell me about the history of artificial intelligence.\"}]"
        "}";

        struct curl_slist *headers = NULL;
        headers = curl_slist_append(headers, "Authorization: Bearer <token>");
        headers = curl_slist_append(headers, "Content-Type: application/json");

        curl_easy_setopt(curl, CURLOPT_URL, url);
        curl_easy_setopt(curl, CURLOPT_POSTFIELDS, payload);
        curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers);

        res = curl_easy_perform(curl);

        if(res != CURLE_OK) {
            fprintf(stderr, "curl_easy_perform() failed: %s\n",
                    curl_easy_strerror(res));
        }

        curl_slist_free_all(headers);
        curl_easy_cleanup(curl);
    }

    curl_global_cleanup();
    return 0;
}
#import <Foundation/Foundation.h>

int main(int argc, const char * argv[]) {
    @autoreleasepool {
        NSURL *url = [NSURL URLWithString:@"https://api.apimart.ai/v1/chat/completions"];

        NSDictionary *payload = @{
            @"model": @"gpt-5",  // Can be replaced with any supported model ID
            @"messages": @[
                @{
                    @"role": @"system",
                    @"content": @"You are a professional AI assistant."
                },
                @{
                    @"role": @"user",
                    @"content": @"Tell me about the history of artificial intelligence."
                }
            ]
        };

        NSError *error;
        NSData *jsonData = [NSJSONSerialization dataWithJSONObject:payload
                                                          options:0
                                                            error:&error];

        NSMutableURLRequest *request = [NSMutableURLRequest requestWithURL:url];
        [request setHTTPMethod:@"POST"];
        [request setValue:@"Bearer <token>" forHTTPHeaderField:@"Authorization"];
        [request setValue:@"application/json" forHTTPHeaderField:@"Content-Type"];
        [request setHTTPBody:jsonData];

        NSURLSessionDataTask *task = [[NSURLSession sharedSession]
            dataTaskWithRequest:request
            completionHandler:^(NSData *data, NSURLResponse *response, NSError *error) {
                if (error) {
                    NSLog(@"Error: %@", error);
                    return;
                }
                NSString *result = [[NSString alloc] initWithData:data
                                                        encoding:NSUTF8StringEncoding];
                NSLog(@"%@", result);
            }];

        [task resume];
        [[NSRunLoop mainRunLoop] run];
    }
    return 0;
}
(* Requires cohttp and yojson libraries *)
open Lwt
open Cohttp
open Cohttp_lwt_unix

let url = "https://api.apimart.ai/v1/chat/completions"

(* Can be replaced with any supported model ID *)
let payload = {|{
  "model": "gpt-5",
  "messages": [
    {
      "role": "system",
      "content": "You are a professional AI assistant."
    },
    {
      "role": "user",
      "content": "Tell me about the history of artificial intelligence."
    }
  ]
}|}

let () =
  let headers = Header.init ()
    |> fun h -> Header.add h "Authorization" "Bearer <token>"
    |> fun h -> Header.add h "Content-Type" "application/json"
  in
  let body = Cohttp_lwt.Body.of_string payload in

  let response = Client.post ~headers ~body (Uri.of_string url) >>= fun (resp, body) ->
    body |> Cohttp_lwt.Body.to_string >|= fun body_str ->
    print_endline body_str
  in
  Lwt_main.run response
import 'dart:convert';
import 'package:http/http.dart' as http;

void main() async {
  final url = Uri.parse('https://api.apimart.ai/v1/chat/completions');

  // Can be replaced with any supported model ID
  final payload = {
    'model': 'gpt-5',
    'messages': [
      {
        'role': 'system',
        'content': 'You are a professional AI assistant.'
      },
      {
        'role': 'user',
        'content': 'Tell me about the history of artificial intelligence.'
      }
    ]
  };

  final response = await http.post(
    url,
    headers: {
      'Authorization': 'Bearer <token>',
      'Content-Type': 'application/json',
    },
    body: jsonEncode(payload),
  );

  print(response.body);
}
library(httr)
library(jsonlite)

url <- "https://api.apimart.ai/v1/chat/completions"

