Merge pull request #4756 from MicrosoftDocs/release-build-agents

Release build agents

Author: thomps23

.openpublishing.redirection.json

@@ -91,8 +91,8 @@
       "redirect_document_id": false
     },
     {
-      "source_path_from_root": "/articles/ai-services/agents/how-to/tools/overview.md",
-      "redirect_url": "/azure/ai-services/agents/overview",
+      "source_path_from_root": "/articles/ai-services/agents/how-to/tools/licensed-data.md",
+      "redirect_url": "/azure/ai-services/agents/how-to/tools/overview",
       "redirect_document_id": false
     },
     {

articles/ai-services/agents/breadcrumb/toc.yml

@@ -6,7 +6,7 @@
     tocHref: /azure/ai-services/
     topicHref: /azure/ai-services/index
     items:
-    - name: Azure AI Agent Service
+    - name: Azure AI Foundry Agent Service
       tocHref: /azure/ai-services/
       topicHref: /azure/ai-services/agents/index
 - name: Azure
@@ -17,6 +17,6 @@
     tocHref: /legal/cognitive-services/openai    # Destination doc set route
     topicHref: /azure/ai-services/agents/index    # Original doc set route
     items:
-    - name: Azure AI Agent Service      # Destination doc set name
+    - name: Azure AI Foundry Agent Service      # Destination doc set name
       tocHref: /legal/cognitive-services/openai      # Destination doc set route
       topicHref: /azure/ai-services/agents/index    # Original doc set route

