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"
}
}
Textserie
Allgemeine Chat-API (Streaming als Standard)
- Einheitliche Chat-API-Schnittstelle mit Unterstützung für alle Textgenerierungsmodelle
- Wahl verschiedener KI-Modelle über den Parameter model
- Kompatibel mit dem Format der 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"
}
}
Autorisierung
Alle API-Endpunkte erfordern eine Bearer-Token-AuthentifizierungSo erhalten Sie Ihren API-Key:Besuchen Sie die Seite zur API-Key-Verwaltung, um Ihren API-Key zu erhaltenFügen Sie ihn dem Anfrage-Header hinzu:
Authorization: Bearer YOUR_API_KEY
Body
ModellnameUnterstützte Modelle umfassen:
- 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 - Weitere Modelle werden laufend hinzugefügt …
Liste der Nachrichten im GesprächNachrichten-Array. Jede Nachricht enthält die Felder
Beispiel:Erweiterte Nutzung:Systemanweisung hinzufügen (zur Definition des KI-Verhaltens):Mehrfach-Dialog (mit Kontext):Rollenbeschreibungen:
role und content.💡 Schnellausfüllen (Try-it-Bereich):- Klicken Sie auf „+ Add an item”, um eine Nachricht hinzuzufügen
- Geben Sie
user(Benutzernachricht),assistant(KI-Antwort) odersystem(Systemanweisung) im Feldroleein - Geben Sie im Feld
contentein, was Sie sagen möchten
Anzeigen Struktur des Nachrichtenobjekts
Anzeigen Struktur des Nachrichtenobjekts
[{"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: Benutzernachricht (in den meisten Fällen verwendet)system: Systemanweisung zur Festlegung von Verhalten und Rolle der KIassistant: Frühere Antworten der KI, verwendet für den Gesprächskontext
Steuert die Zufälligkeit der Ausgabe, Bereich 0–2
- Niedrigere Werte (z. B. 0.2) führen zu deterministischerer Ausgabe
- Höhere Werte (z. B. 1.8) führen zu zufälligerer Ausgabe
Maximale Anzahl der zu generierenden TokensVerschiedene Modelle haben unterschiedliche maximale Grenzwerte, bitte beachten Sie die jeweilige Modelldokumentation
Ob Streaming-Ausgabe verwendet werden soll
true: Streaming-Antwort (SSE-Format)false: vollständige Antwort auf einmal
Nucleus-Sampling-Parameter, Bereich 0–1Steuert die Vielfalt des generierten Texts, es wird empfohlen, entweder diesen Parameter oder temperature zu verwendenStandard: 1.0
Häufigkeitsstrafe, Bereich -2.0 bis 2.0Positive Werte verringern die Wahrscheinlichkeit, dass dieselben Wörter wiederholt werdenStandard: 0
Präsenzstrafe, Bereich -2.0 bis 2.0Positive Werte erhöhen die Wahrscheinlichkeit, dass über neue Themen gesprochen wirdStandard: 0
Stopp-SequenzenBis zu 4 Sequenzen, bei deren Auftreten die Generierung gestoppt wird
Anzahl der zu generierenden VervollständigungenStandard: 1⚠️ Hinweis: Es muss eine einfache Zahl eingegeben werden (z. B.
1), ohne Anführungszeichen, sonst tritt ein Fehler aufResponse
Eindeutiger Identifikator der Antwort
Objekttyp, fest
chat.completionZeitstempel der Erstellung
Der tatsächlich verwendete Modellname
Liste der generierten Antworten
Anzeigen Eigenschaften
Anzeigen Eigenschaften
Index der Auswahl
Grund für den AbschlussMögliche Werte:
stop– natürlicher Abschlusslength– maximale Länge erreichtcontent_filter– Inhalt gefiltertfunction_call– Funktionsaufruf
Unterstützte Modelle
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
Anwendungsbeispiele
Einfacher Dialog
{
"model": "gpt-5",
"messages": [
{"role": "user", "content": "Hello"}
]
}
Systemanweisung
{
"model": "claude-sonnet-4-6",
"messages": [
{"role": "system", "content": "You are a professional Python programming tutor"},
{"role": "user", "content": "How to use list comprehensions?"}
]
}
Mehrfach-Dialog
{
"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?"}
]
}
Streaming-Ausgabe
{
"model": "gpt-5",
"messages": [
{"role": "user", "content": "Write a poem about spring"}
],
"stream": true
}
APIMart — OpenAI-kompatibles API-Gateway (GPT-5, Claude, Gemini)Allgemeine Chat-API (Nicht-Streaming als Standard)
⌘I