diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md
index 25ecc5e13..d551873f5 100644
--- a/.github/PULL_REQUEST_TEMPLATE.md
+++ b/.github/PULL_REQUEST_TEMPLATE.md
@@ -16,5 +16,5 @@ Please provide a short description of what your change does and why it is needed
- [ ] Tests cover the scope above
- [ ] Error handling created / updated & covered by the tests above
- [ ] ~Aligned changes with the JavaScript SDK~
-- [ ] Documentation updated
+- [ ] [Documentation](https://github.com/SAP/ai-sdk/tree/main/docs-java) updated
- [ ] Release notes updated
diff --git a/README.md b/README.md
index 39eb7534f..b545fed2b 100644
--- a/README.md
+++ b/README.md
@@ -35,7 +35,7 @@ To use the SDK in a Java application, it is necessary to understand the technica
- Java 17 or higher.
- Access to an **SAP AI Core Service** instance.
-Please refer to [this documentation on **how to connect the SDK to AI Core**](docs/guides/CONNECTING_TO_AICORE.md).
+Please refer to [this documentation on **how to connect the SDK to AI Core**](https://sap.github.io/ai-sdk/docs/java/guides/connecting-to-ai-core).
The following table lists the required versions, based on the latest release:
@@ -119,26 +119,26 @@ export AICORE_SERVICE_KEY='{ "clientid": "...", "clientsecret": "...", "url": ".
mvn spring-boot:run
```
-Please find **detailed instructions** and more examples [in this documentation](docs/guides/CONNECTING_TO_AICORE.md#using-the-aicore_service_key-environment-variable).
+Please find **detailed instructions** and more examples [in this documentation](https://sap.github.io/ai-sdk/docs/java/guides/connecting-to-ai-core#using-the-aicore_service_key-environment-variable).
### Explore Further Capabilities
Check out the options available for the `OrchestrationPrompt` and `OrchestrationModuleConfig` classes.
You can use templating, content filtering, data masking and more.
-Please refer to [this documentation](docs/guides/ORCHESTRATION_CHAT_COMPLETION.md) for more information.
+Please refer to [this documentation](https://sap.github.io/ai-sdk/docs/java/guides/orchestration-chat-completion) for more information.
## Documentation
For more detailed information and advanced usage, please refer to the following:
-- [
Connecting to AI Core](docs/guides/CONNECTING_TO_AICORE.md)
-- [
Orchestration Chat Completion](docs/guides/ORCHESTRATION_CHAT_COMPLETION.md)
-- [
OpenAI Chat Completion](docs/guides/OPENAI_CHAT_COMPLETION.md)
-- [
Spring AI Integration](docs/guides/SPRING_AI_INTEGRATION.md)
-- [🧰 AI Core Deployment](docs/guides/AI_CORE_DEPLOYMENT.md)
-- [
AI Core Grounding](docs/guides/GROUNDING.md)
+- [ Connecting to AI Core](https://sap.github.io/ai-sdk/docs/java/guides/connecting-to-ai-core)
+- [ Orchestration Chat Completion](https://sap.github.io/ai-sdk/docs/java/guides/orchestration-chat-completion)
+- [ OpenAI Chat Completion](https://sap.github.io/ai-sdk/docs/java/guides/openai-chat-completion)
+- [ Spring AI Integration](https://sap.github.io/ai-sdk/docs/java/guides/spring-ai-integration)
+- [🧰 AI Core Deployment](https://sap.github.io/ai-sdk/docs/java/guides/ai-core-deployment)
+- [ AI Core Grounding](https://sap.github.io/ai-sdk/docs/java/guides/document-grounding)
-For updating versions, please refer to the [**Release Notes**](docs/release-notes/release-notes-0-to-14.md).
+For updating versions, please refer to the [**Release Notes**](https://sap.github.io/ai-sdk/docs/java/release-notes).
## Build the Project
@@ -177,7 +177,7 @@ OrchestrationClient client = new OrchestrationClient(destination);
OpenAiClient client2 = OpenAiClient.withCustomDestination(destination);
```
-For more information, please refer to the [AI Core connectivity guide](./docs/guides/CONNECTING_TO_AICORE.md) and the [SAP Cloud SDK documentation](https://sap.github.io/cloud-sdk/docs/java/features/connectivity/http-destinations).
+For more information, please refer to the [AI Core connectivity guide](https://sap.github.io/ai-sdk/docs/java/guides/connecting-to-ai-core) and the [SAP Cloud SDK documentation](https://sap.github.io/cloud-sdk/docs/java/features/connectivity/http-destinations).
### _"There's a vulnerability warning `CVE-2021-41251`?"_
diff --git a/docs/blog/Introducing.md b/docs/blog/Introducing.md
index 8ed84e2bc..7f311c4bd 100644
--- a/docs/blog/Introducing.md
+++ b/docs/blog/Introducing.md
@@ -41,7 +41,7 @@ String id = deployment.getId();
AiExecutionStatus status = deployment.getStatus();
```
-You can learn more about the SDK's capabilities for SAP AI Core [in the public repository guide](https://github.com/SAP/ai-sdk-java/blob/main/docs/guides/AI_CORE_DEPLOYMENT.md).
+You can learn more about the SDK's capabilities for SAP AI Core [in this guide](https://sap.github.io/ai-sdk/docs/java/guides/ai-core-deployment).
## AI Core - Orchestration
@@ -72,7 +72,7 @@ var result = client.chatCompletion(prompt, config);
String messageResult = result.getContent();
```
-You can learn more about the SDK's capabilities for Orchestration Service [in the public repository guide](https://github.com/SAP/ai-sdk-java/blob/main/docs/guides/ORCHESTRATION_CHAT_COMPLETION.md).
+You can learn more about the SDK's capabilities for Orchestration Service [in this guide](https://sap.github.io/ai-sdk/docs/java/guides/orchestration-chat-completion).
## AI Core - Foundation Models
@@ -101,7 +101,7 @@ var result =
String resultMessage = result.getContent();
```
-You can learn more about the SDK's capabilities for foundation models and OpenAI specific features [in the public repository guide](https://github.com/SAP/ai-sdk-java/blob/main/docs/guides/OPENAI_CHAT_COMPLETION.md).
+You can learn more about the SDK's capabilities for foundation models and OpenAI specific features [this guide](https://sap.github.io/ai-sdk/docs/java/guides/openai-chat-completion).
