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.NET: Replace Azure Foundry/Azure AI Foundry with Microsoft Foundry in .NET samples (#5032)
* Replace Azure Foundry/Azure AI Foundry with Microsoft Foundry in samples Update all .cs, .md, and .yaml files in dotnet/samples/ to use 'Microsoft Foundry' instead of 'Azure Foundry' and 'Azure AI Foundry'. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step04_MemoryUsingFoundry/Program.cs Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update dotnet/samples/02-agents/Agents/Agent_Step15_DeepResearch/Program.cs Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update dotnet/samples/05-end-to-end/A2AClientServer/README.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update dotnet/samples/02-agents/Agents/Agent_Step15_DeepResearch/README.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update dotnet/samples/03-workflows/Agents/FoundryAgent/Program.cs Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update dotnet/samples/02-agents/AgentProviders/Agent_With_AzureAIProject/Program.cs Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Fix grammar: 'an Microsoft' -> 'a Microsoft', 'agents ids' -> 'agent IDs' Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
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25696a72dc
@@ -5,8 +5,8 @@ This sample demonstrates how to create an AIAgent using Anthropic Claude models
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The sample supports three deployment scenarios:
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1. **Anthropic Public API** - Direct connection to Anthropic's public API
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2. **Azure Foundry with API Key** - Anthropic models deployed through Azure Foundry using API key authentication
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3. **Azure Foundry with Azure CLI** - Anthropic models deployed through Azure Foundry using Azure CLI credentials
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2. **Microsoft Foundry with API Key** - Anthropic models deployed through Microsoft Foundry using API key authentication
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3. **Microsoft Foundry with Azure CLI** - Anthropic models deployed through Microsoft Foundry using Azure CLI credentials
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## Prerequisites
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@@ -25,29 +25,29 @@ $env:ANTHROPIC_API_KEY="your-anthropic-api-key" # Replace with your Anthropic A
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$env:ANTHROPIC_CHAT_MODEL_NAME="claude-haiku-4-5" # Optional, defaults to claude-haiku-4-5
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```
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### For Azure Foundry with API Key
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### For Microsoft Foundry with API Key
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- Azure Foundry service endpoint and deployment configured
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- Microsoft Foundry service endpoint and deployment configured
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- Anthropic API key
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Set the following environment variables:
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```powershell
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$env:ANTHROPIC_RESOURCE="your-foundry-resource-name" # Replace with your Azure Foundry resource name (subdomain before .services.ai.azure.com)
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$env:ANTHROPIC_RESOURCE="your-foundry-resource-name" # Replace with your Microsoft Foundry resource name (subdomain before .services.ai.azure.com)
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$env:ANTHROPIC_API_KEY="your-anthropic-api-key" # Replace with your Anthropic API key
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$env:ANTHROPIC_CHAT_MODEL_NAME="claude-haiku-4-5" # Optional, defaults to claude-haiku-4-5
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```
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### For Azure Foundry with Azure CLI
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### For Microsoft Foundry with Azure CLI
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- Azure Foundry service endpoint and deployment configured
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- Microsoft Foundry service endpoint and deployment configured
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- Azure CLI installed and authenticated (for Azure credential authentication)
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Set the following environment variables:
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```powershell
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$env:ANTHROPIC_RESOURCE="your-foundry-resource-name" # Replace with your Azure Foundry resource name (subdomain before .services.ai.azure.com)
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$env:ANTHROPIC_RESOURCE="your-foundry-resource-name" # Replace with your Microsoft Foundry resource name (subdomain before .services.ai.azure.com)
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$env:ANTHROPIC_CHAT_MODEL_NAME="claude-haiku-4-5" # Optional, defaults to claude-haiku-4-5
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```
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**Note**: When using Azure Foundry with Azure CLI, make sure you're logged in with `az login` and have access to the Azure Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
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**Note**: When using Microsoft Foundry with Azure CLI, make sure you're logged in with `az login` and have access to the Microsoft Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
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+1
-1
@@ -2,7 +2,7 @@
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#pragma warning disable CS0618 // Type or member is obsolete - sample uses deprecated PersistentAgentsClientExtensions
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// This sample shows how to create and use a simple AI agent with Azure Foundry Agents as the backend.
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// This sample shows how to create and use a simple AI agent with Microsoft Foundry Agents as the backend.
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using Azure.AI.Agents.Persistent;
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using Azure.Identity;
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+3
-3
@@ -13,14 +13,14 @@ Below is a comparison between the classic and new Foundry Agents approaches:
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Before you begin, ensure you have the following prerequisites:
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- .NET 10 SDK or later
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- Azure Foundry service endpoint and deployment configured
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- Microsoft Foundry service endpoint and deployment configured
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- Azure CLI installed and authenticated (for Azure credential authentication)
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**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
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**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Microsoft Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
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Set the following environment variables:
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```powershell
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$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
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$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Microsoft Foundry resource endpoint
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$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini" # Optional, defaults to gpt-4o-mini
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```
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@@ -1,6 +1,6 @@
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// Copyright (c) Microsoft. All rights reserved.
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// This sample shows how to create and use a AI agents with Azure Foundry Agents as the backend.
