Update Mistral AI function calling docs and layout

Author: tzolov

spring-ai-docs/src/main/antora/modules/ROOT/images/mistral-ai-function-calling-flow.jpg

@@ -1,12 +1,12 @@
-= Mistral Function Calling
+= Mistral AI Function Calling
 
 You can register custom Java functions with the `MistralAiChatClient` and have the Mistral AI models intelligently choose to output a JSON object containing arguments to call one or many of the registered functions.
 This allows you to connect the LLM capabilities with external tools and APIs.
 The `mistral_small_latest` and `mistral_large_latest` models are trained to detect when a function should be called and to respond with JSON that adheres to the function signature.
 
 The MistralAI API does not call the function directly; instead, the model generates JSON that you can use to call the function in your code and return the result back to the model to complete the conversation.
 
-NOTE: Currently the MistralAI API doesn't support parallel function calling, similarly to the OpenAI API, Azure OpenAI API, and Vertex AI Gemini API.
+NOTE: As of March 13, 2024, Mistral AI has integrated support for parallel function calling into their `mistral_large_latest`` model, a feature that was absent at the time of the first Spring AI Mistral AI.
 
 Spring AI provides flexible and user-friendly ways to register and call custom functions.
 In general, the custom functions need to provide a function `name`,  `description`, and the function call `signature` (as JSON schema) to let the model know what arguments the function expects.
@@ -191,3 +191,17 @@ NOTE: The in-prompt registered functions are enabled by default for the duration
 This approach allows to dynamically chose different functions to be called based on the user input.
 
 The https://github.com/spring-projects/spring-ai/blob/main/spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/mistralai/tool/PaymentStatusPromptIT.java[PaymentStatusPromptIT.java] integration test provides a complete example of how to register a function with the `MistralAiChatClient` and use it in a prompt request.
+
+
+== Appendices
+
+=== https://spring.io/blog/2024/03/06/function-calling-in-java-and-spring-ai-using-the-latest-mistral-ai-api[(Blog) Function Calling in Java and Spring AI using the latest Mistral AI API]
+
+=== Mistral AI API Function Calling Flow
+
+The following diagram illustrates the flow of the Mistral AI low-level API for link:https://docs.mistral.ai/guides/function-calling[Function Calling]:
+
+image:mistral-ai-function-calling-flow.jpg[title="Mistral AI API Function Calling Flow", width=800, link=https://docs.mistral.ai/guides/function-calling]
+
+The link:https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-mistral-ai/src/test/java/org/springframework/ai/mistralai/api/tool/PaymentStatusFunctionCallingIT.java[PaymentStatusFunctionCallingIT.java] provides a complete example on how to use the Mistral AI API function calling.
+It is based on the https://docs.mistral.ai/guides/function-calling[Mistral AI Function Calling tutorial].

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/functions/mistralai-chat-functions.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]]
+== Chat 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.
 
@@ -131,7 +131,13 @@ ChatResponse response = chatClient.call(
 
 TIP: In addition to the model specific link:https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-mistral-ai/src/main/java/org/springframework/ai/mistralai/MistralAiChatOptions.java[MistralAiChatOptions] 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)
+== Function Calling
+
+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].
+
+== Sample Controller (Auto-configuration)
 
 https://start.spring.io/[Create] a new Spring Boot project and add the `spring-ai-mistralai-spring-boot-starter` to your pom (or gradle) dependencies.
 

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/clients/mistralai-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]]
+== Chat 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.
 
@@ -135,13 +135,13 @@ ChatResponse response = chatClient.call(
 
 TIP: In addition to the model specific https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-openai/src/main/java/org/springframework/ai/openai/OpenAiChatOptions.java[OpenAiChatOptions] 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 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].
 
-=== Sample Controller (Auto-configuration)
+== Sample Controller (Auto-configuration)
 
 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.