Added Orchestration LLM Config Convenience

docs/guides/ORCHESTRATION_CHAT_COMPLETION.md

@@ -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(LLMModuleConfig.create().modelName("gpt-35-turbo").modelParams(Map.of()));
+        .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.
@@ -214,16 +214,16 @@ In this example, the input will be masked before the call to the LLM. Note that
 
 ### Set model parameters
 
-Change your LLM module configuration to add model parameters:
+Change your LLM configuration to add model parameters:
 
 ```java
-var llmConfig =
-    LLMModuleConfig.create()
-        .modelName("gpt-35-turbo")
-        .modelParams(
+OrchestrationAiModel customGPT4O =
+    OrchestrationAiModel.GPT_4O
+        .withModelParams(
             Map.of(
                 "max_tokens", 50,
                 "temperature", 0.1,
                 "frequency_penalty", 0,
-                "presence_penalty", 0));
+                "presence_penalty", 0))
+        .withModelVersion("2024-05-13");
 ```

orchestration/src/main/java/com/sap/ai/sdk/orchestration/OrchestrationAiModel.java

@@ -0,0 +1,135 @@
+package com.sap.ai.sdk.orchestration;
+
+import com.sap.ai.sdk.core.AiModel;
+import com.sap.ai.sdk.orchestration.client.model.LLMModuleConfig;
+import java.util.Map;
+import javax.annotation.Nonnull;
+import javax.annotation.Nullable;
+import lombok.AccessLevel;
+import lombok.AllArgsConstructor;
+import lombok.With;
+
+/** Large language models available in Orchestration. */
+@With
+@AllArgsConstructor(access = AccessLevel.PRIVATE)
+public class OrchestrationAiModel implements AiModel {
+  /** The name of the model */
+  private String modelName;
+
+  /** The version of the model, defaults to "latest". */
+  private String modelVersion = "latest";
+
+  /**
+   * Optional parameters on this model.
+   *
+   * <pre>{@code
+   * Map.of(
+   *     "max_tokens", 50,
+   *     "temperature", 0.1,
+   *     "frequency_penalty", 0,
+   *     "presence_penalty", 0)
+   * }</pre>
+   */
+  private Map<String, Object> modelParams;
+
+  /** IBM Granite 13B chat completions model */
+  public static final OrchestrationAiModel IBM_GRANITE_13B_CHAT =
+      new OrchestrationAiModel("ibm--granite-13b-chat");
+
+  /** MistralAI Mistral Large Instruct model */
+  public static final OrchestrationAiModel MISTRAL_LARGE_INSTRUCT =
+      new OrchestrationAiModel("mistralai--mistral-large-instruct");
+
+  /** MistralAI Mixtral 8x7B Instruct v01 model */
+  public static final OrchestrationAiModel MIXTRAL_8X7B_INSTRUCT_V01 =
+      new OrchestrationAiModel("mistralai--mixtral-8x7b-instruct-v01");
+
+  /** Meta Llama3 70B Instruct model */
+  public static final OrchestrationAiModel LLAMA3_70B_INSTRUCT =
+      new OrchestrationAiModel("meta--llama3-70b-instruct");
+
+  /** Meta Llama3.1 70B Instruct model */
+  public static final OrchestrationAiModel LLAMA3_1_70B_INSTRUCT =
+      new OrchestrationAiModel("meta--llama3.1-70b-instruct");
+
+  /** Anthropic Claude 3 Sonnet model */
+  public static final OrchestrationAiModel CLAUDE_3_SONNET =
+      new OrchestrationAiModel("anthropic--claude-3-sonnet");
+
+  /** Anthropic Claude 3 Haiku model */
+  public static final OrchestrationAiModel CLAUDE_3_HAIKU =
+      new OrchestrationAiModel("anthropic--claude-3-haiku");
+
+  /** Anthropic Claude 3 Opus model */
+  public static final OrchestrationAiModel CLAUDE_3_OPUS =
+      new OrchestrationAiModel("anthropic--claude-3-opus");
+
+  /** Anthropic Claude 3.5 Sonnet model */
+  public static final OrchestrationAiModel CLAUDE_3_5_SONNET =
+      new OrchestrationAiModel("anthropic--claude-3.5-sonnet");
+
+  /** Amazon Titan Text Lite model */
+  public static final OrchestrationAiModel TITAN_TEXT_LITE =
+      new OrchestrationAiModel("amazon--titan-text-lite");
+
+  /** Amazon Titan Text Express model */
+  public static final OrchestrationAiModel TITAN_TEXT_EXPRESS =
+      new OrchestrationAiModel("amazon--titan-text-express");
+
+  /** Azure OpenAI GPT-3.5 Turbo chat completions model */
+  public static final OrchestrationAiModel GPT_35_TURBO = new OrchestrationAiModel("gpt-35-turbo");
+
+  /** Azure OpenAI GPT-3.5 Turbo chat completions model */
+  public static final OrchestrationAiModel GPT_35_TURBO_16K =
+      new OrchestrationAiModel("gpt-35-turbo-16k");
+
+  /** Azure OpenAI GPT-4 chat completions model */
+  public static final OrchestrationAiModel GPT_4 = new OrchestrationAiModel("gpt-4");
+
+  /** Azure OpenAI GPT-4-32k chat completions model */
+  public static final OrchestrationAiModel GPT_4_32K = new OrchestrationAiModel("gpt-4-32k");
+
+  /** Azure OpenAI GPT-4o chat completions model */
+  public static final OrchestrationAiModel GPT_4O = new OrchestrationAiModel("gpt-4o");
+
+  /** Azure OpenAI GPT-4o-mini chat completions model */
+  public static final OrchestrationAiModel GPT_4O_MINI = new OrchestrationAiModel("gpt-4o-mini");
+
+  /** Google Cloud Platform Gemini 1.0 Pro model */
+  public static final OrchestrationAiModel GEMINI_1_0_PRO =
+      new OrchestrationAiModel("gemini-1.0-pro");
+
+  /** Google Cloud Platform Gemini 1.5 Pro model */
+  public static final OrchestrationAiModel GEMINI_1_5_PRO =
+      new OrchestrationAiModel("gemini-1.5-pro");
+
+  /** Google Cloud Platform Gemini 1.5 Flash model */
+  public static final OrchestrationAiModel GEMINI_1_5_FLASH =
+      new OrchestrationAiModel("gemini-1.5-flash");
+
+  OrchestrationAiModel(@Nonnull final String modelName) {
+    this.modelName = modelName;
+  }
+
+  @Nonnull
+  LLMModuleConfig createConfig() {
+    return new LLMModuleConfig()
+        .modelName(modelName)
+        .modelParams(modelParams)
+        .modelVersion(modelVersion);
+  }
+
+  /** {@inheritDoc} */
+  @Nonnull
+  @Override
+  public String name() {
+    return modelName;
+  }
+
+  /** {@inheritDoc} */
+  @Nullable
+  @Override
+  public String version() {
+    return modelVersion;
+  }
+}

