curl https://api.apimart.ai/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer <token>" \
  -d '{
    "model": "gpt-5.2-pro",
    "input": [
      {
        "role": "user",
        "content": [
          {
            "type": "input_text",
            "text": "这张图片里有什么？"
          },
          {
            "type": "input_image",
            "image_url": "https://openai-documentation.vercel.app/images/cat_and_otter.png"
          }
        ]
      }
    ]
  }'

import requests
import os

url = "https://api.apimart.ai/v1/responses"

payload = {
    "model": "gpt-5.2-pro",
    "input": [
        {
            "role": "user",
            "content": [
                {
                    "type": "input_text",
                    "text": "这张图片里有什么？"
                },
                {
                    "type": "input_image",
                    "image_url": "https://openai-documentation.vercel.app/images/cat_and_otter.png"
                }
            ]
        }
    ]
}

headers = {
    "Authorization": f"Bearer {os.environ.get('OPENAI_API_KEY')}",
    "Content-Type": "application/json"
}

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

print(response.json())

const url = "https://api.apimart.ai/v1/responses";

const payload = {
  model: "gpt-5.2-pro",
  input: [
    {
      role: "user",
      content: [
        {
          type: "input_text",
          text: "这张图片里有什么？"
        },
        {
          type: "input_image",
          image_url: "https://openai-documentation.vercel.app/images/cat_and_otter.png"
        }
      ]
    }
  ]
};

const headers = {
  "Authorization": `Bearer ${process.env.OPENAI_API_KEY}`,
  "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"
    "os"
)

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

    payload := map[string]interface{}{
        "model": "gpt-5.2-pro",
        "input": []map[string]interface{}{
            {
                "role": "user",
                "content": []map[string]string{
                    {
                        "type": "input_text",
                        "text": "这张图片里有什么？",
                    },
                    {
                        "type":      "input_image",
                        "image_url": "https://openai-documentation.vercel.app/images/cat_and_otter.png",
                    },
                },
            },
        },
    }

    jsonData, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    req.Header.Set("Authorization", "Bearer "+os.Getenv("OPENAI_API_KEY"))
    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/responses";
        String apiKey = System.getenv("OPENAI_API_KEY");

        String payload = """
        {
          "model": "gpt-5.2-pro",
          "input": [
            {
              "role": "user",
              "content": [
                {
                  "type": "input_text",
                  "text": "这张图片里有什么？"
                },
                {
                  "type": "input_image",
                  "image_url": "https://openai-documentation.vercel.app/images/cat_and_otter.png"
                }
              ]
            }
          ]
        }
        """;

        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(url))
            .header("Authorization", "Bearer " + apiKey)
            .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/responses";
$apiKey = getenv('OPENAI_API_KEY');

$payload = [
    "model" => "gpt-5.2-pro",
    "input" => [
        [
            "role" => "user",
            "content" => [
                [
                    "type" => "input_text",
                    "text" => "这张图片里有什么？"
                ],
                [
                    "type" => "input_image",
                    "image_url" => "https://openai-documentation.vercel.app/images/cat_and_otter.png"
                ]
            ]
        ]
    ]
];

$ch = curl_init($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 " . $apiKey,
    "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/responses")
api_key = ENV['OPENAI_API_KEY']

payload = {
  model: "gpt-5.2-pro",
  input: [
    {
      role: "user",
      content: [
        {
          type: "input_text",
          text: "这张图片里有什么？"
        },
        {
          type: "input_image",
          image_url: "https://openai-documentation.vercel.app/images/cat_and_otter.png"
        }
      ]
    }
  ]
}

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = "Bearer #{api_key}"
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/responses")!
let apiKey = ProcessInfo.processInfo.environment["OPENAI_API_KEY"] ?? ""

let payload: [String: Any] = [
    "model": "gpt-5.2-pro",
    "input": [
        [
            "role": "user",
            "content": [
                [
                    "type": "input_text",
                    "text": "这张图片里有什么？"
                ],
                [
                    "type": "input_image",
                    "image_url": "https://openai-documentation.vercel.app/images/cat_and_otter.png"
                ]
            ]
        ]
    ]
]

var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer \(apiKey)", 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/responses";
        var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY");

        var payload = @"{
            ""model"": ""gpt-5.2-pro"",
            ""input"": [
                {
                    ""role"": ""user"",
                    ""content"": [
                        {
                            ""type"": ""input_text"",
                            ""text"": ""这张图片里有什么？""
                        },
                        {
                            ""type"": ""input_image"",
                            ""image_url"": ""https://openai-documentation.vercel.app/images/cat_and_otter.png""
                        }
                    ]
                }
            ]
        }";

        using var client = new HttpClient();
        client.DefaultRequestHeaders.Add("Authorization", $"Bearer {apiKey}");

