curl --request POST \
--url https://api.apimart.ai/v1/chat/completions \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-5", # 可替换为任意支持的模型 ID
"messages": [
{
"role": "system",
"content": "你是一个专业的AI助手。"
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。"
}
]
}'
import requests
url = "https://api.apimart.ai/v1/chat/completions"
payload = {
"model": "gpt-5", # 可替换为任意支持的模型 ID
"messages": [
{
"role": "system",
"content": "你是一个专业的AI助手。"
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。"
}
]
}
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", // 可替换为任意支持的模型 ID
messages: [
{
role: "system",
content: "你是一个专业的AI助手。"
},
{
role: "user",
content: "介绍一下人工智能的发展历史。"
}
]
};
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", // 可替换为任意支持的模型 ID
"messages": []map[string]string{
{
"role": "system",
"content": "你是一个专业的AI助手。",
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。",
},
},
}
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";
// 可替换为任意支持的模型 ID
String payload = """
{
"model": "gpt-5",
"messages": [
{
"role": "system",
"content": "你是一个专业的AI助手。"
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。"
}
]
}
""";
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";
// 可替换为任意支持的模型 ID
$payload = [
"model" => "gpt-5",
"messages" => [
[
"role" => "system",
"content" => "你是一个专业的AI助手。"
],
[
"role" => "user",
"content" => "介绍一下人工智能的发展历史。"
]
]
];
$ch = curl_init($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")
# 可替换为任意支持的模型 ID
payload = {
model: "gpt-5",
messages: [
{
role: "system",
content: "你是一个专业的AI助手。"
},
{
role: "user",
content: "介绍一下人工智能的发展历史。"
}
]
}
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", // 可替换为任意支持的模型 ID
"messages": [
[
"role": "system",
"content": "你是一个专业的AI助手。"
],
[
"role": "user",
"content": "介绍一下人工智能的发展历史。"
]
]
]
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";
// 可替换为任意支持的模型 ID
var payload = @"{
""model"": ""gpt-5"",
""messages"": [
{
""role"": ""system"",
""content"": ""你是一个专业的AI助手。""
},
{
""role"": ""user"",
""content"": ""介绍一下人工智能的发展历史。""
}
]
}";
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";
// 可替换为任意支持的模型 ID
const char *payload = "{"
"\"model\":\"gpt-5\","
"\"messages\":[{\"role\":\"system\",\"content\":\"你是一个专业的AI助手。\"},{\"role\":\"user\",\"content\":\"介绍一下人工智能的发展历史。\"}]"
"}";
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"];
// 可替换为任意支持的模型 ID
NSDictionary *payload = @{
@"model": @"gpt-5",
@"messages": @[
@{
@"role": @"system",
@"content": @"你是一个专业的AI助手。"
},
@{
@"role": @"user",
@"content": @"介绍一下人工智能的发展历史。"
}
]
};
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"
(* 可替换为任意支持的模型 ID *)
let payload = {|{
"model": "gpt-5",
"messages": [
{
"role": "system",
"content": "你是一个专业的AI助手。"
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。"
}
]
}|}
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');
// 可替换为任意支持的模型 ID
final payload = {
'model': 'gpt-5',
'messages': [
{
'role': 'system',
'content': '你是一个专业的AI助手。'
},
{
'role': 'user',
'content': '介绍一下人工智能的发展历史。'
}
]
};
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"
# 可替换为任意支持的模型 ID
payload <- list(
model = "gpt-5",
messages = list(
list(
role = "system",
content = "你是一个专业的AI助手。"
),
list(
role = "user",
content = "介绍一下人工智能的发展历史。"
)
)
)
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": "人工智能(AI)的发展历史可以追溯到20世纪50年代...\n\n1. **早期阶段(1950s-1960s)**:图灵测试的提出标志着AI研究的开始...\n\n2. **专家系统时代(1970s-1980s)**:基于规则的系统开始应用于医疗诊断、金融分析等领域...\n\n3. **机器学习兴起(1990s-2000s)**:统计学习方法逐渐成为主流...\n\n4. **深度学习革命(2010s-至今)**:神经网络技术的突破带来了AI的爆发式发展..."
