diff --git a/models/spring-ai-bedrock/README.md b/models/spring-ai-bedrock/README.md
index 1b2b38072..daabdbdf0 100644
--- a/models/spring-ai-bedrock/README.md
+++ b/models/spring-ai-bedrock/README.md
@@ -2,7 +2,6 @@
[Amazon Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html) is a managed service that provides foundation models from various AI providers, available through a unified API.
-
Spring AI implements `API` clients for the [Bedrock models](https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids-arns.html) along with implementations for the `ChatClient`, `StreamingChatClient` and the `EmbeddingClient`.
The API clients provide structured, type-safe implementation for the Bedrock models, while the `ChatClient`, `StreamingChatClient` and the `EmbeddingClient` implementations provide Chat and Embedding clients compliant with the Spring-AI API. Later can be used interchangeably with the other (e.g. OpenAI, Azure OpenAI,
@@ -21,64 +20,13 @@ Also Spring-AI provides Spring Auto-Configurations and Boot Starters for all cli
Go to [Amazon Bedrock](https://us-east-1.console.aws.amazon.com/bedrock/home) and from the [Model Access](https://us-east-1.console.aws.amazon.com/bedrock/home?region=us-east-1#/modelaccess) menu on the left configure the access to the models you are going to use.
-## Quick start
+## User guides
-Add the `spring-ai-bedrock-ai-spring-boot-starter` dependency to your project POM:
+[Amazon Bedrock Overview](https://docs.spring.io/spring-ai/reference/api/bedrock.html)
-```xml
-
- spring-ai-bedrock-ai-spring-boot-starter
- org.springframework.ai
- 0.8.0-SNAPSHOT
-
-```
-
-### Connect to AWS Bedrock
-
-Use the `BedrockAwsConnectionProperties` to configure the AWS credentials and region:
-
-```shell
-spring.ai.bedrock.aws.region=us-east-1
-
-spring.ai.bedrock.aws.access-key=YOUR_ACCESS_KEY
-spring.ai.bedrock.aws.secret-key=YOUR_SECRET_KEY
-```
-
-The `region` property is compulsory.
-
-The AWS credentials are resolved in the following this order:
-
-* Spring-AI Bedrock `spring.ai.bedrock.aws.access-key` and `spring.ai.bedrock.aws.secret-key` properties.
-* Java System Properties - `aws.accessKeyId` and `aws.secretAccessKey`
-* Environment Variables - `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY`
-* Web Identity Token credentials from system properties or environment variables
-* Credential profiles file at the default location (`~/.aws/credentials`) shared by all AWS SDKs and the AWS CLI
-* Credentials delivered through the Amazon EC2 container service if `AWS_CONTAINER_CREDENTIALS_RELATIVE_URI`" environment variable is set and security manager has permission to access the variable,
-* Instance profile credentials delivered through the Amazon EC2 metadata service or set the `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY` environment variables.
-
-### Enable selected Bedrock model
-
-> **NOTE**: By default all models are disabled. You have to enable the chosen Bedrock models explicitly, using the `spring.ai.bedrock...enabled=true` property.
-
-Here are the supported `` and `` combinations:
-
-| Model | Chat | Chat Streaming | Embedding |
-| ------------- | ------------- | ------------- | ------------- |
-| llama2 | Yes | Yes | No |
-| cohere | Yes | Yes | Yes |
-| anthropic | Yes | Yes | No |
-| jurassic2 | Yes | No | No |
-| titan | Yes | Yes | Yes (no batch mode!) |
-
-For example to enable the bedrock Llama2 Chat client you need to set the
-`spring.ai.bedrock.llama2.chat.enabled=true`.
-
-Next you can use the `spring.ai.bedrock...*` properties to configure each model as provided in its documentation:
-
-* [Spring AI Bedrock Llama2 Chat](./README_LLAMA2_CHAT.md) - `spring.ai.bedrock.llama2.chat.enabled=true`
-* [Spring AI Bedrock Cohere Chat](./README_COHERE_CHAT.md) - `spring.ai.bedrock.cohere.chat.enabled=true`
-* [Spring AI Bedrock Cohere Embedding](./README_COHERE_EMBEDDING.md) - `spring.ai.bedrock.cohere.embedding.enabled=true`
-* [Spring AI Bedrock Anthropic Chat](./README_ANTHROPIC_CHAT.md) - `spring.ai.bedrock.anthropic.chat.enabled=true`
-* [Spring AI Bedrock Titan Chat](./README_TITAN_CHAT.md) - `spring.ai.bedrock.titan.chat.enabled=true`
-* [Spring AI Bedrock Titan Embedding](./README_TITAN_EMBEDDING.md) - `spring.ai.bedrock.titan.embedding.enabled=true`
-* (WIP) [Spring AI Bedrock Ai21 Jurassic2 Chat](./README_JURASSIC2_CHAT.md) - `spring.ai.bedrock.jurassic2.chat.enabled=true`
+- [Anthropic Chat Documentation](https://docs.spring.io/spring-ai/reference/api/clients/bedrock/bedrock-anthropic.html).
