メインコンテンツへスキップ
POST
/
v1
/
messages
curl https://api.apimart.ai/v1/messages \
  -H "x-api-key: $API_KEY" \
  -H "anthropic-version: 2025-10-01" \
  -H "content-type: application/json" \
  -d '{
    "model": "claude-sonnet-4-6",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Hello, world"}
    ]
  }'
import anthropic

client = anthropic.Anthropic(
    api_key="YOUR_API_KEY",
    base_url="https://api.apimart.ai"
)

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello, world"}
    ]
)

print(message.content)
import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  apiKey: process.env.API_KEY,
  baseURL: 'https://api.apimart.ai'
});

const message = await client.messages.create({
  model: 'claude-sonnet-4-6',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Hello, world' }
  ]
});

console.log(message.content);
package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
    "os"
)

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

    payload := map[string]interface{}{
        "model": "claude-sonnet-4-6",
        "max_tokens": 1024,
        "messages": []map[string]string{
            {
                "role":    "user",
                "content": "Hello, world",
            },
        },
    }

    jsonData, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    req.Header.Set("x-api-key", os.Getenv("API_KEY"))
    req.Header.Set("anthropic-version", "2025-10-01")
    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/messages";
        String apiKey = System.getenv("API_KEY");

        String payload = """
        {
          "model": "claude-sonnet-4-6",
          "max_tokens": 1024,
          "messages": [
            {
              "role": "user",
              "content": "Hello, world"
            }
          ]
        }
        """;

        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(url))
            .header("x-api-key", apiKey)
            .header("anthropic-version", "2025-10-01")
            .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/messages";
$apiKey = getenv('API_KEY');

$payload = [
    "model" => "claude-sonnet-4-6",
    "max_tokens" => 1024,
    "messages" => [
        [
            "role" => "user",
            "content" => "Hello, world"
        ]
    ]
];

$ch = curl_init($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, [
    "x-api-key: " . $apiKey,
    "anthropic-version: 2025-10-01",
    "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/messages")
api_key = ENV['API_KEY']

payload = {
  model: "claude-sonnet-4-6",
  max_tokens: 1024,
  messages: [
    {
      role: "user",
      content: "Hello, world"
    }
  ]
}

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

request = Net::HTTP::Post.new(url)
request["x-api-key"] = api_key
request["anthropic-version"] = "2025-10-01"
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/messages")!
let apiKey = ProcessInfo.processInfo.environment["API_KEY"] ?? ""

let payload: [String: Any] = [
    "model": "claude-sonnet-4-6",
    "max_tokens": 1024,
    "messages": [
        [
            "role": "user",
            "content": "Hello, world"
        ]
    ]
]

var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue(apiKey, forHTTPHeaderField: "x-api-key")
request.setValue("2025-10-01", forHTTPHeaderField: "anthropic-version")
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/messages";
        var apiKey = Environment.GetEnvironmentVariable("API_KEY");

        var payload = @"{
            ""model"": ""claude-sonnet-4-6"",
            ""max_tokens"": 1024,
            ""messages"": [
                {
                    ""role"": ""user"",
                    ""content"": ""Hello, world""
                }
            ]
        }";

        using var client = new HttpClient();
        client.DefaultRequestHeaders.Add("x-api-key", apiKey);
        client.DefaultRequestHeaders.Add("anthropic-version", "2025-10-01");

        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("API_KEY");

    curl_global_init(CURL_GLOBAL_DEFAULT);
    curl = curl_easy_init();

    if(curl) {
        const char *url = "https://api.apimart.ai/v1/messages";
        const char *payload = "{"
            "\"model\":\"claude-sonnet-4-6\","
            "\"max_tokens\":1024,"
            "\"messages\":[{\"role\":\"user\",\"content\":\"Hello, world\"}]"
        "}";

        char auth_header[256];
        snprintf(auth_header, sizeof(auth_header), "x-api-key: %s", api_key);

        struct curl_slist *headers = NULL;
        headers = curl_slist_append(headers, auth_header);
        headers = curl_slist_append(headers, "anthropic-version: 2025-10-01");
        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/messages"];
        NSString *apiKey = [NSProcessInfo processInfo].environment[@"API_KEY"];
        