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// This sample shows how to create and use AI agents with Microsoft Foundry Agents as the backend.
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using Azure.AI.Projects;
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using Azure.AI.Projects.Agents;
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@@ -13,7 +13,7 @@ var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYME
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const string JokerName = "JokerAgent";
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// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
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// Get a client to create/retrieve/delete server side agents with Microsoft Foundry Agents.
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// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
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// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
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// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
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@@ -13,14 +13,14 @@ Below is a comparison between the classic and new Foundry Agents approaches:
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Before you begin, ensure you have the following prerequisites:
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- .NET 10 SDK or later
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- Azure Foundry service endpoint and deployment configured
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- Microsoft Foundry service endpoint and deployment configured
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- Azure CLI installed and authenticated (for Azure credential authentication)
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**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
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**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Microsoft Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
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Set the following environment variables:
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```powershell
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$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
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$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Microsoft Foundry resource endpoint
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$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini" # Optional, defaults to gpt-4o-mini
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```
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@@ -1,7 +1,7 @@
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// Copyright (c) Microsoft. All rights reserved.
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// This sample shows how to use the OpenAI SDK to create and use a simple AI agent with any model hosted in Azure AI Foundry.
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// You could use models from Microsoft, OpenAI, DeepSeek, Hugging Face, Meta, xAI or any other model you have deployed in your Azure AI Foundry resource.
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// This sample shows how to use the OpenAI SDK to create and use a simple AI agent with any model hosted in Microsoft Foundry.
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// You could use models from Microsoft, OpenAI, DeepSeek, Hugging Face, Meta, xAI or any other model you have deployed in your Microsoft Foundry resource.
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// Note: Ensure that you pick a model that suits your needs. For example, if you want to use function calling, ensure that the model you pick supports function calling.
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using System.ClientModel;
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@@ -15,7 +15,7 @@ var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? th
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var apiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_API_KEY");
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var model = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "Phi-4-mini-instruct";
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// Since we are using the OpenAI Client SDK, we need to override the default endpoint to point to Azure Foundry.
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// Since we are using the OpenAI Client SDK, we need to override the default endpoint to point to Microsoft Foundry.
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var clientOptions = new OpenAIClientOptions() { Endpoint = new Uri(endpoint) };
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// Create the OpenAI client with either an API key or Azure CLI credential.
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@@ -1,8 +1,8 @@
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## Overview
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This sample shows how to use the OpenAI SDK to create and use a simple AI agent with any model hosted in Azure AI Foundry.
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This sample shows how to use the OpenAI SDK to create and use a simple AI agent with any model hosted in Microsoft Foundry.
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You could use models from Microsoft, OpenAI, DeepSeek, Hugging Face, Meta, xAI or any other model you have deployed in Azure AI Foundry.
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You could use models from Microsoft, OpenAI, DeepSeek, Hugging Face, Meta, xAI or any other model you have deployed in Microsoft Foundry.
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**Note**: Ensure that you pick a model that suits your needs. For example, if you want to use function calling, ensure that the model you pick supports function calling.
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@@ -11,19 +11,19 @@ You could use models from Microsoft, OpenAI, DeepSeek, Hugging Face, Meta, xAI o
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Before you begin, ensure you have the following prerequisites:
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- .NET 10 SDK or later
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- Azure AI Foundry resource
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- A model deployment in your Azure AI Foundry resource. This example defaults to using the `Phi-4-mini-instruct` model,
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- Microsoft Foundry resource
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- A model deployment in your Microsoft Foundry resource. This example defaults to using the `Phi-4-mini-instruct` model,
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so if you want to use a different model, ensure that you set your `AZURE_AI_MODEL_DEPLOYMENT_NAME` environment
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variable to the name of your deployed model.
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- An API key or role based authentication to access the Azure AI Foundry resource
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- An API key or role based authentication to access the Microsoft Foundry resource
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See [here](https://learn.microsoft.com/en-us/azure/ai-foundry/quickstarts/get-started-code?tabs=csharp) for more info on setting up these prerequisites
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Set the following environment variables:
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```powershell
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# Replace with your Azure AI Foundry resource endpoint
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# Ensure that you have the "/openai/v1/" path in the URL, since this is required when using the OpenAI SDK to access Azure Foundry models.
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# Replace with your Microsoft Foundry resource endpoint
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# Ensure that you have the "/openai/v1/" path in the URL, since this is required when using the OpenAI SDK to access Microsoft Foundry models.
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$env:AZURE_OPENAI_ENDPOINT="https://ai-foundry-<myresourcename>.services.ai.azure.com/openai/v1/"
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# Optional, defaults to using Azure CLI for authentication if not provided
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@@ -18,7 +18,7 @@ See the README.md for each sample for the prerequisites for that sample.