## Getting Started
diff --git a/docs/guides/AI_CORE_DEPLOYMENT.md b/docs/guides/AI_CORE_DEPLOYMENT.md
deleted file mode 100644
index 56bf24013..000000000
--- a/docs/guides/AI_CORE_DEPLOYMENT.md
+++ /dev/null
@@ -1,108 +0,0 @@
-# AI Core Deployment
-
-## Table of Contents
-
-- [Introduction](#introduction)
-- [Prerequisites](#prerequisites)
- - [Maven Dependencies](#maven-dependencies)
-- [Usage](#usage)
- - [Create a Deployment](#create-a-deployment)
- - [Delete a Deployment](#delete-a-deployment)
-
-## Introduction
-
-This guide provides examples on how to create and manage deployments in SAP AI Core using the SAP AI SDK for Java.
-
-> [!WARNING]
-> The below examples rely on generated model classes.
-> Please be aware of the [implications described here](/README.md#general-requirements).
-
-## Prerequisites
-
-Before using the AI Core module, ensure that you have met all the general requirements outlined in the [README.md](../../README.md#general-requirements).
-Additionally, include the necessary Maven dependency in your project.
-
-### Maven Dependencies
-
-Add the following dependency to your `pom.xml` file:
-
-```xml
-
- com.sap.ai.sdk
- core
- ${ai-sdk.version}
-
-```
-
-See [an example pom in our Spring Boot application](../../sample-code/spring-app/pom.xml)
-
-## Usage
-
-In addition to the prerequisites above, we assume you have already set up the following to carry out the examples in this guide:
-
-- **An AI Core Configuration** created in SAP AI Core.
- -
- Example configuration from the AI Core /configuration endpoint
-
- ```json
- {
- "createdAt": "2024-07-03T12:44:08Z",
- "executableId": "azure-openai",
- "id": "12345-123-123-123-123456abcdefg",
- "inputArtifactBindings": [],
- "name": "gpt-4o-mini",
- "parameterBindings": [
- {
- "key": "modelName",
- "value": "gpt-4o-mini"
- },
- {
- "key": "modelVersion",
- "value": "latest"
- }
- ],
- "scenarioId": "foundation-models"
- }
- ```
-
-
-## Create a Deployment
-
-Use the following code snippet to create a deployment in SAP AI Core:
-
-```java
-var api = new DeploymentApi();
-var resourceGroupId = "default";
-var configurationId = "12345-123-123-123-123456abcdefg";
-
-var request = AiDeploymentCreationRequest.create().configurationId(configurationId);
-var deployment = api.create(resourceGroupId, request);
-
-String id = deployment.getId();
-AiExecutionStatus status = deployment.getStatus();
-```
-
-Refer to the [DeploymentController.java](../../sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/controllers/DeploymentController.java) in our Spring Boot application for a complete example.
-
-## Delete a Deployment
-
-```java
-AiDeploymentCreationResponse deployment; // provided
-String deploymentId = deployment.getId();
-
-var api = new DeploymentApi();
-var resourceGroupId = "default";
-
-if (deployment.getStatus() == AiExecutionStatus.RUNNING) {
- // Only RUNNING deployments can be STOPPED
- api.modify(
- resourceGroupId,
- deploymentId,
- AiDeploymentModificationRequest.create().targetStatus(AiDeploymentTargetStatus.STOPPED));
-}
-// Wait a few seconds for the deployment to stop
-// Only UNKNOWN and STOPPED deployments can be DELETED
-api.delete(resourceGroupId, deployment.getId());
-```
-
-Refer to the [DeploymentController.java](../../sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/controllers/DeploymentController.java) in our Spring Boot application for a complete example.
diff --git a/docs/guides/CONNECTING_TO_AICORE.md b/docs/guides/CONNECTING_TO_AICORE.md
deleted file mode 100644
index ca89d55ad..000000000
--- a/docs/guides/CONNECTING_TO_AICORE.md
+++ /dev/null
@@ -1,175 +0,0 @@
-# Connecting to AI Core
-
-## Table of Contents
-
-- [Using a Service Binding](#using-a-service-binding)
- - [Providing a Service Binding Locally](#providing-a-service-binding-locally)
- - [Using the `AICORE_SERVICE_KEY` Environment Variable](#using-the-aicore_service_key-environment-variable)
-- [Using a Destination from the BTP Destination Service](#using-a-destination-from-the-btp-destination-service)
-- [Creating a Custom Destination](#creating-a-custom-destination)
-
-
-The AI SDK uses the [`Destination` concept of the SAP Cloud SDK](https://sap.github.io/cloud-sdk/docs/java/features/connectivity/destination-service) to connect to AI Core.
-This allows for a seamless integration in BTP and offers a wide variety of managing the credentials for the connection.
-
-## Using a Service Binding
-
-By default, the AI SDK will look for an `aicore` service binding in the environment of the application.
-
-When running on SAP BTP, [create an instance of the AI Core service](https://help.sap.com/docs/sap-ai-core/sap-ai-core-service-guide/create-service-instance) and bind it to your application.
-The AI SDK will automatically detect the service binding and use it to connect to AI Core.
-
-If no service binding could be found (and no other destination has been given), the AI SDK will throw an exception:
-
-> Could not find any matching service bindings for service identifier 'aicore'
-
-To run your code outside SAP BTP (e.g. locally), you will have to provide the credentials manually.
-
-### Providing a Service Binding Locally
-
-For local development, you can provide the service credentials locally in various ways.
-
-#### Using CAP Hybrid Testing
-
-When developing a [CAP application](https://cap.cloud.sap/docs/), you can use the [hybrid testing](https://cap.cloud.sap/docs/advanced/hybrid-testing#services-on-cloud-foundry) approach.
-Assuming your AI Core service instance is called `aicore`, the following command runs a Maven command with the credentials of the service instance:
-
-```bash
-cds bind --to aicore --exec mvn spring-boot:run
-```
-
-#### Using the `AICORE_SERVICE_KEY` Environment Variable
-
-You can also provide the service credentials in the `AICORE_SERVICE_KEY` environment variable.
-First, [create a service key for your AI Core service instance](https://help.sap.com/docs/sap-ai-core/sap-ai-core-service-guide/create-service-key).
-Copy the resulting JSON object.
-
-Then set the environment variable `AICORE_SERVICE_KEY` to be defined for however you want to run your code.