        NSDictionary *payload = @{
            @"model": @"claude-sonnet-4-6",
            @"max_tokens": @1024,
            @"messages": @[
                @{
                    @"role": @"user",
                    @"content": @"Hello, world"
                }
            ]
        };
        
        NSError *error;
        NSData *jsonData = [NSJSONSerialization dataWithJSONObject:payload
                                                          options:0
                                                            error:&error];
        
        NSMutableURLRequest *request = [NSMutableURLRequest requestWithURL:url];
        [request setHTTPMethod:@"POST"];
        [request setValue:apiKey forHTTPHeaderField:@"x-api-key"];
        [request setValue:@"2025-10-01" forHTTPHeaderField:@"anthropic-version"];
        [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/messages"
let api_key = Sys.getenv "API_KEY"

let payload = {|{
  "model": "claude-sonnet-4-6",
  "max_tokens": 1024,
  "messages": [
    {
      "role": "user",
      "content": "Hello, world"
    }
  ]
}|}

let () =
  let headers = Header.init ()
    |> fun h -> Header.add h "x-api-key" api_key
    |> fun h -> Header.add h "anthropic-version" "2025-10-01"
    |> 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/messages');
  final apiKey = Platform.environment['API_KEY'];
  
  final payload = {
    'model': 'claude-sonnet-4-6',
    'max_tokens': 1024,
    'messages': [
      {
        'role': 'user',
        'content': 'Hello, world'
      }
    ]
  };
  
  final response = await http.post(
    url,
    headers: {
      'x-api-key': apiKey!,
      'anthropic-version': '2025-10-01',
      'Content-Type': 'application/json',
    },
    body: jsonEncode(payload),
  );
  
  print(response.body);
}
library(httr)
library(jsonlite)

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

payload <- list(
  model = "claude-sonnet-4-6",
  max_tokens = 1024,
  messages = list(
    list(
      role = "user",
      content = "Hello, world"
    )
  )
)

response <- POST(
  url,
  add_headers(
    `x-api-key` = api_key,
    `anthropic-version` = "2025-10-01",
    `Content-Type` = "application/json"
  ),
  body = toJSON(payload, auto_unbox = TRUE),
  encode = "raw"
)

cat(content(response, "text"))
{
  "code": 200,
  "data": {
    "id": "msg_013Zva2CMHLNnXjNJJKqJ2EF",
    "type": "message",
    "role": "assistant",
    "content": [
      {
        "type": "text",
        "text": "こんにちは!私はClaudeです。お会いできて嬉しいです。"
      }
    ],
    "model": "claude-sonnet-4-6",
    "stop_reason": "end_turn",
    "stop_sequence": null,
    "usage": {
      "input_tokens": 12,
      "output_tokens": 18
    }
  }
}
{
  "type": "error",
  "error": {
    "type": "invalid_request_error",
    "message": "リクエストパラメータが無効です"
  }
}
{
  "type": "error",
  "error": {
    "type": "authentication_error",
    "message": "無効なAPIキー"
  }
}
{
  "type": "error",
  "error": {
    "type": "rate_limit_error",
    "message": "レート制限を超過しました"
  }
}
{
  "type": "error",
  "error": {
    "type": "api_error",
    "message": "サーバー内部エラー"
  }
}
curl https://api.apimart.ai/v1/messages \
  -H "x-api-key: $API_KEY" \
  -H "anthropic-version: 2025-10-01" \
  -H "content-type: application/json" \
  -d '{
    "model": "claude-sonnet-4-6",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Hello, world"}
    ]
  }'
import anthropic

client = anthropic.Anthropic(
    api_key="YOUR_API_KEY",
    base_url="https://api.apimart.ai"
)

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello, world"}
    ]
)

print(message.content)
import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  apiKey: process.env.API_KEY,
  baseURL: 'https://api.apimart.ai'
});

const message = await client.messages.create({
  model: 'claude-sonnet-4-6',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Hello, world' }
  ]
});

console.log(message.content);
package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
    "os"
)

