AWS Bedrock

Since Camel 4.5

Only producer is supported

The AWS2 Bedrock component supports invoking a supported LLM model from AWS Bedrock service.

Prerequisites

You must have a valid Amazon Web Services developer account, and be signed up to use Amazon Bedrock. More information is available at Amazon Bedrock.

URI Format

aws-bedrock://label[?options]

You can append query options to the URI in the following format:

?options=value&option2=value&…​

Configuring Options

Camel components are configured on two separate levels:

  • component level

  • endpoint level

Configuring Component Options

At the component level, you set general and shared configurations that are, then, inherited by the endpoints. It is the highest configuration level.

For example, a component may have security settings, credentials for authentication, urls for network connection and so forth.

Some components only have a few options, and others may have many. Because components typically have pre-configured defaults that are commonly used, then you may often only need to configure a few options on a component; or none at all.

You can configure components using:

  • the Component DSL.

  • in a configuration file (application.properties, *.yaml files, etc).

  • directly in the Java code.

Configuring Endpoint Options

You usually spend more time setting up endpoints because they have many options. These options help you customize what you want the endpoint to do. The options are also categorized into whether the endpoint is used as a consumer (from), as a producer (to), or both.

Configuring endpoints is most often done directly in the endpoint URI as path and query parameters. You can also use the Endpoint DSL and DataFormat DSL as a type safe way of configuring endpoints and data formats in Java.

A good practice when configuring options is to use Property Placeholders.

Property placeholders provide a few benefits:

  • They help prevent using hardcoded urls, port numbers, sensitive information, and other settings.

  • They allow externalizing the configuration from the code.

  • They help the code to become more flexible and reusable.

The following two sections list all the options, firstly for the component followed by the endpoint.

Component Options

The AWS Bedrock component supports 23 options, which are listed below.

Name Description Default Type

configuration (producer)

Component configuration.

BedrockConfiguration

lazyStartProducer (producer)

Whether the producer should be started lazy (on the first message). By starting lazy you can use this to allow CamelContext and routes to startup in situations where a producer may otherwise fail during starting and cause the route to fail being started. By deferring this startup to be lazy then the startup failure can be handled during routing messages via Camel’s routing error handlers. Beware that when the first message is processed then creating and starting the producer may take a little time and prolong the total processing time of the processing.

false

boolean

modelId (producer)

Required Define the model Id we are going to use.

Enum values:

  • amazon.titan-text-express-v1

  • amazon.titan-text-lite-v1

  • amazon.titan-image-generator-v1

  • amazon.titan-embed-text-v1

  • ai21.j2-ultra-v1

  • ai21.j2-mid-v1

  • anthropic.claude-instant-v1

  • anthropic.claude-v2

  • anthropic.claude-v2:1

  • anthropic.claude-3-sonnet-20240229-v1:0

  • anthropic.claude-3-haiku-20240307-v1:0

  • amazon.titan-text-premier-v1:0

  • amazon.titan-embed-text-v2:0

String

operation (producer)

Required The operation to perform.

Enum values:

  • invokeTextModel

  • invokeImageModel

  • invokeEmbeddingsModel

BedrockOperations

overrideEndpoint (producer)

Set the need for overriding the endpoint. This option needs to be used in combination with the uriEndpointOverride option.

false

boolean

pojoRequest (producer)

If we want to use a POJO request as body or not.

false

boolean

profileCredentialsName (producer)

If using a profile credentials provider, this parameter will set the profile name.

false

String

region (producer)

The region in which Bedrock client needs to work. When using this parameter, the configuration will expect the lowercase name of the region (for example, ap-east-1) You’ll need to use the name Region.EU_WEST_1.id().

Enum values:

  • us-east-1

  • us-west-1

  • ap-southeast-1

  • ap-northeast-1

  • eu-central-1

String

uriEndpointOverride (producer)

Set the overriding uri endpoint. This option needs to be used in combination with overrideEndpoint option.

String

useDefaultCredentialsProvider (producer)

Set whether the Bedrock client should expect to load credentials through a default credentials provider or to expect static credentials to be passed in.

false

boolean

useProfileCredentialsProvider (producer)

Set whether the Bedrock client should expect to load credentials through a profile credentials provider.

false

boolean

autowiredEnabled (advanced)

Whether autowiring is enabled. This is used for automatic autowiring options (the option must be marked as autowired) by looking up in the registry to find if there is a single instance of matching type, which then gets configured on the component. This can be used for automatic configuring JDBC data sources, JMS connection factories, AWS Clients, etc.

true

boolean

bedrockRuntimeClient (advanced)

Autowired To use an existing configured AWS Bedrock Runtime client.