+- [Cohere Chat Documentation](https://docs.spring.io/spring-ai/reference/api/clients/bedrock/bedrock-cohere.html).
+- [Cohere Embedding Documentation](https://docs.spring.io/spring-ai/reference/api/embeddings/bedrock-cohere-embedding.html).
+- [Llama2 Chat Documentation](https://docs.spring.io/spring-ai/reference/api/clients/bedrock/bedrock-llama2.html).
+- [Titan Chat Documentation](https://docs.spring.io/spring-ai/reference/api/clients/bedrock/bedrock-titan.html).
+- [Titan Embedding Documentation](https://docs.spring.io/spring-ai/reference/api/embeddings/bedrock-titan-embedding.html).
diff --git a/models/spring-ai-bedrock/README_ANTHROPIC_CHAT.md b/models/spring-ai-bedrock/README_ANTHROPIC_CHAT.md
deleted file mode 100644
index 4c55598e2..000000000
--- a/models/spring-ai-bedrock/README_ANTHROPIC_CHAT.md
+++ /dev/null
@@ -1,5 +0,0 @@
-# Bedrock Anthropic
-
-Provides Bedrock Anthropic Chat API and Spring-AI chat clients.
-
-Visit the Spring AI [Bedrock Anthropic Chat Documentation](https://docs.spring.io/spring-ai/reference/api/clients/bedrock/bedrock-anthropic.html).
\ No newline at end of file
diff --git a/models/spring-ai-bedrock/README_COHERE_CHAT.md b/models/spring-ai-bedrock/README_COHERE_CHAT.md
deleted file mode 100644
index e539a0a58..000000000
--- a/models/spring-ai-bedrock/README_COHERE_CHAT.md
+++ /dev/null
@@ -1,5 +0,0 @@
-# Bedrock Cohere Chat
-
-Provides Bedrock Cohere Chat clients.
-
-Visit the Spring AI [Bedrock Cohere Chat Documentation](https://docs.spring.io/spring-ai/reference/api/clients/bedrock/bedrock-cohere.html).
\ No newline at end of file
diff --git a/models/spring-ai-bedrock/README_COHERE_EMBEDDING.md b/models/spring-ai-bedrock/README_COHERE_EMBEDDING.md
deleted file mode 100644
index 76a2f660d..000000000
--- a/models/spring-ai-bedrock/README_COHERE_EMBEDDING.md
+++ /dev/null
@@ -1,4 +0,0 @@
-# Bedrock Cohere Embedding
-
-Visit the Spring AI [Bedrock Cohere Embedding Documentation](https://docs.spring.io/spring-ai/reference/api/embeddings/bedrock-cohere-embedding.html).
-
diff --git a/models/spring-ai-bedrock/README_LLAMA2_CHAT.md b/models/spring-ai-bedrock/README_LLAMA2_CHAT.md
deleted file mode 100644
index fa7a39a82..000000000
--- a/models/spring-ai-bedrock/README_LLAMA2_CHAT.md
+++ /dev/null
@@ -1,5 +0,0 @@
-# Bedrock Llama2
-
-Provides Bedrock Llama2 Chat API and Spring-AI chat clients.
-
-Visit the Spring AI [Bedrock Llama2 Chat Documentation](https://docs.spring.io/spring-ai/reference/api/clients/bedrock/bedrock-llama2.html).
\ No newline at end of file
diff --git a/models/spring-ai-bedrock/README_TITAN_CHAT.md b/models/spring-ai-bedrock/README_TITAN_CHAT.md
deleted file mode 100644
index a01ae8deb..000000000
--- a/models/spring-ai-bedrock/README_TITAN_CHAT.md
+++ /dev/null
@@ -1,3 +0,0 @@
-# Bedrock Titan Chat
-
-Visit the Spring AI [Bedrock Titan Chat Documentation](https://docs.spring.io/spring-ai/reference/api/clients/bedrock/bedrock-titan.html).