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|[Creating an AIAgent with Anthropic](./Agent_With_Anthropic/)|This sample demonstrates how to create an AIAgent using Anthropic Claude models as the underlying inference service|
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|[Creating an AIAgent with Foundry Agents using Azure.AI.Agents.Persistent](./Agent_With_AzureAIAgentsPersistent/)|This sample demonstrates how to create a Foundry Persistent agent and expose it as an AIAgent using the Azure.AI.Agents.Persistent SDK|
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|[Creating an AIAgent with Foundry Agents using Azure.AI.Project](./Agent_With_AzureAIProject/)|This sample demonstrates how to create an Foundry Project agent and expose it as an AIAgent using the Azure.AI.Project SDK|
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|[Creating an AIAgent with AzureFoundry Model](./Agent_With_AzureFoundryModel/)|This sample demonstrates how to use any model deployed to Azure Foundry to create an AIAgent|
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|[Creating an AIAgent with Foundry Model](./Agent_With_AzureFoundryModel/)|This sample demonstrates how to use any model deployed to Microsoft Foundry to create an AIAgent|
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|[Creating an AIAgent with Azure OpenAI ChatCompletion](./Agent_With_AzureOpenAIChatCompletion/)|This sample demonstrates how to create an AIAgent using Azure OpenAI ChatCompletion as the underlying inference service|
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|[Creating an AIAgent with Azure OpenAI Responses](./Agent_With_AzureOpenAIResponses/)|This sample demonstrates how to create an AIAgent using Azure OpenAI Responses as the underlying inference service|
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|[Creating an AIAgent with a custom implementation](./Agent_With_CustomImplementation/)|This sample demonstrates how to create an AIAgent with a custom implementation|
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@@ -18,9 +18,9 @@ Before you begin, ensure you have the following prerequisites:
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**Note**: These samples use Anthropic Claude models. For more information, see [Anthropic documentation](https://docs.anthropic.com/).
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## Using Anthropic with Azure Foundry
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## Using Anthropic with Microsoft Foundry
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To use Anthropic with Azure Foundry, you can check the sample [AgentProviders/Agent_With_Anthropic](../AgentProviders/Agent_With_Anthropic/README.md) for more details.
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To use Anthropic with Microsoft Foundry, you can check the sample [AgentProviders/Agent_With_Anthropic](../AgentProviders/Agent_With_Anthropic/README.md) for more details.
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## Samples
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+3
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// Copyright (c) Microsoft. All rights reserved.
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// This sample shows how to use the FoundryMemoryProvider to persist and recall memories for an agent.
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// The sample stores conversation messages in an Azure AI Foundry memory store and retrieves relevant
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// The sample stores conversation messages in a Microsoft Foundry memory store and retrieves relevant
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// memories for subsequent invocations, even across new sessions.
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//
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// Note: Memory extraction in Azure AI Foundry is asynchronous and takes time. This sample demonstrates
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// Note: Memory extraction in Microsoft Foundry is asynchronous and takes time. This sample demonstrates
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// a simple polling approach to wait for memory updates to complete before querying.
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using System.Text.Json;
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@@ -62,7 +62,7 @@ await memoryProvider.EnsureStoredMemoriesDeletedAsync(session);
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Console.WriteLine(await agent.RunAsync("Hi there! My name is Taylor and I'm planning a hiking trip to Patagonia in November.", session));
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Console.WriteLine(await agent.RunAsync("I'm travelling with my sister and we love finding scenic viewpoints.", session));
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// Memory extraction in Azure AI Foundry is asynchronous and takes time to process.
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// Memory extraction in Microsoft Foundry is asynchronous and takes time to process.
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// WhenUpdatesCompletedAsync polls all pending updates and waits for them to complete.
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Console.WriteLine("\nWaiting for Foundry Memory to process updates...");
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await memoryProvider.WhenUpdatesCompletedAsync();
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# Agent with Memory Using Azure AI Foundry
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# Agent with Memory Using Microsoft Foundry
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This sample demonstrates how to create and run an agent that uses Azure AI Foundry's managed memory service to extract and retrieve individual memories across sessions.
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This sample demonstrates how to create and run an agent that uses Microsoft Foundry's managed memory service to extract and retrieve individual memories across sessions.
