> ## Documentation Index
> Fetch the complete documentation index at: https://docs.apimart.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Claude 消息接口

>  - 完全兼容 Claude Messages API 格式
- 支持多轮对话和单次查询
- 支持文本、图像等多模态内容 

<RequestExample>
  ```bash cURL theme={null}
  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": "你好，世界"}
      ]
    }'
  ```

  ```python Python theme={null}
  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": "你好，世界"}
      ]
  )

  print(message.content)
  ```

  ```javascript JavaScript theme={null}
  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: '你好，世界' }
    ]
  });

  console.log(message.content);
  ```

  ```go Go theme={null}
  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": "你好，世界",
              },
          },
      }

      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))
  }
  ```

  ```java Java theme={null}
  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": "你好，世界"
              }
            ]
          }
          """;

          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 PHP theme={null}
  <?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" => "你好，世界"
          ]
      ]
  ];

  $ch = curl_init($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;
  ?>
  ```

  ```ruby Ruby theme={null}
  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: "你好，世界"
      }
    ]
  }

  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
  ```

  ```swift Swift theme={null}
  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": "你好，世界"
          ]
      ]
  ]

  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()
  ```

  ```csharp C# theme={null}
  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"": ""你好，世界""
                  }
              ]
          }";

          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);
      }
  }
  ```

  ```c C theme={null}
  #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\":\"你好，世界\"}]"
          "}";

          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;
  }
  ```

  ```objectivec Objective-C theme={null}
  #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": @"你好，世界"
                  }
              ]
          };
          
          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;
  }
  ```

  ```ocaml OCaml theme={null}
  (* 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": "你好，世界"
      }
    ]
  }|}

  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
  ```

  ```dart Dart theme={null}
  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': '你好，世界'
        }
      ]
    };
    
    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);
  }
  ```

  ```r R theme={null}
  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 = "你好，世界"
      )
    )
  )

  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"))
  ```
</RequestExample>

<ResponseExample>
  ```json 200 theme={null}
  {
    "code": 200,
    "data": {
      "id": "msg_013Zva2CMHLNnXjNJJKqJ2EF",
      "type": "message",
      "role": "assistant",
      "content": [
        {
          "type": "text",
          "text": "你好！我是Claude。很高兴见到你。"
        }
      ],
      "model": "claude-sonnet-4-6",
      "stop_reason": "end_turn",
      "stop_sequence": null,
      "usage": {
        "input_tokens": 12,
        "output_tokens": 18
      }
    }
  }
  ```

  ```json 400 theme={null}
  {
    "type": "error",
    "error": {
      "type": "invalid_request_error",
      "message": "请求参数无效"
    }
  }
  ```

  ```json 401 theme={null}
  {
    "type": "error",
    "error": {
      "type": "authentication_error",
      "message": "无效的API密钥"
    }
  }
  ```

  ```json 429 theme={null}
  {
    "type": "error",
    "error": {
      "type": "rate_limit_error",
      "message": "请求过于频繁"
    }
  }
  ```

  ```json 500 theme={null}
  {
    "type": "error",
    "error": {
      "type": "api_error",
      "message": "服务器内部错误"
    }
  }
  ```
</ResponseExample>

## Authorizations

<ParamField header="x-api-key" type="string" required>
  API密钥用于身份验证

  访问 [API Key 管理页面](https://apimart.ai/keys) 获取您的 API Key

  在请求头中添加：

  ```
  x-api-key: YOUR_API_KEY
  ```
</ParamField>

<ParamField header="anthropic-version" type="string" required>
  API版本号

  指定要使用的Claude API版本

  示例：`2025-10-01`
</ParamField>

## Body

<ParamField body="model" type="string" required default="claude-sonnet-4-6">
  模型名称

  * `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
</ParamField>

<ParamField body="messages" type="array" required>
  消息列表

  消息数组，模型会基于这些消息生成下一条回复。每条消息包含 `role` 和 `content` 两个字段。

  **💡 快速填写（Try it 区域）：**

  1. 点击 "+ Add an item" 添加一条消息
  2. `role` 输入：`user`（用户消息）或 `assistant`（AI回复，用于多轮对话）
  3. `content` 输入：你想说的话

  <Expandable title="详细字段说明">
    <ParamField body="role" type="string" required default="user">
      角色类型

      可选值：`user`（用户消息）、`assistant`（AI回复，用于多轮对话和预填充）

      注：Claude API 的 system 提示词使用单独的 `system` 参数，不在 messages 中
    </ParamField>

    <ParamField body="content" type="string" required>
      消息内容

      填写消息的文本内容
    </ParamField>
  </Expandable>

  **单条用户消息示例：**

  ```json theme={null}
  [{"role": "user", "content": "你好，Claude"}]
  ```

  **多轮对话示例：**

  ```json theme={null}
  [
    {"role": "user", "content": "你好"},
    {"role": "assistant", "content": "你好！我是Claude。"},
    {"role": "user", "content": "能解释一下AI吗？"}
  ]
  ```

