curl --request POST \
--url https://api.apimart.ai/api/v1/chat/completions \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-5", # Can be replaced with any supported model ID
"stream": false,
"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/api/v1/chat/completions"
payload = {
"model": "gpt-5", # Can be replaced with any supported model ID
"stream": False,
"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/api/v1/chat/completions";
const payload = {
model: "gpt-5", // Can be replaced with any supported model ID
stream: false,
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/api/v1/chat/completions"
payload := map[string]interface{}{
"model": "gpt-5", // Can be replaced with any supported model ID
"stream": false,
"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/api/v1/chat/completions";
// Can be replaced with any supported model ID
String payload = """
{
"model": "gpt-5",
"stream": false,
"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/api/v1/chat/completions";
// Can be replaced with any supported model ID
$payload = [
"model" => "gpt-5",
"stream" => false,
"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/api/v1/chat/completions")
# Can be replaced with any supported model ID
payload = {
model: "gpt-5",
stream: false,
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/api/v1/chat/completions")!
let payload: [String: Any] = [
"model": "gpt-5", // Can be replaced with any supported model ID
"stream": false,
"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/api/v1/chat/completions";
// Can be replaced with any supported model ID
var payload = @"{
""model"": ""gpt-5"",
""stream"": false,
""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/api/v1/chat/completions";
// Can be replaced with any supported model ID
const char *payload = "{"
"\"model\":\"gpt-5\","
"\"stream\":false,"
"\"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/api/v1/chat/completions"];
NSDictionary *payload = @{
@"model": @"gpt-5", // Can be replaced with any supported model ID
@"stream": @NO,
@"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/api/v1/chat/completions"
(* Can be replaced with any supported model ID *)
let payload = {|{
"model": "gpt-5",
"stream": false,
"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/api/v1/chat/completions');
// Can be replaced with any supported model ID
final payload = {
'model': 'gpt-5',
'stream': false,
'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/api/v1/chat/completions"
# Can be replaced with any supported model ID
payload <- list(
model = "gpt-5",
stream = FALSE,
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"
}
}
Serie de texto
API general de Chat (sin streaming por defecto)
- Interfaz unificada de API de chat compatible con todos los modelos de generación de texto
- Seleccione distintos modelos de IA mediante el parámetro model
- Compatible con el formato de la API OpenAI Chat Completions
- Salida sin streaming, devuelve la respuesta completa de una sola vez
POST
/
api
/
v1
/
chat
/
completions
curl --request POST \
--url https://api.apimart.ai/api/v1/chat/completions \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-5", # Can be replaced with any supported model ID
"stream": false,
"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/api/v1/chat/completions"
payload = {
"model": "gpt-5", # Can be replaced with any supported model ID
"stream": False,
"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/api/v1/chat/completions";
const payload = {
model: "gpt-5", // Can be replaced with any supported model ID
stream: false,
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/api/v1/chat/completions"
payload := map[string]interface{}{
"model": "gpt-5", // Can be replaced with any supported model ID
"stream": false,
"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/api/v1/chat/completions";
// Can be replaced with any supported model ID
String payload = """
{
"model": "gpt-5",
"stream": false,
"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/api/v1/chat/completions";
// Can be replaced with any supported model ID
$payload = [
"model" => "gpt-5",
"stream" => false,
"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/api/v1/chat/completions")
# Can be replaced with any supported model ID
payload = {
model: "gpt-5",
stream: false,
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/api/v1/chat/completions")!