-How exactly to set this depends on how you run your code (e.g. via IDE, command line etc.) and potentially on your operating system.
-
-Here are three examples of how this can be done:
-
-1.
- Using a `.env` file
-
- Create a `.env` file in the **working directory** from which you run your code.
- Add the following line:
-
- ```txt
- AICORE_SERVICE_KEY={ "clientid": "...", "clientsecret": "...", "url": "...", "serviceurls": { "AI_API_URL": "..." } }
- ```
-
- > [!IMPORTANT]
- > The value of `AICORE_SERVICE_KEY` must be a single line, so remove any line breaks from the service key JSON.
-
-
-
-2.
- Using the command line on Mac OS
-
- Run your code with the following command:
-
- ```bash
- export AICORE_SERVICE_KEY='{ "clientid": "...", "clientsecret": "...", "url": "...", "serviceurls": { "AI_API_URL": "..." } }'
- mvn ...
- ```
-
-
-
-3.
- Using PowerShell on Windows
-
- Run your code with the following command:
-
- ```shell
- $env:AICORE_SERVICE_KEY='{ "clientid": "...", "clientsecret": "...", "url": "...", "serviceurls": { "AI_API_URL": "..." } }'
- mvn ...
- ```
-
-
-
-4.
- Using an IntelliJ run configuration
-
- In IntelliJ, go to `Run` > `Edit Configurations...` > `Environment variables`.
- Add a new environment variable with the name `AICORE_SERVICE_KEY` and paste the service key as value.
-
- For more information, see the [official IntelliJ documentation](https://www.jetbrains.com/help/idea/run-debug-configuration-application.html#configure-environment-variables).
-
-
-
-## Using a Destination from the BTP Destination Service
-
-You can define a destination in the BTP Destination Service and use that to connect to AI Core.
-
-
-How to create a Destination in the SAP BTP Cockpit
-
-1. [Create a service key for your AI Core service instance](https://help.sap.com/docs/sap-ai-core/sap-ai-core-service-guide/create-service-key).
-
-2. Create a new Destination in the SAP BTP Cockpit with the following properties:
-
- - **Name**: `my-aicore`
- - **Type**: `HTTP`
- - **URL**: `[serviceurls.AI_API_URL]`
- - **Proxy Type**: `Internet`
- - **Authentication**: `OAuth2ClientCredentials`
- - **Client ID**: `[clientid]`
- - **Client Secret**: `[clientsecret]`
- - **Token Service URL Type**: `Dedicated`
- - **Token Service URL**: `[url]/oauth/token`
-
- Fill in the values for URL, client ID, client secret, and token service URL from the service key JSON.
- Make sure to add `/oauth/token` in the token service URL.
-
-
-
-To use the destination, ensure you have created an instance of the BTP Destination Service and bound it to your application.
-
-> [!Tip]
-> If you are using CAP, you can again use Hybrid Testing to bind the destination service to your application when running **locally**.
-
-```java
-Destination destination = DestinationAccessor.getDestination("my-aicore").asHttp();
-AiCoreService aiCoreService = new AiCoreService().withBaseDestination(destination);
-```
-
-Now you can use the `AiCoreService` as follows:
-
-```java
-// To create an OpenAiClient:
-var openAiDestination = aiCoreService.getInferenceDestination().forModel(OpenAiModel.TEXT_EMBEDDING_3_LARGE);
-var client = OpenAiClient.withCustomDestination(openAiDestination);
-
-// To create an OrchestrationClient:
-var orchestrationDestination = aiCoreService.getInferenceDestination().forScenario("orchestration");
-var client = new OrchestrationClient(orchestrationDestination);
-
-// To create any of the com.sap.ai.sdk.core.client.* classes (e.g. DeploymentApi):
-new DeploymentApi(aiCoreService);
-```
-
-> [!IMPORTANT]
-> The `destination` obtained from BTP destination service will expire once the contained OAuth2 token expires.
-> Please run the above code for each request to ensure the destination is up-to-date.
-> Destinations are cached by default, so this does not come with a performance penalty.
-> To learn more, see the [SAP Cloud SDK documentation](https://sap.github.io/cloud-sdk/docs/java/features/connectivity/destination-service).
-
-## Creating a Custom Destination
-
-If the above options are not suitable for your use case (e.g. because you are obtaining the credentials in a completely different way), you can also use a custom-built destination:
-
-```java
-var destination = OAuth2DestinationBuilder
- .forTargetUrl("https://")
- .withTokenEndpoint("https:///oauth/token")
- .withClient(new ClientCertificate("", "", ""), OnBehalfOf.TECHNICAL_USER_PROVIDER)
- .build();
-
-AiCoreService aiCoreService = new AiCoreService().withBaseDestination(destination);
-```
-
-The above example assumes you are using a client certificate for authentication and have stored the relevant credentials somewhere.
-You are free to use X509 certificates (also via the Zero Trust Identity Service) or a client secret.
-
-For more details, refer to the [SAP Cloud SDK documentation](https://sap.github.io/cloud-sdk/docs/java/features/connectivity/destination-service).
\ No newline at end of file
diff --git a/docs/guides/GROUNDING.md b/docs/guides/GROUNDING.md
deleted file mode 100644
index e106478da..000000000
--- a/docs/guides/GROUNDING.md
+++ /dev/null
@@ -1,155 +0,0 @@
-# Document Grounding Services
-
-## Table of Contents
-
-- [Introduction](#introduction)
- - [Prerequisites](#prerequisites)
- - [Maven Dependencies](#maven-dependencies)
-- [Usage](#usage)
- - [Data Ingestion](#data-ingestion)
- - [Pipeline API](#pipeline-api)
- - [Vector API](#vector-api)
- - [Data Retrieval](#retrieval-api)
- - [Retrieval API](#create-a-deployment)
- - [Grounding via Orchestration](#grounding-via-orchestration)
-
-## Introduction
-
-This guide provides examples on how to manage data in SAP Document Grounding.
-It's divided into two main sections: Data Ingestion and Data Retrieval.
-
-> [!WARNING]
-> The below examples rely on generated model classes.
-> Please be aware of the [implications described here](/README.md#general-requirements).
-
-## Prerequisites
-
-Before using the Document Grounding module, ensure that you have met all the general requirements outlined in the [README.md](../../README.md#general-requirements).
-Additionally, include the necessary Maven dependency in your project.