BedrockRuntimeClient

healthCheckConsumerEnabled (health)

Used for enabling or disabling all consumer based health checks from this component.

true

boolean

healthCheckProducerEnabled (health)

Used for enabling or disabling all producer based health checks from this component. Notice: Camel has by default disabled all producer based health-checks. You can turn on producer checks globally by setting camel.health.producersEnabled=true.

true

boolean

proxyHost (proxy)

To define a proxy host when instantiating the Bedrock client.

String

proxyPort (proxy)

To define a proxy port when instantiating the Bedrock client.

Integer

proxyProtocol (proxy)

To define a proxy protocol when instantiating the Bedrock client.

Enum values:

  • HTTP

  • HTTPS

HTTPS

Protocol

accessKey (security)

Amazon AWS Access Key.

String

secretKey (security)

Amazon AWS Secret Key.

String

sessionToken (security)

Amazon AWS Session Token used when the user needs to assume an IAM role.

String

trustAllCertificates (security)

If we want to trust all certificates in case of overriding the endpoint.

false

boolean

useSessionCredentials (security)

Set whether the Bedrock client should expect to use Session Credentials. This is useful in a situation in which the user needs to assume an IAM role for doing operations in Bedrock.

false

boolean

Endpoint Options

The AWS Bedrock endpoint is configured using URI syntax:

aws-bedrock:label

With the following path and query parameters:

Path Parameters (1 parameters)

Name Description Default Type

label (producer)

Required Logical name.

String

Query Parameters (19 parameters)

Name Description Default Type

modelId (producer)

Required Define the model Id we are going to use.

Enum values:

  • amazon.titan-text-express-v1

  • amazon.titan-text-lite-v1

  • amazon.titan-image-generator-v1

  • amazon.titan-embed-text-v1

  • ai21.j2-ultra-v1

  • ai21.j2-mid-v1

  • anthropic.claude-instant-v1

  • anthropic.claude-v2

  • anthropic.claude-v2:1

  • anthropic.claude-3-sonnet-20240229-v1:0

  • anthropic.claude-3-haiku-20240307-v1:0

  • amazon.titan-text-premier-v1:0

  • amazon.titan-embed-text-v2:0

String

operation (producer)

Required The operation to perform.

Enum values:

  • invokeTextModel

  • invokeImageModel

  • invokeEmbeddingsModel

BedrockOperations

overrideEndpoint (producer)

Set the need for overriding the endpoint. This option needs to be used in combination with the uriEndpointOverride option.

false

boolean

pojoRequest (producer)

If we want to use a POJO request as body or not.

false

boolean

profileCredentialsName (producer)

If using a profile credentials provider, this parameter will set the profile name.

false

String

region (producer)

The region in which Bedrock client needs to work. When using this parameter, the configuration will expect the lowercase name of the region (for example, ap-east-1) You’ll need to use the name Region.EU_WEST_1.id().

Enum values:

  • us-east-1

  • us-west-1

  • ap-southeast-1

  • ap-northeast-1

  • eu-central-1

String

uriEndpointOverride (producer)

Set the overriding uri endpoint. This option needs to be used in combination with overrideEndpoint option.

String

useDefaultCredentialsProvider (producer)

Set whether the Bedrock client should expect to load credentials through a default credentials provider or to expect static credentials to be passed in.

false

boolean

useProfileCredentialsProvider (producer)

Set whether the Bedrock client should expect to load credentials through a profile credentials provider.

false

boolean

lazyStartProducer (producer (advanced))

Whether the producer should be started lazy (on the first message). By starting lazy you can use this to allow CamelContext and routes to startup in situations where a producer may otherwise fail during starting and cause the route to fail being started. By deferring this startup to be lazy then the startup failure can be handled during routing messages via Camel’s routing error handlers. Beware that when the first message is processed then creating and starting the producer may take a little time and prolong the total processing time of the processing.

false

boolean

bedrockRuntimeClient (advanced)

Autowired To use an existing configured AWS Bedrock Runtime client.

BedrockRuntimeClient

proxyHost (proxy)

To define a proxy host when instantiating the Bedrock client.

String

proxyPort (proxy)

To define a proxy port when instantiating the Bedrock client.