        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>
#include <stdlib.h>

int main(void) {
    CURL *curl;
    CURLcode res;
    const char *api_key = getenv("OPENAI_API_KEY");

    curl_global_init(CURL_GLOBAL_DEFAULT);
    curl = curl_easy_init();

    if(curl) {
        const char *url = "https://api.apimart.ai/v1/responses";
        const char *payload = "{"
            "\"model\":\"gpt-5.2-pro\","
            "\"input\":[{\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"这张图片里有什么？\"},{\"type\":\"input_image\",\"image_url\":\"https://openai-documentation.vercel.app/images/cat_and_otter.png\"}]}]"
        "}";

        char auth_header[256];
        snprintf(auth_header, sizeof(auth_header), "Authorization: Bearer %s", api_key);

        struct curl_slist *headers = NULL;
        headers = curl_slist_append(headers, auth_header);
        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/responses"];
        NSString *apiKey = [NSProcessInfo processInfo].environment[@"OPENAI_API_KEY"];
        
        NSDictionary *payload = @{
            @"model": @"gpt-5.2-pro",
            @"input": @[
                @{
                    @"role": @"user",
                    @"content": @[
                        @{
                            @"type": @"input_text",
                            @"text": @"这张图片里有什么？"
                        },
                        @{
                            @"type": @"input_image",
                            @"image_url": @"https://openai-documentation.vercel.app/images/cat_and_otter.png"
                        }
                    ]
                }
            ]
        };
        
        NSError *error;
        NSData *jsonData = [NSJSONSerialization dataWithJSONObject:payload
                                                          options:0
                                                            error:&error];
        
        NSMutableURLRequest *request = [NSMutableURLRequest requestWithURL:url];
        [request setHTTPMethod:@"POST"];
        [request setValue:[NSString stringWithFormat:@"Bearer %@", apiKey] 
            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/responses"
let api_key = Sys.getenv "OPENAI_API_KEY"

let payload = {|{
  "model": "gpt-5.2-pro",
  "input": [
    {
      "role": "user",
      "content": [
        {
          "type": "input_text",
          "text": "这张图片里有什么？"
        },
        {
          "type": "input_image",
          "image_url": "https://openai-documentation.vercel.app/images/cat_and_otter.png"
        }
      ]
    }
  ]
}|}

let () =
  let headers = Header.init ()
    |> fun h -> Header.add h "Authorization" ("Bearer " ^ api_key)
    |> 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 'dart:io';
import 'package:http/http.dart' as http;

void main() async {
  final url = Uri.parse('https://api.apimart.ai/v1/responses');
  final apiKey = Platform.environment['OPENAI_API_KEY'];
  
  final payload = {
    'model': 'gpt-5.2-pro',
    'input': [
      {
        'role': 'user',
        'content': [
          {
            'type': 'input_text',
            'text': '这张图片里有什么？'
          },
          {
            'type': 'input_image',
            'image_url': 'https://openai-documentation.vercel.app/images/cat_and_otter.png'
          }
        ]
      }
    ]
  };
  
  final response = await http.post(
    url,
    headers: {
      'Authorization': 'Bearer $apiKey',
      'Content-Type': 'application/json',
    },
    body: jsonEncode(payload),
  );
  
  print(response.body);
}

library(httr)
library(jsonlite)

url <- "https://api.apimart.ai/v1/responses"
api_key <- Sys.getenv("OPENAI_API_KEY")

payload <- list(
  model = "gpt-5.2-pro",
  input = list(
    list(
      role = "user",
      content = list(
        list(
          type = "input_text",
          text = "这张图片里有什么？"
        ),
        list(
          type = "input_image",
          image_url = "https://openai-documentation.vercel.app/images/cat_and_otter.png"
        )
      )
    )
  )
)

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

cat(content(response, "text"))

{
  "code": 200,
  "data": {
    "id": "resp-9876543210",
    "object": "response",
    "created": 1677652288,
    "model": "gpt-5.2-pro",
    "choices": [
      {
        "index": 0,
        "message": {
          "role": "assistant",
          "content": "这张图片中有一只猫和一只水獭。它们看起来正在互动，场景非常可爱和温馨。猫咪和水獭似乎相处得很融洽。"
        },
        "finish_reason": "stop"
      }
    ],
    "usage": {
      "prompt_tokens": 156,
      "completion_tokens": 45,
      "total_tokens": 201
    }
  }
}

{
  "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"
  }
}