-
-### Maven Dependencies
-
-Add the following dependency to your `pom.xml` file:
-
-```xml
-
- com.sap.ai.sdk
- document-grounding
- ${ai-sdk.version}
-
-```
-
-See [an example pom in our Spring Boot application](../../sample-code/spring-app/pom.xml)
-
-## Usage
-
-In addition to the prerequisites above, we assume you have already set up the following to carry out the examples in this guide:
-
-- A running instance of SAP AI Core with correctly setup credentials, including a resource group id.
-
-## Data Ingestion
-
-The following APIs are available for data ingestion: Pipeline and Vector.
-
-### Pipeline API
-
-Consider the following code sample to read pipelines, create a new one and get its status:
-
-```java
-var api = new GroundingClient().pipelines();
-var resourceGroupId = "default";
-
-// get all pipelines
-Pipelines pipelines = api.getAllPipelines(resourceGroupId);
-
-// create new pipeline
-var type = "MSSharePoint"; // or "S3" or "SFTP"
-var pipelineSecret = "my-secret-name";
-var config = PipelinePostRequstConfiguration.create().destination(pipelineSecret);
-var request = PipelinePostRequst.create().type(type)._configuration(config);
-PipelineId pipeline = api.createPipeline(resourceGroupId, request);
-
-// get pipeline status
-PipelineStatus status = api.getPipelineStatus(resourceGroupId, pipeline.getPipelineId());
-```
-
-### Vector API
-
-```java
-var api = new GroundingClient().vector();
-var resourceGroupId = "default";
-
-// resolve collection id
-var collectionId = UUID.fromString("12345-123-123-123-0123456abcdef");
-
-var request = DocumentCreateRequest.create()
- .documents(BaseDocument.create()
- .chunks(TextOnlyBaseChunk.create()
- .content("The dog makes _woof_")
- .metadata(KeyValueListPair.create()
- .key("animal").value("dog")))
- .metadata(DocumentKeyValueListPair.create()
- .key("topic").value("sound")));
-DocumentsListResponse response = api.createDocuments(resourceGroupId, collectionId, request);
-```
-
-Refer to the [DeploymentController.java](../../sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/controllers/DeploymentController.java) in our Spring Boot application for a complete example.
-
-## Data Retrieval
-
-The following APIs are available for data retrieval: Retrieval and Orchestration.
-
-
-### Retrieval API
-
-Consider the following code sample to search for relevant document grounding data based on a query:
-
-```java
-var api = new GroundingClient().retrieval();
-var resourceGroupId = "default";
-
-var filter =
- RetrievalSearchFilter.create()
- .id("question")
- .dataRepositoryType(DataRepositoryType.VECTOR)
- .dataRepositories(List.of("*"))
- .searchConfiguration(SearchConfiguration.create().maxChunkCount(10));
-var search = RetrievalSearchInput.create().query("What is SAP Cloud SDK for AI?").filters(filter);
-RetievalSearchResults results = api.search(resourceGroupId, search);
-```
-
-### Grounding via Orchestration
-
-You can use the grounding service via orchestration.
-Please find the [documentation on Orchestration client in the dedicated document](ORCHESTRATION_CHAT_COMPLETION.md).
-
-```java
-OrchestrationClient client;
-
-var databaseFilter =
- DocumentGroundingFilter.create()
- .dataRepositoryType(DataRepositoryType.VECTOR)
- .searchConfig(GroundingFilterSearchConfiguration.create().maxChunkCount(3));
-var groundingConfigConfig =
- GroundingModuleConfigConfig.create()
- .inputParams(List.of("query"))
- .outputParam("results")
- .addFiltersItem(databaseFilter);
-var groundingConfig =
- GroundingModuleConfig.create()
- .type(GroundingModuleConfig.TypeEnum.DOCUMENT_GROUNDING_SERVICE)
- .config(groundingConfigConfig);
-var configWithGrounding =
- new OrchestrationModuleConfig()
- .withLlmConfig(GPT_4O)
- .withGroundingConfig(groundingConfig);
-
-var inputParams = Map.of("query", "What is SAP Cloud SDK for AI?");
-
-var prompt =
- new OrchestrationPrompt(
- inputParams,
- Message.system("Context message with embedded grounding results. {{?results}}"));
-
-OrchestrationChatResponse response = client.chatCompletion(prompt, configWithGrounding);
-```
\ No newline at end of file
diff --git a/docs/guides/OPENAI_CHAT_COMPLETION.md b/docs/guides/OPENAI_CHAT_COMPLETION.md
deleted file mode 100644
index a9b0596a5..000000000
--- a/docs/guides/OPENAI_CHAT_COMPLETION.md
+++ /dev/null
@@ -1,312 +0,0 @@
-# OpenAI Chat Completion
-
-## Table of Contents
-
-- [Introduction](#introduction)
- - [New User Interface (v1.4.0)](#new-user-interface-v140)
-- [Prerequisites](#prerequisites)
-- [Maven Dependencies](#maven-dependencies)
-- [Usage](#usage)
- - [Simple Chat Completion](#simple-chat-completion)
- - [Message History](#message-history)
- - [Chat Completion with Custom Model](#chat-completion-with-custom-model)
- - [Stream Chat Completion](#stream-chat-completion)
- - [Asynchronous Streaming](#asynchronous-streaming)
- - [Aggregating Total Output](#aggregating-total-output)
- - [Spring Boot Example](#spring-boot-example)
-
-## Introduction
-
-This guide demonstrates how to use the SAP AI SDK for Java to perform chat completion tasks using OpenAI models deployed on SAP AI Core.
-
-### New User Interface (v1.4.0)
-
-We're excited to introduce a new user interface for OpenAI chat completions starting with **version 1.4.0**. This update is designed to improve the SDK by:
-
-- **Decoupling Layers:** Separating the convenience layer from the model classes to deliver a more stable and maintainable experience.
-- **Staying Current:** Making it easier for the SDK to adapt to the latest changes in the OpenAI API specification.
-- **Consistent Design:** Aligning with the Orchestrator convenience API for a smoother transition and easier adoption.
-
-**Please Note:**
-
-- The new interface is gradually being rolled out across the SDK.
-- We welcome your feedback to help us refine this interface.
-- The existing interface (v1.0.0) remains available for compatibility.
-
-## Prerequisites
-
-Before using the AI Core module, ensure that you have met all the general requirements outlined in the [README.md](../../README.md#general-requirements).