\ No newline at end of file
diff --git a/models/spring-ai-bedrock/README_TITAN_EMBEDDING.md b/models/spring-ai-bedrock/README_TITAN_EMBEDDING.md
deleted file mode 100644
index 7065f09f3..000000000
--- a/models/spring-ai-bedrock/README_TITAN_EMBEDDING.md
+++ /dev/null
@@ -1,95 +0,0 @@
-# 1. Bedrock Titan Embedding
-
-Use the [TitanEmbeddingBedrockApi.java](src/main/java/org/springframework/ai/bedrock/titan/api/TitanEmbeddingBedrockApi.java) Bedrock Embedding client to implement `EmbeddingClient`.
-
-Consult the the existing Cohere embedding client implementation.
-Mind that Titan doesn't support batch embedding. You have to either emulate it (could be very expensive) or throw a not supported exception.
-
-## 1.1 TitanEmbeddingBedrockApi
-
-[TitanEmbeddingBedrockApi](./src/main/java/org/springframework/ai/bedrock/titan/api/TitanEmbeddingBedrockApi.java) provides is lightweight Java client on top of AWS Bedrock [Titan Embedding models](https://docs.aws.amazon.com/bedrock/latest/userguide/titan-embedding-models.html).
-
-> TitanEmbeddingBedrockApi supports Text and Image embedding.
-
-
-> **NOTE:** TitanEmbeddingBedrockApi does NOT support batch embedding.
-
-Following class diagram illustrates the Llama2ChatBedrockApi interface and building blocks:
-
-
-
-The CohereEmbeddingBedrockApi supports the `amazon.titan-embed-image-v1` and `amazon.titan-embed-image-v1` models for single and batch embedding computation.
-
-Here is a simple snippet how to use the api programmatically:
-
-```java
-TitanEmbeddingBedrockApi titanEmbedApi = new TitanEmbeddingBedrockApi(
- TitanEmbeddingModel.TITAN_EMBED_TEXT_V1.id(), Region.US_EAST_1.id());
-
-TitanEmbeddingRequest request = TitanEmbeddingRequest.builder()
- .withInputText("I like to eat apples.")
- .build();
-
-TitanEmbeddingResponse response = titanEmbedApi.embedding(request);
-```
-
-To embed an image you need to convert it into base64 format:
-
-```java
-TitanEmbeddingBedrockApi titanEmbedApi = new TitanEmbeddingBedrockApi(
- TitanEmbeddingModel.TITAN_EMBED_IMAGE_V1.id(), Region.US_EAST_1.id());
-
-byte[] image = new DefaultResourceLoader()
- .getResource("classpath:/spring_framework.png")
- .getContentAsByteArray();
-
-
-TitanEmbeddingRequest request = TitanEmbeddingRequest.builder()
- .withInputImage(Base64.getEncoder().encodeToString(image))
- .build();
-
-TitanEmbeddingResponse response = titanEmbedApi.embedding(request);
-```
-
-## 1.2 BedrockTitanEmbeddingClient
-
-[BedrockTitanEmbeddingClient](./src/main/java/org/springframework/ai/bedrock/titan/BedrockTitanEmbeddingClient.java) implements the Spring-Ai `EmbeddingClient` on top of the `TitanEmbeddingBedrockApi`.
-
-You can use like this:
-
-```java
-@Bean
-public TitanEmbeddingBedrockApi titanEmbeddingApi() {
- return new TitanEmbeddingBedrockApi(
- TitanEmbeddingModel.TITAN_EMBED_IMAGE_V1.id(), Region.US_EAST_1.id());
-}
-
-@Bean
-public BedrockTitanEmbeddingClient titanEmbedding(TitanEmbeddingBedrockApi titanEmbeddingApi) {
- return new BedrockTitanEmbeddingClient(titanEmbeddingApi);
-}
-```
-
-or you can leverage the `spring-ai-bedrock-ai-spring-boot-starter` Boot starter. For this add the following dependency:
-
-```xml
-
- spring-ai-bedrock-ai-spring-boot-starter
- org.springframework.ai
- 0.8.0-SNAPSHOT
-
-```
-
-**NOTE:** You have to enable the Bedrock Titan embedding client with `spring.ai.bedrock.titan.embedding.enabled=true`.
-By default the client is disabled.
