mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Merge remote-tracking branch 'upstream/main' into feature-declarative-agents-dotnet
This commit is contained in:
markwallace-microsoft
+6
-3
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
@@ -13,8 +13,11 @@
|
||||
<PackageReference Include="Azure.AI.OpenAI" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="Microsoft.Extensions.Hosting" />
|
||||
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
|
||||
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup Condition="!$([MSBuild]::IsTargetFrameworkCompatible($(TargetFramework), 'net10.0'))">
|
||||
<PackageReference Include="System.Net.ServerSentEvents" />
|
||||
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
|
||||
@@ -7,7 +7,7 @@ and register these function tools with another AI agent so it can leverage the A
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- Access to the A2A agent host service
|
||||
|
||||
**Note**: These samples need to be run against a valid A2A server. If no A2A server is available, they can be run against the echo-agent that can be
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
@@ -22,7 +22,6 @@
|
||||
<PackageReference Include="OpenTelemetry.Instrumentation.Http" />
|
||||
<PackageReference Include="OpenTelemetry.Instrumentation.Runtime" />
|
||||
<PackageReference Include="OpenTelemetry.Extensions.Hosting" />
|
||||
<PackageReference Include="System.Diagnostics.DiagnosticSource" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
|
||||
@@ -22,7 +22,7 @@ graph TD
|
||||
|
||||
## Prerequisites
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- Azure OpenAI service endpoint and deployment configured
|
||||
- Azure CLI installed and authenticated (for Azure credential authentication)
|
||||
- Docker installed (for running Aspire Dashboard)
|
||||
@@ -71,7 +71,7 @@ If you prefer to run the components manually:
|
||||
#### Step 1: Start the Aspire Dashboard via Docker
|
||||
|
||||
```powershell
|
||||
docker run -d --name aspire-dashboard -p 4318:18888 -p 4317:18889 -e DOTNET_DASHBOARD_UNSECURED_ALLOW_ANONYMOUS=true mcr.microsoft.com/dotnet/aspire-dashboard:9.0
|
||||
docker run -d --name aspire-dashboard -p 4318:18888 -p 4317:18889 -e DOTNET_DASHBOARD_UNSECURED_ALLOW_ANONYMOUS=true mcr.microsoft.com/dotnet/aspire-dashboard:latest
|
||||
```
|
||||
|
||||
#### Step 2: Access the Dashboard
|
||||
@@ -207,7 +207,7 @@ If you encounter port binding errors, try:
|
||||
- Ensure the Azure OpenAI deployment name matches your actual deployment
|
||||
|
||||
### Build Issues
|
||||
- Ensure you're using .NET 9.0 SDK
|
||||
- Ensure you're using .NET 10.0 SDK
|
||||
- Run `dotnet restore` if you encounter package restore issues
|
||||
- Check that all project references are correctly resolved
|
||||
|
||||
|
||||
@@ -65,7 +65,7 @@ $dockerResult = docker run -d `
|
||||
-p 4317:18889 `
|
||||
-e DOTNET_DASHBOARD_UNSECURED_ALLOW_ANONYMOUS=true `
|
||||
--restart unless-stopped `
|
||||
mcr.microsoft.com/dotnet/aspire-dashboard:9.0
|
||||
mcr.microsoft.com/dotnet/aspire-dashboard:latest
|
||||
|
||||
if ($LASTEXITCODE -ne 0) {
|
||||
Write-Host "Failed to start Aspire Dashboard container" -ForegroundColor Red
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
@@ -10,8 +10,6 @@
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="A2A" />
|
||||
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
|
||||
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- Access to the A2A agent host service
|
||||
|
||||
**Note**: These samples need to be run against a valid A2A server. If no A2A server is available, they can be run against the echo-agent that can be spun up locally by following the guidelines at: https://github.com/a2aproject/a2a-dotnet/blob/main/samples/AgentServer/README.md
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- Azure Foundry service endpoint and deployment configured
|
||||
- Azure CLI installed and authenticated (for Azure credential authentication)
|
||||
|
||||
+21
@@ -0,0 +1,21 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<NoWarn>$(NoWarn);IDE0059</NoWarn>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
@@ -0,0 +1,51 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample shows how to create and use a AI agents with Azure Foundry Agents as the backend.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
|
||||
var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
|
||||
var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
|
||||
|
||||
const string JokerInstructions = "You are good at telling jokes.";
|
||||
const string JokerName = "JokerAgent";
|
||||
|
||||
// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
|
||||
var aiProjectClient = new AIProjectClient(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Define the agent you want to create. (Prompt Agent in this case)
|
||||
var agentVersionCreationOptions = new AgentVersionCreationOptions(new PromptAgentDefinition(model: deploymentName) { Instructions = JokerInstructions });
|
||||
// Azure.AI.Agents SDK creates and manages agent by name and versions.