Integer

proxyProtocol (proxy)

To define a proxy protocol when instantiating the Bedrock client.

Enum values:

  • HTTP

  • HTTPS

HTTPS

Protocol

accessKey (security)

Amazon AWS Access Key.

String

secretKey (security)

Amazon AWS Secret Key.

String

sessionToken (security)

Amazon AWS Session Token used when the user needs to assume an IAM role.

String

trustAllCertificates (security)

If we want to trust all certificates in case of overriding the endpoint.

false

boolean

useSessionCredentials (security)

Set whether the Bedrock client should expect to use Session Credentials. This is useful in a situation in which the user needs to assume an IAM role for doing operations in Bedrock.

false

boolean

Required Bedrock component options

You have to provide the bedrockRuntimeClient in the Registry or your accessKey and secretKey to access the Amazon Bedrock service.

Usage

Static credentials, Default Credential Provider and Profile Credentials Provider

You have the possibility of avoiding the usage of explicit static credentials by specifying the useDefaultCredentialsProvider option and set it to true.

The order of evaluation for Default Credentials Provider is the following:

  • Java system properties - aws.accessKeyId and aws.secretKey.

  • Environment variables - AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY.

  • Web Identity Token from AWS STS.

  • The shared credentials and config files.

  • Amazon ECS container credentials - loaded from the Amazon ECS if the environment variable AWS_CONTAINER_CREDENTIALS_RELATIVE_URI is set.

  • Amazon EC2 Instance profile credentials.

You have also the possibility of using Profile Credentials Provider, by specifying the useProfileCredentialsProvider option to true and profileCredentialsName to the profile name.

Only one of static, default and profile credentials could be used at the same time.

For more information about this you can look at AWS credentials documentation

Message Headers

The AWS Bedrock component supports 3 message header(s), which is/are listed below:

Name Description Default Type

CamelAwsBedrockOperation (producer)

Constant: OPERATION

The operation we want to perform.

String

CamelAwsBedrockContentType (producer)

Constant: MODEL_CONTENT_TYPE

The model content type.

String

CamelAwsBedrockAcceptContentType (producer)

Constant: MODEL_ACCEPT_CONTENT_TYPE

The model accept content type.

String

Supported AWS Bedrock Models

  • Titan Text Express V1 with id amazon.titan-text-express-v1 Express is a large language model for text generation. It is useful for a wide range of advanced, general language tasks such as open-ended text generation and conversational chat, as well as support within Retrieval Augmented Generation (RAG).

Json schema for request

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "type": "object",
  "properties": {
    "inputText": {
      "type": "string"
    },
    "textGenerationConfig": {
      "type": "object",
      "properties": {
        "maxTokenCount": {
          "type": "integer"
        },
        "stopSequences": {
          "type": "array",
          "items": [
            {
              "type": "string"
            }
          ]
        },
        "temperature": {
          "type": "integer"
        },
        "topP": {
          "type": "integer"
        }
      },
      "required": [
        "maxTokenCount",
        "stopSequences",
        "temperature",
        "topP"
      ]
    }
  },
  "required": [
    "inputText",
    "textGenerationConfig"
  ]
}

  • Titan Text Lite V1 with id amazon.titan-text-lite-v1 Lite is a light weight efficient model, ideal for fine-tuning of English-language tasks.

Json schema for request

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "type": "object",
  "properties": {
    "inputText": {
      "type": "string"
    },
    "textGenerationConfig": {
      "type": "object",
      "properties": {
        "maxTokenCount": {
          "type": "integer"
        },
        "stopSequences": {
          "type": "array",
          "items": [
            {
              "type": "string"
            }
          ]
        },
        "temperature": {
          "type": "integer"
        },
        "topP": {
          "type": "integer"
        }
      },
      "required": [
        "maxTokenCount",
        "stopSequences",
        "temperature",
        "topP"
      ]
    }
  },
  "required": [
    "inputText",
    "textGenerationConfig"
  ]
}

  • Titan Image Generator G1 with id amazon.titan-image-generator-v1 It generates images from text, and allows users to upload and edit an existing image. Users can edit an image with a text prompt (without a mask) or parts of an image with an image mask. You can extend the boundaries of an image with outpainting, and fill in an image with inpainting.