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

    payload := map[string]interface{}{
        "model": "claude-sonnet-4-6",
        "max_tokens": 1024,
        "messages": []map[string]string{
            {
                "role":    "user",
                "content": "Hello, world",
            },
        },
    }

    jsonData, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    req.Header.Set("x-api-key", os.Getenv("API_KEY"))
    req.Header.Set("anthropic-version", "2025-10-01")
    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/messages";
        String apiKey = System.getenv("API_KEY");

        String payload = """
        {
          "model": "claude-sonnet-4-6",
          "max_tokens": 1024,
          "messages": [
            {
              "role": "user",
              "content": "Hello, world"
            }
          ]
        }
        """;

        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(url))
            .header("x-api-key", apiKey)
            .header("anthropic-version", "2025-10-01")
            .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/messages";
$apiKey = getenv('API_KEY');

$payload = [
    "model" => "claude-sonnet-4-6",
    "max_tokens" => 1024,
    "messages" => [
        [
            "role" => "user",
            "content" => "Hello, world"
        ]
    ]
];

$ch = curl_init($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, [
    "x-api-key: " . $apiKey,
    "anthropic-version: 2025-10-01",
    "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/messages")
api_key = ENV['API_KEY']

payload = {
  model: "claude-sonnet-4-6",
  max_tokens: 1024,
  messages: [
    {
      role: "user",
      content: "Hello, world"
    }
  ]
}

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

request = Net::HTTP::Post.new(url)
request["x-api-key"] = api_key
request["anthropic-version"] = "2025-10-01"
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/messages")!
let apiKey = ProcessInfo.processInfo.environment["API_KEY"] ?? ""

let payload: [String: Any] = [
    "model": "claude-sonnet-4-6",
    "max_tokens": 1024,
    "messages": [
        [
            "role": "user",
            "content": "Hello, world"
        ]
    ]
]

var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue(apiKey, forHTTPHeaderField: "x-api-key")
request.setValue("2025-10-01", forHTTPHeaderField: "anthropic-version")
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/messages";
        var apiKey = Environment.GetEnvironmentVariable("API_KEY");

        var payload = @"{
            ""model"": ""claude-sonnet-4-6"",
            ""max_tokens"": 1024,
            ""messages"": [
                {
                    ""role"": ""user"",
                    ""content"": ""Hello, world""
                }
            ]
        }";

        using var client = new HttpClient();
        client.DefaultRequestHeaders.Add("x-api-key", apiKey);
        client.DefaultRequestHeaders.Add("anthropic-version", "2025-10-01");

        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("API_KEY");

    curl_global_init(CURL_GLOBAL_DEFAULT);
    curl = curl_easy_init();

    if(curl) {
        const char *url = "https://api.apimart.ai/v1/messages";
        const char *payload = "{"
            "\"model\":\"claude-sonnet-4-6\","
            "\"max_tokens\":1024,"
            "\"messages\":[{\"role\":\"user\",\"content\":\"Hello, world\"}]"
        "}";

        char auth_header[256];
        snprintf(auth_header, sizeof(auth_header), "x-api-key: %s", api_key);

        struct curl_slist *headers = NULL;
        headers = curl_slist_append(headers, auth_header);
        headers = curl_slist_append(headers, "anthropic-version: 2025-10-01");
        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/messages"];
        NSString *apiKey = [NSProcessInfo processInfo].environment[@"API_KEY"];
        
        NSDictionary *payload = @{
            @"model": @"claude-sonnet-4-6",
            @"max_tokens": @1024,
            @"messages": @[
                @{
                    @"role": @"user",
                    @"content": @"Hello, world"
                }
            ]
        };
        
        NSError *error;
        NSData *jsonData = [NSJSONSerialization dataWithJSONObject:payload
                                                          options:0
                                                            error:&error];
        
