Merge pull request #4970 from samuel100/asks_PR

Dirty PR: Asks pr

Author: ShannonLeavitt

articles/ai-foundry/concepts/models-featured.md

@@ -251,9 +251,7 @@ See [the Microsoft model collection in Azure AI Foundry portal](https://ai.azure
 Mistral AI offers two categories of models, namely: 
 
 - _Premium models_: These include Mistral Large, Mistral Small, Mistral-OCR-2503, Mistral Medium 3 (25.05), and Ministral 3B models, and are available as serverless APIs with pay-as-you-go token-based billing.  
-- _Premium models_: These include Mistral Large, Mistral Small, Mistral-OCR-2503, and Ministral 3B models, and are available as standard deployments.   
-- _Open models_: These include Mistral-small-2503, Codestral, and Mistral Nemo (that are available as standard deployments), and [Mixtral-8x7B-Instruct-v01, Mixtral-8x7B-v01, Mistral-7B-Instruct-v01, and Mistral-7B-v01](../how-to/deploy-models-mistral-open.md)(that are available to download and run on self-hosted managed endpoints).
-
+- _Open models_: These include Mistral-small-2503, Codestral, and Mistral Nemo (that are available as serverless APIs with pay-as-you-go token-based billing), and [Mixtral-8x7B-Instruct-v01, Mixtral-8x7B-v01, Mistral-7B-Instruct-v01, and Mistral-7B-v01](../how-to/deploy-models-mistral-open.md)(that are available to download and run on self-hosted managed endpoints).
 
 | Model  | Type | Capabilities |
 | ------ | ---- | --- | 

articles/ai-foundry/foundry-local/concepts/foundry-local-architecture.md

@@ -13,6 +13,8 @@ author: samuel100
 
 # Foundry Local architecture
 
+[!INCLUDE [foundry-local-preview](./../includes/foundry-local-preview.md)]
+
 Foundry Local enables efficient, secure, and scalable AI model inference directly on your devices. This article explains the core components of Foundry Local and how they work together to deliver AI capabilities.
 
 Key benefits of Foundry Local include:
@@ -37,7 +39,7 @@ The Foundry Local architecture consists of these main components:
 
 The Foundry Local Service includes an OpenAI-compatible REST server that provides a standard interface for working with the inference engine. It's also possible to manage models over REST. Developers use this API to send requests, run models, and get results programmatically.
 
-- **Endpoint**: The endpoint is *dynamically allocated* when the service starts. You can find the endpoint by running the `foundry service status` command. When using Foundry Local in your applications, we recommend using the SDK that automatically handles the endpoint for you. For more details on how to use the Foundry Local SDK, read the [Integrated inferencing SDKs with Foundry Local](../how-to/how-to-integrate-with-inference-sdks.md) article.
+- **Endpoint**: The endpoint is _dynamically allocated_ when the service starts. You can find the endpoint by running the `foundry service status` command. When using Foundry Local in your applications, we recommend using the SDK that automatically handles the endpoint for you. For more details on how to use the Foundry Local SDK, read the [Integrated inferencing SDKs with Foundry Local](../how-to/how-to-integrate-with-inference-sdks.md) article.
 - **Use Cases**:
   - Connect Foundry Local to your custom applications
   - Execute models through HTTP requests
@@ -109,9 +111,7 @@ The Foundry CLI is a powerful tool for managing models, the inference engine, an
 
 #### Inferencing SDK integration
 
-Foundry Local supports integration with various SDKs, such as the OpenAI SDK, enabling developers to use familiar programming interfaces to interact with the local inference engine.
-
-- **Supported SDKs**: Python, JavaScript, C#, and more.
+Foundry Local supports integration with various SDKs in most languages, such as the OpenAI SDK, enabling developers to use familiar programming interfaces to interact with the local inference engine.
 
 > [!TIP]
 > To learn more about integrating with inferencing SDKs, read [Integrate inferencing SDKs with Foundry Local](../how-to/how-to-integrate-with-inference-sdks.md).

articles/ai-foundry/foundry-local/get-started.md

@@ -16,6 +16,8 @@ ms.custom: build-2025
 
 # Get started with Foundry Local
 
+[!INCLUDE [foundry-local-preview](./includes/foundry-local-preview.md)]
+
 This guide walks you through setting up Foundry Local to run AI models on your device. 
 