Json schema for request

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "type": "object",
  "properties": {
    "textToImageParams": {
      "type": "object",
      "properties": {
        "text": {
          "type": "string"
        },
        "negativeText": {
          "type": "string"
        }
      },
      "required": [
        "text",
        "negativeText"
      ]
    },
    "taskType": {
      "type": "string"
    },
    "imageGenerationConfig": {
      "type": "object",
      "properties": {
        "cfgScale": {
          "type": "integer"
        },
        "seed": {
          "type": "integer"
        },
        "quality": {
          "type": "string"
        },
        "width": {
          "type": "integer"
        },
        "height": {
          "type": "integer"
        },
        "numberOfImages": {
          "type": "integer"
        }
      },
      "required": [
        "cfgScale",
        "seed",
        "quality",
        "width",
        "height",
        "numberOfImages"
      ]
    }
  },
  "required": [
    "textToImageParams",
    "taskType",
    "imageGenerationConfig"
  ]
}

  • Titan Embeddings G1 with id amazon.titan-embed-text-v1 The Amazon Titan Embeddings G1 - Text – Text v1.2 can intake up to 8k tokens and outputs a vector of 1,536 dimensions. The model also works in 25+ different language

Json schema for request

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "type": "object",
  "properties": {
    "inputText": {
      "type": "string"
    }
  },
  "required": [
    "inputText"
  ]
}

  • Jurassic2-Ultra with id ai21.j2-ultra-v1 Jurassic-2 Ultra is AI21’s most powerful model for complex tasks that require advanced text generation and comprehension.

Json schema for request

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "type": "object",
  "properties": {
    "prompt": {
      "type": "string"
    },
    "maxTokens": {
      "type": "integer"
    },
    "temperature": {
      "type": "integer"
    },
    "topP": {
      "type": "integer"
    },
    "stopSequences": {
      "type": "array",
      "items": [
        {
          "type": "string"
        }
      ]
    },
    "presencePenalty": {
      "type": "object",
      "properties": {
        "scale": {
          "type": "integer"
        }
      },
      "required": [
        "scale"
      ]
    },
    "frequencyPenalty": {
      "type": "object",
      "properties": {
        "scale": {
          "type": "integer"
        }
      },
      "required": [
        "scale"
      ]
    }
  },
  "required": [
    "prompt",
    "maxTokens",
    "temperature",
    "topP",
    "stopSequences",
    "presencePenalty",
    "frequencyPenalty"
  ]
}

  • Jurassic2-Mid with id ai21.j2-mid-v1 Jurassic-2 Mid is less powerful than Ultra, yet carefully designed to strike the right balance between exceptional quality and affordability.

Json schema for request

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "type": "object",
  "properties": {
    "prompt": {
      "type": "string"
    },
    "maxTokens": {
      "type": "integer"
    },
    "temperature": {
      "type": "integer"
    },
    "topP": {
      "type": "integer"
    },
    "stopSequences": {
      "type": "array",
      "items": [
        {
          "type": "string"
        }
      ]
    },
    "presencePenalty": {
      "type": "object",
      "properties": {
        "scale": {
          "type": "integer"
        }
      },
      "required": [
        "scale"
      ]
    },
    "frequencyPenalty": {
      "type": "object",
      "properties": {
        "scale": {
          "type": "integer"
        }
      },
      "required": [
        "scale"
      ]
    }
  },
  "required": [
    "prompt",
    "maxTokens",
    "temperature",
    "topP",
    "stopSequences",
    "presencePenalty",
    "frequencyPenalty"
  ]
}

  • Claude Instant V1.2 with id anthropic.claude-instant-v1 A fast, affordable yet still very capable model, which can handle a range of tasks including casual dialogue, text analysis, summarization, and document question-answering.

Json schema for request

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "type": "object",
  "properties": {
    "prompt": {
      "type": "string"
    },
    "max_tokens_to_sample": {
      "type": "integer"
    },
    "stop_sequences": {
      "type": "array",
      "items": [
        {
          "type": "string"
        }
      ]
    },
    "temperature": {
      "type": "number"
    },
    "top_p": {
      "type": "integer"
    },
    "top_k": {
      "type": "integer"
    },
    "anthropic_version": {
      "type": "string"
    }
  },
  "required": [
    "prompt",
    "max_tokens_to_sample",
    "stop_sequences",
    "temperature",
    "top_p",
    "top_k",
    "anthropic_version"
  ]
}

  • Claude 2 with id anthropic.claude-v2 Anthropic’s highly capable model across a wide range of tasks from sophisticated dialogue and creative content generation to detailed instruction following.

