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Amazon Bedrock

Maven Dependency​

<dependency>
    <groupId>dev.langchain4j</groupId>
    <artifactId>langchain4j-bedrock</artifactId>
    <version>1.3.0</version>
</dependency>

AWS credentials​

In order to use Amazon Bedrock models, you need to configure AWS credentials. One of the options is to set the AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY environment variables. More information can be found here. Alternatively, set the AWS_BEARER_TOKEN_BEDROCK environment variable locally for API Key authentication. For additional API key details, refer to docs.

BedrockChatModel​

note

Guardrails is not supported by the current implementation.

Supported models and their features can be found here.

Models ids can be found here.

Configuration​

ChatModel model = BedrockChatModel.builder()
        .client(BedrockRuntimeClient)
        .region(...)
        .modelId("us.amazon.nova-lite-v1:0")
        .returnThinking(...)
        .sendThinking(...)
        .timeout(...)
        .maxRetries(...)
        .logRequests(...)
        .logResponses(...)
        .listeners(...)
        .defaultRequestParameters(BedrockChatRequestParameters.builder()
                .modelName(...)
                .temperature(...)
                .topP(...)
                .maxOutputTokens(...)
                .stopSequences(...)
                .toolSpecifications(...)
                .toolChoice(...)
                .additionalModelRequestFields(...)
                .additionalModelRequestField(...)
                .enableReasoning(...)
                .build())
        .build();

Examples​

BedrockStreamingChatModel​

note

Guardrails is not supported by the current implementation.

Supported models and their features can be found here.

Models ids can be found here.

Configuration​

StreamingChatModel model = BedrockStreamingChatModel.builder()
        .client(BedrockRuntimeAsyncClient)
        .region(...)
        .modelId("us.amazon.nova-lite-v1:0")
        .returnThinking(...)
        .sendThinking(...)
        .timeout(...)
        .logRequests(...)
        .logResponses(...)
        .listeners(...)
        .defaultRequestParameters(BedrockChatRequestParameters.builder()
                .modelName(...)
                .temperature(...)
                .topP(...)
                .maxOutputTokens(...)
                .stopSequences(...)
                .toolSpecifications(...)
                .toolChoice(...)
                .additionalModelRequestFields(...)
                .additionalModelRequestField(...)
                .enableReasoning(...)
                .build())
        .build();

Examples​

Additional Model Request Fields​

The field additionalModelRequestFields in the BedrockChatRequestParameters is a Map<String, Object>. As explained here it allows to add inference parameters for a specific model that is not covered by common InferenceConfiguration.

Thinking / Reasoning​

To enable Claude thinking process, call enableReasoning on BedrockChatRequestParameters and set it via defaultRequestParameters when building the model:

BedrockChatRequestParameters parameters = BedrockChatRequestParameters.builder()
        .enableReasoning(1024) // token budget
        .build();

ChatModel model = BedrockChatModel.builder()
        .modelId("us.anthropic.claude-sonnet-4-20250514-v1:0")
        .defaultRequestParameters(parameters)
        .returnThinking(true)
        .sendThinking(true)
        .build();

The following parameters also control thinking behaviour:

  • returnThinking: controls whether to return thinking (if available) inside AiMessage.thinking() and whether to invoke StreamingChatResponseHandler.onPartialThinking() and TokenStream.onPartialThinking() callbacks when using BedrockStreamingChatModel. Disabled by default. If enabled, tinking signatures will also be stored and returned inside the AiMessage.attributes().
  • sendThinking: controls whether to send thinking and signatures stored in AiMessage to the LLM in follow-up requests. Enabled by default.