Merge pull request #114 from Azure-Samples/howie/rename-foundry

Rename to Foundry

Author: howieleung

README.md

@@ -1,6 +1,6 @@
 <!-- YAML front-matter schema: https://review.learn.microsoft.com/en-us/help/contribute/samples/process/onboarding?branch=main#supported-metadata-fields-for-readmemd -->
 
-# Get Started with Chat Using Azure AI Foundry
+# Get Started with Chat Using Microsoft Foundry
 
 <div style="text-align:center;">
 
@@ -14,9 +14,9 @@
 
 This solution deploys a web-based chat application with AI capabilities running in Azure Container App.
 
-The application leverages Azure AI Foundry projects and Foundry Tools to provide intelligent chat functionality. It supports both direct AI model interaction and Retrieval-Augmented Generation (RAG) using Azure AI Search for knowledge retrieval from uploaded files, enabling it to generate responses with citations. The solution also includes built-in monitoring capabilities with tracing to ensure easier troubleshooting and optimized performance.
+The application leverages Microsoft Foundry projects and Foundry Tools to provide intelligent chat functionality. It supports both direct AI model interaction and Retrieval-Augmented Generation (RAG) using Azure AI Search for knowledge retrieval from uploaded files, enabling it to generate responses with citations. The solution also includes built-in monitoring capabilities with tracing to ensure easier troubleshooting and optimized performance.
 
-This solution creates an Azure AI Foundry project and Foundry Tools. More details about the resources can be found in the [resources](#resources) documentation. There are options to enable RAG, logging, tracing, and monitoring.
+This solution creates an Microsoft Foundry project and Foundry Tools. More details about the resources can be found in the [resources](#resources) documentation. There are options to enable RAG, logging, tracing, and monitoring.
 
 Instructions are provided for deployment through GitHub Codespaces, VS Code Dev Containers, and your local development environment.
 
@@ -70,7 +70,7 @@ This guide covers:
 • Embedding file upload
 • Testing and debugging your application
 
-- **[Tracing and Monitoring](./docs/other_features.md#tracing-and-monitoring)** - View console logs in Azure portal and App Insights tracing in Azure AI Foundry for debugging and performance monitoring.
+- **[Tracing and Monitoring](./docs/other_features.md#tracing-and-monitoring)** - View console logs in Azure portal and App Insights tracing in Microsoft Foundry for debugging and performance monitoring.
 
 ## Resource Clean-up
 
@@ -102,7 +102,7 @@ However, Azure Container Registry has a fixed cost per registry per day.
 
 You can try the [Azure pricing calculator](https://azure.microsoft.com/en-us/pricing/calculator) for the resources:
 
-* Azure AI Foundry: Free tier. [Pricing](https://azure.microsoft.com/pricing/details/ai-studio/)
+* Microsoft Foundry: Free tier. [Pricing](https://azure.microsoft.com/pricing/details/ai-studio/)
 * Azure AI Search: Standard tier, S1. Pricing is based on the number of documents and operations. [Pricing](https://azure.microsoft.com/pricing/details/search/)
 * Azure Storage Account: Standard tier, LRS. Pricing is based on storage and operations. [Pricing](https://azure.microsoft.com/pricing/details/storage/blobs/)
 * Foundry Tools: S0 tier, defaults to gpt-4o-mini and text-embedding-ada-002 models. Pricing is based on token count. [Pricing](https://azure.microsoft.com/pricing/details/cognitive-services/)
@@ -130,7 +130,7 @@ For a more comprehensive list of best practices and security recommendations for
 
 ### Resources
 
-This template creates everything you need to get started with Azure AI Foundry:
+This template creates everything you need to get started with Microsoft Foundry:
 
 | Resource | Description |
 |----------|-------------|

docs/deploy_customization.md

@@ -1,15 +1,15 @@
 
-# Getting Started with Chat Using Azure AI Foundry: Deployment customization
+# Getting Started with Chat Using Microsoft Foundry: Deployment customization
 
-This document describes how to customize the deployment of the Agents Chat with Azure AI Foundry. Once you follow the steps here, you can run `azd up` as described in the section below.
+This document describes how to customize the deployment of the Agents Chat with Microsoft Foundry. Once you follow the steps here, you can run `azd up` as described in the section below.
 