-
-Use the `BedrockTitanEmbeddingProperties` to configure the Bedrock Titan embedding client:
-
-| Property | Description | Default |
-| ------------- | ------------- | ------------- |
-| spring.ai.bedrock.aws.region | AWS region to use. | us-east-1 |
-| spring.ai.bedrock.aws.accessKey | AWS credentials access key. | |
-| spring.ai.bedrock.aws.secretKey | AWS credentials secret key. | |
-| spring.ai.bedrock.titan.embedding.enable | Enable Bedrock Titan embedding client. Disabled by default | false |
-| spring.ai.bedrock.titan.embedding.model | The model id to use. See the `TitanEmbeddingModel` for the supported models. | amazon.titan-embed-image-v1 |
-| spring.ai.bedrock.titan.embedding.inputType | Titan Embedding API input types. Could be either text or image (encoded in base64). | TEXT |
diff --git a/models/spring-ai-bedrock/src/test/resources/doc/Bedrock Cohere Chat API.jpg b/models/spring-ai-bedrock/src/test/resources/doc/Bedrock Cohere Chat API.jpg
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diff --git a/models/spring-ai-bedrock/src/test/resources/doc/Bedrock-Llama2-Chat-API.jpg b/models/spring-ai-bedrock/src/test/resources/doc/Bedrock-Llama2-Chat-API.jpg
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diff --git a/spring-ai-docs/src/main/antora/modules/ROOT/images/bedrock/bedrock-titan-embedding-low-level-api.jpg b/spring-ai-docs/src/main/antora/modules/ROOT/images/bedrock/bedrock-titan-embedding-low-level-api.jpg
new file mode 100644
index 000000000..f0caf4f58
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diff --git a/spring-ai-docs/src/main/antora/modules/ROOT/nav.adoc b/spring-ai-docs/src/main/antora/modules/ROOT/nav.adoc
index 7d6fcc17d..52449cfc3 100644
--- a/spring-ai-docs/src/main/antora/modules/ROOT/nav.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/nav.adoc
@@ -10,6 +10,7 @@
*** xref:api/embeddings/postgresml-embeddings.adoc[]
*** xref:api/bedrock.adoc[Amazon Bedrock Embedding]
**** xref:api/embeddings/bedrock-cohere-embedding.adoc[]
+**** xref:api/embeddings/bedrock-titan-embedding.adoc[]
** xref:api/chatclient.adoc[]
*** xref:api/clients/openai-chat.adoc[]
*** xref:api/clients/azure-openai-chat.adoc[]
diff --git a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/bedrock.adoc b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/bedrock.adoc
index fa6abe2a0..e293b05e5 100644
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/bedrock.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/bedrock.adoc
@@ -74,7 +74,7 @@ Here are the supported `` and `` combinations:
| llama2 | Yes | Yes | No
| cohere | Yes | Yes | Yes
| anthropic | Yes | Yes | No
-| jurassic2 | Yes | No | No
+| jurassic2 (WIP) | Yes | No | No
| titan | Yes | Yes | Yes (however, no batch support)
|====
@@ -89,5 +89,6 @@ For more information, refer to the documentation below for each supported model.
* xref:api/clients/bedrock/bedrock-cohere.adoc[Spring AI Bedrock Cohere Chat]: `spring.ai.bedrock.cohere.chat.enabled=true`
* xref:api/embeddings/bedrock-cohere-embedding.adoc[Spring AI Bedrock Cohere Embeddings]: `spring.ai.bedrock.cohere.embedding.enabled=true`
* xref:api/clients/bedrock/bedrock-titan.adoc[Spring AI Bedrock Titan Chat]: `spring.ai.bedrock.titan.chat.enabled=true`
+* xref:api/embeddings/bedrock-titan-embedding.adoc[Spring AI Bedrock Titan Embeddings]: `spring.ai.bedrock.titan.embedding.enabled=true`
// * xref:api/clients/bedrock/bedrock-jurassic2-chat.adoc[(WIP)Spring AI Bedrock Jurassic Chat]: `spring.ai.bedrock.jurassic2.chat.enabled=true`
diff --git a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings.adoc b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings.adoc
index d50ee03bd..aa82d3855 100644
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings.adoc
@@ -156,3 +156,4 @@ Internally the various `EmbeddingClient` implementations use different low-level
* xref:api/embeddings/onnx.adoc[Spring AI Transformers (ONNX) Embeddings]
* xref:api/embeddings/postgresml-embeddings.adoc[Spring AI PostgresML Embeddings]
* xref:api/embeddings/bedrock-cohere-embedding.adoc[Spring AI Bedrock Cohere Embeddings]
+* xref:api/embeddings/bedrock-titan-embedding.adoc[Spring AI Bedrock Titan Embeddings]
diff --git a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/bedrock-titan-embedding.adoc b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/bedrock-titan-embedding.adoc
new file mode 100644
index 000000000..dd25e6d5b
--- /dev/null
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/bedrock-titan-embedding.adoc
@@ -0,0 +1,199 @@
+= Titan Embedding
+
+Provides Bedrock Titan Embedding client.
