Anthropic Chat

  • 基于 Anthropic 的安全研究，优先考虑交互中的有用性、诚实性和无害性。

Anthropic’s Claude是基于 Anthropic 关于训练有用、诚实和无害的人工智能系统的研究的人工智能助手。Claude 模型具有以下高级功能

Anthropic’s Claude is an AI assistant based on Anthropic’s research into training helpful, honest, and harmless AI systems. The Claude model has the following high level features

  • 200k Token Context Window: Claude boasts a generous token capacity of 200,000, making it ideal for handling extensive information in applications like technical documentation, codebase, and literary works.

  • Supported Tasks: Claude’s versatility spans tasks such as summarization, Q&A, trend forecasting, and document comparisons, enabling a wide range of applications from dialogues to content generation.

  • AI Safety Features: Built on Anthropic’s safety research, Claude prioritizes helpfulness, honesty, and harmlessness in its interactions, reducing brand risk and ensuring responsible AI behavior.

AWS Bedrock Anthropic Model Page 和 Amazon Bedrock User Guide 包含有关如何使用 AWS 托管模型的详细信息。

The AWS Bedrock Anthropic Model Page and Amazon Bedrock User Guide contains detailed information on how to use the AWS hosted model.

Prerequisites

请参阅 Spring AI documentation on Amazon Bedrock 以设置 API 访问。

Refer to the Spring AI documentation on Amazon Bedrock for setting up API access.

Add Repositories and BOM

Spring AI 工件发布在 Spring Milestone 和 Snapshot 存储库中。有关将这些存储库添加到你的构建系统的说明，请参阅 Repositories 部分。

Spring AI artifacts are published in Spring Milestone and Snapshot repositories. Refer to the Repositories section to add these repositories to your build system.

为了帮助进行依赖项管理，Spring AI 提供了一个 BOM（物料清单）以确保在整个项目中使用一致版本的 Spring AI。有关将 Spring AI BOM 添加到你的构建系统的说明，请参阅 Dependency Management 部分。

To help with dependency management, Spring AI provides a BOM (bill of materials) to ensure that a consistent version of Spring AI is used throughout the entire project. Refer to the Dependency Management section to add the Spring AI BOM to your build system.

Auto-configuration

将 spring-ai-bedrock-ai-spring-boot-starter 依赖项添加到项目 Maven 的 pom.xml 文件：

Add the spring-ai-bedrock-ai-spring-boot-starter dependency to your project’s Maven pom.xml file:

<dependency>
  <groupId>org.springframework.ai</groupId>
  <artifactId>spring-ai-bedrock-ai-spring-boot-starter</artifactId>
</dependency>

或添加到 Gradle build.gradle 构建文件中。

or to your Gradle build.gradle build file.

dependencies {
    implementation 'org.springframework.ai:spring-ai-bedrock-ai-spring-boot-starter'
}

  1. 参见 Dependency Management 部分，将 Spring AI BOM 添加到你的构建文件中。

Refer to the Dependency Management section to add the Spring AI BOM to your build file.

Enable Anthropic Chat

默认情况下，Anthropic 模型处于禁用状态。要启用它，请将 spring.ai.bedrock.anthropic.chat.enabled 属性设置为 true。导出环境变量是一种设置此配置属性的方法：

By default the Anthropic model is disabled. To enable it set the spring.ai.bedrock.anthropic.chat.enabled property to true. Exporting environment variable is one way to set this configuration property:

export SPRING_AI_BEDROCK_ANTHROPIC_CHAT_ENABLED=true

Chat Properties

spring.ai.bedrock.aws 前缀是配置与 AWS Bedrock 的连接的属性前缀。

The prefix spring.ai.bedrock.aws is the property prefix to configure the connection to AWS Bedrock.

Property Description Default

spring.ai.bedrock.aws.region

AWS region to use.

us-east-1

spring.ai.bedrock.aws.access-key

AWS access key.

-

spring.ai.bedrock.aws.secret-key

AWS secret key.

-

前缀 spring.ai.bedrock.anthropic.chat 是为 Claude 配置聊天客户端实现的属性前缀。

The prefix spring.ai.bedrock.anthropic.chat is the property prefix that configures the chat client implementation for Claude.

Property Description Default

spring.ai.bedrock.anthropic.chat.enable

Enable Bedrock Anthropic chat client. Disabled by default

false

spring.ai.bedrock.anthropic.chat.model

The model id to use. See the AnthropicChatModel for the supported models.

anthropic.claude-v2

spring.ai.bedrock.anthropic.chat.options.temperature

Controls the randomness of the output. Values can range over [0.0,1.0]

0.8

spring.ai.bedrock.anthropic.chat.options.topP

The maximum cumulative probability of tokens to consider when sampling.