articles/ai-services/agents/concepts/agent-catalog.md

@@ -0,0 +1,83 @@
+---
+title: How to use the AI agent catalog
+titleSuffix: Azure AI Foundry
+description: This article provides instructions on how to use the AI agent catalog to use code samples to quickly deploy agents.
+manager: nitinme
+ms.service: azure-ai-agent-service
+ms.topic: how-to
+ms.date: 04/29/2025
+ms.author: aahi
+author: aahill
+---
+
+# Get started with the Agent Catalog
+
+Accelerate your agent development using code samples and best practices for creating agents. Each agent sample below links to a GitHub Repository, where you can browse the agent's configuration files, setup instructions and source code to start integrating them into your own project in code.
+With agents you create using these code samples, be sure to assess safety and legal implications, and to comply with all applicable laws and safety standards. See the [transparency note](/legal/cognitive-services/agents/transparency-note) for more information.
+
+[!INCLUDE [feature-preview](../../../ai-foundry/includes/feature-preview.md)]
+
+## Prerequisites
+
+- [Azure subscription](https://azure.microsoft.com/free)
+- An [Azure AI Foundry project](../../../ai-foundry/how-to/create-projects.md).
+
+## Find the Agent Catalog in the Azure AI Foundry portal
+
+1. Go to [Azure AI Foundry portal](https://ai.azure.com).
+1. Open your project.
+1. On the left pane, select **Agents**.
+1. Near the top of the screen, select **Catalog**. Find the code sample you want to use.
+
+    :::image type="content" source="../media/agent-catalog.png" alt-text="A screenshot of the model catalog." lightbox="../media/agent-catalog.png":::
+
+1. Select **Open in Github** to view the entire sample application.
+
+## Explore the code samples
+
+Once you're looking at the GitHub repository for your sample, refer to the README for more instructions and information on how to deploy your own version of the application.
+
+Instructions vary by sample, but most include information on:
+* Pre-requisites
+* Setup instructions
+* Configuration files
+* Sample dataset
+* Example prompts and agent interactions
+* Tools used
+
+The README also includes information about the application, such as the use case, architecture, and other tips.
+
+## View all available code samples
+
+A full list of agent samples in the catalog can be found on the Azure AI Foundry. There are several templates available that are authored by Microsoft and partners across different domains such as: travel, finance, insurance, business intelligence, healthcare, and more. 
+
+**Azure AI Agent Service Agent Catalog**
+
+| Code sample | Description | Author | Type | SDK | Difficulty level | Tools |
+|-------------|-------------|--------|--------------|------------------|------|--------|
+| [Browser Automation Agent](https://aka.ms/browser-automation) | Kickstart browser automation scenarios with this Azure Playwright powered template | Microsoft | Single-agent | Agent AI Agent Service | Beginner | Playwright |
+| [AI Red Teaming Agent](https://github.com/microsoft/agent-catalog/tree/main/semantic-kernel-blueprints/ai-red-teaming-agent) | Facilitates the development of a copilot to accelerate your AI red teaming process: through multi-agent system that automates the generation, transformation, and execution of harmful prompts against target generative AI models or applications for AI red teaming purposes. Useful for streamlining safety testing workflows, surfacing guardrail bypasses, and guiding risk mitigation planning. | Microsoft | Multi-agent | Semantic Kernel | Advanced | N/A |
+| [Saifr Communication Compliance Agent](https://aka.ms/saifr-communication-agent) | The Saifr Communication Compliance Agent identifies potentially noncompliant text and generates a more compliant, fair, and balanced version, helping end users better adhere to relevant regulatory guidelines | Saifr from Fidelity Labs | Single-agent | Agent AI Agent Service | Intermediate | OpenAPI Specified Tool |
+| [Auquan Due Diligence Risk Analyst](https://aka.ms/due-diligence-risk-analyst-agent) | Helps create agents that assess risks across financial, operational, regulatory, and ESG domains | Auquan | Single-agent | Agent AI Agent Service | Intermediate | OpenAPI Specified Tool |
+| [Healthcare Multi-agent Orchestrator](https://aka.ms/healthcare-multi-agent) | Facilitates the development and testing of  modular specialized agents that coordinate across diverse data types and tools like M365 and Teams to assist multi-disciplinary healthcare workflows—such as cancer care. | Microsoft | Multi-agent | Semantic Kernel | Advanced |  |
+| [ResearchFlow Agent](https://aka.ms/research-flow) | Helps create agents that execute complex, multi-step research workflows and solve open-ended tasks | Microsoft | Multi-agent | Agent AI Agent Service | Advanced |  |
+| [Magentic-One Agent](https://aka.ms/magnetic-one) | A generalist, autonomous multi-agent system that performs deep research and problem-solving by orchestrating web search, code generation, and code execution agents. Helpful for tackling open-ended analytical or technical tasks. | Microsoft | Multi-agent | Agent AI Agent Service | Advanced |  |
+| [SightMachine Filler Optimization Agent](https://aka.ms/sight-machine-filler-optimization-agent) | The SightMachine Filler Optimization Agent supports building agents that analyze manufacturing data to reduce bottlenecks and improve throughput via predictive insights | SightMachine | Single-agent | Agent AI Agent Service | Intermediate | Azure Functions |
+| [Marquee Insights AI News Agent](https://aka.ms/ai-news-agent) | Enables creating an agent that retrieves and summarize news focused on Microsoft, healthcare, and legal sectors | Marquee Insights | Single-agent | Agent AI Agent Service | Intermediate |  |
+| [MiHCM HR Assist Agent](https://aka.ms/ hr-agent) | Supports agent development for HR scenarios by enabling employees to navigate HR-related records like leave balances, HR requests and work activities using MiHCM's HR APIs | MiHCM | Single-agent | Agent AI Agent Service | Intermediate | OpenAPI Specified Tool |
+| [Claim Concierge](https://aka.ms/claim-concierge) | Helps create agents for multi-lingual claim navigation | Microsoft | Multi-agent | Agent AI Agent Service | Beginner | Connected Agents, File Search, Grounding with Bing, Code Interpreter |
+| [Portfolio Navigator](https://aka.ms/trusty-link) | Supports agent creation for exploring financial topics from Morningstar data and Grounding with Bing | Microsoft | Single-agent | Agent AI Agent Service | Beginner | Morningstar, Grounding with Bing |
+| [Travel Planner](https://aka.ms/travel-planner) | Enables agent creation for travel scenarios | Microsoft | Single-agent | Agent AI Agent Service | Beginner | File Search, Code Interpreter, Tripadvisor, OpenAPI Specified Tool |
+| [Home Loan Guide](https://aka.ms/home-loan-guide) | Enables agent creation to provide users with helpful information about mortgage applications at a fictitious company, Contoso Bank. | Microsoft | Single-agent | Agent AI Agent Service | Beginner | Connected Agents, File Search, Code Interpreter, Grounding with Bing |
+| [Sales Analyst Agent](https://aka.ms/sales-analyst) | Supports building agents that analyze sales data | Microsoft | Single-agent | Agent AI Agent Service | Beginner | File Search, Code Interpreter |
+| [Customer Service Agent](https://aka.ms/customer-service) | Helps create a multi-agent system that manages full-cycle support resolution —from authentication to escalation to resolution | Microsoft | Multi-agent | Agent AI Agent Service | Advanced |  |
+| [Warranty Claim Processing Agent](https://aka.ms/warranty-claim-processing) | Facilitates the development of agents for processing warranty claims | Microsoft | Single-agent | Semantic Kernel | Intermediate | OpenAPI Specified Tool |
+| [Voice Live Agent](https://aka.ms/voice-live-agent) | Enables agent development for real-time, voice-based interactions using Azure AI Voice Live API. | Microsoft | Single-agent | Agent AI Agent Service  | Intermediate |  |
+| [Meeting Prep Agent](https://aka.ms/meeting-prep-agent) | Helps build an agent that helps with meetings by researching attendees and generating contextual summaries | Microsoft | Single-agent | Agent AI Agent Service | Intermediate | Grounding with Bing, Azure Logic Apps |
+| [CommsPilot](https://aka.ms/comms-pilot) | Enables agent creation for personalized outbound sales emails and outreach logging | Microsoft | Single-agent | Agent AI Agent Service | Intermediate | File Search, Grounding with Bing, Azure Logic Apps |
+| [Text Translation Agent](https://aka.ms/translation-agent) | Helps create agents that handle multilingual text processing, including dynamic language detection and bidirectional translation using Azure AI Translator service | Microsoft | Single-agent | Agent AI Agent Service | Beginner | OpenAPI Specified Tool |
+| [Video Translation Agent](https://aka.ms/video-translation-agent) | Supports building agents for multilingual video localization with translation, subtitles, and speech generation | Microsoft | Single-agent | Semantic Kernel | Beginner | N/A |
+| [Intent Routing Agent](https://aka.ms/intent-routing) | Helps create agents that detect user intent and provide exact answering. Perfect for deterministically intent routing and exact question answering with human controls. | Microsoft | Single-agent | Agent AI Agent Service | Beginner | OpenAPI Specified Tool |
+| [Exact Question Answering Agent](https://aka.ms/exact-question-answering) | Supports building agents that answer predefined, high-value questions to ensure consistent and accurate responses. | Microsoft | Single-agent | Agent AI Agent Service | Beginner | OpenAPI Specified Tool |
+| [Contract Analysis Agent](https://aka.ms/contract-analysis-agent) | Enables creating agents that compare contract versions, extract key clauses, highlight differences, and generate review-ready reports. | Microsoft | Single-agent | Semantic Kernel | Intermediate | File Search, OpenAPI Specified Tool |
+| [SOP Forge Agent](https://aka.ms/sop-forge-agent) | Helps create an agent that converts instructional videos into a fully formatted Standard Operating Procedure (SOP). | Microsoft | Single-agent | Semantic Kernel | Intermediate | File Search, OpenAPI Specified Tool |