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## Features Demonstrated
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@@ -13,7 +13,7 @@ This sample demonstrates how to create and run an agent that uses Azure AI Found
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## Prerequisites
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1. Azure subscription with Azure AI Foundry project
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1. Azure subscription with Microsoft Foundry project
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2. Azure OpenAI resource with a chat model deployment (e.g., gpt-4o-mini) and an embedding model deployment (e.g., text-embedding-ada-002)
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3. .NET 10.0 SDK
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4. Azure CLI logged in (`az login`)
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@@ -21,7 +21,7 @@ This sample demonstrates how to create and run an agent that uses Azure AI Found
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## Environment Variables
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```bash
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# Azure AI Foundry project endpoint and memory store name
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# Microsoft Foundry project endpoint and memory store name
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export AZURE_AI_PROJECT_ENDPOINT="https://your-account.services.ai.azure.com/api/projects/your-project"
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export AZURE_AI_MEMORY_STORE_ID="my_memory_store"
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@@ -48,10 +48,10 @@ The agent will:
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## Key Differences from Mem0
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| Aspect | Mem0 | Azure AI Foundry Memory |
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| Aspect | Mem0 | Microsoft Foundry Memory |
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|--------|------|------------------------|
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| Authentication | API Key | Azure Identity (DefaultAzureCredential) |
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| Scope | ApplicationId, UserId, AgentId, ThreadId | Single `Scope` string |
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| Memory Types | Single memory store | User Profile + Chat Summary |
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| Hosting | Mem0 cloud or self-hosted | Azure AI Foundry managed service |
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| Hosting | Mem0 cloud or self-hosted | Microsoft Foundry managed service |
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| Store Creation | N/A (automatic) | Explicit via `EnsureMemoryStoreCreatedAsync` |
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@@ -7,7 +7,7 @@ These samples show how to create an agent with the Agent Framework that uses Mem
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|[Chat History memory](./AgentWithMemory_Step01_ChatHistoryMemory/)|This sample demonstrates how to enable an agent to remember messages from previous conversations.|
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|[Memory with MemoryStore](./AgentWithMemory_Step02_MemoryUsingMem0/)|This sample demonstrates how to create and run an agent that uses the Mem0 service to extract and retrieve individual memories.|
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|[Custom Memory Implementation](../../01-get-started/04_memory/)|This sample demonstrates how to create a custom memory component and attach it to an agent.|
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|[Memory with Azure AI Foundry](./AgentWithMemory_Step04_MemoryUsingFoundry/)|This sample demonstrates how to create and run an agent that uses Azure AI Foundry's managed memory service to extract and retrieve individual memories.|
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|[Memory with Microsoft Foundry](./AgentWithMemory_Step04_MemoryUsingFoundry/)|This sample demonstrates how to create and run an agent that uses Microsoft Foundry's managed memory service to extract and retrieve individual memories.|
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|[Bounded Chat History with Overflow](./AgentWithMemory_Step05_BoundedChatHistory/)|This sample demonstrates how to create a bounded chat history provider that overflows older messages to a vector store and recalls them as memories.|
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> **See also**: [Memory Search with Foundry Agents](../AgentsWithFoundry/Agent_Step22_MemorySearch/) - demonstrates using the built-in Memory Search tool with Azure Foundry agents.
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> **See also**: [Memory Search with Foundry Agents](../AgentsWithFoundry/Agent_Step22_MemorySearch/) - demonstrates using the built-in Memory Search tool with Microsoft Foundry agents.
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- User has the `Cognitive Services OpenAI Contributor` role for the Azure OpenAI resource.
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- An existing Qdrant instance. You can use a managed service or run a local instance using Docker, but the sample assumes the instance is running locally.
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**Note**: These samples use Azure OpenAI models. For more information, see [how to deploy Azure OpenAI models with Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/deploy-models-openai).
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**Note**: These samples use Azure OpenAI models. For more information, see [how to deploy Azure OpenAI models with Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/deploy-models-openai).
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**Note**: These samples use Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource and have the `Cognitive Services OpenAI Contributor` role. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
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@@ -18,7 +18,7 @@ Before you begin, ensure you have the following prerequisites:
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- Azure CLI installed and authenticated (for Azure credential authentication)
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- User has the `Cognitive Services OpenAI Contributor` role for the Azure OpenAI resource
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**Note**: This sample uses Azure OpenAI models. For more information, see [how to deploy Azure OpenAI models with Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/deploy-models-openai).
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**Note**: This sample uses Azure OpenAI models. For more information, see [how to deploy Azure OpenAI models with Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/deploy-models-openai).
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**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource and have the `Cognitive Services OpenAI Contributor` role. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
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@@ -20,8 +20,8 @@ To use the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector)
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MCP Inspector is up and running at http://127.0.0.1:6274
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```
|
||||
1. Open a web browser and navigate to the URL displayed in the terminal. If not opened automatically, this will open the MCP Inspector interface.
|
||||
1. In the MCP Inspector interface, add the following environment variables to allow your MCP server to access Azure AI Foundry Project to create and run the agent:
|
||||
- AZURE_AI_PROJECT_ENDPOINT = https://your-resource.openai.azure.com/ # Replace with your Azure AI Foundry Project endpoint
|
||||
1. In the MCP Inspector interface, add the following environment variables to allow your MCP server to access Microsoft Foundry Project to create and run the agent:
|
||||
- AZURE_AI_PROJECT_ENDPOINT = https://your-resource.openai.azure.com/ # Replace with your Microsoft Foundry Project endpoint
|
||||
- AZURE_AI_MODEL_DEPLOYMENT_NAME = gpt-4o-mini # Replace with your model deployment name
|
||||
1. Find and click the `Connect` button in the MCP Inspector interface to connect to the MCP server.
|
||||
1. As soon as the connection is established, open the `Tools` tab in the MCP Inspector interface and select the `Joker` tool from the list.
|
||||
|
||||
@@ -13,7 +13,7 @@ using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
|
||||
// Get Azure AI Foundry configuration from environment variables
|
||||
// Get Microsoft Foundry configuration from environment variables
|
||||
var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
|
||||
var deploymentName = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o";
|
||||
|
||||
|
||||
@@ -3,7 +3,7 @@
|
||||
// This sample shows how to use a chat history reducer to keep the context within model size limits.
|
||||
// Any implementation of Microsoft.Extensions.AI.IChatReducer can be used to customize how the chat history is reduced.
|
||||
// NOTE: this feature is only supported where the chat history is stored locally, such as with OpenAI Chat Completion.
