Improve Antora documentation layout

- tename /api/clients/ into /api/chat - move the the image from /api/clients to /api - fix the layout inside the chat and embeddings docs. Moving the runtime options and sample controllers at top level. - adjust all affected links.
2024-03-16 11:26:12 +01:00
parent 49a1cc6339
commit 9c19dc1665
40 changed files with 115 additions and 115 deletions
--- a/models/spring-ai-azure-openai/README.md
+++ b/models/spring-ai-azure-openai/README.md
@@ -1,3 +1,3 @@
-[Azure OpenAI Chat Documentation](https://docs.spring.io/spring-ai/reference/api/clients/azure-openai-chat.html)
+[Azure OpenAI Chat Documentation](https://docs.spring.io/spring-ai/reference/api/chat/azure-openai-chat.html)

 [Azure OpenAI Embedding Documentation](https://docs.spring.io/spring-ai/reference/api/embeddings/azure-openai-embeddings.html)
--- a/models/spring-ai-bedrock/README.md
+++ b/models/spring-ai-bedrock/README.md
@@ -1,10 +1,10 @@
 [Amazon Bedrock Overview](https://docs.spring.io/spring-ai/reference/api/bedrock.html)

- [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)
+- [Anthropic Chat Documentation](https://docs.spring.io/spring-ai/reference/api/chat/bedrock/bedrock-anthropic.html)
+- [Cohere Chat Documentation](https://docs.spring.io/spring-ai/reference/api/chat/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)
+- [Llama2 Chat Documentation](https://docs.spring.io/spring-ai/reference/api/chat/bedrock/bedrock-llama2.html)
+- [Titan Chat Documentation](https://docs.spring.io/spring-ai/reference/api/chat/bedrock/bedrock-titan.html)
 - [Titan Embedding Documentation](https://docs.spring.io/spring-ai/reference/api/embeddings/bedrock-titan-embedding.html)

 NOTE: There is not yet an implementation for Jurassic, but you can use the lower level client [Ai21Jurassic2ChatBedrockApi.java](https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/jurassic2/api/Ai21Jurassic2ChatBedrockApi.java) in the meantime.  See [Issue 343](https://github.com/spring-projects/spring-ai/issues/343)
--- a/models/spring-ai-huggingface/README.md
+++ b/models/spring-ai-huggingface/README.md
@@ -1,2 +1,2 @@
-[Huggingface Chat Documentation](https://docs.spring.io/spring-ai/reference/api/clients/huggingface.html)
+[Huggingface Chat Documentation](https://docs.spring.io/spring-ai/reference/api/chat/huggingface.html)

--- a/models/spring-ai-ollama/README.md
+++ b/models/spring-ai-ollama/README.md
@@ -1,3 +1,3 @@
-[Ollama Chat Documentation](https://docs.spring.io/spring-ai/reference/api/clients/ollama-chat.html)
+[Ollama Chat Documentation](https://docs.spring.io/spring-ai/reference/api/chat/ollama-chat.html)

 [Ollama Embedding Documentation](https://docs.spring.io/spring-ai/reference/api/embeddings/ollama-embeddings.html)
--- a/models/spring-ai-openai/README.md
+++ b/models/spring-ai-openai/README.md
@@ -1,7 +1,7 @@
-[OpenAI Chat Documentation](https://docs.spring.io/spring-ai/reference/api/clients/openai-chat.html)
+[OpenAI Chat Documentation](https://docs.spring.io/spring-ai/reference/api/chat/openai-chat.html)

 [OpenAI Embedding Documentation](https://docs.spring.io/spring-ai/reference/api/embeddings/openai-embeddings.html)

-[OpenAI Image Generation](https://docs.spring.io/spring-ai/reference/api/clients/image/openai-image.html)
+[OpenAI Image Generation](https://docs.spring.io/spring-ai/reference/api/image/openai-image.html)

 [OpenAI Transcription Generation](TODO)
--- a/models/spring-ai-vertex-ai-palm2/README.md
+++ b/models/spring-ai-vertex-ai-palm2/README.md
@@ -1,4 +1,4 @@
-[VertexAI PaLM2 Chat Documentation](https://docs.spring.io/spring-ai/reference/api/clients/vertexai-chat.html)
+[VertexAI PaLM2 Chat Documentation](https://docs.spring.io/spring-ai/reference/api/chat/vertexai-chat.html)

 [VertexAI PaLM2 Embedding Documentation](https://docs.spring.io/spring-ai/reference/api/embeddings/vertexai-embeddings.html)