articles/ai-services/agents/concepts/model-region-support.md

@@ -1,7 +1,7 @@
 ---
-title: Supported models in Azure AI Agent Service
-titleSuffix: Azure AI services
-description: Learn about the models you can use with Azure AI Agent Service.
+title: Supported models in Azure AI Foundry Agent Service
+titleSuffix: Azure AI Foundry
+description: Learn about the models you can use with Azure AI Foundry Agent Service.
 manager: nitinme
 author: aahill
 ms.author: aahi
@@ -11,7 +11,7 @@ ms.date: 05/05/2025
 ms.custom: azure-ai-agents
 ---
 
-# Models supported by Azure AI Agent Service
+# Models supported by Azure AI Foundry Agent Service
 
 Agents are powered by a diverse set of models with different capabilities and price points. Model availability varies by region and cloud. Certain tools and capabilities require the latest models. The following models are available in the REST API and SDKs. 
 
@@ -24,7 +24,7 @@ Azure OpenAI provides customers with choices on the hosting structure that fits
 
 All deployments can perform the exact same inference operations, however the billing, scale, and performance are substantially different. To learn more about Azure OpenAI deployment types see [deployment types guide](../../openai/how-to/deployment-types.md).
 
-Azure AI Agent Service supports the following Azure OpenAI models in the listed regions.
+Azure AI Foundry Agent Service supports the following Azure OpenAI models in the listed regions.
 
 > [!NOTE]
 > The following table is for pay-as-you-go. For information on Provisioned Throughput Unit (PTU) availability, see [provisioned throughput](../../openai/concepts/provisioned-throughput.md) in the Azure OpenAI documentation. `GlobalStandard` customers also have access to [global standard models](../../openai/concepts/models.md#global-standard-model-availability). 
@@ -50,7 +50,7 @@ Azure AI Agent Service supports the following Azure OpenAI models in the listed
 
 ## Non-Microsoft models
 
-The Azure AI Agent Service also supports the following models from the Azure AI Foundry model catalog.
+The Azure AI Foundry Agent Service also supports the following models from the Azure AI Foundry model catalog.
 