|
||||
// You can create a server side agent version with the Azure.AI.Agents SDK client below.
|
||||
var agentVersion = aiProjectClient.Agents.CreateAgentVersion(agentName: JokerName, options: agentVersionCreationOptions);
|
||||
|
||||
// Note:
|
||||
// agentVersion.Id = "<agentName>:<versionNumber>",
|
||||
// agentVersion.Version = <versionNumber>,
|
||||
// agentVersion.Name = <agentName>
|
||||
|
||||
// You can retrieve an AIAgent for a already created server side agent version.
|
||||
AIAgent jokerAgentV1 = aiProjectClient.GetAIAgent(agentVersion);
|
||||
|
||||
// You can also create another AIAgent version (V2) by providing the same name with a different definition.
|
||||
AIAgent jokerAgentV2 = aiProjectClient.CreateAIAgent(name: JokerName, model: deploymentName, instructions: JokerInstructions + "V2");
|
||||
|
||||
// You can also get the AIAgent latest version just providing its name.
|
||||
AIAgent jokerAgentLatest = aiProjectClient.GetAIAgent(name: JokerName);
|
||||
var latestVersion = jokerAgentLatest.GetService<AgentVersion>()!;
|
||||
|
||||
// The AIAgent version can be accessed via the GetService method.
|
||||
Console.WriteLine($"Latest agent version id: {latestVersion.Id}");
|
||||
|
||||
// Once you have the AIAgent, you can invoke it like any other AIAgent.
|
||||
AgentThread thread = jokerAgentLatest.GetNewThread();
|
||||
Console.WriteLine(await jokerAgentLatest.RunAsync("Tell me a joke about a pirate.", thread));
|
||||
|
||||
// This will use the same thread to continue the conversation.
|
||||
Console.WriteLine(await jokerAgentLatest.RunAsync("Now tell me a joke about a cat and a dog using last joke as the anchor.", thread));
|
||||
|
||||
// Cleanup by agent name removes both agent versions created (jokerAgentV1 + jokerAgentV2).
|
||||
aiProjectClient.Agents.DeleteAgent(jokerAgentV1.Name);
|
||||
@@ -0,0 +1,16 @@
|
||||
# Prerequisites
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 10 SDK or later
|
||||
- Azure 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).
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
$env:AZURE_FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
|
||||
$env:AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME="gpt-4o-mini" # Optional, defaults to gpt-4o-mini
|
||||
```
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
@@ -10,7 +10,7 @@ You could use models from Microsoft, OpenAI, DeepSeek, Hugging Face, Meta, xAI o
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- Azure AI Foundry resource
|
||||
- A model deployment in your Azure AI Foundry resource. This example defaults to using the `Phi-4-mini-instruct` model,
|
||||
so if you want to use a different model, ensure that you set your `AZURE_FOUNDRY_MODEL_DEPLOYMENT` environment
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- Azure OpenAI service endpoint and deployment configured
|
||||
- Azure CLI installed and authenticated (for Azure credential authentication)
|
||||
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- Azure OpenAI service endpoint and deployment configured
|
||||
- Azure CLI installed and authenticated (for Azure credential authentication)
|
||||
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
@@ -4,7 +4,7 @@ WARNING: ONNX doesn't support function calling, so any function tools passed to
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- An ONNX model downloaded to your machine
|
||||
|
||||
You can download an ONNX model from hugging face, using git clone:
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- Docker installed and running on your machine
|
||||
- An Ollama model downloaded into Ollama
|
||||
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
@@ -5,7 +5,7 @@ For more information see the OpenAI documentation: https://platform.openai.com/d
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- OpenAI API key
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- OpenAI api key
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- OpenAI api key
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
@@ -15,7 +15,8 @@ See the README.md for each sample for the prerequisites for that sample.