--- a/spring-ai-docs/src/main/antora/modules/ROOT/nav.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/nav.adoc
@@ -3,23 +3,23 @@
 * xref:getting-started.adoc[Getting Started]
 * xref:api/index.adoc[]
 ** xref:api/chatclient.adoc[]
-*** xref:api/clients/openai-chat.adoc[OpenAI]
-**** xref:api/clients/functions/openai-chat-functions.adoc[Function Calling]
-*** xref:api/clients/ollama-chat.adoc[Ollama]
-*** xref:api/clients/azure-openai-chat.adoc[Azure OpenAI]
-**** xref:api/clients/functions/azure-open-ai-chat-functions.adoc[Function Calling]
+*** xref:api/chat/openai-chat.adoc[OpenAI]
+**** xref:api/chat/functions/openai-chat-functions.adoc[Function Calling]
+*** xref:api/chat/ollama-chat.adoc[Ollama]
+*** xref:api/chat/azure-openai-chat.adoc[Azure OpenAI]
+**** xref:api/chat/functions/azure-open-ai-chat-functions.adoc[Function Calling]
 *** xref:api/bedrock-chat.adoc[Amazon Bedrock]
-**** xref:api/clients/bedrock/bedrock-anthropic.adoc[Anthropic]
-**** xref:api/clients/bedrock/bedrock-llama2.adoc[Llama2]
-**** xref:api/clients/bedrock/bedrock-cohere.adoc[Cohere]
-**** xref:api/clients/bedrock/bedrock-titan.adoc[Titan]
-*** xref:api/clients/huggingface.adoc[HuggingFace]
-*** xref:api/clients/google-vertexai.adoc[Google VertexAI]
-**** xref:api/clients/vertexai-palm2-chat.adoc[VertexAI PaLM2 ]
-**** xref:api/clients/vertexai-gemini-chat.adoc[VertexAI Gemini]
-***** xref:api/clients/functions/vertexai-gemini-chat-functions.adoc[Function Calling]
-*** xref:api/clients/mistralai-chat.adoc[Mistral AI]
-**** xref:api/clients/functions/mistralai-chat-functions.adoc[Function Calling]
+**** xref:api/chat/bedrock/bedrock-anthropic.adoc[Anthropic]
+**** xref:api/chat/bedrock/bedrock-llama2.adoc[Llama2]
+**** xref:api/chat/bedrock/bedrock-cohere.adoc[Cohere]
+**** xref:api/chat/bedrock/bedrock-titan.adoc[Titan]
+*** xref:api/chat/huggingface.adoc[HuggingFace]
+*** xref:api/chat/google-vertexai.adoc[Google VertexAI]
+**** xref:api/chat/vertexai-palm2-chat.adoc[VertexAI PaLM2 ]
+**** xref:api/chat/vertexai-gemini-chat.adoc[VertexAI Gemini]
+***** xref:api/chat/functions/vertexai-gemini-chat-functions.adoc[Function Calling]
+*** xref:api/chat/mistralai-chat.adoc[Mistral AI]
+**** xref:api/chat/functions/mistralai-chat-functions.adoc[Function Calling]
 ** xref:api/embeddings.adoc[]
 *** xref:api/embeddings/openai-embeddings.adoc[OpenAI]
 *** xref:api/embeddings/ollama-embeddings.adoc[Ollama]
@@ -32,8 +32,8 @@
 *** xref:api/embeddings/onnx.adoc[Transformers (ONNX)]
 *** xref:api/embeddings/mistralai-embeddings.adoc[Mistral AI]
 ** xref:api/imageclient.adoc[]
-*** xref:api/clients/image/openai-image.adoc[OpenAI]
-*** xref:api/clients/image/stabilityai-image.adoc[Stability]
+*** xref:api/image/openai-image.adoc[OpenAI]
+*** xref:api/image/stabilityai-image.adoc[Stability]
 ** xref:api/transcriptions.adoc[]
 *** xref:api/transcriptions/openai-transcriptions.adoc[OpenAI]
 ** xref:api/vectordbs.adoc[]
--- 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
@@ -84,11 +84,11 @@ Next, you can use the `spring.ai.bedrock.<model>.<chat|embedding>.*` properties

 For more information, refer to the documentation below for each supported model.

-* xref:api/clients/bedrock/bedrock-anthropic.adoc[Spring AI Bedrock Anthropic Chat]: `spring.ai.bedrock.anthropic.chat.enabled=true`
-* xref:api/clients/bedrock/bedrock-llama2.adoc[Spring AI Bedrock Llama2 Chat]: `spring.ai.bedrock.llama2.chat.enabled=true`
-* xref:api/clients/bedrock/bedrock-cohere.adoc[Spring AI Bedrock Cohere Chat]: `spring.ai.bedrock.cohere.chat.enabled=true`
+* xref:api/chat/bedrock/bedrock-anthropic.adoc[Spring AI Bedrock Anthropic Chat]: `spring.ai.bedrock.anthropic.chat.enabled=true`
+* xref:api/chat/bedrock/bedrock-llama2.adoc[Spring AI Bedrock Llama2 Chat]: `spring.ai.bedrock.llama2.chat.enabled=true`
+* xref:api/chat/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/chat/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`
+// * xref:api/chat/bedrock/bedrock-jurassic2-chat.adoc[(WIP)Spring AI Bedrock Jurassic Chat]: `spring.ai.bedrock.jurassic2.chat.enabled=true`
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/azure-openai-chat.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/azure-openai-chat.adoc
@@ -111,7 +111,7 @@ Deployments model name to provide as part of this completions request.

 TIP: All properties prefixed with `spring.ai.azure.openai.chat.options` can be overridden at runtime by adding a request specific <<chat-options>> to the `Prompt` call.

-=== Chat Options [[chat-options]]
+== Runtime Options [[chat-options]]

 The link:https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-azure-openai/src/main/java/org/springframework/ai/azure/openai/AzureOpenAiChatOptions.java[AzureOpenAiChatOptions.java] provides model configurations, such as the model to use, the temperature, the frequency penalty, etc.

@@ -135,13 +135,13 @@ ChatResponse response = chatClient.call(
 TIP: In addition to the model specific link:https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-azure-openai/src/main/java/org/springframework/ai/azure/openai/AzureOpenAiChatOptions.java[AzureOpenAiChatOptions.java] you can use a portable https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/ChatOptions.java[ChatOptions] instance, created with the https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/ChatOptionsBuilder.java[ChatOptionsBuilder#builder()].


-=== Function Calling
+== Function Calling

 You can register custom Java functions with the AzureOpenAiChatClient and have the model intelligently choose to output a JSON object containing arguments to call one or many of the registered functions.
 This is a powerful technique to connect the LLM capabilities with external tools and APIs.
-Read more about xref:api/clients/functions/azure-open-ai-chat-functions.adoc[Azure OpenAI Function Calling].
+Read more about xref:api/chat/functions/azure-open-ai-chat-functions.adoc[Azure OpenAI Function Calling].