        NSMutableURLRequest *request = [NSMutableURLRequest requestWithURL:url];
        [request setHTTPMethod:@"POST"];
        [request setValue:apiKey forHTTPHeaderField:@"x-api-key"];
        [request setValue:@"2025-10-01" forHTTPHeaderField:@"anthropic-version"];
        [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/messages"
let api_key = Sys.getenv "API_KEY"

let payload = {|{
  "model": "claude-sonnet-4-6",
  "max_tokens": 1024,
  "messages": [
    {
      "role": "user",
      "content": "Hello, world"
    }
  ]
}|}

let () =
  let headers = Header.init ()
    |> fun h -> Header.add h "x-api-key" api_key
    |> fun h -> Header.add h "anthropic-version" "2025-10-01"
    |> 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/messages');
  final apiKey = Platform.environment['API_KEY'];
  
  final payload = {
    'model': 'claude-sonnet-4-6',
    'max_tokens': 1024,
    'messages': [
      {
        'role': 'user',
        'content': 'Hello, world'
      }
    ]
  };
  
  final response = await http.post(
    url,
    headers: {
      'x-api-key': apiKey!,
      'anthropic-version': '2025-10-01',
      'Content-Type': 'application/json',
    },
    body: jsonEncode(payload),
  );
  
  print(response.body);
}
library(httr)
library(jsonlite)

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

payload <- list(
  model = "claude-sonnet-4-6",
  max_tokens = 1024,
  messages = list(
    list(
      role = "user",
      content = "Hello, world"
    )
  )
)

response <- POST(
  url,
  add_headers(
    `x-api-key` = api_key,
    `anthropic-version` = "2025-10-01",
    `Content-Type` = "application/json"
  ),
  body = toJSON(payload, auto_unbox = TRUE),
  encode = "raw"
)

cat(content(response, "text"))
{
  "code": 200,
  "data": {
    "id": "msg_013Zva2CMHLNnXjNJJKqJ2EF",
    "type": "message",
    "role": "assistant",
    "content": [
      {
        "type": "text",
        "text": "こんにちは!私はClaudeです。お会いできて嬉しいです。"
      }
    ],
    "model": "claude-sonnet-4-6",
    "stop_reason": "end_turn",
    "stop_sequence": null,
    "usage": {
      "input_tokens": 12,
      "output_tokens": 18
    }
  }
}
{
  "type": "error",
  "error": {
    "type": "invalid_request_error",
    "message": "リクエストパラメータが無効です"
  }
}
{
  "type": "error",
  "error": {
    "type": "authentication_error",
    "message": "無効なAPIキー"
  }
}
{
  "type": "error",
  "error": {
    "type": "rate_limit_error",
    "message": "レート制限を超過しました"
  }
}
{
  "type": "error",
  "error": {
    "type": "api_error",
    "message": "サーバー内部エラー"
  }
}

認証

x-api-key
string
必須
認証用APIキーAPIキー管理ページにアクセスしてAPIキーを取得してくださいリクエストヘッダーに追加:
x-api-key: YOUR_API_KEY
anthropic-version
string
必須
APIバージョン使用するClaude APIバージョンを指定します例:2025-10-01