-Additionally, include the necessary Maven dependency in your project.
-
-### Maven Dependencies
-
-Add the following dependency to your `pom.xml` file:
-
-```xml
-
-
- com.sap.ai.sdk.foundationmodels
- openai
- ${ai-sdk.version}
-
-
-```
-
-See [an example pom in our Spring Boot application](../../sample-code/spring-app/pom.xml)
-
-## Usage
-
-In addition to the prerequisites above, we assume you have already set up the following to carry out the examples in this guide:
-
-- **A Deployed OpenAI Model in SAP AI Core**
- - Refer
- to [How to deploy a model to AI Core](https://help.sap.com/docs/sap-ai-core/sap-ai-core-service-guide/create-deployment-for-generative-ai-model-in-sap-ai-core)
- for setup instructions.
- - In case the model is deployed in a custom resource group, refer to [this section](#using-a-custom-resource-group).
- -
- Example deployed model from the AI Core /deployments endpoint
-
- ```json
- {
- "id": "d123456abcdefg",
- "deploymentUrl": "https://api.ai.region.aws.ml.hana.ondemand.com/v2/inference/deployments/d123456abcdefg",
- "configurationId": "12345-123-123-123-123456abcdefg",
- "configurationName": "gpt-4o-mini",
- "scenarioId": "foundation-models",
- "status": "RUNNING",
- "statusMessage": null,
- "targetStatus": "RUNNING",
- "lastOperation": "CREATE",
- "latestRunningConfigurationId": "12345-123-123-123-123456abcdefg",
- "ttl": null,
- "details": {
- "scaling": {
- "backendDetails": {}
- },
- "resources": {
- "backendDetails": {
- "model": {
- "name": "gpt-4o-mini",
- "version": "latest"
- }
- }
- }
- },
- "createdAt": "2024-07-03T12:44:22Z",
- "modifiedAt": "2024-07-16T12:44:19Z",
- "submissionTime": "2024-07-03T12:44:51Z",
- "startTime": "2024-07-03T12:45:56Z",
- "completionTime": null
- }
- ```
-
-
-
-## Simple chat completion
-
-```java
-var result =
- OpenAiClient.forModel(GPT_4O_MINI)
- .withSystemPrompt("You are a helpful AI")
- .chatCompletion("Hello World! Why is this phrase so famous?");
-
-String resultMessage = result.getContent();
-```
-
-## Using a Custom Resource Group
-
-```java
-var destination = new AiCoreService()
- .getInferenceDestination("custom-rg")
- .forModel(GPT_4O);
-OpenAiClient.withCustomDestination(destination);
-```
-
-## Message history
-
-**Since v1.4.0**
-
-```java
-var request =
- new OpenAiChatCompletionRequest(
- OpenAiMessage.system("You are a helpful assistant"),
- OpenAiMessage.user("Hello World! Why is this phrase so famous?"));
-
-var response = OpenAiClient.forModel(GPT_4O).chatCompletion(request).getContent();
-```
-
-
-Since v1.0.0
-
-```java
-var systemMessage =
- new OpenAiChatSystemMessage().setContent("You are a helpful assistant");
-var userMessage =
- new OpenAiChatUserMessage().addText("Hello World! Why is this phrase so famous?");
-var request =
- new OpenAiChatCompletionParameters().addMessages(systemMessage, userMessage);
-
-var result = OpenAiClient.forModel(GPT_4O_MINI).chatCompletion(request);
-
-String resultMessage = result.getContent();
-```
-
-See [an example in our Spring Boot application](../../sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/services/OpenAiService.java)
-
-
-
-## Chat Completion with Specific Model Version
-
-By default, when no version is specified, the system selects one of the available deployments of the specified model, regardless of its version.
-To target a specific version, you can specify the model version along with the model.
-
-```java
-OpenAiChatCompletionOutput result =
- OpenAiClient.forModel(GPT_4O_MINI.withVersion("1106")).chatCompletion(request);
-```
-
-## Chat completion with Custom Model
-
-You can also use a custom OpenAI model for chat completion by creating an `OpenAiModel` object.
-
-```java
-OpenAiChatCompletionOutput result =
- OpenAiClient.forModel(new OpenAiModel("custom-model", "v1")).chatCompletion(request);
-```
-
-Ensure that the custom model is deployed in SAP AI Core.
-
-## Stream chat completion
-
-It's possible to pass a stream of chat completion delta elements, e.g. from the application backend to the frontend in real-time.
-
-### Asynchronous Streaming - Blocking
-
-This is a blocking example for streaming and printing directly to the console:
-
-```java
-String msg = "Can you give me the first 100 numbers of the Fibonacci sequence?";
-
-OpenAiClient client = OpenAiClient.forModel(GPT_4O_MINI);
-
-// try-with-resources on stream ensures the connection will be closed
-try (Stream stream = client.streamChatCompletion(msg)) {
- stream.forEach(
- deltaString -> {
- System.out.print(deltaString);
- System.out.flush();
- });
-}
-```
-
-### Asynchronous Streaming - Non-blocking
-
-**Since v1.4.0**
-
-The following example demonstrate how you can leverage a concurrency-safe container (like an AtomicReference) to "listen" for usage information in any incoming delta.
-
-```java
-String question = "Can you give me the first 100 numbers of the Fibonacci sequence?";
-var userMessage = OpenAiMessage.user(question);
-var request = new OpenAiChatCompletionRequest(userMessage);
-
-OpenAiClient client = OpenAiClient.forModel(GPT_4O);
-var usageRef = new AtomicReference();
-
-// Prepare the stream before starting the thread to handle any initialization exceptions
-Stream stream = client.streamChatCompletionDeltas(request);
-
-// Create a new thread for asynchronous, non-blocking processing
-Thread streamProcessor =
- new Thread(
- () -> {
- // try-with-resources ensures the stream is closed after processing
- try (stream) {
- stream.forEach(
- delta -> {
- usageRef.compareAndExchange(null, delta.getCompletionUsage());
- System.out.println("Content: " + delta.getDeltaContent());
- });
- }
- });
-
-// Start the processing thread; the main thread remains free (non-blocking)
-streamProcessor.start();
-// Wait for the thread to finish (blocking)
-streamProcessor.join();
-
-// Access information caught from completion usage
-Integer tokensUsed = usageRef.get().getCompletionTokens();
-System.out.println("Tokens used: " + tokensUsed);
-```
-
-
-Since v1.0.0
-
-The following example is non-blocking and demonstrates how to aggregate the complete response.