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 28,
"completion_tokens": 320,
"total_tokens": 348
}
}
}
{
"error": {
"code": 400,
"message": "请求参数无效",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "身份验证失败,请检查您的API密钥",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "账户余额不足,请充值后再试",
"type": "payment_required"
}
}
{
"error": {
"code": 403,
"message": "访问被禁止,您没有权限访问此资源",
"type": "permission_error"
}
}
{
"error": {
"code": 429,
"message": "请求过于频繁,请稍后再试",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "服务器内部错误,请稍后重试",
"type": "server_error"
}
}
{
"error": {
"code": 502,
"message": "网关错误,服务器暂时不可用",
"type": "bad_gateway"
}
}
文字系列
通用对话接口(默认流式)
- 统一的对话API接口,支持所有文本生成模型
- 通过 model 参数选择不同的AI模型
- 兼容 OpenAI Chat Completions API 格式
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", # 可替换为任意支持的模型 ID
"messages": [
{
"role": "system",
"content": "你是一个专业的AI助手。"
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。"
}
]
}'
import requests
url = "https://api.apimart.ai/v1/chat/completions"
payload = {
"model": "gpt-5", # 可替换为任意支持的模型 ID
"messages": [
{
"role": "system",
"content": "你是一个专业的AI助手。"
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。"
}
]
}
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", // 可替换为任意支持的模型 ID
messages: [
{
role: "system",
content: "你是一个专业的AI助手。"
},
{
role: "user",
content: "介绍一下人工智能的发展历史。"
}
]
};
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", // 可替换为任意支持的模型 ID
"messages": []map[string]string{
{
"role": "system",
"content": "你是一个专业的AI助手。",
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。",
},
},
}
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";
// 可替换为任意支持的模型 ID
String payload = """
{
"model": "gpt-5",
"messages": [
{
"role": "system",
"content": "你是一个专业的AI助手。"
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。"
}
]
}
""";
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";
// 可替换为任意支持的模型 ID
$payload = [
"model" => "gpt-5",
"messages" => [
[
"role" => "system",
"content" => "你是一个专业的AI助手。"
],
[
"role" => "user",
"content" => "介绍一下人工智能的发展历史。"
]
]
];
$ch = curl_init($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")
# 可替换为任意支持的模型 ID
payload = {
model: "gpt-5",
messages: [
{
role: "system",
content: "你是一个专业的AI助手。"
},
{
role: "user",
content: "介绍一下人工智能的发展历史。"
}
]
}
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", // 可替换为任意支持的模型 ID
"messages": [
[
"role": "system",
"content": "你是一个专业的AI助手。"
],
[
"role": "user",
"content": "介绍一下人工智能的发展历史。"
]
]
]
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";
// 可替换为任意支持的模型 ID
var payload = @"{
""model"": ""gpt-5"",
""messages"": [
{
""role"": ""system"",
""content"": ""你是一个专业的AI助手。""
},
{
""role"": ""user"",
""content"": ""介绍一下人工智能的发展历史。""
}
]
}";
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";
// 可替换为任意支持的模型 ID
const char *payload = "{"
"\"model\":\"gpt-5\","
"\"messages\":[{\"role\":\"system\",\"content\":\"你是一个专业的AI助手。\"},{\"role\":\"user\",\"content\":\"介绍一下人工智能的发展历史。\"}]"
"}";
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"];
// 可替换为任意支持的模型 ID
NSDictionary *payload = @{
@"model": @"gpt-5",
@"messages": @[
@{
@"role": @"system",
@"content": @"你是一个专业的AI助手。"
},
@{
@"role": @"user",
@"content": @"介绍一下人工智能的发展历史。"
}
]
};
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"
(* 可替换为任意支持的模型 ID *)
let payload = {|{
"model": "gpt-5",
"messages": [
{
"role": "system",
"content": "你是一个专业的AI助手。"
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。"
}
]
}|}
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');
// 可替换为任意支持的模型 ID
final payload = {
'model': 'gpt-5',
'messages': [
{
'role': 'system',
'content': '你是一个专业的AI助手。'
},
{
'role': 'user',
'content': '介绍一下人工智能的发展历史。'
}
]
};
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"
# 可替换为任意支持的模型 ID
payload <- list(
model = "gpt-5",
messages = list(
list(
role = "system",
content = "你是一个专业的AI助手。"
),
list(
role = "user",
content = "介绍一下人工智能的发展历史。"
)
)
)
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": "人工智能(AI)的发展历史可以追溯到20世纪50年代...\n\n1. **早期阶段(1950s-1960s)**:图灵测试的提出标志着AI研究的开始...\n\n2. **专家系统时代(1970s-1980s)**:基于规则的系统开始应用于医疗诊断、金融分析等领域...\n\n3. **机器学习兴起(1990s-2000s)**:统计学习方法逐渐成为主流...\n\n4. **深度学习革命(2010s-至今)**:神经网络技术的突破带来了AI的爆发式发展..."