|
||||
|Sample|Description|
|
||||
|---|---|
|
||||
|[Creating an AIAgent with A2A](./Agent_With_A2A/)|This sample demonstrates how to create AIAgent for an existing A2A agent.|
|
||||
|[Creating an AIAgent with AzureFoundry Agent](./Agent_With_AzureFoundryAgent/)|This sample demonstrates how to create an Azure Foundry agent and expose it as an AIAgent|
|
||||
|[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|
|
||||
|[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|
|
||||
|[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|
|
||||
|[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|
|
||||
|[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|
|
||||
|
||||
+1
-2
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
@@ -13,7 +13,6 @@
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
|
||||
<PackageReference Include="Microsoft.SemanticKernel.Connectors.InMemory" />
|
||||
<PackageReference Include="System.Linq.Async" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -31,7 +31,7 @@ AIAgent agent = new AzureOpenAIClient(
|
||||
.CreateAIAgent(new ChatClientAgentOptions()
|
||||
{
|
||||
Instructions = "You are a friendly travel assistant. Use known memories about the user when responding, and do not invent details.",
|
||||
AIContextProviderFactory = ctx => ctx.SerializedState.ValueKind is not JsonValueKind.Null or JsonValueKind.Undefined
|
||||
AIContextProviderFactory = ctx => ctx.SerializedState.ValueKind is not JsonValueKind.Null and not JsonValueKind.Undefined
|
||||
// If each thread should have its own Mem0 scope, you can create a new id per thread here:
|
||||
// ? new Mem0Provider(mem0HttpClient, new Mem0ProviderScope() { ThreadId = Guid.NewGuid().ToString() })
|
||||
// In this case we are storing memories scoped by application and user instead so that memories are retained across threads.
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+5
-9
@@ -98,8 +98,8 @@ public sealed partial class TextSearchStore : IDisposable
|
||||
// Create a definition so that we can use the dimensions provided at runtime.
|
||||
VectorStoreCollectionDefinition ragDocumentDefinition = new()
|
||||
{
|
||||
Properties = new List<VectorStoreProperty>()
|
||||
{
|
||||
Properties =
|
||||
[
|
||||
new VectorStoreKeyProperty("Key", this._options.KeyType ?? typeof(string)),
|
||||
new VectorStoreDataProperty("Namespaces", typeof(List<string>)) { IsIndexed = true },
|
||||
new VectorStoreDataProperty("SourceId", typeof(string)) { IsIndexed = true },
|
||||
@@ -107,7 +107,7 @@ public sealed partial class TextSearchStore : IDisposable
|
||||
new VectorStoreDataProperty("SourceName", typeof(string)),
|
||||
new VectorStoreDataProperty("SourceLink", typeof(string)),
|
||||
new VectorStoreVectorProperty("TextEmbedding", typeof(string), vectorDimensions),
|
||||
}
|
||||
]
|
||||
};
|
||||
|
||||
this._vectorStoreRecordCollection = this._vectorStore.GetDynamicCollection(collectionName, ragDocumentDefinition);
|
||||
@@ -267,7 +267,7 @@ public sealed partial class TextSearchStore : IDisposable
|
||||
cancellationToken: cancellationToken);
|
||||
|
||||
// Retrieve the documents from the search results.
|
||||
List<Dictionary<string, object?>> searchResponseDocs = new();
|
||||
List<Dictionary<string, object?>> searchResponseDocs = [];
|
||||
await foreach (var searchResponseDoc in searchResult.WithCancellation(cancellationToken).ConfigureAwait(false))
|
||||
{
|
||||
searchResponseDocs.Add(searchResponseDoc.Record);
|
||||
@@ -291,12 +291,8 @@ public sealed partial class TextSearchStore : IDisposable
|
||||
}
|
||||
|
||||
// Retrieve the source text for the documents that need it.
|
||||
var retrievalResponses = await this._options.SourceRetrievalCallback(sourceIdsToRetrieve).ConfigureAwait(false);
|
||||
|
||||
if (retrievalResponses is null)
|
||||
{
|
||||
var retrievalResponses = await this._options.SourceRetrievalCallback(sourceIdsToRetrieve).ConfigureAwait(false) ??
|
||||
throw new InvalidOperationException($"The {nameof(TextSearchStoreOptions.SourceRetrievalCallback)} must return a non-null value.");
|
||||
}
|
||||
|
||||
// Update the retrieved documents with the retrieved text.