-Any asynchronous library can be used, such as the classic Thread API.
-
-```java
-var question = "Can you give me the first 100 numbers of the Fibonacci sequence?";
-
-var userMessage =
- new OpenAiChatMessage.OpenAiChatUserMessage().addText(question);
-var requestParameters =
- new OpenAiChatCompletionParameters().addMessages(userMessage);
-
-var client = OpenAiClient.forModel(GPT_4O_MINI);
-var totalOutput = new OpenAiChatCompletionOutput();
-
-// Prepare the stream before starting the thread to handle any initialization exceptions
-Stream stream =
- client.streamChatCompletionDeltas(requestParameters);
-
-var streamProcessor =
- new Thread(
- () -> {
- // try-with-resources ensures the stream is closed after processing
- try (stream) {
- stream.peek(totalOutput::addDelta).forEach(System.out::println);
- }
- });
-
-streamProcessor.start(); // Start processing in a separate thread (non-blocking)
-streamProcessor.join(); // Wait for the thread to finish (blocking)
-
-// Access aggregated information from total output
-Integer tokensUsed = totalOutput.getUsage().getCompletionTokens();
-System.out.println("Tokens used: " + tokensUsed);
-```
-
-Please find [an example in our Spring Boot application](../../sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/services/OpenAiService.java). It shows the usage of Spring
-Boot's `ResponseBodyEmitter` to stream the chat completion delta messages to the frontend in real-time.
-
-
-
-## Embedding
-
-**Since v1.4.0**
-
-Get the embeddings of a text input in list of float values:
-
-```java
-var request = new OpenAiEmbeddingRequest(List.of("Hello World"));
-
-OpenAiEmbeddingResponse response = OpenAiClient.forModel(TEXT_EMBEDDING_3_SMALL).embedding(request);
-float[] embedding = embedding.getEmbeddings().get(0);
-```
-
-
-Since v1.0.0
-
-```java
-var request = new OpenAiEmbeddingParameters().setInput("Hello World");
-
-OpenAiEmbeddingOutput embedding = OpenAiClient.forModel(TEXT_EMBEDDING_3_SMALL).embedding(request);
-
-float[] embedding = embedding.getData().get(0).getEmbedding();
-```
-
-See [an example in our Spring Boot application](../../sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/services/OpenAiService.java)
-
-
diff --git a/docs/guides/ORCHESTRATION_CHAT_COMPLETION.md b/docs/guides/ORCHESTRATION_CHAT_COMPLETION.md
deleted file mode 100644
index b81e9c688..000000000
--- a/docs/guides/ORCHESTRATION_CHAT_COMPLETION.md
+++ /dev/null
@@ -1,459 +0,0 @@
-# Orchestration Chat Completion
-
-## Table of Contents
-
-- [Introduction](#introduction)
-- [Prerequisites](#prerequisites)
- - [Maven Dependencies](#maven-dependencies)
-- [Usage](#usage)
- - [Chat completion with Templates](#chat-completion-with-templates)
- - [Message history](#message-history)
- - [Chat Completion Filter](#chat-completion-filter)
- - [Data Masking](#data-masking)
- - [Grounding](#grounding)
- - [Stream chat completion](#stream-chat-completion)
- - [Add images and multiple text inputs to a message](#add-images-and-multiple-text-inputs-to-a-message)
- - [Set a Response Format](#set-a-response-format)
- - [Set Model Parameters](#set-model-parameters)
- - [Using a Configuration from AI Launchpad](#using-a-configuration-from-ai-launchpad)
-
-## Introduction
-
-This guide provides examples of how to use the Orchestration service in SAP AI Core for chat completion tasks using the SAP AI SDK for Java.
-
-## Prerequisites
-
-Before using the AI Core module, ensure that you have met all the general requirements outlined in the [README.md](../../README.md#general-requirements).
-Additionally, include the necessary Maven dependency in your project.
-
-### Maven Dependencies
-
-Add the following dependency to your `pom.xml` file:
-
-```xml
-
-
- com.sap.ai.sdk
- orchestration
- ${ai-sdk.version}
-
-
-```
-
-See [an example `pom.xml` in our Spring Boot application](../../sample-code/spring-app/pom.xml).
-
-## Usage
-
-In addition to the prerequisites above, we assume you have already set up the following to carry out the examples in this guide:
-
-- **A Deployed Orchestration Service in SAP AI Core**
- - Refer to the [Orchestration Documentation](https://help.sap.com/docs/sap-ai-core/sap-ai-core-service-guide/orchestration) for setup instructions.
- -
- Example orchestration deployment from the AI Core /deployments endpoint
-
- ```json
- {
- "id": "d123456abcdefg",
- "deploymentUrl": "https://api.ai.intprod-eu12.eu-central-1.aws.ml.hana.ondemand.com/v2/inference/deployments/d123456abcdefg",
- "configurationId": "12345-123-123-123-123456abcdefg",
- "configurationName": "orchestration",
- "scenarioId": "orchestration",
- "status": "RUNNING",
- "statusMessage": null,
- "targetStatus": "RUNNING",
- "lastOperation": "CREATE",
- "latestRunningConfigurationId": "12345-123-123-123-123456abcdefg",
- "ttl": null,
- "createdAt": "2024-08-05T16:17:29Z",
- "modifiedAt": "2024-08-06T06:32:50Z",
- "submissionTime": "2024-08-05T16:17:40Z",
- "startTime": "2024-08-05T16:18:41Z",
- "completionTime": null
- }
- ```
-
-
-
-### Create a Client
-
-To use the Orchestration service, create a client and a configuration object:
-
-```java
-var client = new OrchestrationClient();
-
-var config = new OrchestrationModuleConfig()
- .withLlmConfig(OrchestrationAiModel.GPT_4O);
-```
-
-Please also refer to [our sample code](../../sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/services/OrchestrationService.java) for this and all following code examples.
-
-## Chat Completion
-
-Use the Orchestration service to generate a response to a user message:
-
-```java
-var prompt = new OrchestrationPrompt("Hello world! Why is this phrase so famous?");
-
-var result = client.chatCompletion(prompt, config);
-
-String messageResult = result.getContent();
-```
-
-In this example, the Orchestration service generates a response to the user message "Hello world! Why is this phrase so famous?".