リクエストボディ

model
string
デフォルト:"claude-sonnet-4-6"
必須
Model name
  • claude-opus-4-8 - Claude Opus 4.8 flagship model
  • claude-opus-4-7 - Claude Opus 4.7 flagship model
  • claude-opus-4-6 - Claude Opus 4.6 flagship model
  • claude-sonnet-4-6 - Claude Sonnet 4.6 balanced version
  • claude-opus-4-5-20251101 - Claude Opus 4.5 model
messages
array
必須
メッセージのリストモデルが次のレスポンスを生成するためのメッセージの配列。各メッセージには rolecontent の2つのフィールドが含まれます。💡 クイック入力(Try itエリア):
  1. ”+ Add an item” をクリックしてメッセージを追加
  2. role に入力:user(ユーザーメッセージ)または assistant(AI応答、複数ターン会話用)
  3. content に入力:話したい内容
単一のユーザーメッセージ:
[{"role": "user", "content": "こんにちは、Claude"}]
複数ターンの会話:
[
  {"role": "user", "content": "こんにちは。"},
  {"role": "assistant", "content": "こんにちは、私はClaudeです。どのようにお手伝いできますか?"},
  {"role": "user", "content": "LLMを分かりやすく説明していただけますか?"}
]
事前入力されたアシスタント応答:
[
  {"role": "user", "content": "太陽のギリシャ語名は? (A) Sol (B) Helios (C) Sun"},
  {"role": "assistant", "content": "正解は("}
]
max_tokens
integer
生成する最大トークン数停止前に生成する最大トークン数。モデルはこの制限に達する前に停止する可能性があります。モデルによって最大値が異なります。最小値:1
system
string | array
システムプロンプトシステムプロンプトはClaudeの役割、性格、目標、指示を設定します。文字列形式:
{
  "system": "あなたはプロフェッショナルなPythonプログラミング講師です"
}
構造化形式:
{
  "system": [
    {
      "type": "text",
      "text": "あなたはプロフェッショナルなPythonプログラミング講師です"
    }
  ]
}
temperature
number
温度パラメータ、範囲は0~1出力のランダム性を制御:
  • 低い値(例:0.2):より決定的、保守的
  • 高い値(例:0.8):よりランダム、創造的
デフォルト:1.0
top_p
number
ニュークレアスサンプリングパラメータ、範囲は0~1ニュークレアスサンプリングを使用します。temperatureまたはtop_pのいずれかの使用を推奨します。デフォルト:1.0
top_k
integer
Top-Kサンプリング上位K個のオプションのみからサンプリングし、「ロングテール」の低確率応答を除去します。高度なユースケースにのみ推奨。
stream
boolean
ストリーミングを有効化trueの場合、Server-Sent Events(SSE)を使用してレスポンスをストリーミングします。デフォルト:false
stop_sequences
array
停止シーケンスモデルの生成を停止させるカスタムテキストシーケンス。最大4つのシーケンス。例:["\n\nHuman:", "\n\nAssistant:"]
metadata
object
MetadataMetadata object for the request.Includes:
  • user_id: User identifier
tools
array
Tool definitionsList of tools the model can use to complete tasks.Function tool example:
{
  "tools": [
    {
      "name": "get_weather",
      "description": "Get the current weather in a given location",
      "input_schema": {
        "type": "object",
        "properties": {
          "location": {
            "type": "string",
            "description": "The city and state, e.g. San Francisco, CA"
          },
          "unit": {
            "type": "string",
            "enum": ["celsius", "fahrenheit"],
            "description": "Temperature unit"
          }
        },
        "required": ["location"]
      }
    }
  ]
}
Supported tool types:
  • Custom function tools
  • Computer use tool (computer_20241022)
  • Text editor tool (text_editor_20241022)
  • Bash tool (bash_20241022)
tool_choice
object
Tool choice strategyControls how the model uses tools:
  • {"type": "auto"}: Auto-decide (default)
  • {"type": "any"}: Must use a tool
  • {"type": "tool", "name": "tool_name"}: Use specific tool

Response

id
string
Unique message identifierExample: "msg_013Zva2CMHLNnXjNJJKqJ2EF"
type
string
Object typeAlways "message"
role
string
RoleAlways "assistant"
content
array
Content blocks arrayContent generated by the model, as an array of content blocks.Text content:
[{"type": "text", "text": "Hello! I'm Claude."}]
Tool use:
[
  {
    "type": "tool_use",
    "id": "toolu_01A09q90qw90lq917835lq9",
    "name": "get_weather",
    "input": {"location": "San Francisco, CA", "unit": "celsius"}
  }
]
Content types:
  • text: Text content
  • tool_use: Tool invocation
model
string
Model that handled the requestExample: "claude-sonnet-4-6"
stop_reason
string
Stop reasonPossible values:
  • end_turn: Natural completion
  • max_tokens: Reached maximum tokens
  • stop_sequence: Hit stop sequence
  • tool_use: Invoked a tool
stop_sequence
string | null
Stop sequence triggeredThe stop sequence that was generated, if any; otherwise null
usage
object
Token usage statistics

Usage Examples

Basic Conversation

import anthropic

client = anthropic.Anthropic(
    api_key="YOUR_API_KEY",
    base_url="https://api.apimart.ai"
)

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Explain quantum computing basics"}
    ]
)

print(message.content[0].text)

Multi-turn Conversation

messages = [
    {"role": "user", "content": "What is machine learning?"},
    {"role": "assistant", "content": "Machine learning is a branch of AI..."},
    {"role": "user", "content": "Can you give a practical example?"}
]

