Modify the sample code

- Modify how OpenAiChatOption is used
- Modify how OllamaOptions is used

Signed-off-by: birariro <vps32@naver.com>

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chat/deepseek-chat.adoc

@@ -145,13 +145,13 @@ ChatResponse response = chatModel.call(
     new Prompt(
         "Generate the names of 5 famous pirates.",
         OpenAiChatOptions.builder()
-            .withModel("deepseek-chat")
-            .withTemperature(0.4)
+            .model("deepseek-chat")
+            .temperature(0.4)
         .build()
     ));
 ----
 
-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/prompt/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/prompt/ChatOptionsBuilder.java[ChatOptionsBuilder#builder()].
+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/prompt/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/prompt/ChatOptions.java[ChatOptions#builder()].
 
 == Function Calling
 

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chat/groq-chat.adoc

@@ -150,13 +150,13 @@ ChatResponse response = chatModel.call(
     new Prompt(
         "Generate the names of 5 famous pirates.",
         OpenAiChatOptions.builder()
-            .withModel("mixtral-8x7b-32768")
-            .withTemperature(0.4)
+            .model("mixtral-8x7b-32768")
+            .temperature(0.4)
         .build()
     ));
 ----
 
-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/prompt/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/prompt/ChatOptionsBuilder.java[ChatOptionsBuilder#builder()].
+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/prompt/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/prompt/ChatOptions.java[ChatOptions#builder()].
 
 == Function Calling
 
@@ -303,9 +303,9 @@ Next, create a `OpenAiChatModel` and use it for text generations:
 ----
 var openAiApi = new OpenAiApi("https://api.groq.com/openai", System.getenv("GROQ_API_KEY"));
 var openAiChatOptions = OpenAiChatOptions.builder()
-            .withModel("llama3-70b-8192")
-            .withTemperature(0.4)
-            .withMaxTokens(200)
+            .model("llama3-70b-8192")
+            .temperature(0.4)
+            .maxTokens(200)
         .build();
 var chatModel = new OpenAiChatModel(this.openAiApi, this.openAiChatOptions);
 

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chat/nvidia-chat.adoc

@@ -121,13 +121,13 @@ ChatResponse response = chatModel.call(
     new Prompt(
         "Generate the names of 5 famous pirates.",
         OpenAiChatOptions.builder()
-            .withModel("mixtral-8x7b-32768")
-            .withTemperature(0.4)
+            .model("mixtral-8x7b-32768")
+            .temperature(0.4)
         .build()
     ));
 ----
 
-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/prompt/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/prompt/ChatOptionsBuilder.java[ChatOptionsBuilder#builder()].
+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/prompt/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/prompt/ChatOptions.java[ChatOptions#builder()].
 
 == Function Calling
 

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chat/ollama-chat.adoc

@@ -309,8 +309,8 @@ String jsonSchema = """
 
 Prompt prompt = new Prompt("how can I solve 8x + 7 = -23",
         OllamaOptions.builder()
-            .withModel(OllamaModel.LLAMA3_2.getName())
-            .withFormat(new ObjectMapper().readValue(jsonSchema, Map.class))
+            .model(OllamaModel.LLAMA3_2.getName())
+            .format(new ObjectMapper().readValue(jsonSchema, Map.class))
             .build());
 
 ChatResponse response = this.ollamaChatModel.call(this.prompt);
@@ -340,8 +340,8 @@ var outputConverter = new BeanOutputConverter<>(MathReasoning.class);
 
 Prompt prompt = new Prompt("how can I solve 8x + 7 = -23",
         OllamaOptions.builder()
-            .withModel(OllamaModel.LLAMA3_2.getName())
-            .withFormat(outputConverter.getJsonSchemaMap())
+            .model(OllamaModel.LLAMA3_2.getName())
+            .format(outputConverter.getJsonSchemaMap())
             .build());
 
 ChatResponse response = this.ollamaChatModel.call(this.prompt);
@@ -466,10 +466,14 @@ Next, create an `OllamaChatModel` instance and use it to send requests for text
 ----
 var ollamaApi = new OllamaApi();
 
-var chatModel = new OllamaChatModel(this.ollamaApi,
-            OllamaOptions.create()
-                .model(OllamaOptions.DEFAULT_MODEL)
-                .temperature(0.9));
+var chatModel = OllamaChatModel.builder()
+                    .ollamaApi(ollamaApi)
+                    .defaultOptions(
+                        OllamaOptions.builder()
+                            .model(OllamaModel.MISTRAL)
+                            .temperature(0.9)
+                            .build())
+                    .build();
 
 ChatResponse response = this.chatModel.call(
     new Prompt("Generate the names of 5 famous pirates."));
@@ -508,7 +512,7 @@ var request = ChatRequest.builder("orca-mini")
                 .content("What is the capital of Bulgaria and what is the size? "
                         + "What is the national anthem?")
                 .build()))
-    .options(OllamaOptions.create().temperature(0.9))
+    .options(OllamaOptions.builder().temperature(0.9).build())
     .build();
 
 ChatResponse response = this.ollamaApi.chat(this.request);
@@ -519,7 +523,7 @@ var request2 = ChatRequest.builder("orca-mini")
     .messages(List.of(Message.builder(Role.USER)
         .content("What is the capital of Bulgaria and what is the size? " + "What is the national anthem?")
         .build()))
-    .options(OllamaOptions.create().temperature(0.9).toMap())
+    .options(OllamaOptions.builder().temperature(0.9).build().toMap())
     .build();
 
 Flux<ChatResponse> streamingResponse = this.ollamaApi.streamingChat(this.request2);

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chat/perplexity-chat.adoc

@@ -147,7 +147,7 @@ ChatResponse response = chatModel.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/prompt/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/prompt/ChatOptions.java#L97[ChatOptions#builder()].
+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/prompt/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/prompt/ChatOptions.java[ChatOptions#builder()].
 
 
 == Function Calling