orchestration/src/main/java/com/sap/ai/sdk/orchestration/OrchestrationModuleConfig.java

@@ -4,6 +4,7 @@
 import com.sap.ai.sdk.orchestration.client.model.LLMModuleConfig;
 import com.sap.ai.sdk.orchestration.client.model.MaskingModuleConfig;
 import com.sap.ai.sdk.orchestration.client.model.TemplatingModuleConfig;
+import javax.annotation.Nonnull;
 import javax.annotation.Nullable;
 import lombok.AccessLevel;
 import lombok.AllArgsConstructor;
@@ -28,7 +29,6 @@
  * </ul>
  */
 @Value
-@With
 @AllArgsConstructor(access = AccessLevel.PRIVATE)
 @NoArgsConstructor(force = true)
 public class OrchestrationModuleConfig {
@@ -41,11 +41,23 @@ public class OrchestrationModuleConfig {
    * A template to be populated with input parameters. Upon request execution, this template will be
    * enhanced with any messages and parameter values from {@link OrchestrationPrompt}.
    */
-  @Nullable TemplatingModuleConfig templateConfig;
+  @With @Nullable TemplatingModuleConfig templateConfig;
 
   /** A masking configuration to pseudonymous or anonymize sensitive data in the input. */
-  @Nullable MaskingModuleConfig maskingConfig;
+  @With @Nullable MaskingModuleConfig maskingConfig;
 
   /** A content filter to filter the prompt. */
-  @Nullable FilteringModuleConfig filteringConfig;
+  @With @Nullable FilteringModuleConfig filteringConfig;
+
+  /**
+   * Creates a new configuration with the given LLM configuration.
+   *
+   * @param aiModel The LLM configuration to use.
+   * @return A new configuration with the given LLM configuration.
+   */
+  @Nonnull
+  public OrchestrationModuleConfig withLlmConfig(@Nonnull final OrchestrationAiModel aiModel) {
+    return new OrchestrationModuleConfig(
+        aiModel.createConfig(), templateConfig, maskingConfig, filteringConfig);
+  }
 }

orchestration/src/test/java/com/sap/ai/sdk/orchestration/ConfigToRequestTransformerTest.java

@@ -1,6 +1,6 @@
 package com.sap.ai.sdk.orchestration;
 