|
||||
return searchResponseDocs.GroupJoin(
|
||||
|
||||
+2
-9
@@ -107,15 +107,8 @@ public sealed class TextSearchStoreOptions
|
||||
/// <param name="text">The source text that was retrieved.</param>
|
||||
public SourceRetrievalResponse(SourceRetrievalRequest request, string text)
|
||||
{
|
||||
if (request == null)
|
||||
{
|
||||
throw new ArgumentNullException(nameof(request));
|
||||
}
|
||||
|
||||
if (text == null)
|
||||
{
|
||||
throw new ArgumentNullException(nameof(text));
|
||||
}
|
||||
ArgumentNullException.ThrowIfNull(request);
|
||||
ArgumentNullException.ThrowIfNull(text);
|
||||
|
||||
this.SourceId = request.SourceId;
|
||||
this.SourceLink = request.SourceLink;
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -6,7 +6,7 @@ This sample uses Qdrant for the vector store, but this can easily be swapped out
|
||||
|
||||
## Prerequisites
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- Azure OpenAI service endpoint
|
||||
- Both a chat completion and embedding deployment configured in the Azure OpenAI resource
|
||||
- Azure CLI installed and authenticated (for Azure credential authentication)
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -48,7 +48,7 @@ static Task<IEnumerable<TextSearchProvider.TextSearchResult>> MockSearchAsync(st
|
||||
{
|
||||
// The mock search inspects the user's question and returns pre-defined snippets
|
||||
// that resemble documents stored in an external knowledge source.
|
||||
List<TextSearchProvider.TextSearchResult> results = new();
|
||||
List<TextSearchProvider.TextSearchResult> results = [];
|
||||
|
||||
if (query.Contains("return", StringComparison.OrdinalIgnoreCase) || query.Contains("refund", StringComparison.OrdinalIgnoreCase))
|
||||
{
|
||||
|
||||
+26
@@ -0,0 +1,26 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<None Update="contoso-outdoors-knowledge-base.md">
|
||||
<CopyToOutputDirectory>Always</CopyToOutputDirectory>
|
||||
</None>
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
+60
@@ -0,0 +1,60 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample shows how to use the built in RAG capabilities that the Foundry service provides when using AI Agents provided by Foundry.
|
||||
|
||||
using System.ClientModel;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
using OpenAI;
|
||||
using OpenAI.Files;
|
||||
using OpenAI.VectorStores;
|
||||
|
||||
var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
|
||||
var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
|
||||
|
||||
// Create an AI Project client and get an OpenAI client that works with the foundry service.
|
||||
AIProjectClient aiProjectClient = new(
|
||||
new Uri(endpoint),
|
||||
new AzureCliCredential());
|
||||
OpenAIClient openAIClient = aiProjectClient.GetProjectOpenAIClient();
|
||||
|
||||
// Upload the file that contains the data to be used for RAG to the Foundry service.
|
||||
OpenAIFileClient fileClient = openAIClient.GetOpenAIFileClient();
|
||||
ClientResult<OpenAIFile> uploadResult = await fileClient.UploadFileAsync(
|
||||
filePath: "contoso-outdoors-knowledge-base.md",
|
||||
purpose: FileUploadPurpose.Assistants);
|
||||
|
||||
// Create a vector store in the Foundry service using the uploaded file.