-=== Sample Controller (Auto-configuration)
+== Sample Controller

 https://start.spring.io/[Create] a new Spring Boot project and add the `spring-ai-azure-openai-spring-boot-starter` to your pom (or gradle) dependencies.

@@ -210,7 +210,7 @@ dependencies {

 TIP: Refer to the xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build file.

-TIP: The `spring-ai-azure-openai` dependency also provide the access to the `AzureOpenAiChatClient`. For more information about the `AzureOpenAiChatClient` refer to the link:../clients/azure-openai-chat.html[Azure OpenAI Chat] section.
+TIP: The `spring-ai-azure-openai` dependency also provide the access to the `AzureOpenAiChatClient`. For more information about the `AzureOpenAiChatClient` refer to the link:../chat/azure-openai-chat.html[Azure OpenAI Chat] section.

 Next, create an `AzureOpenAiChatClient` instance and use it to generate text responses:

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/bedrock/bedrock-anthropic.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/bedrock/bedrock-anthropic.adoc
@@ -89,7 +89,7 @@ Model ID values can also be found in the https://docs.aws.amazon.com/bedrock/lat

 TIP: All properties prefixed with `spring.ai.bedrock.anthropic.chat.options` can be overridden at runtime by adding a request specific <<chat-options>> to the `Prompt` call.

-=== Chat Options [[chat-options]]
+== Runtime Options [[chat-options]]

 The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic/AnthropicChatOptions.java[AnthropicChatOptions.java] provides model configurations, such as temperature, topK, topP, etc.

@@ -111,7 +111,7 @@ ChatResponse response = chatClient.call(

 TIP: In addition to the model specific https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic/AnthropicChatOptions.java[AnthropicChatOptions] you can use a portable https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/ChatOptions.java[ChatOptions] instance, created with the https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/ChatOptionsBuilder.java[ChatOptionsBuilder#builder()].

-=== Sample Controller (Auto-configuration)
+== Sample Controller

 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.

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/bedrock/bedrock-cohere.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/bedrock/bedrock-cohere.adoc
@@ -88,7 +88,7 @@ Model ID values can also be found in the https://docs.aws.amazon.com/bedrock/lat

 TIP: All properties prefixed with `spring.ai.bedrock.cohere.chat.options` can be overridden at runtime by adding a request specific <<chat-options>> to the `Prompt` call.

-=== Chat Options [[chat-options]]
+== Runtime Options [[chat-options]]

 The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/cohere/BedrockCohereChatOptions.java[BedrockCohereChatOptions.java] provides model configurations, such as temperature, topK, topP, etc.

@@ -110,7 +110,7 @@ ChatResponse response = chatClient.call(

 TIP: In addition to the model specific https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/cohere/BedrockCohereChatOptions.java[BedrockCohereChatOptions] you can use a portable https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/ChatOptions.java[ChatOptions] instance, created with the https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/ChatOptionsBuilder.java[ChatOptionsBuilder#builder()].

-=== Sample Controller (Auto-configuration)
+== Sample Controller

 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.

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/bedrock/bedrock-llama2.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/bedrock/bedrock-llama2.adoc
@@ -86,7 +86,7 @@ Model ID values can also be found in the https://docs.aws.amazon.com/bedrock/lat

 TIP: All properties prefixed with `spring.ai.bedrock.llama2.chat.options` can be overridden at runtime by adding a request specific <<chat-options>> to the `Prompt` call.

-=== Chat Options [[chat-options]]
+== Runtime Options [[chat-options]]

 The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/llama2/BedrockLlama2ChatOptions.java[BedrockLlama2ChatOptions.java] provides model configurations, such as temperature, topK, topP, etc.

@@ -108,7 +108,7 @@ ChatResponse response = chatClient.call(

 TIP: In addition to the model specific https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/llama2/BedrockLlama2ChatOptions.java[BedrockLlama2ChatOptions] you can use a portable https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/ChatOptions.java[ChatOptions] instance, created with the https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/ChatOptionsBuilder.java[ChatOptionsBuilder#builder()].

-=== Sample Controller (Auto-configuration)
+== Sample Controller

 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.

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/bedrock/bedrock-titan.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/bedrock/bedrock-titan.adoc
@@ -84,7 +84,7 @@ Model ID values can also be found in the https://docs.aws.amazon.com/bedrock/lat

 TIP: All properties prefixed with `spring.ai.bedrock.titan.chat.options` can be overridden at runtime by adding a request specific <<chat-options>> to the `Prompt` call.

-=== Chat Options [[chat-options]]
+== Runtime Options [[chat-options]]

 The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/titan/BedrockTitanChatOptions.java[BedrockTitanChatOptions.java] provides model configurations, such as temperature, topP, etc.

@@ -106,7 +106,7 @@ ChatResponse response = chatClient.call(

 TIP: In addition to the model specific https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/titan/BedrockTitanChatOptions.java[BedrockTitanChatOptions] you can use a portable https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/ChatOptions.java[ChatOptions] instance, created with the https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/ChatOptionsBuilder.java[ChatOptionsBuilder#builder()].

-=== Sample Controller (Auto-configuration)
+== Sample Controller

 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.

@@ -201,7 +201,7 @@ Flux<ChatResponse> response = chatClient.stream(
    new Prompt("Generate the names of 5 famous pirates."));
 ----

-=== Low-level TitanChatBedrockApi Client [[low-level-api]]
+== Low-level TitanChatBedrockApi 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/TitanChatBedrockApi.java[TitanChatBedrockApi] provides is lightweight Java client on top of AWS Bedrock link:https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-titan-text.html[Bedrock Titan models].