 ## Prerequisites

articles/ai-foundry/foundry-local/how-to/how-to-chat-application-with-open-web-ui.md

@@ -16,6 +16,8 @@ ms.custom: build-2025
 
 # Integrate Open Web UI with Foundry Local
 
+[!INCLUDE [foundry-local-preview](./../includes/foundry-local-preview.md)]
+
 This tutorial shows you how to create a chat application using Foundry Local and Open Web UI. When you finish, you have a working chat interface running entirely on your local device.
 
 ## Prerequisites

articles/ai-foundry/foundry-local/how-to/how-to-compile-hugging-face-models.md

@@ -13,6 +13,8 @@ author: samuel100
 
 # Compile Hugging Face models to run on Foundry Local
 
+[!INCLUDE [foundry-local-preview](./../includes/foundry-local-preview.md)]
+
 Foundry Local runs ONNX models on your device with high performance. While the model catalog offers _out-of-the-box_ precompiled options, you can use any model in the ONNX format.
 
 To compile existing models in Safetensor or PyTorch format into the ONNX format, you can use [Olive](https://microsoft.github.io/Olive). Olive is a tool that optimizes models to ONNX format, making them suitable for deployment in Foundry Local. It uses techniques like _quantization_ and _graph optimization_ to improve performance.

articles/ai-foundry/foundry-local/how-to/how-to-integrate-with-inference-sdks.md

@@ -14,6 +14,8 @@ author: samuel100
 
 # Integrate inferencing SDKs with Foundry Local
 
+[!INCLUDE [foundry-local-preview](./../includes/foundry-local-preview.md)]
+
 Foundry Local integrates with various inferencing SDKs - such as OpenAI, Azure OpenAI, Langchain, etc. This guide shows you how to connect your applications to locally running AI models using popular SDKs.
 
 ## Prerequisites

articles/ai-foundry/foundry-local/how-to/how-to-use-langchain-with-foundry-local.md

@@ -17,6 +17,8 @@ zone_pivot_groups: foundry-local-sdk
 
 # Build a translation application with LangChain
 
+[!INCLUDE [foundry-local-preview](./../includes/foundry-local-preview.md)]
+
 This tutorial shows you how to create an application using the Foundry Local SDK and [LangChain](https://www.langchain.com/langchain). In this tutorial, you build a translation application that translates text from one language to another that uses a local model.
 
 ::: zone pivot="programming-language-python"

articles/ai-foundry/foundry-local/includes/foundry-local-preview.md

@@ -0,0 +1,14 @@
+---
+title: include file
+description: include file
+author: jonburchel
+ms.author: jburchel
+ms.service: azure-ai-foundry
+ms.topic: include
+ms.date: 05/19/2025
+ms.custom: include file
+---
+
+> [!IMPORTANT]
+> - Foundry Local is available in preview. Public preview releases provide early access to features that are in active deployment.
+> - Features, approaches, and processes can change or have limited capabilities, before General Availability (GA).

articles/ai-foundry/foundry-local/includes/integrate-examples/javascript.md

@@ -32,15 +32,15 @@ import { FoundryLocalManager } from "foundry-local-sdk";
 // to your end-user's device.
 // TIP: You can find a list of available models by running the 
 // following command in your terminal: `foundry model list`.
-const modelAlias = "deepseek-r1-1.5b";
+const alias = "deepseek-r1-1.5b";
 
 // Create a FoundryLocalManager instance. This will start the Foundry 
 // Local service if it is not already running.
 const foundryLocalManager = new FoundryLocalManager()
 
 // Initialize the manager with a model. This will download the model 
 // if it is not already present on the user's device.
-const modelInfo = await foundryLocalManager.init(modelAlias)
+const modelInfo = await foundryLocalManager.init(alias)
 console.log("Model Info:", modelInfo)
 
 const openai = new OpenAI({
@@ -83,15 +83,15 @@ import { FoundryLocalManager } from "foundry-local-sdk";
 // to your end-user's device.
 // TIP: You can find a list of available models by running the 
 // following command in your terminal: `foundry model list`.
-const modelAlias = "deepseek-r1-1.5b";
+const alias = "deepseek-r1-1.5b";
 
 // Create a FoundryLocalManager instance. This will start the Foundry 
 // Local service if it is not already running.
 const foundryLocalManager = new FoundryLocalManager()
 