 * [Use existing resources](#use-existing-resources)
 * [Enabling and disabling resources provision](#enabling-and-disabling-resources-provision)
 * [Customizing resource names](#customizing-resource-names)
 * [Customizing model deployments](#customizing-model-deployments)
 
 ## Use existing resources
-Be default, this template provisions a new resource group along with other resources.   If you already have provisioned Azure AI Foundry and Azure AI Foundry Project (not a hub based project), you might reuse these resources by setting:
+Be default, this template provisions a new resource group along with other resources.   If you already have provisioned Microsoft Foundry and Microsoft Foundry Project (not a hub based project), you might reuse these resources by setting:
 
 To find the value:
 
@@ -40,8 +40,8 @@ Once you disable these resources, they will not be deployed when you run `azd up
 By default, this template will use a naming convention with unique strings to prevent naming collisions within Azure.
 To override default naming conventions, the following keys can be set:
 
-* `AZURE_AIPROJECT_NAME` - The name of the Azure AI Foundry project
-* `AZURE_AISERVICES_NAME` - The name of the Azure AI Foundry
+* `AZURE_AIPROJECT_NAME` - The name of the Microsoft Foundry project
+* `AZURE_AISERVICES_NAME` - The name of the Microsoft Foundry
 * `AZURE_STORAGE_ACCOUNT_NAME` - The name of the Storage Account
 * `AZURE_APPLICATION_INSIGHTS_NAME` - The name of the Application Insights instance
 * `AZURE_LOG_ANALYTICS_WORKSPACE_NAME` - The name of the Log Analytics workspace used by Application Insights

docs/deployment.md

@@ -14,7 +14,7 @@ You can view the permissions for your account and subscription by going to Azure
 
 Check the [Azure Products by Region](https://azure.microsoft.com/en-us/explore/global-infrastructure/products-by-region/?products=all&regions=all) page and select a **region** where the following services are available:
 
-- [Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/)
+- [Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/)
 - [Azure Container Apps](https://learn.microsoft.com/en-us/azure/container-apps/)
 - [Azure Container Registry](https://learn.microsoft.com/en-us/azure/container-registry/)
 - [Azure AI Search](https://learn.microsoft.com/en-us/azure/search/)
@@ -184,7 +184,7 @@ When you start a deployment, most parameters will have default values. You can c
 