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/functions/azure-open-ai-chat-functions.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/functions/azure-open-ai-chat-functions.adoc
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/functions/mistralai-chat-functions.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/functions/mistralai-chat-functions.adoc
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/functions/openai-chat-functions.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/functions/openai-chat-functions.adoc
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/functions/vertexai-gemini-chat-functions.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/functions/vertexai-gemini-chat-functions.adoc
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/google-vertexai.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/google-vertexai.adoc
@@ -5,5 +5,5 @@ link:https://cloud.google.com/vertex-ai/docs/reference[VertexAI API] provides hi

 Spring AI provides integration with VertexAI API through the following clients:

-* xref:api/clients/vertexai-palm2-chat.adoc[]
-* xref:api/clients/vertexai-gemini-chat.adoc[]
+* xref:api/chat/vertexai-palm2-chat.adoc[]
+* xref:api/chat/vertexai-gemini-chat.adoc[]
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/huggingface.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/huggingface.adoc
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/mistralai-chat.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/mistralai-chat.adoc
@@ -108,7 +108,7 @@ This is useful if you want to use different MistralAI accounts for different mod

 TIP: All properties prefixed with `spring.ai.mistralai.chat.options` can be overridden at runtime by adding a request specific <<chat-options>> to the `Prompt` call.

-== Chat Options [[chat-options]]
+== Runtime Options [[chat-options]]

 The link:https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-mistral-ai/src/main/java/org/springframework/ai/mistralai/MistralAiChatOptions.java[MistralAiChatOptions.java] provides model configurations, such as the model to use, the temperature, the frequency penalty, etc.

@@ -135,7 +135,7 @@ TIP: In addition to the model specific link:https://github.com/spring-projects/s

 You can register custom Java functions with the MistralAiChatClient and have the Mistral AI model intelligently choose to output a JSON object containing arguments to call one or many of the registered functions.
 This is a powerful technique to connect the LLM capabilities with external tools and APIs.
-Read more about xref:api/clients/functions/mistralai-chat-functions.adoc[Mistral AI Function Calling].
+Read more about xref:api/chat/functions/mistralai-chat-functions.adoc[Mistral AI Function Calling].

 == Sample Controller (Auto-configuration)

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/ollama-chat.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/ollama-chat.adoc
@@ -102,7 +102,7 @@ NOTE: The list of options for chat is to be reviewed. This https://github.com/sp

 TIP: All properties prefixed with `spring.ai.ollama.chat.options` can be overridden at runtime by adding a request specific <<chat-options>> to the `Prompt` call.

-=== Chat Options [[chat-options]]
+== Runtime Options [[chat-options]]

 The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-ollama/src/main/java/org/springframework/ai/ollama/api/OllamaOptions.java[OllamaOptions.java] provides model configurations, such as the model to use, the temperature,  etc.

@@ -124,7 +124,7 @@ ChatResponse response = chatClient.call(

 TIP: In addition to the model specific link:https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-ollama/src/main/java/org/springframework/ai/ollama/api/OllamaOptions.java[OllamaOptions] you can use a portable https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/ChatOptions.java[ChatOptions] instance, created with the https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/ChatOptionsBuilder.java[ChatOptionsBuilder#builder()].

-=== Sample Controller (Auto-configuration)
+== Sample Controller

 https://start.spring.io/[Create] a new Spring Boot project and add the `spring-ai-openai-spring-boot-starter` to your pom (or gradle) dependencies.

@@ -218,7 +218,7 @@ Flux<ChatResponse> response = chatClient.stream(

 The `OllamaOptions` provides the configuration information for all chat requests.

-=== Low-level OpenAiApi Client [[low-level-api]]
+== Low-level OpenAiApi Client [[low-level-api]]

 The link:https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-ollama/src/main/java/org/springframework/ai/ollama/api/OllamaApi.java[OllamaApi] provides is lightweight Java client for Ollama Chat API link:https://github.com/ollama/ollama/blob/main/docs/api.md#generate-a-chat-completion[Ollama Chat Completion API].

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/openai-chat.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/openai-chat.adoc
@@ -112,7 +112,7 @@ This is useful if you want to use different OpenAI accounts for different models

 TIP: All properties prefixed with `spring.ai.openai.chat.options` can be overridden at runtime by adding a request specific <<chat-options>> to the `Prompt` call.

-== Chat Options [[chat-options]]
+== Runtime Options [[chat-options]]

 The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-openai/src/main/java/org/springframework/ai/openai/OpenAiChatOptions.java[OpenAiChatOptions.java] provides model configurations, such as the model to use, the temperature, the frequency penalty, etc.

@@ -139,9 +139,9 @@ TIP: In addition to the model specific https://github.com/spring-projects/spring

 You can register custom Java functions with the OpenAiChatClient and have the OpenAI model intelligently choose to output a JSON object containing arguments to call one or many of the registered functions.
 This is a powerful technique to connect the LLM capabilities with external tools and APIs.
-Read more about xref:api/clients/functions/openai-chat-functions.adoc[OpenAI Function Calling].
+Read more about xref:api/chat/functions/openai-chat-functions.adoc[OpenAI Function Calling].

-== Sample Controller (Auto-configuration)
+== Sample Controller

 https://start.spring.io/[Create] a new Spring Boot project and add the `spring-ai-openai-spring-boot-starter` to your pom (or gradle) dependencies.

@@ -233,7 +233,7 @@ Flux<ChatResponse> response = chatClient.stream(
 The `OpenAiChatOptions` provides the configuration information for the chat requests.
 The `OpenAiChatOptions.Builder` is fluent options builder.