Json schema for request

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "type": "object",
  "properties": {
    "prompt": {
      "type": "string"
    },
    "max_tokens_to_sample": {
      "type": "integer"
    },
    "stop_sequences": {
      "type": "array",
      "items": [
        {
          "type": "string"
        }
      ]
    },
    "temperature": {
      "type": "number"
    },
    "top_p": {
      "type": "integer"
    },
    "top_k": {
      "type": "integer"
    },
    "anthropic_version": {
      "type": "string"
    }
  },
  "required": [
    "prompt",
    "max_tokens_to_sample",
    "stop_sequences",
    "temperature",
    "top_p",
    "top_k",
    "anthropic_version"
  ]
}

  • Claude 2.1 with id anthropic.claude-v2:1 An update to Claude 2 that features double the context window, plus improvements across reliability, hallucination rates, and evidence-based accuracy in long document and RAG contexts.

Json schema for request

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "type": "object",
  "properties": {
    "prompt": {
      "type": "string"
    },
    "max_tokens_to_sample": {
      "type": "integer"
    },
    "stop_sequences": {
      "type": "array",
      "items": [
        {
          "type": "string"
        }
      ]
    },
    "temperature": {
      "type": "number"
    },
    "top_p": {
      "type": "integer"
    },
    "top_k": {
      "type": "integer"
    },
    "anthropic_version": {
      "type": "string"
    }
  },
  "required": [
    "prompt",
    "max_tokens_to_sample",
    "stop_sequences",
    "temperature",
    "top_p",
    "top_k",
    "anthropic_version"
  ]
}

  • Claude 3 Sonnet with id anthropic.claude-3-sonnet-20240229-v1:0 Claude 3 Sonnet by Anthropic strikes the ideal balance between intelligence and speed—particularly for enterprise workloads.

Json schema for request

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "type": "object",
  "properties": {
    "messages": {
      "type": "array",
      "items": [
        {
          "type": "object",
          "properties": {
            "role": {
              "type": "string"
            },
            "content": {
              "type": "array",
              "items": [
                {
                  "type": "object",
                  "properties": {
                    "type": {
                      "type": "string"
                    },
                    "text": {
                      "type": "string"
                    }
                  },
                  "required": [
                    "type",
                    "text"
                  ]
                }
              ]
            }
          },
          "required": [
            "role",
            "content"
          ]
        }
      ]
    },
    "max_tokens": {
      "type": "integer"
    },
    "anthropic_version": {
      "type": "string"
    }
  },
  "required": [
    "messages",
    "max_tokens",
    "anthropic_version"
  ]
}

  • Claude 3 Haiku with id anthropic.claude-3-haiku-20240307-v1:0 Claude 3 Haiku is Anthropic’s fastest, most compact model for near-instant responsiveness. It answers simple queries and requests with speed.

Json schema for request

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "type": "object",
  "properties": {
    "messages": {
      "type": "array",
      "items": [
        {
          "type": "object",
          "properties": {
            "role": {
              "type": "string"
            },
            "content": {
              "type": "array",
              "items": [
                {
                  "type": "object",
                  "properties": {
                    "type": {
                      "type": "string"
                    },
                    "text": {
                      "type": "string"
                    }
                  },
                  "required": [
                    "type",
                    "text"
                  ]
                }
              ]
            }
          },
          "required": [
            "role",
            "content"
          ]
        }
      ]
    },
    "max_tokens": {
      "type": "integer"
    },
    "anthropic_version": {
      "type": "string"
    }
  },
  "required": [
    "messages",
    "max_tokens",
    "anthropic_version"
  ]
}

Bedrock Producer operations

Camel-AWS Bedrock component provides the following operation on the producer side:

  • invokeTextModel

  • invokeImageModel

  • invokeEmbeddingsModel

Examples

Producer Examples

  • invokeTextModel: this operation will invoke a model from Bedrock. This is an example for both Titan Express and Titan Lite.

from("direct:invoke")
    .to("aws-bedrock://test?bedrockRuntimeClient=#amazonBedrockRuntimeClient&operation=invokeTextModel&modelId="
                            + BedrockModels.TITAN_TEXT_EXPRESS_V1.model))

and you can then send to the direct endpoint something like

        final Exchange result = template.send("direct:invoke", exchange -> {
            ObjectMapper mapper = new ObjectMapper();
            ObjectNode rootNode = mapper.createObjectNode();
            rootNode.put("inputText",
                    "User: Generate synthetic data for daily product sales in various categories - include row number, product name, category, date of sale and price. Produce output in JSON format. Count records and ensure there are no more than 5.");