+link:https://aws.amazon.com/bedrock/titan/[Amazon Titan] foundation models (FMs) provide customers with a breadth of high-performing image, multimodal, and text model choices, via a fully managed API.
+Amazon Titan models are created by AWS and pretrained on large datasets, making them powerful, general-purpose models built to support a variety of use cases, while also supporting the responsible use of AI.
+Use them as is or privately customize them with your own data.
+
+NOTE: Bedrock Titan Embedding supports Text and Image embedding.
+
+NOTE: Bedrock Titan Embedding does NOT support batch embedding.
+
+The https://aws.amazon.com/bedrock/titan/[AWS Bedrock Titan Model Page] and https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html[Amazon Bedrock User Guide] contains detailed information on how to use the AWS hosted model.
+
+== Prerequisites
+
+Refer to the xref:api/bedrock.adoc[Spring AI documentation on Amazon Bedrock] for setting up API access.
+
+== Auto-configuration
+
+Add the `spring-ai-bedrock-ai-spring-boot-starter` dependency to your project's Maven `pom.xml` file:
+
+[source,xml]
+----
+
+ org.springframework.ai
+ spring-ai-bedrock-ai-spring-boot-starter
+ 0.8.0-SNAPSHOT
+
+----
+
+or to your Gradle `build.gradle` build file.
+
+[source,gradle]
+----
+dependencies {
+ implementation 'org.springframework.ai:spring-ai-bedrock-ai-spring-boot-starter:0.8.0-SNAPSHOT'
+}
+----
+
+TIP: Refer to the xref:getting-started.adoc#_dependency_management[Dependency Management] section to add Milestone and/or Snapshot Repositories to your build file.
+
+=== Enable Titan Embedding Support
+
+By default the Titan embedding model is disabled.
+To enable it set the `spring.ai.bedrock.titan.embedding.enabled` property to `true`.
+Exporting environment variable is one way to set this configuration property:
+
+[source,shell]
+----
+export SPRING_AI_BEDROCK_TITAN_EMBEDDING_ENABLED=true
+----
+
+=== Embedding Properties
+
+The prefix `spring.ai.bedrock.aws` is the property prefix to configure the connection to AWS Bedrock.
+
+[cols="3,4,1"]
+|====
+| Property | Description | Default
+
+| spring.ai.bedrock.aws.region | AWS region to use. | us-east-1
+| spring.ai.bedrock.aws.access-key | AWS access key. | -
+| spring.ai.bedrock.aws.secret-key | AWS secret key. | -
+|====
+
+The prefix `spring.ai.bedrock.titan.embedding` (defined in `BedrockTitanEmbeddingProperties`) is the property prefix that configures the embedding client implementation for Titan.
+
+[cols="3,4,1"]
+|====
+| Property | Description | Default
+| spring.ai.bedrock.titan.embedding.enabled | Enable or disable support for Titan embedding | false
+| spring.ai.bedrock.titan.embedding.model | The model id to use. See the `TitanEmbeddingModel` for the supported models. | amazon.titan-embed-image-v1
+|====
+
+Supported values are: `amazon.titan-embed-image-v1` and `amazon.titan-embed-text-v1`.
+Model ID values can also be found in the https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids-arns.html[AWS Bedrock documentation for base model IDs].
+
+
+=== Sample Controller (Auto-configuration)
+
+https://start.spring.io/[Create] a new Spring Boot project and add the `spring-ai-bedrock-ai-spring-boot-starter` to your pom (or gradle) dependencies.
+
+Add a `application.properties` file, under the `src/main/resources` directory, to enable and configure the Titan Embedding client:
+
+[source]
+----
+spring.ai.bedrock.aws.region=eu-central-1
+spring.ai.bedrock.aws.access-key=${AWS_ACCESS_KEY_ID}
+spring.ai.bedrock.aws.secret-key=${AWS_SECRET_ACCESS_KEY}
+
+spring.ai.bedrock.titan.embedding.enabled=true
+----
+
+TIP: replace the `regions`, `access-key` and `secret-key` with your AWS credentials.