 // Initialize the manager with a model. This will download the model 
 // if it is not already present on the user's device.
-const modelInfo = await foundryLocalManager.init(modelAlias)
+const modelInfo = await foundryLocalManager.init(alias)
 console.log("Model Info:", modelInfo)
 
 const openai = new OpenAI({
@@ -133,15 +133,15 @@ import { FoundryLocalManager } from "foundry-local-sdk";
 // to your end-user's device.
 // TIP: You can find a list of available models by running the 
 // following command in your terminal: `foundry model list`.
-const modelAlias = "deepseek-r1-1.5b";
+const alias = "deepseek-r1-1.5b";
 
 // Create a FoundryLocalManager instance. This will start the Foundry 
 // Local service if it is not already running.
 const foundryLocalManager = new FoundryLocalManager()
 
 // Initialize the manager with a model. This will download the model 
 // if it is not already present on the user's device.
-const modelInfo = await foundryLocalManager.init(modelAlias)
+const modelInfo = await foundryLocalManager.init(alias)
 console.log("Model Info:", modelInfo)
 
 async function queryModel() {
@@ -176,15 +176,15 @@ import { FoundryLocalManager } from "foundry-local-sdk";
 // to your end-user's device.
 // TIP: You can find a list of available models by running the 
 // following command in your terminal: `foundry model list`.
-const modelAlias = "deepseek-r1-1.5b";
+const alias = "deepseek-r1-1.5b";
 
 // Create a FoundryLocalManager instance. This will start the Foundry 
 // Local service if it is not already running.
 const foundryLocalManager = new FoundryLocalManager()
 
 // Initialize the manager with a model. This will download the model 
 // if it is not already present on the user's device.
-const modelInfo = await foundryLocalManager.init(modelAlias)
+const modelInfo = await foundryLocalManager.init(alias)
 console.log("Model Info:", modelInfo)
 
 async function streamWithFetch() {

articles/ai-foundry/foundry-local/includes/sdk-reference/javascript.md

@@ -33,12 +33,21 @@ Available options:
 - `serviceUrl`: Base URL of the Foundry Local service
 - `fetch`: (optional) Custom fetch implementation for environments like Node.js
 
+### A note on aliases
+
+Many methods outlined in this reference have an `aliasOrModelId` parameter in the signature. You can pass into the method either an **alias** or **model ID** as a value. Using an alias will:
+
+- Select the *best model* for the available hardware. For example, if a Nvidia CUDA GPU is available, Foundry Local selects the CUDA model. If a supported NPU is available, Foundry Local selects the NPU model.
+- Allow you to use a shorter name without needing to remember the model ID.
+
+> [!TIP]
+> We recommend passing into the `aliasOrModelId` parameter an **alias** because when you deploy your application, Foundry Local acquires the best model for the end user's machine at run-time.
 
 ### Service Management
 
 | Method                | Signature                  | Description                                      |
 |-----------------------|---------------------------|--------------------------------------------------|
-| `init()`              | `(modelAliasOrId?: string) => Promise<void>` | Initializes the SDK and optionally loads a model. |
+| `init()`              | `(aliasOrModelId?: string) => Promise<void>` | Initializes the SDK and optionally loads a model. |
 | `isServiceRunning()`  | `() => Promise<boolean>`  | Checks if the Foundry Local service is running.   |
 | `startService()`      | `() => Promise<void>`     | Starts the Foundry Local service.                |
 | `serviceUrl`          | `string`                  | The base URL of the Foundry Local service.        |
@@ -52,24 +61,24 @@ Available options:
 |---------------------------|---------------------------------------------------------------------------|--------------------------------------------------|
 | `listCatalogModels()`     | `() => Promise<FoundryModelInfo[]>`                                       | Lists all available models in the catalog.        |
 | `refreshCatalog()`        | `() => Promise<void>`                                                     | Refreshes the model catalog.                     |
-| `getModelInfo()`          | `(modelAliasOrId: string, throwOnNotFound = false) => Promise<FoundryModelInfo \| null>` | Gets model info by alias or ID.                  |
+| `getModelInfo()`          | `(aliasOrModelId: string, throwOnNotFound = false) => Promise<FoundryModelInfo \| null>` | Gets model info by alias or ID.                  |
 
 
 ### Cache Management
 
 | Method                    | Signature                                         | Description                                      |
 |---------------------------|---------------------------------------------------|--------------------------------------------------|
 | `getCacheLocation()`      | `() => Promise<string>`                           | Returns the model cache directory path.           |
-| `listLocalModels()`       | `() => Promise<FoundryModelInfo[]>`               | Lists models downloaded to the local cache.       |
+| `listCachedModels()`       | `() => Promise<FoundryModelInfo[]>`               | Lists models downloaded to the local cache.       |
 
