chore: Docs add model version and api version (#188)

* docs: add model version for orchestration * docs: add api version and request config * docs: add custom request config to orchestration * fix: Changes from lint * docs: remove api version configuration * docs: change headers in foundation-models --------- Co-authored-by: cloud-sdk-js <[email protected]>
SAP · Oct 2, 2024 · 189a238 · 189a238
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diff --git a/packages/foundation-models/README.md b/packages/foundation-models/README.md
@@ -4,15 +4,15 @@ This package incorporates generative AI foundation models into your AI activitie
 
 ## Table of Contents
 
-1. [Installation](#installation)
-2. [Prerequisites](#prerequisites)
-3. [Usage](#usage)
-   - [Client Initialization](#client-initialization)
-   - [Azure OpenAI Client](#azure-openai-client)
-     - [Chat Client](#chat-client)
-     - [Embedding Client](#embedding-client)
-4. [Support, Feedback, Contribution](#support-feedback-contribution)
-5. [License](#license)
+- [Table of Contents](#table-of-contents)
+- [Installation](#installation)
+- [Prerequisites](#prerequisites)
+- [Usage](#usage)
+  - [Client Initialization](#client-initialization)
+  - [Chat Client](#chat-client)
+  - [Embedding Client](#embedding-client)
+- [Support, Feedback, Contribution](#support-feedback-contribution)
+- [License](#license)
 
 ## Installation
 
@@ -60,26 +60,38 @@ const chatClient = new AzureOpenAiChatClient({
 });
 ```
 
-### Azure OpenAI Client
+### Chat Client
 
-The Azure OpenAI client can then be used to send chat completion or embedding requests to models deployed in the SAP generative AI hub.
+Use the `AzureOpenAiChatClient` to send chat completion requests to an OpenAI model deployed in SAP generative AI hub.
 
-#### Chat Client
+The client sends request with Azure OpenAI API version `2024-06-01`.
 
-Use the `AzureOpenAiChatClient` to send chat completion requests to an OpenAI model deployed in SAP generative AI hub.
+Set request configuration in the `requestConfig` parameter. The following example shows a call with messages and optional request configuration.
 
 ```ts
 import { AzureOpenAiChatClient } from '@sap-ai-sdk/foundation-models';
 
 const chatClient = new AzureOpenAiChatClient('gpt-4o');
-const response = await chatClient.run({
-  messages: [
-    {
-      role: 'user',
-      content: 'Where is the deepest place on earth located'
+const response = await chatClient.run(
+  {
+    messages: [
+      {
+        role: 'user',
+        content: 'Where is the deepest place on earth located'
+      }
+    ]
+  },
+  {
+    headers: {
+      'x-custom-header': 'custom-value'
+      // Add more headers here
+    },
+    params: {
+      // Add more parameters here
     }
-  ]
-});
+    // Add more request configuration here
+  }
+);
 
 const responseContent = response.getContent();
 ```
@@ -124,7 +136,7 @@ logger.info(
 
 Refer to `AzureOpenAiChatCompletionParameters` interface for other parameters that can be passed to the chat completion request.
 
-#### Embedding Client
+### Embedding Client
 
 Use the `AzureOpenAiEmbeddingClient` to send embedding requests to an OpenAI model deployed in SAP generative AI hub.
 
@@ -140,6 +152,8 @@ const response = await embeddingClient.run({
 const embedding = response.getEmbedding();
 ```
 
+Define optional request configuration when running the client, similar to the chat client.
+
 ## Support, Feedback, Contribution
 
 This project is open to feature requests/suggestions, bug reports etc. via [GitHub issues](https://github.com/SAP/ai-sdk-js/issues).

diff --git a/packages/orchestration/README.md b/packages/orchestration/README.md
@@ -2,16 +2,18 @@
 
 This package incorporates generative AI orchestration capabilities into your AI activities in SAP AI Core and SAP AI Launchpad.
 
-## Table of Contents
-
-1. [Installation](#installation)
-2. [Prerequisites](#prerequisites)
-3. [Orchestration Service](#orchestration-service)
-4. [Usage](#usage)
-   - [Templating](#templating)
-   - [Content Filtering](#content-filtering)
-5. [Support, Feedback, Contribution](#support-feedback-contribution)
-6. [License](#license)
+### Table of Contents
+
+- [Installation](#installation)
+  - [Prerequisites](#prerequisites)
+- [Orchestration Service](#orchestration-service)
+- [Usage](#usage)
+  - [Templating](#templating)
+    - [Token Usage](#token-usage)
+  - [Content Filtering](#content-filtering)
+    - [Data Masking](#data-masking)
+- [Support, Feedback, Contribution](#support-feedback-contribution)
+- [License](#license)
 
 ## Installation
 
@@ -39,12 +41,30 @@ Find more details about orchestration workflow [here](https://help.sap.com/docs/
 ## Usage
 
 Leverage the orchestration service capabilities by using the orchestration client.
-The client allows you to configure various modules, such as templating and content filtering, while sending chat completion requests to an orchestration-compatible generative AI model.
+Configure the LLM module by setting the `model_name` and `model_params` properties.
+Define the optional `model_version` property to choose an available model version.
+By default, the version is set to `latest`.
+
+```ts
+import { OrchestrationClient } from '@sap-ai-sdk/orchestration';
+
+const orchestrationClient = new OrchestrationClient({
+  llm: {
+    model_name: 'gpt-4-32k',
+    model_params: { max_tokens: 50, temperature: 0.1 }
+    model_version: 'latest'
+  },
+  ...
+});
+```
+
+The client allows you to combine various modules, such as templating and content filtering, while sending chat completion requests to an orchestration-compatible generative AI model.
 
 ### Templating
 
 Use the orchestration client with templating to pass a prompt containing placeholders that will be replaced with input parameters during a chat completion request.
 This allows for variations in the prompt based on the input parameters.
+Set custom request configuration when calling `chatCompletion` function.
 
 ```ts
 import { OrchestrationClient } from '@sap-ai-sdk/orchestration';
@@ -61,9 +81,20 @@ const orchestrationClient = new OrchestrationClient({
   }
 });
 
-const response = await orchestrationClient.chatCompletion({
-  inputParams: { country: 'France' }
-});
+const response = await orchestrationClient.chatCompletion(
+  {
+    inputParams: { country: 'France' }
+  },
+  {
+    headers: {
+      // Add more headers here
+    },
+    params: {
+      // Add more parameters here
+    }
+    // Add more request configuration here
+  }
+);
 
 const responseContent = response.getContent();
 ```