|
||||
VectorStoreClient vectorStoreClient = openAIClient.GetVectorStoreClient();
|
||||
ClientResult<VectorStore> vectorStoreCreate = await vectorStoreClient.CreateVectorStoreAsync(options: new VectorStoreCreationOptions()
|
||||
{
|
||||
Name = "contoso-outdoors-knowledge-base",
|
||||
FileIds = { uploadResult.Value.Id }
|
||||
});
|
||||
|
||||
var fileSearchTool = new HostedFileSearchTool() { Inputs = [new HostedVectorStoreContent(vectorStoreCreate.Value.Id)] };
|
||||
|
||||
AIAgent agent = await aiProjectClient
|
||||
.CreateAIAgentAsync(
|
||||
model: deploymentName,
|
||||
name: "AskContoso",
|
||||
instructions: "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available.",
|
||||
tools: [fileSearchTool]);
|
||||
|
||||
AgentThread thread = agent.GetNewThread();
|
||||
|
||||
Console.WriteLine(">> Asking about returns\n");
|
||||
Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", thread));
|
||||
|
||||
Console.WriteLine("\n>> Asking about shipping\n");
|
||||
Console.WriteLine(await agent.RunAsync("How long does standard shipping usually take?", thread));
|
||||
|
||||
Console.WriteLine("\n>> Asking about product care\n");
|
||||
Console.WriteLine(await agent.RunAsync("What is the best way to maintain the TrailRunner tent fabric?", thread));
|
||||
|
||||
// Cleanup
|
||||
await fileClient.DeleteFileAsync(uploadResult.Value.Id);
|
||||
await vectorStoreClient.DeleteVectorStoreAsync(vectorStoreCreate.Value.Id);
|
||||
await aiProjectClient.Agents.DeleteAgentAsync(agent.Name);
|
||||
+19
@@ -0,0 +1,19 @@
|
||||
# Contoso Outdoors Knowledge Base
|
||||
|
||||
## Contoso Outdoors Return Policy
|
||||
|
||||
Customers may return any item within 30 days of delivery. Items should be unused and include original packaging. Refunds are issued to the original payment method within 5 business days of inspection.
|
||||
|
||||
## Contoso Outdoors Shipping Guide
|
||||
|
||||
Standard shipping is free on orders over $50 and typically arrives in 3-5 business days within the continental United States. Expedited options are available at checkout.
|
||||
|
||||
## Product Information
|
||||
|
||||
### TrailRunner Tent
|
||||
|
||||
The TrailRunner Tent is a lightweight, 2-person tent designed for easy setup and durability. It features waterproof materials, ventilation windows, and a compact carry bag.
|
||||
|
||||
#### Care Instructions
|
||||
|
||||
Clean the tent fabric with lukewarm water and a non-detergent soap. Allow it to air dry completely before storage and avoid prolonged UV exposure to extend the lifespan of the waterproof coating.
|
||||
@@ -7,3 +7,4 @@ These samples show how to create an agent with the Agent Framework that uses Ret
|
||||
|[Basic Text RAG](./AgentWithRAG_Step01_BasicTextRAG/)|This sample demonstrates how to create and run a basic agent with simple text Retrieval Augmented Generation (RAG).|
|
||||
|[RAG with Vector Store and custom schema](./AgentWithRAG_Step02_CustomVectorStoreRAG/)|This sample demonstrates how to create and run an agent that uses Retrieval Augmented Generation (RAG) with a vector store. It also uses a custom schema for the documents stored in the vector store.|
|
||||
|[RAG with custom RAG data source](./AgentWithRAG_Step03_CustomRAGDataSource/)|This sample demonstrates how to create and run an agent that uses Retrieval Augmented Generation (RAG) with a custom RAG data source.|
|
||||
|[RAG with Foundry VectorStore service](./AgentWithRAG_Step04_FoundryServiceRAG/)|This sample demonstrates how to create and run an agent that uses Retrieval Augmented Generation (RAG) with the Foundry VectorStore service.|
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
@@ -32,7 +32,7 @@ string tempFilePath = Path.GetTempFileName();
|
||||
await File.WriteAllTextAsync(tempFilePath, JsonSerializer.Serialize(serializedThread));
|
||||
|
||||
// Load the serialized thread from the temporary file (for demonstration purposes).
|
||||
JsonElement reloadedSerializedThread = JsonSerializer.Deserialize<JsonElement>(await File.ReadAllTextAsync(tempFilePath));
|
||||
JsonElement reloadedSerializedThread = JsonElement.Parse(await File.ReadAllTextAsync(tempFilePath));
|
||||
|
||||
// Deserialize the thread state after loading from storage.
