AWS SDK for Java 2.x - Amazon Bedrock

Overview

Invokes foundation models through AWS SDK for Java 2.x. Configures clients, builds model-specific JSON payloads, handles streaming responses with error recovery, creates embeddings for RAG, integrates generative AI into Spring Boot applications, and implements exponential backoff for resilience.

When to Use

• Invoke Claude, Llama, Titan, or Stable Diffusion for text/image generation
• Configure BedrockClient and BedrockRuntimeClient instances
• Build and parse model-specific payloads (Claude, Titan, Llama formats)
• Stream real-time AI responses with async handlers and error recovery
• Create embeddings for retrieval-augmented generation
• Integrate generative AI into Spring Boot microservices
• Handle throttling with exponential backoff retry logic

Quick Start

Dependencies

<!-- Bedrock (model management) -->
<dependency>
    <groupId>software.amazon.awssdk</groupId>
    <artifactId>bedrock</artifactId>
</dependency>

<!-- Bedrock Runtime (model invocation) -->
<dependency>
    <groupId>software.amazon.awssdk</groupId>
    <artifactId>bedrockruntime</artifactId>
</dependency>

<!-- For JSON processing -->
<dependency>
    <groupId>org.json</groupId>
    <artifactId>json</artifactId>
    <version>20231013</version>
</dependency>

Client Setup

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.bedrock.BedrockClient;
import software.amazon.awssdk.services.bedrockruntime.BedrockRuntimeClient;

// Model management client
BedrockClient bedrockClient = BedrockClient.builder()
    .region(Region.US_EAST_1)
    .build();

// Model invocation client
BedrockRuntimeClient bedrockRuntimeClient = BedrockRuntimeClient.builder()
    .region(Region.US_EAST_1)
    .build();

Instructions

Follow these steps for production-ready Bedrock integration:

1. Configure AWS Credentials - Set up IAM roles with Bedrock permissions (avoid access keys)
2. Enable Model Access - Request access to specific foundation models in AWS Console
3. Initialize Clients - Create reusable BedrockClient and BedrockRuntimeClient instances
4. Validate Model Availability - Test with a simple invocation before production use
5. Build Payloads - Create model-specific JSON payloads with proper format
6. Handle Responses - Parse response structure and extract content
7. Implement Streaming - Use response stream handlers for real-time generation
8. Add Error Handling - Implement retry logic with exponential backoff

Validation Checkpoint: Always test with a simple prompt (e.g., "Hello") before production use to verify model access and response parsing.

Examples

Text Generation with Claude

public String generateWithClaude(BedrockRuntimeClient client, String prompt) {
    JSONObject payload = new JSONObject()
        .put("anthropic_version", "bedrock-2023-05-31")
        .put("max_tokens", 1000)
        .put("messages", new JSONObject[]{
            new JSONObject().put("role", "user").put("content", prompt)
        });

    InvokeModelResponse response = client.invokeModel(InvokeModelRequest.builder()
        .modelId("anthropic.claude-sonnet-4-5-20250929-v1:0")
        .body(SdkBytes.fromUtf8String(payload.toString()))
        .build());

    JSONObject responseBody = new JSONObject(response.body().asUtf8String());
    return responseBody.getJSONArray("content")
        .getJSONObject(0)
        .getString("text");
}

Model Discovery

import software.amazon.awssdk.services.bedrock.model.*;

public List<FoundationModelSummary> listFoundationModels(BedrockClient bedrockClient) {
    return bedrockClient.listFoundationModels().modelSummaries();
}

Multi-Model Invocation

public String invokeModel(BedrockRuntimeClient client, String modelId, String prompt) {
    JSONObject payload = createPayload(modelId, prompt);

    InvokeModelResponse response = client.invokeModel(request -> request
        .modelId(modelId)
        .body(SdkBytes.fromUtf8String(payload.toString())));

    return extractTextFromResponse(modelId, response.body().asUtf8String());
}

private JSONObject createPayload(String modelId, String prompt) {
    if (modelId.startsWith("anthropic.claude")) {
        return new JSONObject()
            .put("anthropic_version", "bedrock-2023-05-31")
            .put("max_tokens", 1000)
            .put("messages", new JSONObject[]{
                new JSONObject().put("role", "user").put("content", prompt)
            });
    } else if