# Can be replaced with any supported model ID
payload <- list(
  model = "gpt-5",
  messages = list(
    list(
      role = "system",
      content = "You are a professional AI assistant."
    ),
    list(
      role = "user",
      content = "Tell me about the history of artificial intelligence."
    )
  )
)

response <- POST(
  url,
  add_headers(
    Authorization = "Bearer <token>",
    `Content-Type` = "application/json"
  ),
  body = toJSON(payload, auto_unbox = TRUE),
  encode = "raw"
)

cat(content(response, "text"))
{
  "code": 200,
  "data": {
    "id": "chatcmpl-9876543210",
    "object": "chat.completion",
    "created": 1677652288,
    "model": "gpt-5",
    "choices": [
      {
        "index": 0,
        "message": {
          "role": "assistant",
          "content": "The history of artificial intelligence (AI) dates back to the 1950s...\n\n1. **Early Period (1950s-1960s)**: The proposal of the Turing Test marked the beginning of AI research...\n\n2. **Expert Systems Era (1970s-1980s)**: Rule-based systems began to be applied in medical diagnosis, financial analysis, and other fields...\n\n3. **Rise of Machine Learning (1990s-2000s)**: Statistical learning methods gradually became mainstream...\n\n4. **Deep Learning Revolution (2010s-Present)**: Breakthroughs in neural network technology brought explosive growth to AI..."
        },
        "finish_reason": "stop"
      }
    ],
    "usage": {
      "prompt_tokens": 28,
      "completion_tokens": 320,
      "total_tokens": 348
    }
  }
}
{
  "error": {
    "code": 400,
    "message": "Invalid request parameters",
    "type": "invalid_request_error"
  }
}
{
  "error": {
    "code": 401,
    "message": "Authentication failed, please check your API key",
    "type": "authentication_error"
  }
}
{
  "error": {
    "code": 402,
    "message": "Insufficient account balance, please recharge",
    "type": "payment_required"
  }
}
{
  "error": {
    "code": 403,
    "message": "Access forbidden, you don't have permission to access this resource",
    "type": "permission_error"
  }
}
{
  "error": {
    "code": 429,
    "message": "Too many requests, please try again later",
    "type": "rate_limit_error"
  }
}
{
  "error": {
    "code": 500,
    "message": "Internal server error, please try again later",
    "type": "server_error"
  }
}
{
  "error": {
    "code": 502,
    "message": "Bad gateway, service temporarily unavailable",
    "type": "bad_gateway"
  }
}

Autorizaciones

Authorization
string
requerido
Todos los endpoints de la API requieren autenticación mediante Bearer TokenObtenga su API Key:Visite la página de gestión de API Keys para obtener su API KeyAñádala al encabezado de la solicitud:
Authorization: Bearer YOUR_API_KEY

Body

model
string
predeterminado:"gpt-5"
requerido
Nombre del modeloLos modelos admitidos incluyen:
  • OpenAI: gpt-5, gpt-5.1, gpt-5-chat-latest, gpt-5-mini
  • Anthropic: claude-opus-4-8, claude-opus-4-7, claude-opus-4-6, claude-sonnet-4-6, claude-opus-4-5-20251101
  • Google: gemini-3.5-flash, gemini-3.1-pro-preview, gemini-3-pro-preview, gemini-3-pro-preview-thinking, gemini-3-flash-preview, gemini-2.5-pro, gemini-2.5-flash, gemini-2.5-flash-lite
  • DeepSeek: deepseek-v4-pro, deepseek-v4-flash, deepseek-v3.2, deepseek-v3.2-exp, deepseek-r1-250528, deepseek-v3-0324
  • Se incorporan continuamente más modelos…
messages
array
requerido
Lista de mensajes de la conversaciónArray de mensajes. Cada mensaje contiene los campos role y content.💡 Relleno rápido (área Try it):
  1. Haga clic en ”+ Add an item” para agregar un mensaje
  2. Introduzca user (mensaje del usuario), assistant (respuesta de la IA) o system (prompt del sistema) en role
  3. Introduzca lo que desea decir en content
Ejemplo:
[{"role": "user", "content": "Hello, please introduce yourself"}]
Uso avanzado:Agregar un prompt del sistema (para definir el comportamiento de la IA):
[
  {"role": "system", "content": "You are a professional Python tutor"},
  {"role": "user", "content": "How do I learn programming?"}
]
Conversación de múltiples turnos (con contexto):
[
  {"role": "user", "content": "Hello"},
  {"role": "assistant", "content": "Hi! How can I help you?"},
  {"role": "user", "content": "Tell me about AI"}
]
Descripciones de roles:
  • user: Mensaje del usuario (úselo la mayoría de las veces)
  • system: Prompt del sistema para definir el comportamiento y rol de la IA
  • assistant: Respuestas anteriores de la IA, utilizadas como contexto de la conversación
temperature
number
Controla la aleatoriedad de la salida, rango 0-2
  • Los valores más bajos (por ejemplo, 0.2) hacen la salida más determinística
  • Los valores más altos (por ejemplo, 1.8) hacen la salida más aleatoria
Valor por defecto: 1.0
max_tokens
integer
Número máximo de tokens a generarLos distintos modelos tienen límites máximos diferentes; consulte la documentación específica de cada modelo
stream
boolean
Si se debe usar salida en streaming
  • true: Respuesta en streaming (formato SSE)
  • false: Respuesta completa de una sola vez
Valor por defecto: true
top_p
number
Parámetro de muestreo por núcleo (nucleus sampling), rango 0-1Controla la diversidad del texto generado; se recomienda usar este parámetro o temperatureValor por defecto: 1.0
frequency_penalty
number
Penalización por frecuencia, rango -2.0 a 2.0Los valores positivos reducen la probabilidad de repetir las mismas palabrasValor por defecto: 0
presence_penalty
number
Penalización por presencia, rango -2.0 a 2.0Los valores positivos aumentan la probabilidad de abordar nuevos temasValor por defecto: 0
stop
string or array
Secuencias de paradaHasta 4 secuencias en las que la generación se detendrá al encontrarlas
n
integer
Número de completions a generarValor por defecto: 1⚠️ Nota: Debe introducir un número simple (por ejemplo, 1), sin comillas; de lo contrario, se producirá un error

