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"
}
}
Seri Teks
API Chat Umum (Streaming Bawaan)
- Antarmuka Chat API terpadu yang mendukung semua model pembuatan teks
- Pilih berbagai model AI melalui parameter model
- Kompatibel dengan format OpenAI Chat Completions API
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"
}
}
Otorisasi
Semua endpoint API memerlukan autentikasi Bearer TokenDapatkan API Key Anda:Kunjungi Halaman Manajemen API Key untuk mendapatkan API Key AndaTambahkan ke header request:
Authorization: Bearer YOUR_API_KEY
Body
Nama modelModel yang didukung meliputi:
- 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 - Model lainnya terus ditambahkan…
Daftar pesan percakapanArray pesan. Setiap pesan berisi field
Contoh:Penggunaan lanjutan:Tambahkan prompt sistem (untuk menentukan perilaku AI):Percakapan multi-giliran (dengan konteks):Deskripsi role:
role dan content.💡 Pengisian cepat (area Try it):- Klik ”+ Add an item” untuk menambahkan pesan
- Masukkan
user(pesan pengguna),assistant(respons AI), atausystem(prompt sistem) untukrole - Masukkan pesan yang ingin Anda sampaikan di
content
Tampilkan Struktur objek pesan
Tampilkan Struktur objek pesan
[{"role": "user", "content": "Hello, please introduce yourself"}]
[
{"role": "system", "content": "You are a professional Python tutor"},
{"role": "user", "content": "How do I learn programming?"}
]
[
{"role": "user", "content": "Hello"},
{"role": "assistant", "content": "Hi! How can I help you?"},
{"role": "user", "content": "Tell me about AI"}
]
user: Pesan pengguna (gunakan ini dalam sebagian besar kasus)system: Prompt sistem untuk mengatur perilaku dan role AIassistant: Respons AI sebelumnya, digunakan sebagai konteks percakapan
Mengontrol keacakan output, rentang 0-2
- Nilai yang lebih rendah (misalnya 0,2) membuat output lebih deterministik
- Nilai yang lebih tinggi (misalnya 1,8) membuat output lebih acak
Jumlah maksimum token yang akan dibuatSetiap model memiliki batas maksimum yang berbeda; lihat dokumentasi model terkait
Apakah akan menggunakan output streaming
true: Respons streaming (format SSE)false: Respons lengkap sekaligus
Parameter nucleus sampling, rentang 0-1Mengontrol keragaman teks yang dihasilkan; sebaiknya gunakan salah satu dari parameter ini atau temperatureDefault: 1.0
Penalti frekuensi, rentang -2,0 hingga 2,0Nilai positif mengurangi kemungkinan pengulangan kata yang samaDefault: 0
Penalti kehadiran, rentang -2,0 hingga 2,0Nilai positif meningkatkan kemungkinan model membahas topik baruDefault: 0
Urutan penghentiMaksimal 4 urutan; generasi akan berhenti saat urutan tersebut ditemukan
Jumlah completion yang akan dibuatDefault: 1⚠️ Catatan: Masukkan angka biasa (misalnya
1), jangan gunakan tanda kutip karena akan menyebabkan errorRespons
Pengidentifikasi unik untuk respons
Jenis objek, tetap sebagai
chat.completionTimestamp pembuatan
Nama model aktual yang digunakan
Daftar respons yang dihasilkan
Tampilkan Properti
Tampilkan Properti
Indeks pilihan
Alasan completion selesaiNilai yang mungkin:
stop- Selesai secara alamilength- Mencapai panjang maksimumcontent_filter- Konten difilterfunction_call- Pemanggilan fungsi
Model yang Didukung
OpenAI Series
gpt-5- GPT-5 base modelgpt-5.1- GPT-5.1 enhanced versiongpt-5-chat-latest- GPT-5 latest chat versiongpt-5-mini- GPT-5 lightweight version, cost-effective
Anthropic Series
claude-opus-4-8- Claude Opus 4.8 flagship modelclaude-opus-4-7- Claude Opus 4.7 flagship modelclaude-opus-4-6- Claude Opus 4.6 flagship modelclaude-sonnet-4-6- Claude Sonnet 4.6 balanced versionclaude-opus-4-5-20251101- Claude Opus 4.5 model
Google Series
gemini-3.5-flash- Gemini 3.5 fast versiongemini-3.1-pro-preview- Gemini 3.1 Pro preview versiongemini-3-pro-preview- Gemini 3 Pro preview versiongemini-3-pro-preview-thinking- Gemini 3 Pro deep thinking preview versiongemini-3-flash-preview- Gemini 3 Flash preview versiongemini-2.5-pro- Gemini 2.5 professional versiongemini-2.5-flash- Gemini 2.5 fast versiongemini-2.5-flash-lite- Gemini 2.5 ultra-lightweight version
DeepSeek Series
deepseek-v4-pro- DeepSeek V4 professional versiondeepseek-v4-flash- DeepSeek V4 fast versiondeepseek-v3.2- DeepSeek V3.2 standard versiondeepseek-v3.2-exp- DeepSeek V3.2 experimental versiondeepseek-r1-250528- DeepSeek R1 reasoning modeldeepseek-v3-0324- DeepSeek V3 standard version
Contoh Penggunaan
Percakapan Dasar
{
"model": "gpt-5",
"messages": [
{"role": "user", "content": "Hello"}
]
}
Prompt Sistem
{
"model": "claude-sonnet-4-6",
"messages": [
{"role": "system", "content": "You are a professional Python programming tutor"},
{"role": "user", "content": "How to use list comprehensions?"}
]
}
Percakapan Multi-Giliran
{
"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?"}
]
}
Output Streaming
{
"model": "gpt-5",
"messages": [
{"role": "user", "content": "Write a poem about spring"}
],
"stream": true
}
APIMart — Gateway API yang Kompatibel dengan OpenAI (GPT-5, Claude, Gemini)API Chat Umum (Non-Streaming Bawaan)
⌘I