-import static com.sap.ai.sdk.orchestration.OrchestrationUnitTest.LLM_CONFIG;
+import static com.sap.ai.sdk.orchestration.OrchestrationUnitTest.CUSTOM_GPT_35;
 import static org.assertj.core.api.Assertions.assertThat;
 import static org.assertj.core.api.Assertions.assertThatThrownBy;
 
@@ -71,7 +71,7 @@ void testMessagesHistory() {
     var prompt = new OrchestrationPrompt("bar").messageHistory(List.of(systemMessage));
     var actual =
         ConfigToRequestTransformer.toCompletionPostRequest(
-            prompt, new OrchestrationModuleConfig().withLlmConfig(LLM_CONFIG));
+            prompt, new OrchestrationModuleConfig().withLlmConfig(CUSTOM_GPT_35));
 
     assertThat(actual.getMessagesHistory()).containsExactly(systemMessage);
   }

orchestration/src/test/java/com/sap/ai/sdk/orchestration/OrchestrationUnitTest.java

@@ -16,6 +16,7 @@
 import static com.github.tomakehurst.wiremock.client.WireMock.stubFor;
 import static com.github.tomakehurst.wiremock.client.WireMock.urlPathEqualTo;
 import static com.github.tomakehurst.wiremock.client.WireMock.verify;
+import static com.sap.ai.sdk.orchestration.OrchestrationAiModel.GPT_35_TURBO_16K;
 import static com.sap.ai.sdk.orchestration.client.model.AzureThreshold.NUMBER_0;
 import static com.sap.ai.sdk.orchestration.client.model.AzureThreshold.NUMBER_4;
 import static org.apache.hc.core5.http.HttpStatus.SC_BAD_REQUEST;
@@ -39,7 +40,6 @@
 import com.sap.ai.sdk.orchestration.client.model.FilteringModuleConfig;
 import com.sap.ai.sdk.orchestration.client.model.GenericModuleResult;
 import com.sap.ai.sdk.orchestration.client.model.InputFilteringConfig;
-import com.sap.ai.sdk.orchestration.client.model.LLMModuleConfig;
 import com.sap.ai.sdk.orchestration.client.model.LLMModuleResultSynchronous;
 import com.sap.ai.sdk.orchestration.client.model.MaskingModuleConfig;
 import com.sap.ai.sdk.orchestration.client.model.OutputFilteringConfig;
@@ -62,10 +62,9 @@
  */
 @WireMockTest
 class OrchestrationUnitTest {
-  static final LLMModuleConfig LLM_CONFIG =
-      new LLMModuleConfig()
-          .modelName("gpt-35-turbo-16k")
-          .modelParams(
+  static final OrchestrationAiModel CUSTOM_GPT_35 =
+      GPT_35_TURBO_16K
+          .withModelParams(
               Map.of(
                   "max_tokens", 50,
                   "temperature", 0.1,
@@ -106,7 +105,7 @@ void setup(WireMockRuntimeInfo server) {
             .forDeploymentByScenario("orchestration")
             .withResourceGroup("my-resource-group");
     client = new OrchestrationClient(deployment);
-    config = new OrchestrationModuleConfig().withLlmConfig(LLM_CONFIG);
+    config = new OrchestrationModuleConfig().withLlmConfig(CUSTOM_GPT_35);
     prompt = new OrchestrationPrompt("Hello World! Why is this phrase so famous?");
   }
 
@@ -146,6 +145,7 @@ void testTemplating() throws IOException {
         .isEqualTo("Reply with 'Orchestration Service is working!' in German");
     assertThat(response.getModuleResults().getTemplating().get(0).getRole()).isEqualTo("user");
     var llm = (LLMModuleResultSynchronous) response.getModuleResults().getLlm();
+    assertThat(llm).isNotNull();
     assertThat(llm.getId()).isEqualTo("chatcmpl-9lzPV4kLrXjFckOp2yY454wksWBoj");
     assertThat(llm.getObject()).isEqualTo("chat.completion");
     assertThat(llm.getCreated()).isEqualTo(1721224505);
@@ -315,6 +315,7 @@ void maskingPseudonymization() throws IOException {
 
     assertThat(response).isNotNull();
     GenericModuleResult inputMasking = response.getModuleResults().getInputMasking();
+    assertThat(inputMasking).isNotNull();
     assertThat(inputMasking.getMessage()).isEqualTo("Input to LLM is masked successfully.");
     assertThat(inputMasking.getData()).isNotNull();
     assertThat(result.getContent()).contains("Hi Mallory");

sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/controllers/OrchestrationController.java

@@ -1,5 +1,7 @@
 package com.sap.ai.sdk.app.controllers;
 
