npx skills add ...
npx skills add giuseppe-trisciuoglio/developer-kit --skill 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.
npx skills add giuseppe-trisciuoglio/developer-kit --skill aws-sdk-java-v2-bedrock
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.
Follow these steps for production-ready Bedrock integration:
BedrockClient and BedrockRuntimeClient instancesValidation Checkpoint: Always test with a simple prompt (e.g., "Hello") before production use to verify model access and response parsing.
See examples directory for comprehensive usage patterns.
anthropic.claude-sonnet-4-5-20250929-v1:0anthropic.claude-haiku-4-5-20251001-v1:0meta.llama3-1-70b-instruct-v1:0amazon.titan-embed-text-v1See Model Reference for complete list.
aws-sdk-java-v2-core - Core AWS SDK patternslangchain4j-ai-services-patterns - LangChain4j integrationspring-boot-dependency-injection - Spring DI patternsimport 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();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");
}import software.amazon.awssdk.services.bedrock.model.*;
public List<FoundationModelSummary> listFoundationModels(BedrockClient bedrockClient) {
return bedrockClient.listFoundationModels().modelSummaries();
}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);
}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");
}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");
}public double[] createEmbeddings(BedrockRuntimeClient client, String text) {
String modelId = "amazon.titan-embed-text-v1";
JSONObject payload = new JSONObject().put("inputText", text);
InvokeModelResponse response = client.invokeModel(request -> request
.modelId(modelId)
.body(SdkBytes.fromUtf8String(payload.toString())));
JSONObject responseBody = new JSONObject(response.body().asUtf8String());
JSONArray embeddingArray = responseBody.getJSONArray("embedding");
double[] embeddings = new double[embeddingArray.length()];
for (int i = 0; i < embeddingArray.length(); i++) {
embeddings[i] = embeddingArray.getDouble(i);
}
return embeddings;
}@Configuration
public class BedrockConfiguration {
@Bean
public BedrockClient bedrockClient() {
return BedrockClient.builder()
.region(Region.US_EAST_1)
.build();
}
@Bean
public BedrockRuntimeClient bedrockRuntimeClient() {
return BedrockRuntimeClient.builder()
.region(Region.US_EAST_1)
.build();
}
}
@Service
public class BedrockAIService {
private final BedrockRuntimeClient bedrockRuntimeClient;
private final ObjectMapper mapper;
@Value("${bedrock.default-model-id:anthropic.claude-sonnet-4-5-20250929-v1:0}")
private String defaultModelId;
public BedrockAIService(BedrockRuntimeClient bedrockRuntimeClient, ObjectMapper mapper) {
this.bedrockRuntimeClient = bedrockRuntimeClient;
this.mapper = mapper;
}
public String generateText(String prompt) {
Map<String, Object> payload = Map.of(
"anthropic_version", "bedrock-2023-05-31",
"max_tokens", 1000,
"messages", List.of(Map.of("role", "user", "content", prompt))
);
InvokeModelResponse response = bedrockRuntimeClient.invokeModel(
InvokeModelRequest.builder()
.modelId(defaultModelId)
.body(SdkBytes.fromUtf8String(mapper.writeValueAsString(payload)))
.build());
return extractText(response.body().asUtf8String());
}
}