|
||||
// Where the chat history is stored server side, such as with Azure Foundry Agents, the service must manage the chat history size.
|
||||
// Where the chat history is stored server side, such as with Microsoft Foundry Agents, the service must manage the chat history size.
|
||||
|
||||
using Azure.AI.OpenAI;
|
||||
using Azure.Identity;
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
|
||||
#pragma warning disable CS0618 // Type or member is obsolete - sample uses deprecated PersistentAgentsClientExtensions
|
||||
|
||||
// This sample shows how to create an Azure AI Foundry Agent with the Deep Research Tool.
|
||||
// This sample shows how to create a Microsoft Foundry Agent with the Deep Research Tool.
|
||||
|
||||
using Azure.AI.Agents.Persistent;
|
||||
using Azure.Identity;
|
||||
|
||||
@@ -11,10 +11,10 @@ Key features:
|
||||
|
||||
Before running this sample, ensure you have:
|
||||
|
||||
1. An Azure AI Foundry project set up
|
||||
1. A Microsoft Foundry project set up
|
||||
2. A deep research model deployment (e.g., o3-deep-research)
|
||||
3. A model deployment (e.g., gpt-4o)
|
||||
4. A Bing Connection configured in your Azure AI Foundry project
|
||||
4. A Bing Connection configured in your Microsoft Foundry project
|
||||
5. Azure CLI installed and authenticated
|
||||
|
||||
**Important**: Please visit the following documentation for detailed setup instructions:
|
||||
@@ -29,14 +29,14 @@ Pay special attention to the purple `Note` boxes in the Azure documentation.
|
||||
/subscriptions/<sub-id>/resourceGroups/<rg>/providers/Microsoft.CognitiveServices/accounts/<account>/projects/<project>/connections/<connection-name>
|
||||
```
|
||||
|
||||
You can find this in the Azure AI Foundry portal under **Management > Connected resources**, or retrieve it programmatically via the connections API (`.id` property).
|
||||
You can find this in the Microsoft Foundry portal under **Management > Connected resources**, or retrieve it programmatically via the connections API (`.id` property).
|
||||
|
||||
## Environment Variables
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
# Replace with your Azure AI Foundry project endpoint
|
||||
# Replace with your Microsoft Foundry project endpoint
|
||||
$env:AZURE_AI_PROJECT_ENDPOINT="https://your-project.services.ai.azure.com/"
|
||||
|
||||
# Replace with your Bing Grounding connection ID (full ARM resource URI)
|
||||
|
||||
@@ -18,7 +18,7 @@ Before you begin, ensure you have the following prerequisites:
|
||||
- Azure CLI installed and authenticated (for Azure credential authentication)
|
||||
- User has the `Cognitive Services OpenAI Contributor` role for the Azure OpenAI resource.
|
||||
|
||||
**Note**: These samples use Azure OpenAI models. For more information, see [how to deploy Azure OpenAI models with Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/deploy-models-openai).
|
||||
**Note**: These samples use Azure OpenAI models. For more information, see [how to deploy Azure OpenAI models with Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/deploy-models-openai).
|
||||
|
||||
**Note**: These samples use Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource and have the `Cognitive Services OpenAI Contributor` role. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
|
||||
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample shows how to create, use, and clean up a FoundryAgent backed by a server-side
|
||||
// versioned agent in Azure AI Foundry. It demonstrates the full lifecycle:
|
||||
// versioned agent in Microsoft Foundry. It demonstrates the full lifecycle:
|
||||
// create agent version -> wrap as FoundryAgent -> run -> delete.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# Getting started with Foundry Agents
|
||||
|
||||
These samples demonstrate how to use Azure AI Foundry with Agent Framework.
|
||||
These samples demonstrate how to use Microsoft Foundry with Agent Framework.
|
||||
|
||||
## Quick start
|
||||
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample shows how to create and use a simple AI agent with Azure Foundry Agents as the backend, that uses a Hosted MCP Tool.
|
||||
// In this case the Azure Foundry Agents service will invoke any MCP tools as required. MCP tools are not invoked by the Agent Framework.
|
||||
// This sample shows how to create and use a simple AI agent with Microsoft Foundry Agents as the backend, that uses a Hosted MCP Tool.
|
||||
// In this case the Microsoft Foundry Agents service will invoke any MCP tools as required. MCP tools are not invoked by the Agent Framework.
|
||||
// The sample first shows how to use MCP tools with auto approval, and then how to set up a tool that requires approval before it can be invoked and how to approve such a tool.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
|
||||
@@ -3,14 +3,14 @@
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 10 SDK or later
|
||||
- Azure Foundry service endpoint and deployment configured
|
||||
- Microsoft Foundry service endpoint and deployment configured
|
||||
- Azure CLI installed and authenticated (for Azure credential authentication)
|
||||
|
||||
**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
|
||||
**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Microsoft Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
|
||||
$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Microsoft Foundry resource endpoint
|
||||
$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4.1-mini" # Optional, defaults to gpt-4.1-mini
|
||||
```
|
||||
|
||||
@@ -11,7 +11,7 @@ Before you begin, ensure you have the following prerequisites:
|
||||
- Azure CLI installed and authenticated (for Azure credential authentication)
|
||||
- User has the `Cognitive Services OpenAI Contributor` role for the Azure OpenAI resource.