let payload: [String: Any] = [
"model": "gpt-5", // Can be replaced with any supported model ID
"stream": false,
"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/api/v1/chat/completions";
// Can be replaced with any supported model ID
var payload = @"{
""model"": ""gpt-5"",
""stream"": false,
""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/api/v1/chat/completions";
// Can be replaced with any supported model ID
const char *payload = "{"
"\"model\":\"gpt-5\","
"\"stream\":false,"
"\"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/api/v1/chat/completions"];
NSDictionary *payload = @{
@"model": @"gpt-5", // Can be replaced with any supported model ID
@"stream": @NO,
@"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/api/v1/chat/completions"
(* Can be replaced with any supported model ID *)
let payload = {|{
"model": "gpt-5",
"stream": false,
"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/api/v1/chat/completions');
// Can be replaced with any supported model ID
final payload = {
'model': 'gpt-5',
'stream': false,
'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/api/v1/chat/completions"
# Can be replaced with any supported model ID
payload <- list(
model = "gpt-5",
stream = FALSE,
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/api/v1/chat/completions \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-5", # Can be replaced with any supported model ID
"stream": false,
"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/api/v1/chat/completions"
payload = {
"model": "gpt-5", # Can be replaced with any supported model ID
"stream": False,
"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/api/v1/chat/completions";
const payload = {
model: "gpt-5", // Can be replaced with any supported model ID
stream: false,
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/api/v1/chat/completions"
payload := map[string]interface{}{
"model": "gpt-5", // Can be replaced with any supported model ID
"stream": false,
"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/api/v1/chat/completions";
// Can be replaced with any supported model ID
String payload = """
{
"model": "gpt-5",
"stream": false,
"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/api/v1/chat/completions";
// Can be replaced with any supported model ID
$payload = [
"model" => "gpt-5",
"stream" => false,
"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/api/v1/chat/completions")
# Can be replaced with any supported model ID
payload = {
model: "gpt-5",
stream: false,
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/api/v1/chat/completions")!
let payload: [String: Any] = [
"model": "gpt-5", // Can be replaced with any supported model ID
"stream": false,
"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/api/v1/chat/completions";
// Can be replaced with any supported model ID
var payload = @"{
""model"": ""gpt-5"",
""stream"": false,
""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/api/v1/chat/completions";
// Can be replaced with any supported model ID
const char *payload = "{"
"\"model\":\"gpt-5\","
"\"stream\":false,"
"\"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/api/v1/chat/completions"];
NSDictionary *payload = @{
@"model": @"gpt-5", // Can be replaced with any supported model ID
@"stream": @NO,
@"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/api/v1/chat/completions"
(* Can be replaced with any supported model ID *)
let payload = {|{
"model": "gpt-5",
"stream": false,
"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/api/v1/chat/completions');
// Can be replaced with any supported model ID
final payload = {
'model': 'gpt-5',
'stream': false,
'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/api/v1/chat/completions"
# Can be replaced with any supported model ID
payload <- list(
model = "gpt-5",
stream = FALSE,
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
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
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…
Lista de mensajes de la conversaciónArray de mensajes. Cada mensaje contiene los campos
Ejemplo:Uso avanzado:Agregar un prompt del sistema (para definir el comportamiento de la IA):Conversación de múltiples turnos (con contexto):Descripciones de roles:
role y content.💡 Relleno rápido (área Try it):- Haga clic en ”+ Add an item” para agregar un mensaje
- Introduzca
user(mensaje del usuario),assistant(respuesta de la IA) osystem(prompt del sistema) enrole - Introduzca lo que desea decir en
content
Mostrar Estructura del objeto mensaje
Mostrar Estructura del objeto mensaje
[{"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: Mensaje del usuario (úselo la mayoría de las veces)system: Prompt del sistema para definir el comportamiento y rol de la IAassistant: Respuestas anteriores de la IA, utilizadas como contexto de la conversación
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
Número máximo de tokens a generarLos distintos modelos tienen límites máximos diferentes; consulte la documentación específica de cada modelo
Si se debe usar salida en streaming
false: Respuesta completa de una sola veztrue: Devolución en streaming
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
Penalización por frecuencia, rango -2.0 a 2.0Los valores positivos reducen la probabilidad de repetir las mismas palabrasValor por defecto: 0
Penalización por presencia, rango -2.0 a 2.0Los valores positivos aumentan la probabilidad de abordar nuevos temasValor por defecto: 0
Secuencias de paradaHasta 4 secuencias en las que la generación se detendrá al encontrarlas
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 errorRespuesta
Identificador único de la respuesta
Tipo de objeto, fijado como
chat.completionTimestamp de creación
Nombre del modelo realmente utilizado
Lista de respuestas generadas
Mostrar Propiedades
Mostrar Propiedades
Índice de la elección
Motivo de finalizaciónValores posibles:
stop- Finalización naturallength- Se alcanzó la longitud máximacontent_filter- Contenido filtradofunction_call- Llamada a función
Modelos admitidos
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
Ejemplos de uso
Conversación básica
{
"model": "gpt-5",
"stream": false,
"messages": [
{"role": "user", "content": "Hello"}
]
}
Prompt del sistema
{
"model": "claude-sonnet-4-6",
"stream": false,
"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",
"stream": false,
"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?"}
]
}
⌘I