Merge pull request #279971 from santiagxf/santiagxf-patch-2

SDKs update 2

Author: prmerger-automator[bot]

articles/ai-studio/reference/reference-model-inference-api.md

@@ -136,7 +136,7 @@ Content-Type: application/json
 
 The Azure AI Model Inference API specifies a set of modalities and parameters that models can subscribe to. However, some models may have further capabilities that the ones the API indicates. On those cases, the API allows the developer to pass them as extra parameters in the payload.
 
-By setting a header `extra-parameters: allow`, the API will attempt to pass any unknown parameter directly to the underlying model. If the model can handle that parameter, the request completes.
+By setting a header `extra-parameters: pass-through`, the API will attempt to pass any unknown parameter directly to the underlying model. If the model can handle that parameter, the request completes.
 
 The following example shows a request passing the parameter `safe_prompt` supported by Mistral-Large, which isn't specified in the Azure AI Model Inference API:
 
@@ -163,6 +163,7 @@ var messages = [
 ];
 
 var response = await client.path("/chat/completions").post({
+    "extra-parameters": "pass-through",
     body: {
         messages: messages,
         safe_mode: true
@@ -178,7 +179,7 @@ __Request__
 POST /chat/completions?api-version=2024-04-01-preview
 Authorization: Bearer <bearer-token>
 Content-Type: application/json
-extra-parameters: allow
+extra-parameters: pass-through
 ```
 
 ```JSON
@@ -203,7 +204,7 @@ extra-parameters: allow
 ---
 
 > [!TIP]
-> Alternatively, you can set `extra-parameters: drop` to drop any unknown parameter in the request. Use this capability in case you happen to be sending requests with extra parameters that you know the model won't support but you want the request to completes anyway. A typical example of this is indicating `seed` parameter.
+> The default value for `extra-parameters` is `error` which returns an error if an extra parameter is indicated in the payload. Alternatively, you can set `extra-parameters: ignore` to drop any unknown parameter in the request. Use this capability in case you happen to be sending requests with extra parameters that you know the model won't support but you want the request to completes anyway. A typical example of this is indicating `seed` parameter.
 
 ### Models with disparate set of capabilities
 
@@ -426,3 +427,27 @@ __Response__
 ## Getting started
 
 The Azure AI Model Inference API is currently supported in certain models deployed as [Serverless API endpoints](../how-to/deploy-models-serverless.md) and Managed Online Endpoints. Deploy any of the [supported models](#availability) and use the exact same code to consume their predictions.
+
+# [Python](#tab/python)
+
+The client library `azure-ai-inference` does inference, including chat completions, for AI models deployed by Azure AI Studio and Azure Machine Learning Studio. It supports Serverless API endpoints and Managed Compute endpoints (formerly known as Managed Online Endpoints).
+
+Explore our [samples](https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/ai/azure-ai-inference/samples) and read the [API reference documentation](https://aka.ms/azsdk/azure-ai-inference/python/reference) to get yourself started.
+
+# [JavaScript](#tab/javascript)
+
+The client library `@azure-rest/ai-inference` does inference, including chat completions, for AI models deployed by Azure AI Studio and Azure Machine Learning Studio. It supports Serverless API endpoints and Managed Compute endpoints (formerly known as Managed Online Endpoints).
+
+Explore our [samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/ai/ai-inference-rest/samples) and read the [API reference documentation](https://aka.ms/AAp1kxa) to get yourself started.
+
+# [REST](#tab/rest)
+
+Explore the reference section of the Azure AI model inference API to see parameters and options to consume models, including chat completions models, deployed by Azure AI Studio and Azure Machine Learning Studio. It supports Serverless API endpoints and Managed Compute endpoints (formerly known as Managed Online Endpoints).
+
+* [Get info](reference-model-inference-info.md): Returns the information about the model deployed under the endpoint.
+* [Text embeddings](reference-model-inference-embeddings.md): Creates an embedding vector representing the input text.
+* [Text completions](reference-model-inference-completions.md): Creates a completion for the provided prompt and parameters.
+* [Chat completions](reference-model-inference-chat-completions.md): Creates a model response for the given chat conversation.
+* [Image embeddings](reference-model-inference-images-embeddings.md): Creates an embedding vector representing the input text and image.
+
+---

