Remove unnecessary formatting change in docs.

Author: rpanackal

docs/guides/ORCHESTRATION_CHAT_COMPLETION.md

@@ -1,4 +1,4 @@
-# Orchestration Chat Completion
+=# Orchestration Chat Completion
 
 ## Table of Contents
 
@@ -77,7 +77,7 @@ To use the Orchestration service, create a client and a configuration object:
 var client = new OrchestrationClient();
 
 var config = new OrchestrationModuleConfig()
-    .withLlmConfig(OrchestrationAiModel.GPT_4O);
+        .withLlmConfig(OrchestrationAiModel.GPT_4O);
 ```
 
 Please also refer to [our sample code](../../sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/controllers/OrchestrationController.java) for this and all following code examples.
@@ -120,9 +120,9 @@ Include a message history to maintain context in the conversation:
 
 ```java
 var messagesHistory =
-    List.of(
-        Message.user("What is the capital of France?"),
-        Message.assistant("The capital of France is Paris."));
+        List.of(
+            Message.user("What is the capital of France?"),
+            Message.assistant("The capital of France is Paris."));
 var message =
     Message.user("What is the typical food there?");
 
@@ -198,27 +198,27 @@ Use the grounding module to provide additional context to the AI model.
 
 ```java
     var message =
-    Message.user(
-        "{{?groundingInput}} Use the following information as additional context: {{?groundingOutput}}");
-var prompt =
-    new OrchestrationPrompt(Map.of("groundingInput", "What does Joule do?"), message);
-
-var filterInner =
-    DocumentGroundingFilter.create().id("someID").dataRepositoryType(DataRepositoryType.VECTOR);
-var groundingConfigConfig =
-    GroundingModuleConfigConfig.create()
-        .inputParams(List.of("groundingInput"))
-        .outputParam("groundingOutput")
-        .addFiltersItem(filterInner);
-
-var groundingConfig =
-    GroundingModuleConfig.create()
-        .type(GroundingModuleConfig.TypeEnum.DOCUMENT_GROUNDING_SERVICE)
-        .config(groundingConfigConfig);
-var configWithGrounding = config.withGroundingConfig(groundingConfig);
-
-var result =
-    new OrchestrationClient().chatCompletion(prompt, configWithGrounding);
+        Message.user(
+            "{{?groundingInput}} Use the following information as additional context: {{?groundingOutput}}");
+    var prompt =
+        new OrchestrationPrompt(Map.of("groundingInput", "What does Joule do?"), message);
+
+    var filterInner =
+        DocumentGroundingFilter.create().id("someID").dataRepositoryType(DataRepositoryType.VECTOR);
+    var groundingConfigConfig =
+        GroundingModuleConfigConfig.create()
+            .inputParams(List.of("groundingInput"))
+            .outputParam("groundingOutput")
+            .addFiltersItem(filterInner);
+    
+    var groundingConfig =
+        GroundingModuleConfig.create()
+            .type(GroundingModuleConfig.TypeEnum.DOCUMENT_GROUNDING_SERVICE)
+            .config(groundingConfigConfig);
+    var configWithGrounding = config.withGroundingConfig(groundingConfig);
+
+    var result =  
+            new OrchestrationClient().chatCompletion(prompt, configWithGrounding);
 ```
 
 In this example, the AI model is provided with additional context in the form of grounding information. Note, that it is necessary to provide the grounding input via one or more input variables.
@@ -235,20 +235,13 @@ This is a blocking example for streaming and printing directly to the console:
 String msg = "Can you give me the first 100 numbers of the Fibonacci sequence?";
 
 // try-with-resources on stream ensures the connection will be closed
-try(
-Stream<String> stream = client.streamChatCompletion(prompt, config)){
-    stream.
-
-forEach(
-    deltaString ->{
-    System.out.
-
-print(deltaString);
-            System.out.
-
-flush();
+try (Stream<String> stream = client.streamChatCompletion(prompt, config)) {
+        stream.forEach(
+        deltaString -> {
+        System.out.print(deltaString);
+            System.out.flush();
         });
-            }
+                }
 ```
 
 #### Spring Boot example
@@ -262,12 +255,12 @@ Change your LLM configuration to add model parameters:
 
 ```java
 OrchestrationAiModel customGPT4O =
-    OrchestrationAiModel.GPT_4O
-        .withParam(MAX_TOKENS, 50)
-        .withParam(TEMPERATURE, 0.1)
-        .withParam(FREQUENCY_PENALTY, 0)
-        .withParam(PRESENCE_PENALTY, 0)
-        .withVersion("2024-05-13");
+        OrchestrationAiModel.GPT_4O
+                .withParam(MAX_TOKENS, 50)
+                .withParam(TEMPERATURE, 0.1)
+                .withParam(FREQUENCY_PENALTY, 0)
+                .withParam(PRESENCE_PENALTY, 0)
+                .withVersion("2024-05-13");
 ```
 
 ### Using a Configuration from AI Launchpad
@@ -276,8 +269,8 @@ In case you have created a configuration in AI Launchpad, you can copy or downlo
 
 ```java
 var configJson = """
-    ... paste your configuration JSON in here ...
-    """;
+        ... paste your configuration JSON in here ...
+        """;
 // or load your config from a file, e.g.
 // configJson = Files.readString(Paths.get("path/to/my/orchestration-config.json"));
 
@@ -286,4 +279,4 @@ var prompt = new OrchestrationPrompt(Map.of("your-input-parameter", "your-param-
 new OrchestrationClient().executeRequestFromJsonModuleConfig(prompt, configJson);
 ```
 
-While this is not recommended for long term use, it can be useful for creating demos and PoCs.
+While this is not recommended for long term use, it can be useful for creating demos and PoCs.