|
||||
AgentThread resumedThread = agent.DeserializeThread(reloadedSerializedThread);
|
||||
|
||||
+1
-2
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
@@ -13,7 +13,6 @@
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
|
||||
<PackageReference Include="Microsoft.SemanticKernel.Connectors.InMemory" />
|
||||
<PackageReference Include="System.Linq.Async" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+5
-2
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
@@ -14,7 +14,10 @@
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="Microsoft.Extensions.Hosting" />
|
||||
<PackageReference Include="ModelContextProtocol" />
|
||||
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup Condition="!$([MSBuild]::IsTargetFrameworkCompatible($(TargetFramework), 'net10.0'))">
|
||||
<PackageReference Include="System.Net.ServerSentEvents" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -14,7 +14,7 @@ For more information, see the [official documentation](https://learn.microsoft.c
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- Azure OpenAI service endpoint and deployment configured
|
||||
- Azure CLI installed and authenticated (for Azure credential authentication)
|
||||
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
@@ -154,10 +154,11 @@ async Task<AgentRunResponse> PIIMiddleware(IEnumerable<ChatMessage> messages, Ag
|
||||
static string FilterPii(string content)
|
||||
{
|
||||
// Regex patterns for PII detection (simplified for demonstration)
|
||||
Regex[] piiPatterns = [
|
||||
Regex[] piiPatterns =
|
||||
[
|
||||
new(@"\b\d{3}-\d{3}-\d{4}\b", RegexOptions.Compiled), // Phone number (e.g., 123-456-7890)
|
||||
new(@"\b[\w\.-]+@[\w\.-]+\.\w+\b", RegexOptions.Compiled), // Email address
|
||||
new(@"\b[A-Z][a-z]+\s[A-Z][a-z]+\b", RegexOptions.Compiled) // Full name (e.g., John Doe)
|
||||
new(@"\b[\w\.-]+@[\w\.-]+\.\w+\b", RegexOptions.Compiled), // Email address
|
||||
new(@"\b[A-Z][a-z]+\s[A-Z][a-z]+\b", RegexOptions.Compiled) // Full name (e.g., John Doe)
|
||||
];
|
||||
|
||||
foreach (var pattern in piiPatterns)
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
@@ -13,7 +13,7 @@ For more information, see the [official documentation](https://learn.microsoft.c
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- Azure OpenAI service endpoint and deployment configured
|
||||
- Azure CLI installed and authenticated (for Azure credential authentication)
|
||||
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
@@ -13,7 +13,7 @@ see the [How to create an agent for each provider](../AgentProviders/README.md)
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 8.0 SDK or later
|
||||
- .NET 10 SDK or later
|
||||
- Azure OpenAI service endpoint and deployment configured
|
||||
- Azure CLI installed and authenticated (for Azure credential authentication)
|
||||
- User has the `Cognitive Services OpenAI Contributor` role for the Azure OpenAI resource.
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
+1
-2
@@ -2,7 +2,7 @@
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<Nullable>enable</Nullable>
|
||||
<RootNamespace>DevUI_Step01_BasicUsage</RootNamespace>
|
||||
@@ -19,7 +19,6 @@
|
||||
<PackageReference Include="Azure.AI.OpenAI" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
|
||||
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
|
||||
@@ -2,6 +2,7 @@
|
||||
|
||||
// This sample demonstrates basic usage of the DevUI in an ASP.NET Core application with AI agents.
|
||||
|
||||
using System.ComponentModel;
|
||||
using Azure.AI.OpenAI;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
@@ -18,10 +19,11 @@ namespace DevUI_Step01_BasicUsage;
|
||||
/// <remarks>
|
||||
/// This sample shows how to:
|
||||
/// 1. Set up Azure OpenAI as the chat client
|
||||
/// 2. Register agents and workflows using the hosting packages
|
||||
/// 3. Map the DevUI endpoint which automatically configures the middleware
|
||||
/// 4. Map the dynamic OpenAI Responses API for Python DevUI compatibility
|
||||
/// 5. Access the DevUI in a web browser
|
||||
/// 2. Create function tools for agents to use
|
||||
/// 3. Register agents and workflows using the hosting packages with tools
|
||||
/// 4. Map the DevUI endpoint which automatically configures the middleware
|
||||
/// 5. Map the dynamic OpenAI Responses API for Python DevUI compatibility
|
||||
/// 6. Access the DevUI in a web browser
|
||||
///
|
||||
/// The DevUI provides an interactive web interface for testing and debugging AI agents.
|
||||
/// DevUI assets are served from embedded resources within the assembly.
|
||||
@@ -50,10 +52,30 @@ internal static class Program
|
||||
|
||||
builder.Services.AddChatClient(chatClient);
|
||||
|
||||
// Register sample agents
|
||||
builder.AddAIAgent("assistant", "You are a helpful assistant. Answer questions concisely and accurately.");
|
||||
// Define some example tools
|
||||
[Description("Get the weather for a given location.")]