AWS Bedrock default

spring.ai.bedrock.anthropic.chat.options.topK

Specify the number of token choices the generative uses to generate the next token.

AWS Bedrock default

spring.ai.bedrock.anthropic.chat.options.stopSequences

Configure up to four sequences that the generative recognizes. After a stop sequence, the generative stops generating further tokens. The returned text doesn’t contain the stop sequence.

10

spring.ai.bedrock.anthropic.chat.options.anthropicVersion

The version of the generative to use.

bedrock-2023-05-31

spring.ai.bedrock.anthropic.chat.options.maxTokensToSample

Specify the maximum number of tokens to use in the generated response. Note that the models may stop before reaching this maximum. This parameter only specifies the absolute maximum number of tokens to generate. We recommend a limit of 4,000 tokens for optimal performance.

500

查看 AnthropicChatModel 了解其他模型 ID。支持的值为： anthropic.claude-instant-v1、anthropic.claude-v2 和 anthropic.claude-v2:1。模型 ID 值也可在 AWS Bedrock documentation for base model IDs 中找到。

Look at the AnthropicChatModel for other model IDs. Supported values are: anthropic.claude-instant-v1, anthropic.claude-v2 and anthropic.claude-v2:1. Model ID values can also be found in the AWS Bedrock documentation for base model IDs.

所有带有 spring.ai.bedrock.anthropic.chat.options 前缀的属性都可以通过在 Prompt 调用中添加一个特定于请求的 Chat Options 来在运行时覆盖。

All properties prefixed with spring.ai.bedrock.anthropic.chat.options can be overridden at runtime by adding a request specific Chat Options to the Prompt call.

Chat Options

AnthropicChatOptions.java 提供模型配置，如温度、topK、topP 等。

The AnthropicChatOptions.java provides model configurations, such as temperature, topK, topP, etc.

在启动时，可以使用 BedrockAnthropicChatClient(api, options) 构造函数或 spring.ai.bedrock.anthropic.chat.options.* 属性配置默认选项。

On start-up, the default options can be configured with the BedrockAnthropicChatClient(api, options) constructor or the spring.ai.bedrock.anthropic.chat.options.* properties.

在运行时，你可以通过向 Prompt 调用添加新的请求特定选项来覆盖默认选项。例如，覆盖特定请求的默认温度：

At run-time you can override the default options by adding new, request specific, options to the Prompt call. For example to override the default temperature for a specific request:

ChatResponse response = chatClient.call(
    new Prompt(
        "Generate the names of 5 famous pirates.",
        AnthropicChatOptions.builder()
            .withTemperature(0.4)
        .build()
    ));

  1. 除了模型特定的 AnthropicChatOptions 之外，你还可以使用用 ChatOptionsBuilder#builder() 创建的便携式 ChatOptions 实例。

In addition to the model specific AnthropicChatOptions you can use a portable ChatOptions instance, created with the ChatOptionsBuilder#builder().

Sample Controller (Auto-configuration)

Create一个新的 Spring Boot 项目，并将 `spring-ai-bedrock-ai-spring-boot-starter`添加到您的 pom（或 gradle）依赖项。

Create a new Spring Boot project and add the spring-ai-bedrock-ai-spring-boot-starter to your pom (or gradle) dependencies.

在 src/main/resources 目录下添加一个 application.properties 文件，以启用和配置 Anthropic Chat 客户端：

Add a application.properties file, under the src/main/resources directory, to enable and configure the Anthropic Chat client:

spring.ai.bedrock.aws.region=eu-central-1
spring.ai.bedrock.aws.access-key=${AWS_ACCESS_KEY_ID}
spring.ai.bedrock.aws.secret-key=${AWS_SECRET_ACCESS_KEY}

spring.ai.bedrock.anthropic.chat.enabled=true
spring.ai.bedrock.anthropic.chat.options.temperature=0.8
spring.ai.bedrock.anthropic.chat.options.top-k=15

将 regions、access-key 和 secret-key 替换为 AWS 凭证。

replace the regions, access-key and secret-key with your AWS credentials.

这将创建一个 BedrockAnthropicChatClient 实现，你可以将其注入到你的类中。这是一个简单的 @Controller 类示例，它将聊天客户端用于文本生成。

This will create a BedrockAnthropicChatClient implementation that you can inject into your class. Here is an example of a simple @Controller class that uses the chat client for text generations.