+
+This will create a `EmbeddingController` implementation that you can inject into your class.
+Here is an example of a simple `@Controller` class that uses the chat client for text generations.
+
+[source,java]
+----
+@RestController
+public class EmbeddingController {
+
+ private final EmbeddingClient embeddingClient;
+
+ @Autowired
+ public EmbeddingController(EmbeddingClient embeddingClient) {
+ this.embeddingClient = embeddingClient;
+ }
+
+ @GetMapping("/ai/embedding")
+ public Map embed(@RequestParam(value = "message", defaultValue = "Tell me a joke") String message) {
+ EmbeddingResponse embeddingResponse = this.embeddingClient.embedForResponse(List.of(message));
+ return Map.of("embedding", embeddingResponse);
+ }
+}
+----
+
+== Manual Configuration
+
+The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/titan/BedrockTitanEmbeddingClient.java[BedrockTitanEmbeddingClient] implements the `EmbeddingClient` and uses the <> to connect to the Bedrock Titan service.
+
+Add the `spring-ai-bedrock` dependency to your project's Maven `pom.xml` file:
+
+[source,xml]
+----
+
+ org.springframework.ai
+ spring-ai-bedrock
+ 0.8.0-SNAPSHOT
+
+----
+
+or to your Gradle `build.gradle` build file.
+
+[source,gradle]
+----
+dependencies {
+ implementation 'org.springframework.ai:spring-ai-bedrock:0.8.0-SNAPSHOT'
+}
+----
+
+TIP: Refer to the xref:getting-started.adoc#_dependency_management[Dependency Management] section to add Milestone and/or Snapshot Repositories to your build file.
+
+Next, create an https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/titan/BedrockTitanEmbeddingClient.java[BedrockTitanEmbeddingClient] and use it for text embeddings:
+
+[source,java]
+----
+var titanEmbeddingApi = new TitanEmbeddingBedrockApi(
+ TitanEmbeddingModel.TITAN_EMBED_IMAGE_V1.id(), Region.US_EAST_1.id());
+
+var embeddingClient new BedrockTitanEmbeddingClient(titanEmbeddingApi);
+
+EmbeddingResponse embeddingResponse = embeddingClient
+ .embedForResponse(List.of("Hello World")); // NOTE titan does not support batch embedding.
+----
+
+== Low-level TitanEmbeddingBedrockApi Client [[low-level-api]]
+
+The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/titan/api/TitanEmbeddingBedrockApi.java[TitanEmbeddingBedrockApi] provides is lightweight Java client on top of AWS Bedrock https://docs.aws.amazon.com/bedrock/latest/userguide/titan-multiemb-models.html[Titan Embedding models].
+
+Following class diagram illustrates the TitanEmbeddingBedrockApi interface and building blocks:
+
+image::bedrock/bedrock-titan-embedding-low-level-api.jpg[align="center", width="500px"]
+
+The TitanEmbeddingBedrockApi supports the `amazon.titan-embed-image-v1` and `amazon.titan-embed-image-v1` models for single and batch embedding computation.
+
+Here is a simple snippet how to use the api programmatically:
+
+[source,java]
+----
+TitanEmbeddingBedrockApi titanEmbedApi = new TitanEmbeddingBedrockApi(
+ TitanEmbeddingModel.TITAN_EMBED_TEXT_V1.id(), Region.US_EAST_1.id());
+
+TitanEmbeddingRequest request = TitanEmbeddingRequest.builder()
+ .withInputText("I like to eat apples.")
+ .build();
+
+TitanEmbeddingResponse response = titanEmbedApi.embedding(request);
+----
+
+To embed an image you need to convert it into `base64` format:
+
+[source,java]
+----
+TitanEmbeddingBedrockApi titanEmbedApi = new TitanEmbeddingBedrockApi(
+ TitanEmbeddingModel.TITAN_EMBED_IMAGE_V1.id(), Region.US_EAST_1.id());
+
+byte[] image = new DefaultResourceLoader()
+ .getResource("classpath:/spring_framework.png")
+ .getContentAsByteArray();
+
+
+TitanEmbeddingRequest request = TitanEmbeddingRequest.builder()
+ .withInputImage(Base64.getEncoder().encodeToString(image))
+ .build();
+
+TitanEmbeddingResponse response = titanEmbedApi.embedding(request);
+----
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