|
||||
|
||||
**Note**: These samples use Azure OpenAI models. For more information, see [how to deploy Azure OpenAI models with Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/deploy-models-openai).
|
||||
**Note**: These samples use Azure OpenAI models. For more information, see [how to deploy Azure OpenAI models with Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/deploy-models-openai).
|
||||
|
||||
**Note**: These samples use Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource and have the `Cognitive Services OpenAI Contributor` role. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
|
||||
|
||||
|
||||
@@ -11,12 +11,12 @@ using Microsoft.Extensions.AI;
|
||||
namespace WorkflowFoundryAgentSample;
|
||||
|
||||
/// <summary>
|
||||
/// This sample shows how to use Azure Foundry Agents within a workflow.
|
||||
/// This sample shows how to use Microsoft Foundry Agents within a workflow.
|
||||
/// </summary>
|
||||
/// <remarks>
|
||||
/// Pre-requisites:
|
||||
/// - Foundational samples should be completed first.
|
||||
/// - An Azure Foundry project endpoint and model id.
|
||||
/// - A Microsoft Foundry project endpoint and model ID.
|
||||
/// </remarks>
|
||||
public static class Program
|
||||
{
|
||||
|
||||
@@ -30,7 +30,7 @@ namespace Demo.Workflows.Declarative.InvokeMcpTool;
|
||||
/// <item>Integrating with MCP-compatible services</item>
|
||||
/// </list>
|
||||
/// <para>
|
||||
/// This sample uses the Microsoft Learn MCP server to search Azure documentation and the Azure foundry MCP server to get AI model details.
|
||||
/// This sample uses the Microsoft Learn MCP server to search Azure documentation and the Microsoft Foundry MCP server to get AI model details.
|
||||
/// When you run the sample, provide an AI model (e.g. gpt-4.1-mini) as input,
|
||||
/// The workflow will use the MCP tools to find relevant information about the model from Microsoft Learn and foundry, then an agent will summarize the results.
|
||||
/// </para>
|
||||
|
||||
@@ -6,7 +6,7 @@ to build a `Workflow` that may be executed using the same pattern as any code-ba
|
||||
## Configuration
|
||||
|
||||
These samples must be configured to create and use agents your
|
||||
[Azure Foundry Project](https://learn.microsoft.com/azure/ai-foundry).
|
||||
[Microsoft Foundry Project](https://learn.microsoft.com/azure/ai-foundry).
|
||||
|
||||
### Settings
|
||||
|
||||
@@ -18,9 +18,9 @@ The configuraton required by the samples is:
|
||||
|
||||
|Setting Name| Description|
|
||||
|:--|:--|
|
||||
|AZURE_AI_PROJECT_ENDPOINT| The endpoint URL of your Azure Foundry Project.|
|
||||
|AZURE_AI_PROJECT_ENDPOINT| The endpoint URL of your Microsoft Foundry Project.|
|
||||
|AZURE_AI_MODEL_DEPLOYMENT_NAME| The name of the model deployment to use
|
||||
|AZURE_AI_BING_CONNECTION_ID| The name of the Bing Grounding connection configured in your Azure Foundry Project.|
|
||||
|AZURE_AI_BING_CONNECTION_ID| The name of the Bing Grounding connection configured in your Microsoft Foundry Project.|
|
||||
|
||||
To set your secrets with .NET Secret Manager:
|
||||
|
||||
@@ -42,13 +42,13 @@ To set your secrets with .NET Secret Manager:
|
||||
dotnet user-secrets init
|
||||
```
|
||||
|
||||
4. Define setting that identifies your Azure Foundry Project (endpoint):
|
||||
4. Define setting that identifies your Microsoft Foundry Project (endpoint):
|
||||
|
||||
```
|
||||
dotnet user-secrets set "AZURE_AI_PROJECT_ENDPOINT" "https://..."
|
||||
```
|
||||
|
||||
5. Define setting that identifies your Azure Foundry Model Deployment (endpoint):
|
||||
5. Define setting that identifies your Microsoft Foundry Model Deployment (endpoint):
|
||||
|
||||
```
|
||||
dotnet user-secrets set "AZURE_AI_MODEL_DEPLOYMENT_NAME" "gpt-5"
|
||||
@@ -70,7 +70,7 @@ $env:AZURE_AI_BING_CONNECTION_ID="mybinggrounding"
|
||||
|
||||
### Authorization
|
||||
|
||||
Use [_Azure CLI_](https://learn.microsoft.com/cli/azure/authenticate-azure-cli) to authorize access to your Azure Foundry Project:
|
||||
Use [_Azure CLI_](https://learn.microsoft.com/cli/azure/authenticate-azure-cli) to authorize access to your Microsoft Foundry Project:
|
||||
|
||||
```
|
||||
az login
|
||||
|
||||
@@ -26,7 +26,7 @@ Once completed, please proceed to the other samples listed below.