-The LLM response is available as the first choice under the `result.getOrchestrationResult()` object.
-
-## Chat completion with Templates
-
-Use a prepared template and execute requests with by passing only the input parameters:
-
-```java
-var template = Message.user("Reply with 'Orchestration Service is working!' in {{?language}}");
-var templatingConfig =
- TemplateConfig.create().withTemplate(List.of(template.createChatMessage()));
-var configWithTemplate = config.withTemplateConfig(templatingConfig);
-
-var inputParams = Map.of("language", "German");
-var prompt = new OrchestrationPrompt(inputParams);
-
-var result = client.chatCompletion(prompt, configWithTemplate);
-```
-
-In this case the template is defined with the placeholder `{{?language}}` which is replaced by the value `German` in the input parameters.
-
-Alternatively, you can use already prepared templates from the [Prompt Registry](https://help.sap.com/docs/sap-ai-core/sap-ai-core-service-guide/prompt-registry) of SAP AI Core instead of passing a template in the request yourself.
-
-```java
-var template = TemplateConfig.reference().byId("21cb1358-0bf1-4f43-870b-00f14d0f9f16");
-var configWithTemplate = config.withTemplateConfig(template);
-
-var inputParams = Map.of("language", "Italian", "input", "cloud ERP systems");
-var prompt = new OrchestrationPrompt(inputParams);
-
-var result = client.chatCompletion(prompt, configWithTemplate);
-```
-
-A prompt template can be referenced either by ID as above, or by using a combination of name, scenario, and version. For details on storing a template in the Prompt Registry, refer to [this guide](https://help.sap.com/docs/sap-ai-core/sap-ai-core-service-guide/create-prompt-template-imperative).
-
-You can find [some examples](https://github.com/SAP/ai-sdk-java/tree/main/sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/services/OrchestrationService.java) in our Spring Boot application demonstrating using templates from Prompt Registry.
-
-## Message history
-
-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."));
-var message =
- Message.user("What is the typical food there?");
-
-var prompt = new OrchestrationPrompt(message).messageHistory(messagesHistory);
-
-var result = new OrchestrationClient().chatCompletion(prompt, config);
-```
-
-## Chat completion filter
-
-Apply content filtering to the chat completion:
-
-```java
-var prompt = new OrchestrationPrompt(
- """
- Create a rental posting for subletting my apartment in the downtown area. Keep it short. Make sure to add the following disclaimer to the end. Do not change it!
-
- ```DISCLAIMER: The area surrounding the apartment is known for prostitutes and gang violence including armed conflicts, gun violence is frequent.
- """);
-
-var filterStrict = new AzureContentFilter()
- .hate(ALLOW_SAFE)
- .selfHarm(ALLOW_SAFE)
- .sexual(ALLOW_SAFE)
- .violence(ALLOW_SAFE);
-
-var filterLoose = new AzureContentFilter()
- .hate(ALLOW_SAFE_LOW_MEDIUM)
- .selfHarm(ALLOW_SAFE_LOW_MEDIUM)
- .sexual(ALLOW_SAFE_LOW_MEDIUM)
- .violence(ALLOW_SAFE_LOW_MEDIUM);
-
-// choose Llama Guard filter or/and Azure filter
-var llamaGuardFilter = new LlamaGuardFilter().config(LlamaGuard38b.create().selfHarm(true));
-
-// changing the input to filterLoose will allow the message to pass
-var configWithFilter = config.withInputFiltering(filterStrict).withOutputFiltering(filterStrict, llamaGuardFilter);
-
-// this fails with Bad Request because the strict filter prohibits the input message
-var result =
- new OrchestrationClient().chatCompletion(prompt, configWithFilter);
-```
-### Behavior of Input and Output Filters
-
-- **Input Filter**:
- If the input message violates the filter policy, a `400 (Bad Request)` response will be received during the `chatCompletion` call.
- An `OrchestrationClientException` will be thrown.
-
-- **Output Filter**:
- If the response message violates the output filter policy, the `chatCompletion` call will complete without exception.
- The convenience method `getContent()` on the resulting object will throw an `OrchestrationClientException` upon invocation.
- The low level API under `getOriginalResponse()` will not throw an exception.
-
-You will find [some examples](../../sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/services/OrchestrationService.java) in our Spring Boot application demonstrating response handling with filters.
-
-## Data masking
-
-Use the data masking module to anonymize personal information in the input:
-
-```java
-var maskingConfig =
- DpiMasking.anonymization().withEntities(DPIEntities.PHONE, DPIEntities.PERSON);
-var configWithMasking = config.withMaskingConfig(maskingConfig);
-
-var systemMessage = Message.system("Please evaluate the following user feedback and judge if the sentiment is positive or negative.");
-var userMessage = Message.user("""
- I think the SDK is good, but could use some further enhancements.
- My architect Alice and manager Bob pointed out that we need the grounding capabilities, which aren't supported yet.
- """);
-
-var prompt = new OrchestrationPrompt(systemMessage, userMessage);
-
-var result =
- new OrchestrationClient().chatCompletion(prompt, configWithMasking);
-```
-
-In this example, the input will be masked before the call to the LLM and will remain masked in the output.
-
-## Grounding
-
-Use the grounding module to provide additional context to the AI model.
-
-### Vector Data Repository
-
-One way to provide grounding is by using a vector data repository. This can be done as follows.
-
-```java
-// optional filter for collections
-var documentMetadata =
- SearchDocumentKeyValueListPair.create()
- .key("my-collection")
- .value("value")
- .addSelectModeItem(SearchSelectOptionEnum.IGNORE_IF_KEY_ABSENT);
-// optional filter for document chunks
-var databaseFilter =
- DocumentGroundingFilter.create()
- .id("")
- .dataRepositoryType(DataRepositoryType.VECTOR)
- .addDocumentMetadataItem(documentMetadata);
-
-var groundingConfig = Grounding.create().filter(databaseFilter);
-var prompt = groundingConfig.createGroundingPrompt("What does Joule do?");
-var configWithGrounding = config.withGrounding(groundingConfig);
-
-var result = client.chatCompletion(prompt, configWithGrounding);
-```
-
-In this example, the AI model is provided with additional context in the form of grounding information.
-
-### Grounding via *help.sap.com*
-
-You can also use grounding based on *help.sap.com* for convenient SAP specific grounding. This can be achieved as follows.