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=messages
)

Using System Prompts

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    system="You are a senior Python developer expert in code review and optimization.",
    messages=[
        {"role": "user", "content": "How to optimize this code?\n\n[code]"}
    ]
)

Streaming Response

with client.messages.stream(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Write a short essay about AI"}
    ]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

Tool Use

tools = [
    {
        "name": "get_stock_price",
        "description": "Get real-time stock price",
        "input_schema": {
            "type": "object",
            "properties": {
                "ticker": {
                    "type": "string",
                    "description": "Stock ticker symbol, e.g., AAPL"
                }
            },
            "required": ["ticker"]
        }
    }
]

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    tools=tools,
    messages=[
        {"role": "user", "content": "What's Tesla's stock price?"}
    ]
)

# Handle tool calls
if message.stop_reason == "tool_use":
    tool_use = next(block for block in message.content if block.type == "tool_use")
    print(f"Calling tool: {tool_use.name}")
    print(f"Arguments: {tool_use.input}")

Vision Understanding

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "image",
                    "source": {
                        "type": "url",
                        "url": "https://example.com/image.jpg"
                    }
                },
                {
                    "type": "text",
                    "text": "Describe this image"
                }
            ]
        }
    ]
)

Base64 Image

import base64

with open("image.jpg", "rb") as image_file:
    image_data = base64.b64encode(image_file.read()).decode("utf-8")

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "image",
                    "source": {
                        "type": "base64",
                        "media_type": "image/jpeg",
                        "data": image_data
                    }
                },
                {
                    "type": "text",
                    "text": "Analyze this image"
                }
            ]
        }
    ]
)

Best Practices

1. Prompt Engineering

Clear role definition:
system = """You are an experienced data scientist specializing in:
- Statistical analysis and data visualization
- Machine learning model development
- Python and R programming
Provide professional, accurate advice."""
Structured output:
message = "Please return the analysis results in JSON format with summary, key_findings, and recommendations fields."

2. Error Handling

from anthropic import APIError, RateLimitError

try:
    message = client.messages.create(
        model="claude-sonnet-4-6",
        max_tokens=1024,
        messages=[{"role": "user", "content": "Hello"}]
    )
except RateLimitError:
    print("Rate limit exceeded, please retry later")
except APIError as e:
    print(f"API error: {e}")

3. Token Optimization

# Use shorter prompts
messages = [
    {"role": "user", "content": "Summarize key points:\n\n[long text]"}
]

# Limit output length
message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=500,  # Limit output
    messages=messages
)

4. Prefilling Responses

# Guide model to specific format
messages = [
    {"role": "user", "content": "List 5 Python best practices"},
    {"role": "assistant", "content": "Here are 5 Python best practices:\n\n1."}
]

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=messages
)

Streaming Response Handling

Python Streaming

import anthropic

client = anthropic.Anthropic(
    api_key="YOUR_API_KEY",
    base_url="https://api.apimart.ai"
)

with client.messages.stream(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Write a Python decorator example"}
    ]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

JavaScript Streaming

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  apiKey: process.env.API_KEY,
  baseURL: 'https://api.apimart.ai'
});

const stream = await client.messages.stream({
  model: 'claude-sonnet-4-6',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Write a React component example' }
  ]
});

for await (const chunk of stream) {
  if (chunk.type === 'content_block_delta' && 
      chunk.delta.type === 'text_delta') {
    process.stdout.write(chunk.delta.text);
  }
}

Important Notes

  1. API Key Security:
    • Store API keys in environment variables
    • Never hardcode keys in source code
    • Rotate keys regularly
  2. Rate Limiting:
    • Be aware of API rate limits
    • Implement retry mechanisms
    • Use exponential backoff
  3. Token Management:
    • Monitor token usage
    • Optimize prompt length
    • Use appropriate max_tokens values
  4. Model Selection:
    • Opus: Complex tasks, deep thinking required
    • Sonnet: Balanced performance and cost
    • Haiku: Fast response, simple tasks
  5. Content Filtering:
    • Validate user input
    • Filter sensitive information
    • Implement content moderation