  **预填充助手回复：**

  ```json theme={null}
  [
    {"role": "user", "content": "太阳的希腊名称是？(A) Sol (B) Helios (C) Sun"},
    {"role": "assistant", "content": "答案是 ("}
  ]
  ```
</ParamField>

<ParamField body="max_tokens" type="integer">
  最大生成token数

  生成停止前的最大token数量。模型可能会在达到此限制前停止。

  不同模型有不同的最大值，请参考模型文档。最小值：1
</ParamField>

<ParamField body="system" type="string | array">
  系统提示词

  系统提示词用于设置Claude的角色、个性、目标和指令。

  **字符串格式：**

  ```json theme={null}
  {
    "system": "你是一位专业的Python编程导师"
  }
  ```

  **结构化格式：**

  ```json theme={null}
  {
    "system": [
      {
        "type": "text",
        "text": "你是一位专业的Python编程导师"
      }
    ]
  }
  ```
</ParamField>

<ParamField body="temperature" type="number">
  温度参数，范围 0-1

  控制输出的随机性：

  * 低值（如0.2）：更确定、更保守
  * 高值（如0.8）：更随机、更有创意

  默认值：1.0
</ParamField>

<ParamField body="top_p" type="number">
  核采样参数，范围 0-1

  使用nucleus sampling。建议使用 `temperature` 或 `top_p` 其中之一，不要同时使用。

  默认值：1.0
</ParamField>

<ParamField body="top_k" type="integer">
  Top-K采样

  只从概率最高的K个选项中采样，用于移除"长尾"低概率响应。

  建议仅在高级用例中使用。
</ParamField>

<ParamField body="stream" type="boolean">
  是否启用流式输出

  设置为 `true` 时，使用服务器发送事件（SSE）流式返回响应。

  默认值：false
</ParamField>

<ParamField body="stop_sequences" type="array">
  停止序列

  自定义文本序列，遇到这些序列时模型将停止生成。

  最多4个序列。

  示例：`["\n\nHuman:", "\n\nAssistant:"]`
</ParamField>

<ParamField body="metadata" type="object">
  元数据

  用于请求的元数据对象。

  包含：

  * `user_id`: 用户标识符
</ParamField>

<ParamField body="tools" type="array">
  工具定义

  工具列表，模型可以调用这些工具来完成任务。

  **函数工具示例：**

  ```json theme={null}
  {
    "tools": [
      {
        "name": "get_weather",
        "description": "获取指定位置的当前天气",
        "input_schema": {
          "type": "object",
          "properties": {
            "location": {
              "type": "string",
              "description": "城市和省份，例如：北京"
            },
            "unit": {
              "type": "string",
              "enum": ["celsius", "fahrenheit"],
              "description": "温度单位"
            }
          },
          "required": ["location"]
        }
      }
    ]
  }
  ```

  支持的工具类型：

  * 自定义函数工具
  * 计算机使用工具（computer\_20241022）
  * 文本编辑器工具（text\_editor\_20241022）
  * Bash工具（bash\_20241022）
</ParamField>

<ParamField body="tool_choice" type="object">
  工具选择策略

  控制模型如何使用工具：

  * `{"type": "auto"}`: 自动决定（默认）
  * `{"type": "any"}`: 必须使用工具
  * `{"type": "tool", "name": "tool_name"}`: 使用指定工具
</ParamField>

## Response

<ResponseField name="id" type="string">
  唯一消息标识符

  示例：`"msg_013Zva2CMHLNnXjNJJKqJ2EF"`
</ResponseField>

<ResponseField name="type" type="string">
  对象类型

  固定为 `"message"`
</ResponseField>

<ResponseField name="role" type="string">
  角色

  固定为 `"assistant"`
</ResponseField>

<ResponseField name="content" type="array">
  内容块数组

  模型生成的内容，是一个内容块数组。

  **文本内容：**

  ```json theme={null}
  [{"type": "text", "text": "你好！我是Claude。"}]
  ```

  **工具使用：**

  ```json theme={null}
  [
    {
      "type": "tool_use",
      "id": "toolu_01A09q90qw90lq917835lq9",
      "name": "get_weather",
      "input": {"location": "北京", "unit": "celsius"}
    }
  ]
  ```