articles/ai-studio/reference/reference-model-inference-chat-completions.md

@@ -35,7 +35,7 @@ POST /chat/completions?api-version=2024-04-01-preview
 
 | Name | Required | Type | Description |
 | --- | --- | --- | --- |
-| extra-parameters | | string | The behavior of the API when extra parameters are indicated in the payload. Using `allow` makes the API to pass the parameter to the underlying model. Use this value when you want to pass parameters that you know the underlying model can support. Using `drop` makes the API to drop any unsupported parameter. Use this value when you need to use the same payload across different models, but one of the extra parameters may make a model to error out if not supported. Using `error` makes the API to reject any extra parameter in the payload. Only parameters specified in this API can be indicated, or a 400 error is returned. |
+| extra-parameters | | string | The behavior of the API when extra parameters are indicated in the payload. Using `pass-through` makes the API to pass the parameter to the underlying model. Use this value when you want to pass parameters that you know the underlying model can support. Using `ignore` makes the API to drop any unsupported parameter. Use this value when you need to use the same payload across different models, but one of the extra parameters may make a model to error out if not supported. Using `error` makes the API to reject any extra parameter in the payload. Only parameters specified in this API can be indicated, or a 400 error is returned. |
 | azureml-model-deployment |     | string | Name of the deployment you want to route the request to. Supported for endpoints that support multiple deployments. |
 
 ## Request Body

articles/ai-studio/reference/reference-model-inference-completions.md

@@ -28,6 +28,14 @@ POST /completions?api-version=2024-04-01-preview
 | --- | --- | --- | --- | --- |
 | api-version | query | True | string | The version of the API in the format "YYYY-MM-DD" or "YYYY-MM-DD-preview". |
 
+## Request Header
+
+
+| Name | Required | Type | Description |
+| --- | --- | --- | --- |
+| extra-parameters | | string | The behavior of the API when extra parameters are indicated in the payload. Using `pass-through` makes the API to pass the parameter to the underlying model. Use this value when you want to pass parameters that you know the underlying model can support. Using `ignore` makes the API to drop any unsupported parameter. Use this value when you need to use the same payload across different models, but one of the extra parameters may make a model to error out if not supported. Using `error` makes the API to reject any extra parameter in the payload. Only parameters specified in this API can be indicated, or a 400 error is returned. |
+| azureml-model-deployment |     | string | Name of the deployment you want to route the request to. Supported for endpoints that support multiple deployments. |
+
 
 ## Request Body
 
@@ -285,4 +293,4 @@ The object type, which is always "list".
 | detail | [Detail](#detail) |     |
 | error | string | The error description. |
 | message | string | The error message. |
-| status | integer | The HTTP status code. |
+| status | integer | The HTTP status code. |

articles/ai-studio/reference/reference-model-inference-embeddings.md

@@ -35,7 +35,7 @@ POST /embeddings?api-version=2024-04-01-preview
 
 | Name | Required | Type | Description |
 | --- | --- | --- | --- |
-| extra-parameters | | string | The behavior of the API when extra parameters are indicated in the payload. Using `allow` makes the API to pass the parameter to the underlying model. Use this value when you want to pass parameters that you know the underlying model can support. Using `drop` makes the API to drop any unsupported parameter. Use this value when you need to use the same payload across different models, but one of the extra parameters may make a model to error out if not supported. Using `error` makes the API to reject any extra parameter in the payload. Only parameters specified in this API can be indicated, or a 400 error is returned. |
+| extra-parameters | | string | The behavior of the API when extra parameters are indicated in the payload. Using `pass-through` makes the API to pass the parameter to the underlying model. Use this value when you want to pass parameters that you know the underlying model can support. Using `ignore` makes the API to drop any unsupported parameter. Use this value when you need to use the same payload across different models, but one of the extra parameters may make a model to error out if not supported. Using `error` makes the API to reject any extra parameter in the payload. Only parameters specified in this API can be indicated, or a 400 error is returned. |
 | azureml-model-deployment |     | string | Name of the deployment you want to route the request to. Supported for endpoints that support multiple deployments. |
 
 ## Request Body

articles/ai-studio/reference/reference-model-inference-images-embeddings.md

@@ -35,7 +35,7 @@ POST /images/embeddings?api-version=2024-04-01-preview
 
 | Name | Required | Type | Description |
 | --- | --- | --- | --- |
-| extra-parameters | | string | The behavior of the API when extra parameters are indicated in the payload. Using `allow` makes the API to pass the parameter to the underlying model. Use this value when you want to pass parameters that you know the underlying model can support. Using `drop` makes the API to drop any unsupported parameter. Use this value when you need to use the same payload across different models, but one of the extra parameters may make a model to error out if not supported. Using `error` makes the API to reject any extra parameter in the payload. Only parameters specified in this API can be indicated, or a 400 error is returned. |
+| extra-parameters | | string | The behavior of the API when extra parameters are indicated in the payload. Using `pass-through` makes the API to pass the parameter to the underlying model. Use this value when you want to pass parameters that you know the underlying model can support. Using `ignore` makes the API to drop any unsupported parameter. Use this value when you need to use the same payload across different models, but one of the extra parameters may make a model to error out if not supported. Using `error` makes the API to reject any extra parameter in the payload. Only parameters specified in this API can be indicated, or a 400 error is returned. |
 | azureml-model-deployment |     | string | Name of the deployment you want to route the request to. Supported for endpoints that support multiple deployments. |
 
 ## Request Body