|
||||
|
||||
| Sample | Concepts |
|
||||
|--------|----------|
|
||||
| [Foundry Agents in Workflows](./Agents/FoundryAgent) | Demonstrates using Azure Foundry agents in a workflow through `ChatClientAgent` |
|
||||
| [Foundry Agents in Workflows](./Agents/FoundryAgent) | Demonstrates using Microsoft Foundry agents in a workflow through `ChatClientAgent` |
|
||||
| [Custom Agent Executors](./Agents/CustomAgentExecutors) | Shows how to create a custom agent executor for more complex scenarios |
|
||||
| [Workflow as an Agent](./Agents/WorkflowAsAnAgent) | Illustrates how to encapsulate a workflow as an agent |
|
||||
| [Group Chat with Tool Approval](./Agents/GroupChatToolApproval) | Shows multi-agent group chat with tool approval requests and human-in-the-loop interaction |
|
||||
|
||||
@@ -51,7 +51,7 @@ dotnet run --urls "http://localhost:5002;https://localhost:5012" --agentType "lo
|
||||
|
||||
### Configuring for use with Azure AI Agents
|
||||
|
||||
You must create the agents in an Azure AI Foundry project and then provide the project endpoint and agents ids. The instructions for each agent are as follows:
|
||||
You must create the agents in a Microsoft Foundry project and then provide the project endpoint and agent IDs. The instructions for each agent are as follows:
|
||||
|
||||
- Invoice Agent
|
||||
```
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// Seattle Hotel Agent - A simple agent with a tool to find hotels in Seattle.
|
||||
// Uses Microsoft Agent Framework with Azure AI Foundry.
|
||||
// Uses Microsoft Agent Framework with Microsoft Foundry.
|
||||
// Ready for deployment to Foundry Hosted Agent service.
|
||||
|
||||
using System.ClientModel.Primitives;
|
||||
|
||||
@@ -4,7 +4,7 @@ This sample demonstrates how to build a hosted agent that uses local C# function
|
||||
|
||||
Key features:
|
||||
- Defining local C# functions as agent tools using `AIFunctionFactory`
|
||||
- Using `AIProjectClient` to discover the OpenAI connection from the Azure AI Foundry project
|
||||
- Using `AIProjectClient` to discover the OpenAI connection from the Microsoft Foundry project
|
||||
- Building a `ChatClientAgent` with custom instructions and tools
|
||||
- Deploying to the Foundry Hosted Agent service
|
||||
|
||||
@@ -15,7 +15,7 @@ Key features:
|
||||
Before running this sample, ensure you have:
|
||||
|
||||
1. .NET 10 SDK installed
|
||||
2. An Azure AI Foundry Project with a chat model deployed (e.g., gpt-4o-mini)
|
||||
2. A Microsoft Foundry Project with a chat model deployed (e.g., gpt-4o-mini)
|
||||
3. Azure CLI installed and authenticated (`az login`)
|
||||
|
||||
## Environment Variables
|
||||
@@ -23,7 +23,7 @@ Before running this sample, ensure you have:
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
# Replace with your Azure AI Foundry project endpoint
|
||||
# Replace with your Microsoft Foundry project endpoint
|
||||
$env:AZURE_AI_PROJECT_ENDPOINT="https://your-project.services.ai.azure.com/api/projects/your-project-name"
|
||||
|
||||
# Optional, defaults to gpt-4o-mini
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample demonstrates a multi-agent workflow with Writer and Reviewer agents
|
||||
// using Azure AI Foundry AIProjectClient and the Agent Framework WorkflowBuilder.
|
||||
// using Microsoft Foundry AIProjectClient and the Agent Framework WorkflowBuilder.
|
||||
|
||||
#pragma warning disable CA2252 // AIProjectClient and Agents API require opting into preview features
|
||||
|
||||
|
||||
@@ -42,7 +42,7 @@ which provisions a REST API endpoint compatible with the OpenAI Responses protoc
|
||||
|
||||
Before running this sample, ensure you have:
|
||||
|
||||
1. **Azure AI Foundry Project**
|
||||
1. **Microsoft Foundry Project**
|
||||
- Project created.
|
||||
- Chat model deployed (e.g., `gpt-4o` or `gpt-4.1`)
|
||||
- Note your project endpoint URL and model deployment name
|
||||
|
||||
@@ -4,7 +4,7 @@ name: FoundryMultiAgent
|
||||
displayName: "Foundry Multi-Agent Workflow"
|
||||
description: >
|
||||
A multi-agent workflow featuring a Writer and Reviewer that collaborate
|
||||
to create and refine content using Azure AI Foundry PersistentAgentsClient.
|
||||
to create and refine content using Microsoft Foundry PersistentAgentsClient.
|
||||
metadata:
|
||||
authors:
|
||||
- Microsoft Agent Framework Team
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// Seattle Hotel Agent - A simple agent with a tool to find hotels in Seattle.
|
||||
// Uses Microsoft Agent Framework with Azure AI Foundry.
|
||||
// Uses Microsoft Agent Framework with Microsoft Foundry.
|
||||
// Ready for deployment to Foundry Hosted Agent service.