@RestController
public class ChatController {

    private final BedrockAnthropicChatClient chatClient;

    @Autowired
    public ChatController(BedrockAnthropicChatClient chatClient) {
        this.chatClient = chatClient;
    }

    @GetMapping("/ai/generate")
    public Map generate(@RequestParam(value = "message", defaultValue = "Tell me a joke") String message) {
        return Map.of("generation", chatClient.call(message));
    }

    @GetMapping("/ai/generateStream")
	public Flux<ChatResponse> generateStream(@RequestParam(value = "message", defaultValue = "Tell me a joke") String message) {
        Prompt prompt = new Prompt(new UserMessage(message));
        return chatClient.stream(prompt);
    }
}

Manual Configuration

BedrockAnthropicChatClient实现 ChatClient`和 `StreamingChatClient，并使用 Low-level AnthropicChatBedrockApi Client连接到 Bedrock Anthropic 服务。

The BedrockAnthropicChatClient implements the ChatClient and StreamingChatClient and uses the Low-level AnthropicChatBedrockApi Client to connect to the Bedrock Anthropic service.

将 spring-ai-bedrock 依赖项添加到项目的 Maven pom.xml 文件：

Add the spring-ai-bedrock dependency to your project’s Maven pom.xml file:

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-bedrock</artifactId>
</dependency>

或添加到 Gradle build.gradle 构建文件中。

or to your Gradle build.gradle build file.

dependencies {
    implementation 'org.springframework.ai:spring-ai-bedrock'
}

  1. 参见 Dependency Management 部分，将 Spring AI BOM 添加到你的构建文件中。

Refer to the Dependency Management section to add the Spring AI BOM to your build file.

接下来，创建一个 BedrockAnthropicChatClient 并将其用于文本生成：

Next, create an BedrockAnthropicChatClient and use it for text generations:

AnthropicChatBedrockApi anthropicApi =  new AnthropicChatBedrockApi(
    AnthropicChatBedrockApi.AnthropicModel.CLAUDE_V2.id(),
    EnvironmentVariableCredentialsProvider.create(),
    Region.EU_CENTRAL_1.id(),
    new ObjectMapper());

BedrockAnthropicChatClient chatClient = new BedrockAnthropicChatClient(anthropicApi,
    AnthropicChatOptions.builder()
        .withTemperature(0.6f)
        .withTopK(10)
        .withTopP(0.8f)
        .withMaxTokensToSample(100)
        .withAnthropicVersion(AnthropicChatBedrockApi.DEFAULT_ANTHROPIC_VERSION)
        .build());

ChatResponse response = chatClient.call(
    new Prompt("Generate the names of 5 famous pirates."));

// Or with streaming responses
Flux<ChatResponse> response = chatClient.stream(
    new Prompt("Generate the names of 5 famous pirates."));

Low-level AnthropicChatBedrockApi Client

AnthropicChatBedrockApi 在 AWS Bedrock Anthropic Claude models 之上提供轻量级 Java 客户端。

The AnthropicChatBedrockApi provides is lightweight Java client on top of AWS Bedrock Anthropic Claude models.

以下类图说明了 AnthropicChatBedrockApi 接口和构建模块：

Following class diagram illustrates the AnthropicChatBedrockApi interface and building blocks:

bedrock anthropic chat api

客户端同时支持 anthropic.claude-instant-v1、anthropic.claude-v2 和 anthropic.claude-v2:1 模型的同步（例如 chatCompletion()）和流式（例如 chatCompletionStream()）响应。

Client supports the anthropic.claude-instant-v1, anthropic.claude-v2 and anthropic.claude-v2:1 models for both synchronous (e.g. chatCompletion()) and streaming (e.g. chatCompletionStream()) responses.

下面是一个简单的片段，说明如何以编程方式使用 API：

Here is a simple snippet how to use the api programmatically:

AnthropicChatBedrockApi anthropicChatApi = new AnthropicChatBedrockApi(
   AnthropicModel.CLAUDE_V2.id(), Region.EU_CENTRAL_1.id());

AnthropicChatRequest request = AnthropicChatRequest
  .builder(String.format(AnthropicChatBedrockApi.PROMPT_TEMPLATE, "Name 3 famous pirates"))
  .withTemperature(0.8f)
  .withMaxTokensToSample(300)
  .withTopK(10)
  .build();

// Sync request
AnthropicChatResponse response = anthropicChatApi.chatCompletion(request);

// Streaming request
Flux<AnthropicChatResponse> responseStream = anthropicChatApi.chatCompletionStream(request);
List<AnthropicChatResponse> responses = responseStream.collectList().block();

关注 AnthropicChatBedrockApi.java 的 JavaDoc 了解详细信息。

Follow the AnthropicChatBedrockApi.java's JavaDoc for further information.