            ArrayNode stopSequences = mapper.createArrayNode();
            stopSequences.add("User:");
            ObjectNode childNode = mapper.createObjectNode();
            childNode.put("maxTokenCount", 1024);
            childNode.put("stopSequences", stopSequences);
            childNode.put("temperature", 0).put("topP", 1);

            rootNode.put("textGenerationConfig", childNode);
            exchange.getMessage().setBody(mapper.writer().writeValueAsString(rootNode));
            exchange.getMessage().setHeader(BedrockConstants.MODEL_CONTENT_TYPE, "application/json");
            exchange.getMessage().setHeader(BedrockConstants.MODEL_ACCEPT_CONTENT_TYPE, "application/json");
        });

where template is a ProducerTemplate.

  • invokeImageModel: this operation will invoke a model from Bedrock. This is an example for both Titan Express and Titan Lite.

from("direct:invoke")
    .to("aws-bedrock://test?bedrockRuntimeClient=#amazonBedrockRuntimeClient&operation=invokeImageModel&modelId="
                            + BedrockModels.TITAN_IMAGE_GENERATOR_V1.model))
                        .split(body())
                        .unmarshal().base64()
                        .setHeader("CamelFileName", simple("image-${random(128)}.png")).to("file:target/generated_images")

and you can then send to the direct endpoint something like

        final Exchange result = template.send("direct:send_titan_image", exchange -> {
            ObjectMapper mapper = new ObjectMapper();
            ObjectNode rootNode = mapper.createObjectNode();
            ObjectNode textParameter = mapper.createObjectNode();
            textParameter.putIfAbsent("text",
                    new TextNode("A Sci-fi camel running in the desert"));
            rootNode.putIfAbsent("textToImageParams", textParameter);
            rootNode.putIfAbsent("taskType", new TextNode("TEXT_IMAGE"));
            ObjectNode childNode = mapper.createObjectNode();
            childNode.putIfAbsent("numberOfImages", new IntNode(3));
            childNode.putIfAbsent("quality", new TextNode("standard"));
            childNode.putIfAbsent("cfgScale", new IntNode(8));
            childNode.putIfAbsent("height", new IntNode(512));
            childNode.putIfAbsent("width", new IntNode(512));
            childNode.putIfAbsent("seed", new IntNode(0));

            rootNode.putIfAbsent("imageGenerationConfig", childNode);

            exchange.getMessage().setBody(mapper.writer().writeValueAsString(rootNode));
            exchange.getMessage().setHeader(BedrockConstants.MODEL_CONTENT_TYPE, "application/json");
            exchange.getMessage().setHeader(BedrockConstants.MODEL_ACCEPT_CONTENT_TYPE, "application/json");
        });

where template is a ProducerTemplate.

  • invokeEmbeddingsModel: this operation will invoke an Embeddings model from Bedrock. This is an example for Titan Embeddings G1.

from("direct:send_titan_embeddings")
    .to("aws-bedrock:label?useDefaultCredentialsProvider=true&region=us-east-1&operation=invokeEmbeddingsModel&modelId="
    + BedrockModels.TITAN_EMBEDDINGS_G1.model)
    .to(result);

and you can then send to the direct endpoint something like

        final Exchange result = template.send("direct:send_titan_embeddings", exchange -> {
            ObjectMapper mapper = new ObjectMapper();
            ObjectNode rootNode = mapper.createObjectNode();
            rootNode.putIfAbsent("inputText",
                    new TextNode("A Sci-fi camel running in the desert"));

            exchange.getMessage().setBody(mapper.writer().writeValueAsString(rootNode));
            exchange.getMessage().setHeader(BedrockConstants.MODEL_CONTENT_TYPE, "application/json");
            exchange.getMessage().setHeader(BedrockConstants.MODEL_ACCEPT_CONTENT_TYPE, "*/*");
        });

where template is a ProducerTemplate.

Dependencies

Maven users will need to add the following dependency to their pom.xml.

pom.xml

<dependency>
    <groupId>org.apache.camel</groupId>
    <artifactId>camel-aws-bedrock</artifactId>
    <version>${camel-version}</version>
</dependency>

where ${camel-version} must be replaced by the actual version of Camel.