= Bedrock Anthropic 2 Chat

NOTE: The Anthropic 2 Chat API is deprecated and replaced by the new Anthropic Claude 3 Message API.
Please use the xref:api/chat/bedrock/bedrock-anthropic3.adoc[Anthropic Claude 3 Message API] for new projects.

https://www.anthropic.com/product[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.

The https://aws.amazon.com/bedrock/claude[AWS Bedrock Anthropic Model Page] and https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html[Amazon Bedrock User Guide] contains detailed information on how to use the AWS hosted model.

TIP: Anthropic’s Claude 2 and 3 models are also available directly on the Anthropic's own cloud platform.
Spring AI provides dedicated xref:api/chat/anthropic-chat.adoc[Anthropic Claude] client to access it.

== Prerequisites

Refer to the xref:api/bedrock.adoc[Spring AI documentation on Amazon Bedrock] for setting up API access.

=== Add Repositories and BOM

Spring AI artifacts are published in Spring Milestone and Snapshot repositories.   Refer to the xref:getting-started.adoc#repositories[Repositories] section to add these repositories to your build system.

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 xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build system.


== Auto-configuration

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

[source,xml]
----
<dependency>
  <groupId>org.springframework.ai</groupId>
  <artifactId>spring-ai-bedrock-ai-spring-boot-starter</artifactId>
</dependency>
----

or to your Gradle `build.gradle` build file.

[source,gradle]
----
dependencies {
    implementation 'org.springframework.ai:spring-ai-bedrock-ai-spring-boot-starter'
}
----

TIP: Refer to the xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build file.

=== Enable Anthropic Chat

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:

[source,shell]
----
export SPRING_AI_BEDROCK_ANTHROPIC_CHAT_ENABLED=true
----

=== Chat Properties

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

[cols="3,3,1"]
|====
| Property | Description | Default

| spring.ai.bedrock.aws.region     | AWS region to use.  | us-east-1
| spring.ai.bedrock.aws.timeout    | AWS timeout to use. | 5m
| spring.ai.bedrock.aws.access-key | AWS access key.  | -
| spring.ai.bedrock.aws.secret-key | AWS secret key.  | -
|====

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

[cols="2,5,1"]
|====
| Property | Description | Default

| spring.ai.bedrock.anthropic.chat.enabled | Enable Bedrock Anthropic chat model. Disabled by default | false
| spring.ai.bedrock.anthropic.chat.model  | The model id to use. See the https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic/api/AnthropicChatBedrockApi.java[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
|====

Look at the https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic/api/AnthropicChatBedrockApi.java[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 https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids-arns.html[AWS Bedrock documentation for base model IDs].

TIP: 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.

== Runtime Options [[chat-options]]

The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic/AnthropicChatOptions.java[AnthropicChatOptions.java] provides model configurations, such as temperature, topK, topP, etc.

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

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:

[source,java]
----
ChatResponse response = chatModel.call(
    new Prompt(
        "Generate the names of 5 famous pirates.",
        AnthropicChatOptions.builder()
            .withTemperature(0.4)
        .build()
    ));
----

TIP: In addition to the model specific https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic/AnthropicChatOptions.java[AnthropicChatOptions] you can use a portable https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/prompt/ChatOptions.java[ChatOptions] instance, created with the https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/prompt/ChatOptionsBuilder.java[ChatOptionsBuilder#builder()].

== Sample Controller

https://start.spring.io/[Create] a new Spring Boot project and add the `spring-ai-bedrock-ai-spring-boot-starter` to your pom (or gradle) dependencies.

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

[source]
----
spring.ai.bedrock.aws.region=eu-central-1
spring.ai.bedrock.aws.timeout=1000ms
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
----

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

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

[source,java]
----
@RestController
public class ChatController {

    private final BedrockAnthropicChatModel chatModel;

    @Autowired
    public ChatController(BedrockAnthropicChatModel chatModel) {
        this.chatModel = chatModel;
    }

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

== Manual Configuration

The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic/BedrockAnthropicChatModel.java[BedrockAnthropicChatModel] implements the `ChatModel` and `StreamingChatModel` and uses the <<low-level-api>> to connect to the Bedrock Anthropic service.

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

[source,xml]
----
<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-bedrock</artifactId>
</dependency>
----

or to your Gradle `build.gradle` build file.

[source,gradle]
----
dependencies {
    implementation 'org.springframework.ai:spring-ai-bedrock'
}
----

TIP: Refer to the xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build file.

Next, create an https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic/BedrockAnthropicChatModel.java[BedrockAnthropicChatModel] and use it for text generations:

[source,java]
----
AnthropicChatBedrockApi anthropicApi =  new AnthropicChatBedrockApi(
    AnthropicChatBedrockApi.AnthropicModel.CLAUDE_V2.id(),
    EnvironmentVariableCredentialsProvider.create(),
    Region.EU_CENTRAL_1.id(),
    new ObjectMapper(),
    Duration.ofMillis(1000L));

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

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

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

=== Low-level AnthropicChatBedrockApi Client [[low-level-api]]

The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic/api/AnthropicChatBedrockApi.java[AnthropicChatBedrockApi] provides is lightweight Java client on top of AWS Bedrock link:https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-claude.html[Anthropic Claude models].

Following class diagram illustrates the AnthropicChatBedrockApi interface and building blocks:

image::bedrock/bedrock-anthropic-chat-api.png[AnthropicChatBedrockApi Class Diagram]

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.

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

[source,java]
----
AnthropicChatBedrockApi anthropicChatApi = new AnthropicChatBedrockApi(
   AnthropicModel.CLAUDE_V2.id(), Region.EU_CENTRAL_1.id(), Duration.ofMillis(1000L));

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();
----

Follow the https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic/api/AnthropicChatBedrockApi.java[AnthropicChatBedrockApi.java]'s JavaDoc for further information.