-=== Low-level OpenAiApi Client [[low-level-api]]
+== Low-level OpenAiApi Client [[low-level-api]]

 The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-openai/src/main/java/org/springframework/ai/openai/api/OpenAiApi.java[OpenAiApi] provides is lightweight Java client for OpenAI Chat API link:https://platform.openai.com/docs/api-reference/chat[OpenAI Chat API].

@@ -262,7 +262,7 @@ Flux<ChatCompletionChunk> streamResponse = openAiApi.chatCompletionStream(

 Follow the https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-openai/src/main/java/org/springframework/ai/openai/api/OpenAiApi.java[OpenAiApi.java]'s JavaDoc for further information.

-== Example Code
+=== Low-level API Examples
 * The link:https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/api/OpenAiApiIT.java[OpenAiApiIT.java] test provides some general examples how to use the lightweight library.

 * The link:https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/api/tool/OpenAiApiToolFunctionCallIT.java[OpenAiApiToolFunctionCallIT.java] test shows how to use the low-level API to call tool functions.
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/vertexai-gemini-chat.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/vertexai-gemini-chat.adoc
@@ -103,7 +103,7 @@ TIP: In addition to the model specific `VertexAiChatPaLm2Options` you can use a

 You can register custom Java functions with the VertexAiGeminiChatClient and have the Gemini Pro model intelligently choose to output a JSON object containing arguments to call one or many of the registered functions.
 This is a powerful technique to connect the LLM capabilities with external tools and APIs.
-Read more about xref:api/clients/functions/vertexai-gemini-chat-functions.adoc[Vertex AI Gemini Function Calling].
+Read more about xref:api/chat/functions/vertexai-gemini-chat-functions.adoc[Vertex AI Gemini Function Calling].

 == Multimodal
 Multimodality refers to a model's ability to simultaneously understand and process information from various sources, including text, images, audio, and other data formats. This paradigm represents a significant advancement in AI models.
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/vertexai-palm2-chat.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/vertexai-palm2-chat.adoc
@@ -77,7 +77,7 @@ The prefix `spring.ai.vertex.ai.chat` is the property prefix that lets you confi

 TIP: All properties prefixed with `spring.ai.vertex.ai.chat.options` can be overridden at runtime by adding a request specific <<chat-options>> to the `Prompt` call.

-=== Chat Options [[chat-options]]
+== Runtime Options [[chat-options]]

 The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-vertex-ai-palm2/src/main/java/org/springframework/ai/vertexai/palm2/VertexAiPaLm2ChatOptions.java[VertexAiPaLm2ChatOptions.java] provides model configurations, such as the temperature, the topK, etc.

@@ -99,7 +99,7 @@ ChatResponse response = chatClient.call(

 TIP: In addition to the model specific `VertexAiPaLm2ChatOptions` you can use a portable https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/ChatOptions.java[ChatOptions] instance, created with the https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/ChatOptionsBuilder.java[ChatOptionsBuilder#builder()].

-=== Sample Controller (Auto-configuration)
+== Sample Controller

 https://start.spring.io/[Create] a new Spring Boot project and add the `spring-ai-vertex-ai-palm2-spring-boot-starter` to your pom (or gradle) dependencies.

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chatclient.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chatclient.adoc
@@ -175,18 +175,18 @@ The `ChatClient` and `StreamingChatClient` implementations are provided for the

 image::spring-ai-chat-completions-clients.jpg[align="center", width="800px"]

-* xref:api/clients/openai-chat.adoc[OpenAI Chat Completion] (streaming & function-calling support)
-* xref:api/clients/azure-openai-chat.adoc[Microsoft Azure Open AI Chat Completion] (streaming & function-calling support)
-* xref:api/clients/ollama-chat.adoc[Ollama Chat Completion]
-* xref:api/clients/huggingface.adoc[HuggingFace Chat Completion] (no streaming support)
-* xref:api/clients/vertexai-palm2-chat.adoc[Google Vertex AI PaLM2 Chat Completion] (no streaming support)
-* xref:api/clients/vertexai-gemini-chat.adoc[Google Vertex AI Gemini Chat Completion] (streaming, multi-modality & function-calling support)
+* xref:api/chat/openai-chat.adoc[OpenAI Chat Completion] (streaming & function-calling support)
+* xref:api/chat/azure-openai-chat.adoc[Microsoft Azure Open AI Chat Completion] (streaming & function-calling support)
+* xref:api/chat/ollama-chat.adoc[Ollama Chat Completion]
+* xref:api/chat/huggingface.adoc[HuggingFace Chat Completion] (no streaming support)
+* xref:api/chat/vertexai-palm2-chat.adoc[Google Vertex AI PaLM2 Chat Completion] (no streaming support)
+* xref:api/chat/vertexai-gemini-chat.adoc[Google Vertex AI Gemini Chat Completion] (streaming, multi-modality & function-calling support)
 * xref:api/bedrock.adoc[Amazon Bedrock]
-** xref:api/clients/bedrock/bedrock-cohere.adoc[Cohere Chat Completion]
-** xref:api/clients/bedrock/bedrock-llama2.adoc[Llama2 Chat Completion]
-** xref:api/clients/bedrock/bedrock-titan.adoc[Titan Chat Completion]
-** xref:api/clients/bedrock/bedrock-anthropic.adoc[Anthropic Chat Completion]
-* xref:api/clients/mistralai-chat.adoc[Mistral AI Chat Completion] (streaming & function-calling support)
+** xref:api/chat/bedrock/bedrock-cohere.adoc[Cohere Chat Completion]
+** xref:api/chat/bedrock/bedrock-llama2.adoc[Llama2 Chat Completion]
+** xref:api/chat/bedrock/bedrock-titan.adoc[Titan Chat Completion]
+** xref:api/chat/bedrock/bedrock-anthropic.adoc[Anthropic Chat Completion]
+* xref:api/chat/mistralai-chat.adoc[Mistral AI Chat Completion] (streaming & function-calling support)

 == Chat Model API

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/azure-openai-embeddings.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/azure-openai-embeddings.adoc
@@ -80,7 +80,7 @@ The prefix `spring.ai.azure.openai.embeddings` is the property prefix that confi

 TIP: All properties prefixed with `spring.ai.azure.openai.embedding.options` can be overridden at runtime by adding a request specific <<embedding-options>> to the `EmbeddingRequest` call.