  内容类型：

  * `text`: 文本内容
  * `tool_use`: 工具调用
</ResponseField>

<ResponseField name="model" type="string">
  处理请求的模型

  示例：`"claude-sonnet-4-6"`
</ResponseField>

<ResponseField name="stop_reason" type="string">
  停止原因

  可能的值：

  * `end_turn`: 自然结束
  * `max_tokens`: 达到最大token数
  * `stop_sequence`: 遇到停止序列
  * `tool_use`: 调用了工具
</ResponseField>

<ResponseField name="stop_sequence" type="string | null">
  触发的停止序列

  如果因停止序列而停止，则为该序列内容；否则为 `null`
</ResponseField>

<ResponseField name="usage" type="object">
  Token使用统计

  <Expandable title="属性">
    <ResponseField name="input_tokens" type="integer">
      输入token数
    </ResponseField>

    <ResponseField name="output_tokens" type="integer">
      输出token数
    </ResponseField>
  </Expandable>
</ResponseField>

## 使用示例

### 基础对话

```python theme={null}
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": "解释量子计算的基本原理"}
    ]
)

print(message.content[0].text)
```

### 多轮对话

```python theme={null}
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": "能举个实际应用的例子吗？"}
]

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

### 使用系统提示词

```python theme={null}
message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    system="你是一位资深的Python开发专家，擅长代码审查和优化建议。",
    messages=[
        {"role": "user", "content": "如何优化这段代码？\n\n[代码]"}
    ]
)
```

### 流式响应

```python theme={null}
with client.messages.stream(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "写一篇关于AI的短文"}
    ]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)
```

### 工具使用

```python theme={null}
tools = [
    {
        "name": "get_stock_price",
        "description": "获取股票的实时价格",
        "input_schema": {
            "type": "object",
            "properties": {
                "ticker": {
                    "type": "string",
                    "description": "股票代码，例如：AAPL"
                }
            },
            "required": ["ticker"]
        }
    }
]

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    tools=tools,
    messages=[
        {"role": "user", "content": "特斯拉的股价是多少？"}
    ]
)

# 处理工具调用
if message.stop_reason == "tool_use":
    tool_use = next(block for block in message.content if block.type == "tool_use")
    print(f"调用工具: {tool_use.name}")
    print(f"参数: {tool_use.input}")
```

### 视觉理解

```python theme={null}
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": "描述这张图片"
                }
            ]
        }
    ]
)
```

### Base64图像

```python theme={null}
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": "分析这张图片"
                }
            ]
        }
    ]
)
```

## 最佳实践

### 1. 提示词工程

**清晰的角色定义：**

```python theme={null}
system = """你是一位经验丰富的数据科学家，专长包括：
- 统计分析和数据可视化
- 机器学习模型开发
- Python和R编程
请提供专业、准确的建议。"""
```

**结构化输出：**

```python theme={null}
message = "请以JSON格式返回分析结果，包含summary、key_findings和recommendations字段。"
```

### 2. 错误处理

```python theme={null}
from anthropic import APIError, RateLimitError

try:
    message = client.messages.create(
        model="claude-sonnet-4-6",
        max_tokens=1024,
        messages=[{"role": "user", "content": "你好"}]
    )
except RateLimitError:
    print("速率限制，请稍后重试")
except APIError as e:
    print(f"API错误: {e}")
```

### 3. Token优化

```python theme={null}
# 使用更短的提示词
messages = [
    {"role": "user", "content": "总结要点：\n\n[长文本]"}
]

# 限制输出长度
message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=500,  # 限制输出
    messages=messages
)
```

### 4. 预填充响应

```python theme={null}
# 引导模型以特定格式回复
messages = [
    {"role": "user", "content": "列出5个Python最佳实践"},
    {"role": "assistant", "content": "以下是5个Python最佳实践：\n\n1."}
]

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

## 流式响应处理

### Python流式示例

```python theme={null}
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": "写一个Python装饰器示例"}
    ]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)
```

### JavaScript流式示例

```javascript theme={null}
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: '写一个React组件示例' }
  ]
});

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

## 注意事项

1. **API密钥安全**：
   * 使用环境变量存储API密钥
   * 不要在代码中硬编码密钥
   * 定期轮换密钥

2. **速率限制**：
   * 注意API的速率限制
   * 实现重试机制
   * 使用指数退避策略

3. **Token管理**：
   * 监控token使用量
   * 优化提示词长度
   * 使用适当的max\_tokens值

4. **模型选择**：
   * Opus: 复杂任务、需要深度思考
   * Sonnet: 平衡性能和成本
   * Haiku: 快速响应、简单任务

5. **内容过滤**：
   * 验证用户输入
   * 过滤敏感信息
   * 实现内容审核机制