|
||||
static string GetWeather([Description("The location to get the weather for.")] string location)
|
||||
=> $"The weather in {location} is cloudy with a high of 15°C.";
|
||||
|
||||
[Description("Calculate the sum of two numbers.")]
|
||||
static double Add([Description("The first number.")] double a, [Description("The second number.")] double b)
|
||||
=> a + b;
|
||||
|
||||
[Description("Get the current time.")]
|
||||
static string GetCurrentTime()
|
||||
=> DateTime.Now.ToString("HH:mm:ss");
|
||||
|
||||
// Register sample agents with tools
|
||||
builder.AddAIAgent("assistant", "You are a helpful assistant. Answer questions concisely and accurately.")
|
||||
.WithAITools(
|
||||
AIFunctionFactory.Create(GetWeather, name: "get_weather"),
|
||||
AIFunctionFactory.Create(GetCurrentTime, name: "get_current_time")
|
||||
);
|
||||
|
||||
builder.AddAIAgent("poet", "You are a creative poet. Respond to all requests with beautiful poetry.");
|
||||
builder.AddAIAgent("coder", "You are an expert programmer. Help users with coding questions and provide code examples.");
|
||||
|
||||
builder.AddAIAgent("coder", "You are an expert programmer. Help users with coding questions and provide code examples.")
|
||||
.WithAITool(AIFunctionFactory.Create(Add, name: "add"));
|
||||
|
||||
// Register sample workflows
|
||||
var assistantBuilder = builder.AddAIAgent("workflow-assistant", "You are a helpful assistant in a workflow.");
|
||||
|
||||
+21
@@ -0,0 +1,21 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<NoWarn>$(NoWarn);IDE0059</NoWarn>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
@@ -0,0 +1,50 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample shows how to create and use AI agents with Azure Foundry Agents as the backend.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
|
||||
|
||||
const string JokerInstructionsV1 = "You are good at telling jokes.";
|
||||
const string JokerInstructionsV2 = "You are extremely hilarious at telling jokes.";
|
||||
const string JokerName = "JokerAgent";
|
||||
|
||||
// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
|
||||
AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Define the agent you want to create. (Prompt Agent in this case)
|
||||
AgentVersionCreationOptions options = new(new PromptAgentDefinition(model: deploymentName) { Instructions = JokerInstructionsV1 });
|
||||
|
||||
// Azure.AI.Agents SDK creates and manages agent by name and versions.
|
||||
// You can create a server side agent version with the Azure.AI.Agents SDK client below.
|
||||
AgentVersion agentVersion = aiProjectClient.Agents.CreateAgentVersion(agentName: JokerName, options);
|
||||
|
||||
// Note:
|
||||
// agentVersion.Id = "<agentName>:<versionNumber>",
|
||||
// agentVersion.Version = <versionNumber>,
|
||||
// agentVersion.Name = <agentName>
|
||||
|
||||
// You can retrieve an AIAgent for an already created server side agent version.
|
||||
AIAgent jokerAgentV1 = aiProjectClient.GetAIAgent(agentVersion);
|
||||
|
||||
// You can also create another AIAgent version (V2) by providing the same name with a different definition/instruction.
|
||||
AIAgent jokerAgentV2 = aiProjectClient.CreateAIAgent(name: JokerName, model: deploymentName, instructions: JokerInstructionsV2);
|
||||
|
||||
// You can also get the AIAgent latest version by just providing its name.
|
||||
AIAgent jokerAgentLatest = aiProjectClient.GetAIAgent(name: JokerName);
|
||||
AgentVersion latestVersion = jokerAgentLatest.GetService<AgentVersion>()!;
|
||||
|
||||
// The AIAgent version can be accessed via the GetService method.
|
||||
Console.WriteLine($"Latest agent version id: {latestVersion.Id}");
|
||||
|
||||
// Once you have the AIAgent, you can invoke it like any other AIAgent.
|
||||
Console.WriteLine(await jokerAgentLatest.RunAsync("Tell me a joke about a pirate."));
|
||||
|
||||
// Cleanup by agent name removes both agent versions created (jokerAgentV1 + jokerAgentV2).
|
||||
await aiProjectClient.Agents.DeleteAgentAsync(jokerAgentV1.Name);
|
||||
@@ -0,0 +1,40 @@
|
||||
# Creating and Managing AI Agents with Versioning
|
||||
|
||||
This sample demonstrates how to create and manage AI agents with Azure Foundry Agents, including:
|
||||
- Creating agents with different versions
|
||||
- Retrieving agents by version or latest version
|
||||
- Running multi-turn conversations with agents
|
||||
- Managing agent lifecycle (creation and deletion)
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 10 SDK or later
|
||||
- Azure 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).