 | **Setting** | **Description** |  **Default value** |
 |------------|----------------|  ------------|
-| **Existing Project Resource ID** | Specify an existing project resource ID to be used instead of provisioning new Azure AI Foundry project and Foundry Tools. |   |
+| **Existing Project Resource ID** | Specify an existing project resource ID to be used instead of provisioning new Microsoft Foundry project and Foundry Tools. |   |
 | **Azure Region** | Select a region with quota which supports your selected model. |   |
 | **Model** | Choose from the [list of models](https://learn.microsoft.com/azure/ai-foundry/foundry-models/concepts/models) for your selected region. | gpt-4o-mini |  
 | **Model Format** | Choose from OpenAI or Microsoft, depending on your model. | OpenAI |  
@@ -228,7 +228,7 @@ To enable message contents to be included in the traces, set the following envir
 azd env set AZURE_TRACING_GEN_AI_CONTENT_RECORDING_ENABLED true
 ```
 
-You can view the App Insights tracing in Azure AI Foundry. Select your project on the Azure AI Foundry page and then click 'Tracing'.
+You can view the App Insights tracing in Microsoft Foundry. Select your project on the Microsoft Foundry page and then click 'Tracing'.
 
 </details>
 
@@ -239,7 +239,7 @@ You can view the App Insights tracing in Azure AI Foundry. Select your project o
 
 The default for the model capacity in deployment is 80k tokens for chat model and 50k for embedded model for AI Search. For optimal performance, it is recommended to increase to 100k tokens. You can change the capacity by following the steps in [setting capacity and deployment SKU](deploy_customization.md#customizing-model-deployments).
 
-- Navigate to the home screen of the [Azure AI Foundry Portal](https://ai.azure.com/)
+- Navigate to the home screen of the [Microsoft Foundry Portal](https://ai.azure.com/)
 - Select Quota Management buttom at the bottom of the home screen
 * In the Quota tab, click the GlobalStandard dropdown and select the model and region you are using for this accelerator to see your available quota. Please note gpt-4o-mini and text-embedding-3-small are used as default.
 - Request more quota or delete any unused model deployments as needed.
@@ -259,7 +259,7 @@ Once you've opened the project in [Codespaces](#github-codespaces) or in [Dev Co
     azd env set AZURE_AI_CHAT_DEPLOYMENT_CAPACITY 100
     ```
 
-    ⚠️ If you do not increase your quota, you may encounter rate limit issues. If needed, you can increase the quota after deployment by editing your model in the Models and Endpoints tab of the [Azure AI Foundry Portal](https://ai.azure.com/).
+    ⚠️ If you do not increase your quota, you may encounter rate limit issues. If needed, you can increase the quota after deployment by editing your model in the Models and Endpoints tab of the [Microsoft Foundry Portal](https://ai.azure.com/).
 
 2. Provision resources, build a docker image using `src` folder, and deploy:
 
@@ -283,9 +283,9 @@ Once you've opened the project in [Codespaces](#github-codespaces) or in [Dev Co
         azd show
         ```
 
-5. (Optional) Now that your app has deployed, you can view your resources in the Azure Portal and your deployments in Azure AI Foundry.
+5. (Optional) Now that your app has deployed, you can view your resources in the Azure Portal and your deployments in Microsoft Foundry.
     - In the [Azure Portal](https://portal.azure.com/), navigate to your environment's resource group. The name will be `rg-[your environment name]`. Here, you should see your container app, storage account, and all of the other [resources](#resources) that are created in the deployment.
-    - In the [Azure AI Foundry Portal](https://ai.azure.com/), select your project. If you navigate to the Playgrounds tab followed by Chat playground, you should be able to view your new deployment. If you navigate to the Models and Endpoints tab, you should see your AI Services connection with your model deployments.
+    - In the [Microsoft Foundry Portal](https://ai.azure.com/), select your project. If you navigate to the Playgrounds tab followed by Chat playground, you should be able to view your new deployment. If you navigate to the Models and Endpoints tab, you should see your AI Services connection with your model deployments.
 
 6. (Optional) You can use a local development server to test app changes locally. To do so, follow the steps in [local deployment server](#develop-with-local-development-server) after your app is deployed.
 

docs/images/architecture.png

@@ -17,6 +17,6 @@ Or if you want to navigate from the Azure portal main page, select your resource
 
 After accessing your resource group in Azure portal, choose your container app from the list of resources. Then open 'Monitoring' and 'Log Stream'. Choose the 'Application' radio button to view application logs. You can choose between real-time and historical using the corresponding radio buttons. Note that it may take some time for the historical view to be updated with the latest logs.
 
-You can view the App Insights tracing in Azure AI Foundry. Select your project on the Azure AI Foundry page and then click 'Tracing'. 
+You can view the App Insights tracing in Microsoft Foundry. Select your project on the Microsoft Foundry page and then click 'Tracing'. 
 
 ![Tracing Tab](../docs/images/tracing_tab.png)

docs/other_features.md

@@ -46,6 +46,6 @@ This guide provides solutions to common issues you may encounter when deploying
 
 If you continue to experience issues after trying these solutions:
 
-1. Check the [Azure AI Foundry documentation](https://learn.microsoft.com/azure/ai-foundry/)
+1. Check the [Microsoft Foundry documentation](https://learn.microsoft.com/azure/ai-foundry/)
 2. Review the [Azure Container Apps troubleshooting guide](https://learn.microsoft.com/azure/container-apps/troubleshooting)
 3. Consult the [Azure Developer CLI reference](https://learn.microsoft.com/azure/developer/azure-developer-cli/reference)

docs/troubleshooting.md

@@ -22,7 +22,7 @@ param location string
 param azureExistingAIProjectResourceId string = ''
 @description('The Azure resource group where new resources will be deployed')
 param resourceGroupName string = ''
-@description('The Azure AI Foundry Hub resource name. If ommited will be generated')
+@description('The Microsoft Foundry Hub resource name. If ommited will be generated')
 param aiProjectName string = ''
 @description('The application insights resource name. If ommited will be generated')
 param applicationInsightsName string = ''

infra/main.bicep

@@ -69,14 +69,14 @@
       "type": "string",
       "defaultValue": "",
       "metadata": {
-        "description": "The Azure AI Foundry Hub resource name. If ommited will be generated"
+        "description": "The Microsoft Foundry Hub resource name. If ommited will be generated"
       }
     },
     "aiProjectName": {
       "type": "string",
       "defaultValue": "",
       "metadata": {
-        "description": "The Azure AI Foundry project name. If ommited will be generated"
+        "description": "The Microsoft Foundry project name. If ommited will be generated"
       }
     },
     "applicationInsightsName": {