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 28,
"completion_tokens": 320,
"total_tokens": 348
}
}
}
{
"error": {
"code": 400,
"message": "请求参数无效",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "身份验证失败,请检查您的API密钥",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "账户余额不足,请充值后再试",
"type": "payment_required"
}
}
{
"error": {
"code": 403,
"message": "访问被禁止,您没有权限访问此资源",
"type": "permission_error"
}
}
{
"error": {
"code": 429,
"message": "请求过于频繁,请稍后再试",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "服务器内部错误,请稍后重试",
"type": "server_error"
}
}
{
"error": {
"code": 502,
"message": "网关错误,服务器暂时不可用",
"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", # 可替换为任意支持的模型 ID
"messages": [
{
"role": "system",
"content": "你是一个专业的AI助手。"
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。"
}
]
}'
import requests
url = "https://api.apimart.ai/v1/chat/completions"
payload = {
"model": "gpt-5", # 可替换为任意支持的模型 ID
"messages": [
{
"role": "system",
"content": "你是一个专业的AI助手。"
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。"
}
]
}
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", // 可替换为任意支持的模型 ID
messages: [
{
role: "system",
content: "你是一个专业的AI助手。"
},
{
role: "user",
content: "介绍一下人工智能的发展历史。"
}
]
};
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", // 可替换为任意支持的模型 ID
"messages": []map[string]string{
{
"role": "system",
"content": "你是一个专业的AI助手。",
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。",
},
},
}
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";
// 可替换为任意支持的模型 ID
String payload = """
{
"model": "gpt-5",
"messages": [
{
"role": "system",
"content": "你是一个专业的AI助手。"
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。"
}
]
}
""";
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";
// 可替换为任意支持的模型 ID
$payload = [
"model" => "gpt-5",
"messages" => [
[
"role" => "system",
"content" => "你是一个专业的AI助手。"
],
[
"role" => "user",
"content" => "介绍一下人工智能的发展历史。"
]
]
];
$ch = curl_init($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")
# 可替换为任意支持的模型 ID
payload = {
model: "gpt-5",
messages: [
{
role: "system",
content: "你是一个专业的AI助手。"
},
{
role: "user",
content: "介绍一下人工智能的发展历史。"
}
]
}
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", // 可替换为任意支持的模型 ID
"messages": [
[
"role": "system",
"content": "你是一个专业的AI助手。"
],
[
"role": "user",
"content": "介绍一下人工智能的发展历史。"
]
]
]
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";
// 可替换为任意支持的模型 ID
var payload = @"{
""model"": ""gpt-5"",
""messages"": [
{
""role"": ""system"",
""content"": ""你是一个专业的AI助手。""
},
{
""role"": ""user"",
""content"": ""介绍一下人工智能的发展历史。""
}
]
}";
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";
// 可替换为任意支持的模型 ID
const char *payload = "{"
"\"model\":\"gpt-5\","
"\"messages\":[{\"role\":\"system\",\"content\":\"你是一个专业的AI助手。\"},{\"role\":\"user\",\"content\":\"介绍一下人工智能的发展历史。\"}]"
"}";
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"];
// 可替换为任意支持的模型 ID
NSDictionary *payload = @{
@"model": @"gpt-5",
@"messages": @[
@{
@"role": @"system",
@"content": @"你是一个专业的AI助手。"
},
@{
@"role": @"user",
@"content": @"介绍一下人工智能的发展历史。"
}
]
};
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"
(* 可替换为任意支持的模型 ID *)
let payload = {|{
"model": "gpt-5",
"messages": [
{
"role": "system",
"content": "你是一个专业的AI助手。"
},
{
"role": "user",
"content": "介绍一下人工智能的发展历史。"
}
]
}|}
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');
// 可替换为任意支持的模型 ID
final payload = {
'model': 'gpt-5',
'messages': [
{
'role': 'system',
'content': '你是一个专业的AI助手。'
},
{
'role': 'user',
'content': '介绍一下人工智能的发展历史。'
}
]
};
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"
# 可替换为任意支持的模型 ID
payload <- list(
model = "gpt-5",
messages = list(
list(
role = "system",
content = "你是一个专业的AI助手。"
),
list(
role = "user",
content = "介绍一下人工智能的发展历史。"
)
)
)
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": "人工智能(AI)的发展历史可以追溯到20世纪50年代...\n\n1. **早期阶段(1950s-1960s)**:图灵测试的提出标志着AI研究的开始...\n\n2. **专家系统时代(1970s-1980s)**:基于规则的系统开始应用于医疗诊断、金融分析等领域...\n\n3. **机器学习兴起(1990s-2000s)**:统计学习方法逐渐成为主流...\n\n4. **深度学习革命(2010s-至今)**:神经网络技术的突破带来了AI的爆发式发展..."