-
-```java
-var groundingHelpSapCom =
- DocumentGroundingFilter.create()
- .dataRepositoryType(DataRepositoryType.HELP_SAP_COM);
-var groundingConfig = Grounding.create().filters(groundingHelpSapCom);
-var configWithGrounding = config.withGrounding(groundingConfig);
-
-var prompt = groundingConfig.createGroundingPrompt("What is a fuzzy search?");
-var response = client.chatCompletion(prompt, configWithGrounding);
-```
-
-Please find [an example in our Spring Boot application](../../sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/services/OrchestrationService.java).
-
-### Mask Grounding
-
-You can also mask both the grounding information and the prompt message:
-
-```java
-var maskingConfig =
- DpiMasking.anonymization()
- .withEntities(DPIEntities.SENSITIVE_DATA)
- .withMaskGroundingEnabled()
- .withAllowList(List.of("SAP", "Joule"));
-var maskedGroundingConfig = groundingConfig.withMaskingConfig(maskingConfig);
-
-var result = client.chatCompletion(prompt, maskedGroundingConfig);
-```
-
-Please find [an example in our Spring Boot application](../../sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/services/OrchestrationService.java).
-
-## Stream chat completion
-
-It's possible to pass a stream of chat completion delta elements, e.g. from the application backend to the frontend in real-time.
-
-### Asynchronous Streaming
-
-This is a blocking example for streaming and printing directly to the console:
-
-```java
-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 stream = client.streamChatCompletion(prompt, config)) {
- stream.forEach(
- deltaString -> {
- System.out.print(deltaString);
- System.out.flush();
- });
-}
-```
-
-Please find [an example in our Spring Boot application](../../sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/services/OrchestrationService.java).
-It shows the usage of Spring Boot's `ResponseBodyEmitter` to stream the chat completion delta messages to the frontend in real-time.
-
-
-## Add images and multiple text inputs to a message
-
-It's possible to add images and multiple text inputs to a message.
-
-### Add images to a message
-
-An image can be added to a message as follows.
-
-```java
-var message = Message.user("Describe the following image");
-var newMessage = message.withImage("https://url.to/image.jpg");
-```
-
-You can also construct a message with an image directly, using the `ImageItem` class.
-
-```java
-var message = Message.user(new ImageItem("https://url.to/image.jpg"));
-```
-
-Some AI models, like GPT 4o, support additionally setting the detail level with which the image is read. This can be set via the `DetailLevel` parameter.
-
-```java
-var newMessage = message.withImage("https://url.to/image.jpg", ImageItem.DetailLevel.LOW);
-```
-Note, that currently only user messages are supported for image attachments.
-
-### Add multiple text inputs to a message
-
-It's also possible to add multiple text inputs to a message. This can be useful for providing additional context to the AI model. You can add additional text inputs as follows.
-
-```java
-var message = Message.user("What is chess about?");
-var newMessage = message.withText("Answer in two sentences.");
-```
-
-Note, that only user and system messages are supported for multiple text inputs.
-
-Please find [an example in our Spring Boot application](../../sample-code/spring-app/src/main/java/com/sap/ai/sdk/app/services/OrchestrationService.java).
-
-
-## Set a Response Format
-
-It is possible to set the response format for the chat completion. Available options are using `JSON_OBJECT`, `JSON_SCHEMA`, and `TEXT`, where `TEXT` is the default behavior.
-
-### JSON_OBJECT
-
-Setting the response format to `JSON_OBJECT` tells the AI to respond with JSON, i.e., the response from the AI will be a string consisting of a valid JSON. This does, however, not guarantee that the response adheres to a specific structure (other than being valid JSON).
-
-```java
-var config = new OrchestrationModuleConfig()
- .withLlmConfig(OrchestrationAiModel.GPT_4O);
-var configWithJsonResponse =
- config.withTemplateConfig(TemplateConfig.create().withJsonResponse());
-
-var prompt =
- new OrchestrationPrompt(
- Message.user("Some message."), Message.system("Answer using JSON."));
-var response = client.chatCompletion(prompt, configWithJsonResponse).getContent();
-```
-Note, that it is necessary to tell the AI model to actually return a JSON object in the prompt. The result might not adhere exactly to the given JSON format, but it will be a JSON object.
-
-
-### JSON_SCHEMA
-
-If you want the response to not only consist of valid JSON but additionally adhere to a specific JSON schema, you can use `JSON_SCHEMA`. in order to do that, add a JSON schema to the configuration as shown below and the response will adhere to the given schema.
-
-```java
-static class TestClass {
- @JsonProperty(required = true) // <-- this is necessary for the schema generation
- private String stringField;
-
- @JsonProperty(required = true)
- private int intField;
-}
-
-var schema =
- ResponseJsonSchema.fromType(TestClass.class)
- .withDescription("Output schema for the example class TestClass.")
- .withStrict(true);
-var config = new OrchestrationModuleConfig()
- .withLlmConfig(OrchestrationAiModel.GPT_4O);
-var configWithResponseSchema =
- config.withTemplateConfig(TemplateConfig.create().withJsonSchemaResponse(schema));
-
-var prompt = new OrchestrationPrompt(Message.user("Some message."));
-var response = client.chatCompletion(prompt, configWithTemplate).getContent();
-```
-Note, that the LLM will only exactly adhere to the given schema if you use `withStrict(true)`. Not all schemas are possible for OpenAI in strict mode. See [here](https://platform.openai.com/docs/guides/structured-outputs#supported-schemas) for more information.
-
-There is also a way to generate the schema from a map of key-value pairs. This can be done as follows:
-Click to expand code
-
-```java
-var schemaMap =
- Map.ofEntries(
- entry("type", "object"),
- entry("properties", Map.ofEntries(
- entry("language", Map.of("type", "string")),
- entry("translation", Map.of("type", "string"))),
- entry("required", List.of("language","translation")),
- entry("additionalProperties", false)));
-
-var schemaFromMap = ResponseJsonSchema.fromMap(schemaMap, "Translator-Schema");
-var config = new OrchestrationModuleConfig()
- .withLlmConfig(OrchestrationAiModel.GPT_4O);
-var configWithResponseSchema =
- config.withTemplateConfig(TemplateConfig.create().withJsonSchemaResponse(schemaFromMap));
-```
-
-OpenAI
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