 * Meta-Llama-405B-Instruct
 

articles/ai-services/agents/concepts/standard-agent-setup.md

@@ -0,0 +1,88 @@
+---
+title: Built-in enterprise readiness with standard agent setup
+titleSuffix: Azure AI Foundry
+description: Learn about the enterprise features of the standard setup
+manager: nitinme
+author: fosteramanda
+ms.author: fosteramanda
+ms.service: azure-ai-agent-service
+ms.topic: conceptual
+ms.date: 05/05/2025
+ms.custom: azure-ai-agents
+---
+
+# Built-in enterprise readiness with standard agent setup 
+
+Standard Agent Setup offers enterprise-grade security, compliance, and control. This configuration uses customer-managed, single-tenant resources to store agent state and ensures all data remains within your control.  
+
+In this setup: 
+* Agent states (files, threads, vector stores) are stored in your own Azure resources. 
+* Available with both public networking and private networking (Bring Your Own virtual network) options. 
+
+## Leveraging your own resources for storing customer data
+Both standard setup configurations are designed to give you complete control over sensitive data by requiring the use of your own Azure resources. The required Bring Your Own (BYO) resources include:   
+* BYO File Storage: All files uploaded by developers (during agent configuration) or end-users (during interactions) are stored directly in the customer’s Azure Storage account.   
+* BYO Search: All vector stores created by the agent leverage the customer’s Azure AI Search resource.   
+* BYO Thread Storage: All customer messages and conversation history will be stored in the customer’s own Azure Cosmos DB account.  
+
+By bundling these BYO features (file storage, search, and thread storage), the standard setup guarantees that your deployment is secure by default. All data processed by Azure AI Agent Service is automatically stored at rest in your own Azure resources, helping you meet internal policies, compliance requirements, and enterprise security standards. 
+
+## Project-Level Data Isolation
+
+Azure AI Foundry enforces project-level data isolation by default. When you configure your own resources in the project capability host: 
+* **Azure Storage**: Two Blob containers are automatically provisioned: 
+    * One for uploaded files 
+    * One for intermediate system data (for example, chunks, embeddings) 
+* **Azure Cosmos DB**: Three containers are provisioned under a dedicated enterprise_memory database: 
+    * thread-message-store: End-user conversations 
+    * system-thread-message-store: Internal system messages 
+    * agent-entity-store: Model inputs and outputs 
+
+This default behavior was chosen to reduce configuration complexity while still enforcing strict data boundaries—ensuring each project has a clean, isolated storage footprint without requiring manual setup. 
+
+## Capability hosts
+**Capability hosts** are sub-resources on both the Account and Project, enabling interaction with the Azure AI Agent Service. 
+- **Account Capability Host**: The account capability host has an empty request body except for the parameter capabilityHostKind="Agents". 
+- **Project Capability Host**: Specifies resources for storing agent state, either managed multitenant (basic setup) or customer-owned (standard setup), single-tenant resource. Think of project capability host as the project settings.
+
+### Limitations
+- **Update Not Supported**: Cannot update the capability host for a project or account.
+
+
+## Step by Step Provisioning Process
+1. Create project dependent resources for standard setup
+    * Create new (or pass in resource ID of existing) Cosmos DB resource 
+    * Create new (or pass in resource ID of existing) Azure Storage resource 
+    * Create new (or pass in resource ID of existing) Azure AI Search resource 
+    * Create a new Key Vault resource 
+    * [Optional]: Create new application insights resource 
+    * [Optional]: pass in resource ID of existing AI Foundry resource 
+2. Create Azure AI Foundry Resource (cognitive service/accounts kind=AIServices) 
+3. Create Account-level connections 
+    * Create account connection to Application Insights resource 
+4. Deploy gpt-4o or other agent compatible model 
+5. Create Project (cognitive service/accounts/project) 
+6. Create project connections 
+    * [if provided] Project connection to AI Foundry resource 
+    * Create project connection to Azure Storage account 
+    * Create project connection to Azure AI Search account 
+    * Create project connection to Cosmos DB account 
+7. Assign the project-managed identity (including for SMI) the following roles: 
+    * Cosmos DB Operator at the scope of the account level for the Cosmos DB account resource 
+    * Storage Account Contributor at the scope of the account level for the Storage Account resource 
+8. Set Account capability host with empty properties section. 
+9. Set Project capability host with properties Cosmos DB, Azure Storage, AI Search connections 
+10. Assign the Project Managed Identity (both for SMI and UMI) the following roles on the specified resource scopes: 
+    * Azure AI Search (can be assigned either before or after capHost creation) 
+        * Assign roles: Search Index Data Contributor, Search Service Contributor 
+    * Azure Blob Storage Container: `<workspaceId>-azureml-blobstore`
+        * Assign role: Storage Blob Data Contributor 
+    * Azure Blob Storage Container: `<workspaceId>- agents-blobstore` 
+        * Assign role: Storage Blob Data Owner  
+    * Cosmos DB for NoSQL container: `<'${projectWorkspaceId}>-thread-message-store'`
+        * Assign role: Cosmos DB Built-in Data Contributor 
+    * Cosmos DB for NoSQL container: `<'${projectWorkspaceId}>-thread-message-store'` 
+        * Assign role: Cosmos DB Built-in Data Contributor 
+    * Cosmos DB for NoSQL container: `<'${projectWorkspaceId}>-agent-entity-store'` 
+        * Assign role: Cosmos DB Built-in Data Contributor 
+11. Once all resources are provisioned, all developers who want to create/edit agents in the project should be assigned the role: Azure AI User on the project scope.