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 28,
"completion_tokens": 320,
"total_tokens": 348
}
}
}
{
"error": {
"code": 400,
"message": "请求参数无效",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "身份验证失败,请检查您的API密钥",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "账户余额不足,请充值后再试",
"type": "payment_required"
}
}
{
"error": {
"code": 403,
"message": "访问被禁止,您没有权限访问此资源",
"type": "permission_error"
}
}
{
"error": {
"code": 429,
"message": "请求过于频繁,请稍后再试",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "服务器内部错误,请稍后重试",
"type": "server_error"
}
}
{
"error": {
"code": 502,
"message": "网关错误,服务器暂时不可用",
"type": "bad_gateway"
}
}
Authorizations
所有接口均需要使用Bearer Token进行认证获取 API Key:访问 API Key 管理页面 获取您的 API Key使用时在请求头中添加:
Authorization: Bearer YOUR_API_KEY
Body
模型名称支持的模型包括:
- 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 - 更多模型持续更新中…
对话消息列表消息数组,每条消息包含
示例:进阶用法:添加系统提示词(让 AI 扮演特定角色):多轮对话(包含上下文):角色说明:
role 和 content 两个字段。💡 快速填写(Try it 区域):- 点击 ”+ Add an item” 添加一条消息
role输入:user(用户消息)、assistant(AI回复)或system(系统提示词)content输入:你想说的话
显示 详细字段说明
显示 详细字段说明
[{"role": "user", "content": "你好,请介绍一下你自己"}]
[
{"role": "system", "content": "你是专业的Python导师"},
{"role": "user", "content": "如何学习编程?"}
]
[
{"role": "user", "content": "你好"},
{"role": "assistant", "content": "你好!有什么可以帮你的?"},
{"role": "user", "content": "介绍一下人工智能"}
]
user: 用户消息(大多数情况用这个)system: 系统提示词,设置 AI 的行为和角色assistant: AI 的历史回复,用于多轮对话时提供上下文
控制输出随机性,范围 0-2
- 较低的值(如 0.2)使输出更确定
- 较高的值(如 1.8)使输出更随机
生成的最大token数量不同模型有不同的最大值限制,请参考具体模型文档
是否使用流式输出
true: 流式返回(SSE格式)false: 一次性返回完整响应
核采样参数,范围 0-1控制生成文本的多样性,建议与 temperature 二选一使用默认值:1.0
频率惩罚,范围 -2.0 到 2.0正值会降低重复使用相同词汇的可能性默认值:0
存在惩罚,范围 -2.0 到 2.0正值会增加谈论新主题的可能性默认值:0
停止序列最多4个序列,遇到这些序列时将停止生成
生成的回复数量默认值:1⚠️ 注意: 必须输入纯数字(如
1),不要加引号,否则会报错Response
响应的唯一标识符
对象类型,固定为
chat.completion创建时间戳
实际使用的模型名称
支持的模型列表
OpenAI 系列
gpt-5- GPT-5 基础模型gpt-5.1- GPT-5.1 增强版本gpt-5-chat-latest- GPT-5 最新对话版本gpt-5-mini- GPT-5 轻量级版本,性价比高
Anthropic 系列
claude-opus-4-8- Claude Opus 4.8 旗舰模型claude-opus-4-7- Claude Opus 4.7 旗舰模型claude-opus-4-6- Claude Opus 4.6 旗舰模型claude-sonnet-4-6- Claude Sonnet 4.6 平衡版本claude-opus-4-5-20251101- Claude Opus 4.5 模型
Google 系列
gemini-3.5-flash- Gemini 3.5 快速版gemini-3.1-pro-preview- Gemini 3.1 Pro 预览版gemini-3-pro-preview- Gemini 3 Pro 预览版gemini-3-pro-preview-thinking- Gemini 3 Pro 深度思考预览版gemini-3-flash-preview- Gemini 3 Flash 预览版gemini-2.5-pro- Gemini 2.5 专业版gemini-2.5-flash- Gemini 2.5 快速版gemini-2.5-flash-lite- Gemini 2.5 超轻量版
DeepSeek 系列
deepseek-v4-pro- DeepSeek V4 专业版deepseek-v4-flash- DeepSeek V4 快速版deepseek-v3.2- DeepSeek V3.2 标准版deepseek-v3.2-exp- DeepSeek V3.2 实验版deepseek-r1-250528- DeepSeek R1 推理模型deepseek-v3-0324- DeepSeek V3 标准版
使用示例
基础对话
{
"model": "gpt-5",
"messages": [
{"role": "user", "content": "你好"}
]
}
系统提示词
{
"model": "claude-sonnet-4-6",
"messages": [
{"role": "system", "content": "你是一位专业的Python编程导师"},
{"role": "user", "content": "如何使用列表推导式?"}
]
}
多轮对话
{
"model": "gemini-2.5-flash",
"messages": [
{"role": "user", "content": "什么是机器学习?"},
{"role": "assistant", "content": "机器学习是人工智能的一个分支..."},
{"role": "user", "content": "能举个例子吗?"}
]
}
流式输出
{
"model": "gpt-5",
"messages": [
{"role": "user", "content": "写一首关于春天的诗"}
],
"stream": true
}
⌘I