 
 ### Model Management
 
 | Method                        | Signature                                                                 | Description                                      |
 |-------------------------------|---------------------------------------------------------------------------|--------------------------------------------------|
-| `downloadModel()`             | `(modelAliasOrId: string, force = false, onProgress?) => Promise<FoundryModelInfo>` | Downloads a model to the local cache.            |
-| `loadModel()`                 | `(modelAliasOrId: string, ttl = 600) => Promise<FoundryModelInfo>`        | Loads a model into the inference server.         |
-| `unloadModel()`               | `(modelAliasOrId: string, force = false) => Promise<void>`                | Unloads a model from the inference server.       |
+| `downloadModel()`             | `(aliasOrModelId: string, token?: string, force = false, onProgress?) => Promise<FoundryModelInfo>` | Downloads a model to the local cache.            |
+| `loadModel()`                 | `(aliasOrModelId: string, ttl = 600) => Promise<FoundryModelInfo>`        | Loads a model into the inference server.         |
+| `unloadModel()`               | `(aliasOrModelId: string, force = false) => Promise<void>`                | Unloads a model from the inference server.       |
 | `listLoadedModels()`          | `() => Promise<FoundryModelInfo[]>`                                       | Lists all models currently loaded in the service.|
 
 ## Example Usage
@@ -83,12 +92,12 @@ import { FoundryLocalManager } from "foundry-local-sdk";
 // to your end-user's device.
 // TIP: You can find a list of available models by running the 
 // following command in your terminal: `foundry model list`.
-const modelAlias = "deepseek-r1-1.5b";
+const alias = "deepseek-r1-1.5b";
 
 const manager = new FoundryLocalManager()
 
 // Initialize the SDK and optionally load a model
-const modelInfo = await manager.init(modelAlias)
+const modelInfo = await manager.init(alias)
 console.log("Model Info:", modelInfo)
 
 // Check if the service is running
@@ -99,17 +108,17 @@ console.log(`Service running: ${isRunning}`)
 const catalog = await manager.listCatalogModels()
 
 // Download and load a model
-await manager.downloadModel(modelAlias)
-await manager.loadModel(modelAlias)
+await manager.downloadModel(alias)
+await manager.loadModel(alias)
 
 // List models in cache
-const localModels = await manager.listLocalModels()
+const localModels = await manager.listCachedModels()
 
 // List loaded models
 const loaded = await manager.listLoadedModels()
 
 // Unload a model
-await manager.unloadModel(modelAlias)
+await manager.unloadModel(alias)
 ```
 
 ---
@@ -132,15 +141,15 @@ import { FoundryLocalManager } from "foundry-local-sdk";
 // to your end-user's device.
 // TIP: You can find a list of available models by running the 
 // following command in your terminal: `foundry model list`.
-const modelAlias = "deepseek-r1-1.5b";
+const alias = "deepseek-r1-1.5b";
 
 // Create a FoundryLocalManager instance. This will start the Foundry 
 // Local service if it is not already running.
 const foundryLocalManager = new FoundryLocalManager()
 
 // Initialize the manager with a model. This will download the model 
 // if it is not already present on the user's device.
-const modelInfo = await foundryLocalManager.init(modelAlias)
+const modelInfo = await foundryLocalManager.init(alias)
 console.log("Model Info:", modelInfo)
 
 const openai = new OpenAI({
@@ -199,15 +208,15 @@ const endpoint = "ENDPOINT"
 
 const manager = new FoundryLocalManager({serviceUrl: endpoint})
 
-const modelAlias = 'deepseek-r1-1.5b'
+const alias = 'deepseek-r1-1.5b'
 
 // Get all available models
 const catalog = await manager.listCatalogModels()
 console.log("Available models in catalog:", catalog)
 
 // Download and load a specific model
-await manager.downloadModel(modelAlias)
-await manager.loadModel(modelAlias)
+await manager.downloadModel(alias)
+await manager.loadModel(alias)
 
 // View models in your local cache
 const localModels = await manager.listLocalModels()
@@ -218,5 +227,5 @@ const loaded = await manager.listLoadedModels()
 console.log("Loaded models in inference service:", loaded)
 
 // Unload a model when finished
-await manager.unloadModel(modelAlias)
+await manager.unloadModel(alias)
 ```