+import static com.sap.ai.sdk.orchestration.OrchestrationAiModel.GPT_35_TURBO;
+
 import com.sap.ai.sdk.orchestration.OrchestrationChatResponse;
 import com.sap.ai.sdk.orchestration.OrchestrationClient;
 import com.sap.ai.sdk.orchestration.OrchestrationModuleConfig;
@@ -13,7 +15,6 @@
 import com.sap.ai.sdk.orchestration.client.model.DPIEntityConfig;
 import com.sap.ai.sdk.orchestration.client.model.FilteringModuleConfig;
 import com.sap.ai.sdk.orchestration.client.model.InputFilteringConfig;
-import com.sap.ai.sdk.orchestration.client.model.LLMModuleConfig;
 import com.sap.ai.sdk.orchestration.client.model.MaskingModuleConfig;
 import com.sap.ai.sdk.orchestration.client.model.OutputFilteringConfig;
 import com.sap.ai.sdk.orchestration.client.model.Template;
@@ -30,12 +31,8 @@
 @RestController
 @RequestMapping("/orchestration")
 class OrchestrationController {
-  static final LLMModuleConfig LLM_CONFIG =
-      new LLMModuleConfig().modelName("gpt-35-turbo").modelParams(Map.of());
-
   private final OrchestrationClient client = new OrchestrationClient();
-  private final OrchestrationModuleConfig config =
-      new OrchestrationModuleConfig().withLlmConfig(LLM_CONFIG);
+  OrchestrationModuleConfig config = new OrchestrationModuleConfig().withLlmConfig(GPT_35_TURBO);
 
   /**
    * Chat request to OpenAI through the Orchestration service with a simple prompt.
@@ -170,7 +167,7 @@ public OrchestrationChatResponse maskingAnonymization() {
 
   /**
    * Let the orchestration service a response to a hypothetical user who provided feedback on the AI
-   * SDK. Pseydonymize the user's name and location to protect their privacy.
+   * SDK. Pseudonymize the user's name and location to protect their privacy.
    *
    * @return the result object
    */

sample-code/spring-app/src/test/java/com/sap/ai/sdk/app/controllers/OrchestrationTest.java

@@ -10,10 +10,12 @@
 import com.sap.ai.sdk.orchestration.client.model.LLMModuleResultSynchronous;
 import java.util.List;
 import java.util.Map;
+import lombok.extern.slf4j.Slf4j;
 import org.assertj.core.api.InstanceOfAssertFactories;
 import org.junit.jupiter.api.BeforeEach;
 import org.junit.jupiter.api.Test;
 
+@Slf4j
 class OrchestrationTest {
   OrchestrationController controller;
 
@@ -32,6 +34,9 @@ void testCompletion() {
 
   @Test
   void testTemplate() {
+    assertThat(controller.config.getLlmConfig()).isNotNull();
+    final var modelName = controller.config.getLlmConfig().getModelName();
+
     final var response = controller.template();
     final var result = response.getOriginalResponse();
 
@@ -43,7 +48,7 @@ void testTemplate() {
     assertThat(llm.getId()).isNotEmpty();
     assertThat(llm.getObject()).isEqualTo("chat.completion");
     assertThat(llm.getCreated()).isGreaterThan(1);
-    assertThat(llm.getModel()).isEqualTo(OrchestrationController.LLM_CONFIG.getModelName());
+    assertThat(llm.getModel()).isEqualTo(modelName);
     var choices = llm.getChoices();
     assertThat(choices.get(0).getIndex()).isZero();
     assertThat(choices.get(0).getMessage().getContent()).isNotEmpty();
@@ -57,8 +62,7 @@ void testTemplate() {
     var orchestrationResult = ((LLMModuleResultSynchronous) result.getOrchestrationResult());
     assertThat(orchestrationResult.getObject()).isEqualTo("chat.completion");
     assertThat(orchestrationResult.getCreated()).isGreaterThan(1);
-    assertThat(orchestrationResult.getModel())
-        .isEqualTo(OrchestrationController.LLM_CONFIG.getModelName());
+    assertThat(orchestrationResult.getModel()).isEqualTo(modelName);
     choices = orchestrationResult.getChoices();
     assertThat(choices.get(0).getIndex()).isZero();
     assertThat(choices.get(0).getMessage().getContent()).isNotEmpty();

sample-code/spring-app/src/test/java/com/sap/ai/sdk/app/controllers/ScenarioTest.java

@@ -11,12 +11,12 @@
 import org.junit.jupiter.api.DisplayName;
 import org.junit.jupiter.api.Test;
 
-public class ScenarioTest {
+class ScenarioTest {
 
   @Test
   @DisplayName("Declared OpenAI models must match AI Core's available OpenAI models")
   @SneakyThrows
-  public void openAiModelAvailability() {
+  void openAiModelAvailability() {
 
     // Gather AI Core's list of available OpenAI models
     final var aiModelList = new ScenarioController().getModels().getResources();