|
||||
|
||||
#pragma warning disable CA2252 // AIProjectClient and Agents API require opting into preview features
|
||||
|
||||
@@ -39,7 +39,7 @@ which provisions a REST API endpoint compatible with the OpenAI Responses protoc
|
||||
|
||||
Before running this sample, ensure you have:
|
||||
|
||||
1. **Azure AI Foundry Project**
|
||||
1. **Microsoft Foundry Project**
|
||||
- Project created.
|
||||
- Chat model deployed (e.g., `gpt-4o` or `gpt-4.1`)
|
||||
- Note your project endpoint URL and model deployment name
|
||||
@@ -57,7 +57,7 @@ Before running this sample, ensure you have:
|
||||
|
||||
Set the following environment variables (matching `agent.yaml`):
|
||||
|
||||
- `AZURE_AI_PROJECT_ENDPOINT` - Your Azure AI Foundry project endpoint URL (required)
|
||||
- `AZURE_AI_PROJECT_ENDPOINT` - Your Microsoft Foundry project endpoint URL (required)
|
||||
- `MODEL_DEPLOYMENT_NAME` - The deployment name for your chat model (defaults to `gpt-4o-mini`)
|
||||
|
||||
**PowerShell:**
|
||||
|
||||
@@ -20,7 +20,7 @@ Before running any sample, ensure you have:
|
||||
|
||||
1. **.NET 10 SDK** or later — [Download](https://dotnet.microsoft.com/download/dotnet/10.0)
|
||||
2. **Azure CLI** installed — [Install guide](https://learn.microsoft.com/cli/azure/install-azure-cli)
|
||||
3. **Azure OpenAI** or **Azure AI Foundry project** with a chat model deployed (e.g., `gpt-4o-mini`)
|
||||
3. **Azure OpenAI** or **Microsoft Foundry project** with a chat model deployed (e.g., `gpt-4o-mini`)
|
||||
|
||||
### Authenticate with Azure CLI
|
||||
|
||||
@@ -39,14 +39,14 @@ Most samples require one or more of these environment variables:
|
||||
|----------|---------|-------------|
|
||||
| `AZURE_OPENAI_ENDPOINT` | Most samples | Your Azure OpenAI resource endpoint URL |
|
||||
| `AZURE_OPENAI_DEPLOYMENT_NAME` | Most samples | Chat model deployment name (defaults to `gpt-4o-mini`) |
|
||||
| `AZURE_AI_PROJECT_ENDPOINT` | AgentWithLocalTools, FoundryMultiAgent, FoundrySingleAgent | Azure AI Foundry project endpoint |
|
||||
| `AZURE_AI_PROJECT_ENDPOINT` | AgentWithLocalTools, FoundryMultiAgent, FoundrySingleAgent | Microsoft Foundry project endpoint |
|
||||
| `MODEL_DEPLOYMENT_NAME` | AgentWithLocalTools, FoundryMultiAgent, FoundrySingleAgent | Chat model deployment name (defaults to `gpt-4o-mini`) |
|
||||
|
||||
See each sample's README for the specific variables required.
|
||||
|
||||
## Azure AI Foundry Setup (for samples that use Foundry)
|
||||
## Microsoft Foundry Setup (for samples that use Foundry)
|
||||
|
||||
Some samples (`AgentWithLocalTools`, `FoundrySingleAgent`, `FoundryMultiAgent`) connect to an Azure AI Foundry project. If you're using these samples, you'll need additional setup.
|
||||
Some samples (`AgentWithLocalTools`, `FoundrySingleAgent`, `FoundryMultiAgent`) connect to a Microsoft Foundry project. If you're using these samples, you'll need additional setup.
|
||||
|
||||
### Azure AI Developer Role
|
||||
|
||||
@@ -61,7 +61,7 @@ az role assignment create `
|
||||
|
||||
> **Note**: You need **Owner** or **User Access Administrator** permissions on the resource to assign roles. If you don't have this, you may need to request JIT (Just-In-Time) elevated access via [Azure PIM](https://portal.azure.com/#view/Microsoft_Azure_PIMCommon/ActivationMenuBlade/~/aadmigratedresource).
|
||||
|
||||
For more details on permissions, see [Azure AI Foundry Permissions](https://aka.ms/FoundryPermissions).
|
||||
For more details on permissions, see [Microsoft Foundry Permissions](https://aka.ms/FoundryPermissions).
|
||||
|
||||
## Running a Sample
|
||||
|
||||
|
||||
@@ -28,7 +28,7 @@ dotnet/samples/
|
||||
│ ├── AGUI/ # AG-UI protocol samples
|
||||
│ ├── DeclarativeAgents/ # Declarative agent definitions
|
||||
│ ├── DevUI/ # DevUI samples
|
||||
│ ├── AgentsWithFoundry/ # Azure AI Foundry samples (FoundryAgent + AsAIAgent extensions)
|
||||
│ ├── AgentsWithFoundry/ # Microsoft Foundry samples (FoundryAgent + AsAIAgent extensions)
|
||||
│ └── ModelContextProtocol/ # MCP server/client patterns
|
||||
├── 03-workflows/ # Workflow patterns
|
||||
│ ├── _StartHere/ # Introductory workflow samples
|
||||
|
||||
Reference in New Issue
Block a user