-=== Embedding Options [[embedding-options]]
+== Runtime Options [[embedding-options]]

 The `AzureOpenAiEmbeddingOptions` provides the configuration information for the embedding requests.
 The `AzureOpenAiEmbeddingOptions` offers a builder to create the options.
@@ -100,7 +100,7 @@ EmbeddingResponse embeddingResponse = embeddingClient.call(
 ----


-=== Sample Code
+== Sample Code

 This will create a `EmbeddingClient` implementation that you can inject into your class.
 Here is an example of a simple `@Controller` class that uses the `EmbeddingClient` implementation.
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/bedrock-cohere-embedding.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/bedrock-cohere-embedding.adoc
@@ -79,7 +79,7 @@ Model ID values can also be found in the https://docs.aws.amazon.com/bedrock/lat

 TIP: All properties prefixed with `spring.ai.bedrock.cohere.embedding.options` can be overridden at runtime by adding a request specific <<embedding-options>> to the `EmbeddingRequest` call.

-=== Embedding Options [[embedding-options]]
+== Runtime Options [[embedding-options]]

 The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/cohere/BedrockCohereEmbeddingOptions.java[BedrockCohereEmbeddingOptions.java] provides model configurations, such as `input-type` or `truncate`.

@@ -97,7 +97,7 @@ EmbeddingResponse embeddingResponse = embeddingClient.call(
        .build()));
 ----

-=== Sample Controller (Auto-configuration)
+== Sample Controller

 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.

--- 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
@@ -82,7 +82,7 @@ Supported values are: `amazon.titan-embed-image-v1` and `amazon.titan-embed-text
 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)
+== Sample Controller

 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.

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/mistralai-embeddings.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/mistralai-embeddings.adoc
@@ -100,7 +100,7 @@ This is useful if you want to use different MistralAI accounts for different mod

 TIP: All properties prefixed with `spring.ai.mistralai.embedding.options` can be overridden at runtime by adding a request specific <<embedding-options>> to the `EmbeddingRequest` call.

-=== Embedding Options [[embedding-options]]
+== Runtime Options [[embedding-options]]

 The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-mistral-ai/src/main/java/org/springframework/ai/mistralai/MistralAiEmbeddingOptions.java[MistralAiEmbeddingOptions.java] provides the MistralAI configurations, such as the model to use and etc.

@@ -120,7 +120,7 @@ EmbeddingResponse embeddingResponse = embeddingClient.call(
        .build()));
 ----

-=== Sample Controller (Auto-configuration)
+== Sample Controller

 This will create a `EmbeddingClient` implementation that you can inject into your class.
 Here is an example of a simple `@Controller` class that uses the `EmbeddingClient` implementation.
@@ -175,7 +175,7 @@ dependencies {
 TIP: Refer to the xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build file.

 NOTE: The `spring-ai-mistralai` dependency provides access also to the `MistralAiChatClient`.
-For more information about the `MistralAiChatClient` refer to the link:../clients/mistralai-chat.html[MistralAI Chat Client] section.
+For more information about the `MistralAiChatClient` refer to the link:../chat/mistralai-chat.html[MistralAI Chat Client] section.

 Next, create an `MistralAiEmbeddingClient` instance and use it to compute the similarity between two input texts:

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/ollama-embeddings.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/ollama-embeddings.adoc
@@ -108,7 +108,7 @@ NOTE: The `spring.ai.ollama.embedding.options.*` properties are based on the htt

 TIP: All properties prefixed with `spring.ai.ollama.embedding.options` can be overridden at runtime by adding a request specific <<embedding-options>> to the `EmbeddingRequest` call.

-=== Embedding Options [[embedding-options]]
+== Runtime Options [[embedding-options]]

 The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-ollama/src/main/java/org/springframework/ai/ollama/api/OllamaOptions.java[OllamaOptions.java] provides the Ollama configurations, such as the model to use, the low level GPU and CPU tuning, etc.

@@ -127,7 +127,7 @@ EmbeddingResponse embeddingResponse = embeddingClient.call(
            .withModel("Different-Embedding-Model-Deployment-Name"));
 ----

-=== Sample Controller (Auto-configuration)
+== Sample Controller

 This will create a `EmbeddingClient` implementation that you can inject into your class.
 Here is an example of a simple `@Controller` class that uses the `EmbeddingClient` implementation.
@@ -177,7 +177,7 @@ dependencies {
 TIP: Refer to the xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build file.

 NOTE: The `spring-ai-ollama` dependency provides access also to the `OllamaChatClient`.
-For more information about the `OllamaChatClient` refer to the link:../clients/ollama-chat.html[Ollama Chat Client] section.
+For more information about the `OllamaChatClient` refer to the link:../chat/ollama-chat.html[Ollama Chat Client] section.

 Next, create an `OllamaEmbeddingClient` instance and use it to compute the similarity between two input texts:

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/openai-embeddings.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/openai-embeddings.adoc
@@ -102,7 +102,7 @@ This is useful if you want to use different OpenAI accounts for different models

 TIP: All properties prefixed with `spring.ai.openai.embedding.options` can be overridden at runtime by adding a request specific <<embedding-options>> to the `EmbeddingRequest` call.

