aws-sdk-java-v2-bedrock
Provides Amazon Bedrock patterns using AWS SDK for Java 2.x. Invokes foundation models (Claude, Llama, Titan), generates text and images, creates embeddings for RAG, streams real-time responses, and configures Spring Boot integration. Use when asking about Bedrock integration, Java SDK for AI models, AWS generative AI, Claude/Llama invocation, embeddings for RAG, or Spring Boot AI setup.
What this skill does
# 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
```xml
<!-- 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
```java
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
```java
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
```java
import software.amazon.awssdk.services.bedrock.model.*;
public List<FoundationModelSummary> listFoundationModels(BedrockClient bedrockClient) {
return bedrockClient.listFoundationModels().modelSummaries();
}
```
### Multi-Model Invocation
```java
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 (modelId.startsWith("amazon.titan")) {
return new JSONObject()
.put("inputText", prompt)
.put("textGenerationConfig", new JSONObject()
.put("maxTokenCount", 512)
.put("temperature", 0.7));
} else if (modelId.startsWith("meta.llama")) {
return new JSONObject()
.put("prompt", "[INST] " + prompt + " [/INST]")
.put("max_gen_len", 512)
.put("temperature", 0.7);
}
throw new IllegalArgumentException("Unsupported model: " + modelId);
}
```
### Streaming Response with Error Handling
```java
public String streamResponseWithRetry(BedrockRuntimeClient client, String modelId, String prompt, int maxRetries) {
int attempt = 0;
while (attempt < maxRetries) {
try {
JSONObject payload = createPayload(modelId, prompt);
StringBuilder fullResponse = new StringBuilder();
InvokeModelWithResponseStreamRequest request = InvokeModelWithResponseStreamRequest.builder()
.modelId(modelId)
.body(SdkBytes.fromUtf8String(payload.toString()))
.build();
client.invokeModelWithResponseStream(request,
InvokeModelWithResponseStreamResponseHandler.builder()
.onEventStream(stream -> stream.forEach(event -> {
if (event instanceof PayloadPart) {
String chunk = ((PayloadPart) event).bytes().asUtf8String();
fullResponse.append(chunk);
}
}))
.onError(e -> System.err.println("Stream error: " + e.getMessage()))
.build());
return fullResponse.toString();
} catch (Exception e) {
attempt++;
if (attempt >= maxRetries) {
throw new RuntimeException("Stream failed after " + maxRetries + " attempts", e);
}
try {
Thread.sleep((long) Math.pow(2, attempt) * 1000); // Exponential backoff
} catch (InterruptedException ie) {
Thread.currentThread().interrupt();
throw new RuntimeException("Interrupted during retry", ie);
}
}
}
throw new RuntimeException("Unexpected error in streaming");
}
```
### Exponential Backoff for Throttling
```java
import software.amazon.awssdk.awscore.exception.AwsServiceException;
public <T> T invokeWithRetry(Supplier<T> invocation, int maxRetries) {
int attempt = 0;
while (attempt < maxRetries) {
try {
return invocation.get();
} catch (AwsServiceException e) {
if (e.statusCode() == 429 || e.statusCode() >= 500) {
attempt++;
if (attempt >= maxRetries) throw e;
long delayMs = Math.min(1000 * (1L << attempt) + (long) (Math.random() * 1000), 30000);
Thread.sleep(delayMs);
} else {
throw e;
}
}
}
throw new IllegalStateException("Should not reach here");
}
```
### Text Embeddings
```java
public double[] createEmbeddings(BedrockRuntimeClient client, String text) {
String modelId = "amazon.titan-embed-text-v1";
JSONObject payload = new JSONObject().put("inputText", text);
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