Respuesta

id
string
Identificador único de la respuesta
object
string
Tipo de objeto, fijado como chat.completion
created
integer
Timestamp de creación
model
string
Nombre del modelo realmente utilizado
choices
array
Lista de respuestas generadas
usage
object
Estadísticas de uso de tokens

Modelos admitidos

OpenAI Series

  • gpt-5 - GPT-5 base model
  • gpt-5.1 - GPT-5.1 enhanced version
  • gpt-5-chat-latest - GPT-5 latest chat version
  • gpt-5-mini - GPT-5 lightweight version, cost-effective

Anthropic Series

  • claude-opus-4-8 - Claude Opus 4.8 flagship model
  • claude-opus-4-7 - Claude Opus 4.7 flagship model
  • claude-opus-4-6 - Claude Opus 4.6 flagship model
  • claude-sonnet-4-6 - Claude Sonnet 4.6 balanced version
  • claude-opus-4-5-20251101 - Claude Opus 4.5 model

Google Series

  • gemini-3.5-flash - Gemini 3.5 fast version
  • gemini-3.1-pro-preview - Gemini 3.1 Pro preview version
  • gemini-3-pro-preview - Gemini 3 Pro preview version
  • gemini-3-pro-preview-thinking - Gemini 3 Pro deep thinking preview version
  • gemini-3-flash-preview - Gemini 3 Flash preview version
  • gemini-2.5-pro - Gemini 2.5 professional version
  • gemini-2.5-flash - Gemini 2.5 fast version
  • gemini-2.5-flash-lite - Gemini 2.5 ultra-lightweight version

DeepSeek Series

  • deepseek-v4-pro - DeepSeek V4 professional version
  • deepseek-v4-flash - DeepSeek V4 fast version
  • deepseek-v3.2 - DeepSeek V3.2 standard version
  • deepseek-v3.2-exp - DeepSeek V3.2 experimental version
  • deepseek-r1-250528 - DeepSeek R1 reasoning model
  • deepseek-v3-0324 - DeepSeek V3 standard version

Ejemplos de uso

Conversación básica

{
  "model": "gpt-5",
  "messages": [
    {"role": "user", "content": "Hello"}
  ]
}

Prompt del sistema

{
  "model": "claude-sonnet-4-6",
  "messages": [
    {"role": "system", "content": "You are a professional Python programming tutor"},
    {"role": "user", "content": "How to use list comprehensions?"}
  ]
}

Conversación de múltiples turnos

{
  "model": "gemini-2.5-flash",
  "messages": [
    {"role": "user", "content": "What is machine learning?"},
    {"role": "assistant", "content": "Machine learning is a branch of artificial intelligence..."},
    {"role": "user", "content": "Can you give me an example?"}
  ]
}

Salida en streaming

{
  "model": "gpt-5",
  "messages": [
    {"role": "user", "content": "Write a poem about spring"}
  ],
  "stream": true
}