-=== Embedding Options [[embedding-options]]
+== Runtime Options [[embedding-options]]

 The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-openai/src/main/java/org/springframework/ai/openai/OpenAiEmbeddingOptions.java[OpenAiEmbeddingOptions.java] provides the OpenAI configurations, such as the model to use and etc.

@@ -122,7 +122,7 @@ EmbeddingResponse embeddingResponse = embeddingClient.call(
        .build()));
 ----

-=== Sample Controller (Auto-configuration)
+== Sample Controller

 This will create a `EmbeddingClient` implementation that you can inject into your class.
 Here is an example of a simple `@Controller` class that uses the `EmbeddingClient` implementation.
@@ -177,7 +177,7 @@ dependencies {
 TIP: Refer to the xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build file.

 NOTE: The `spring-ai-openai` dependency provides access also to the `OpenAiChatClient`.
-For more information about the `OpenAiChatClient` refer to the link:../clients/openai-chat.html[OpenAI Chat Client] section.
+For more information about the `OpenAiChatClient` refer to the link:../chat/openai-chat.html[OpenAI Chat Client] section.

 Next, create an `OpenAiEmbeddingClient` instance and use it to compute the similarity between two input texts:

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/postgresml-embeddings.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/postgresml-embeddings.adoc
@@ -59,7 +59,7 @@ The prefix `spring.ai.postgresml.embedding` is property prefix that configures t

 TIP: All properties prefixed with `spring.ai.postgresml.embedding.options` can be overridden at runtime by adding a request specific <<embedding-options>> to the `EmbeddingRequest` call.

-=== EmbeddingOptions [[embedding-options]]
+== Runtime Options [[embedding-options]]

 Use the https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-openai/src/main/java/org/springframework/ai/postgresml/PostgresMlEmbeddingOptions.java[PostgresMlEmbeddingOptions.java] to configure the `PostgresMlEmbeddingClient` with options, such as the model to use and etc.

@@ -82,7 +82,7 @@ EmbeddingResponse embeddingResponse = embeddingClient.call(
                .build()));
 ----

-=== Sample Controller (Auto-configuration)
+== Sample Controller

 This will create a `EmbeddingClient` implementation that you can inject into your class.
 Here is an example of a simple `@Controller` class that uses the `EmbeddingClient` implementation.
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/vertexai-embeddings.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/embeddings/vertexai-embeddings.adoc
@@ -72,7 +72,7 @@ The prefix `spring.ai.vertex.ai.embedding` is the property prefix that lets you
 |====


-=== Sample Controller (Auto-configuration)
+== Sample Controller

 https://start.spring.io/[Create] a new Spring Boot project and add the `spring-ai-vertex-ai-palm2-spring-boot-starter` to your pom (or gradle) dependencies.

@@ -146,7 +146,7 @@ EmbeddingResponse embeddingResponse = embeddingClient
 	.embedForResponse(List.of("Hello World", "World is big and salvation is near"));
 ----

-=== Low-level VertexAiPaLm2Api Client [[low-level-api]]
+== Low-level VertexAiPaLm2Api Client [[low-level-api]]

 The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-vertex-ai-palm2/src/main/java/org/springframework/ai/vertexai/palm2/api/VertexAiPaLm2Api.java[VertexAiPaLm2Api] provides is lightweight Java client for VertexAiPaLm2Api Chat API.

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/functions.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/functions.adoc
@@ -5,7 +5,7 @@ The integration of function support in AI models, such as ChatGPT, permits the m

 Spring AI currently supports Function invocation for the following AI Models

-* OpenAI: Refer to the xref:api/clients/functions/openai-chat-functions.adoc[Open AI function invocation docs].
-* VertexAI Gemini: Refer to the xref:api/clients/functions/vertexai-gemini-chat-functions.adoc[Vertex AI Gemini function invocation docs].
-* Azure OpenAI: Refer to the xref:api/clients/functions/azure-open-ai-chat-functions.adoc[Azure OpenAI function invocation docs].
-* Mistral AI: Refer to the xref:api/clients/functions/mistralai-chat-functions.adoc[Mistral AI function invocation docs].
+* OpenAI: Refer to the xref:api/chat/functions/openai-chat-functions.adoc[Open AI function invocation docs].
+* VertexAI Gemini: Refer to the xref:api/chat/functions/vertexai-gemini-chat-functions.adoc[Vertex AI Gemini function invocation docs].
+* Azure OpenAI: Refer to the xref:api/chat/functions/azure-open-ai-chat-functions.adoc[Azure OpenAI function invocation docs].
+* Mistral AI: Refer to the xref:api/chat/functions/mistralai-chat-functions.adoc[Mistral AI function invocation docs].
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/image/openai-image.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/image/openai-image.adoc
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/image/stabilityai-image.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/image/stabilityai-image.adoc
@@ -74,7 +74,7 @@ The prefix `spring.ai.stabilityai.image` is the property prefix that lets you co
 |====


-=== Image Options [[image-options]]
+== Runtime Options [[image-options]]

 The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-stabilityai/src/main/java/org/springframework/ai/stabilityai/api/StabilityAiImageOptions.java[StabilityAiImageOptions.java] provides model configurations, such as the model to use, the style, the size, etc.

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/imageclient.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/imageclient.adoc
@@ -159,8 +159,8 @@ public class ImageGeneration implements ModelResult<Image> {

 `ImageClient` implementations are provided for the following Model providers:

-* xref:api/clients/image/openai-image.adoc[OpenAI Image Generation]
-* xref:api/clients/image/stabilityai-image.adoc[StabilityAI Image Generation]
+* xref:api/image/openai-image.adoc[OpenAI Image Generation]
+* xref:api/image/stabilityai-image.adoc[StabilityAI Image Generation]

 == API Docs

--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/contribution-guidelines.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/contribution-guidelines.adoc
@@ -17,7 +17,7 @@ you'll need to develop a low-level client API class. This often involves utilizi
 `RestClient` class from the Spring Framework, similar to the `OpenAiApi` class.

 . *Create a ModelClient implementation*
-Ensure your client conforms to the link:https://docs.spring.io/spring-ai/reference/api/clients/generic-model.html[Generic Model API].
+Ensure your client conforms to the link:https://docs.spring.io/spring-ai/reference/api/chat/generic-model.html[Generic Model API].
 Use existing request and response classes if your model's inputs and outputs are supported.
 If not, create new classes for the Generic Model API and establish a new Java package.

@@ -30,7 +30,7 @@ Existing tests can serve as a useful reference for structuring and implementing

 . *Document Your Contribution*: Ensure your documentation follows the existing format,
 For an example of the suggested structure and formatting, refer to the
-link:https://docs.spring.io/spring-ai/reference/api/clients/openai-chat.html[Open AI Chat documentation].
+link:https://docs.spring.io/spring-ai/reference/api/chat/openai-chat.html[Open AI Chat documentation].

 By following these guidelines, we can greatly expand the framework's range of supported models
 while following a common implementation and documentation pattern.
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/getting-started.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/getting-started.adoc
@@ -139,24 +139,24 @@ Each of the following sections in the documentation shows which dependencies you

 === Chat Models
 * xref:api/chatclient.adoc[Chat Completion API]
-** xref:api/clients/openai-chat.adoc[OpenAI Chat Completion] (streaming and function-calling support)
-** xref:api/clients/azure-openai-chat.adoc[Microsoft Azure Open AI Chat Completion] (streaming and function-calling support)
-** xref:api/clients/ollama-chat.adoc[Ollama Chat Completion]
-** xref:api/clients/huggingface.adoc[HuggingFace Chat Completion] (no streaming support)
-** xref:api/clients/vertexai-palm2-chat.adoc[Google Vertex AI PaLM2 Chat Completion] (no streaming support)
-** xref:api/clients/vertexai-gemini-chat.adoc[Google Vertex AI Gemini Chat Completion] (streaming, multi-modality & function-calling support)
+** xref:api/chat/openai-chat.adoc[OpenAI Chat Completion] (streaming and function-calling support)
+** xref:api/chat/azure-openai-chat.adoc[Microsoft Azure Open AI Chat Completion] (streaming and function-calling support)
+** xref:api/chat/ollama-chat.adoc[Ollama Chat Completion]
+** xref:api/chat/huggingface.adoc[HuggingFace Chat Completion] (no streaming support)
+** xref:api/chat/vertexai-palm2-chat.adoc[Google Vertex AI PaLM2 Chat Completion] (no streaming support)
+** xref:api/chat/vertexai-gemini-chat.adoc[Google Vertex AI Gemini Chat Completion] (streaming, multi-modality & function-calling support)
 ** xref:api/bedrock.adoc[Amazon Bedrock]
-*** xref:api/clients/bedrock/bedrock-cohere.adoc[Cohere Chat Completion]
-*** xref:api/clients/bedrock/bedrock-llama2.adoc[Llama2 Chat Completion]
-*** xref:api/clients/bedrock/bedrock-titan.adoc[Titan Chat Completion]
-*** xref:api/clients/bedrock/bedrock-anthropic.adoc[Anthropic Chat Completion]
-** xref:api/clients/mistralai-chat.adoc[MistralAI Chat Completion] (streaming and function-calling support)
-// ** xref:api/clients/bedrock/bedrock-jurassic.adoc[Jurassic2 Chat Completion] (WIP, no streaming support)
+*** xref:api/chat/bedrock/bedrock-cohere.adoc[Cohere Chat Completion]
+*** xref:api/chat/bedrock/bedrock-llama2.adoc[Llama2 Chat Completion]
+*** xref:api/chat/bedrock/bedrock-titan.adoc[Titan Chat Completion]
+*** xref:api/chat/bedrock/bedrock-anthropic.adoc[Anthropic Chat Completion]
+** xref:api/chat/mistralai-chat.adoc[MistralAI Chat Completion] (streaming and function-calling support)
+// ** xref:api/chat/bedrock/bedrock-jurassic.adoc[Jurassic2 Chat Completion] (WIP, no streaming support)

 === Image Generation Models
 * xref:api/imageclient.adoc[]
-** xref:api/clients/image/openai-image.adoc[OpenAI Image Generation]
-** xref:api/clients/image/stabilityai-image.adoc[StabilityAI Image Generation]
+** xref:api/image/openai-image.adoc[OpenAI Image Generation]
+** xref:api/image/stabilityai-image.adoc[StabilityAI Image Generation]

 === Vector Databases
 * xref:api/vectordbs.adoc[Vector Database API]
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/upgrade-notes.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/upgrade-notes.adoc
@@ -68,7 +68,7 @@ The following OpenAi Autoconfiguration chat properties has changed
 * from `spring.ai.openai.model` to `spring.ai.openai.chat.options.model`.
 * from `spring.ai.openai.temperature` to `spring.ai.openai.chat.options.temperature`.

-Find updated documentation about the OpenAi properties: https://docs.spring.io/spring-ai/reference/api/clients/openai-chat.html
+Find updated documentation about the OpenAi properties: https://docs.spring.io/spring-ai/reference/api/chat/openai-chat.html

 === December 27, 2023 Update