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
$env:AZURE_FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
|
||||
$env:AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME="gpt-4o-mini" # Optional, defaults to gpt-4o-mini
|
||||
```
|
||||
|
||||
## Run the sample
|
||||
|
||||
Navigate to the FoundryAgents sample directory and run:
|
||||
|
||||
```powershell
|
||||
cd dotnet/samples/GettingStarted/FoundryAgents
|
||||
dotnet run --project .\FoundryAgents_Step01.1_Basics
|
||||
```
|
||||
|
||||
## What this sample demonstrates
|
||||
|
||||
1. **Creating agents with versions**: Shows how to create multiple versions of the same agent with different instructions
|
||||
2. **Retrieving agents**: Demonstrates retrieving agents by specific version or getting the latest version
|
||||
3. **Multi-turn conversations**: Shows how to use threads to maintain conversation context across multiple agent runs
|
||||
4. **Agent cleanup**: Demonstrates proper resource cleanup by deleting agents
|
||||
+20
@@ -0,0 +1,20 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
@@ -0,0 +1,36 @@
|
||||
// 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.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
|
||||
|
||||
const string JokerInstructions = "You are good at telling jokes.";
|
||||
const string JokerName = "JokerAgent";
|
||||
|
||||
// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
|
||||
AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Define the agent you want to create. (Prompt Agent in this case)
|
||||
AgentVersionCreationOptions options = new(new PromptAgentDefinition(model: deploymentName) { Instructions = JokerInstructions });
|
||||
|
||||
// Azure.AI.Agents SDK creates and manages agent by name and versions.
|
||||
// You can create a server side agent version with the Azure.AI.Agents SDK client below.
|
||||
AgentVersion agentVersion = aiProjectClient.Agents.CreateAgentVersion(agentName: JokerName, options);
|
||||
|
||||
// You can retrieve an AIAgent for a already created server side agent version.
|
||||
AIAgent jokerAgent = aiProjectClient.GetAIAgent(agentVersion);
|
||||
|
||||
// Invoke the agent with streaming support.
|
||||
await foreach (AgentRunResponseUpdate update in jokerAgent.RunStreamingAsync("Tell me a joke about a pirate."))
|
||||
{
|
||||
Console.WriteLine(update);
|
||||
}
|
||||
|
||||
// Cleanup by agent name removes the agent version created.
|
||||
await aiProjectClient.Agents.DeleteAgentAsync(jokerAgent.Name);
|
||||
@@ -0,0 +1,46 @@
|
||||
# Running a Simple AI Agent with Streaming
|
||||
|
||||
This sample demonstrates how to create and run a simple AI agent with Azure Foundry Agents, including both text and streaming responses.
|
||||
|
||||
## What this sample demonstrates
|
||||
|
||||
- Creating a simple AI agent with instructions
|
||||
- Running an agent with text output
|
||||
- Running an agent with streaming output
|
||||
- Managing agent lifecycle (creation and deletion)
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 10 SDK or later
|
||||
- Azure 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).
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
$env:AZURE_FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
|
||||
$env:AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME="gpt-4o-mini" # Optional, defaults to gpt-4o-mini
|
||||
```
|
||||
|
||||
## Run the sample
|
||||
|
||||
Navigate to the FoundryAgents sample directory and run:
|
||||
|
||||
```powershell
|
||||
cd dotnet/samples/GettingStarted/FoundryAgents
|
||||
dotnet run --project .\FoundryAgents_Step01.2_Running
|
||||
```
|
||||
|
||||
## Expected behavior
|
||||
|
||||
The sample will:
|
||||
|
||||
1. Create an agent named "JokerAgent" with instructions to tell jokes
|
||||
2. Run the agent with a text prompt and display the response
|
||||
3. Run the agent again with streaming to display the response as it's generated
|
||||
4. Clean up resources by deleting the agent
|
||||
|
||||
+20
@@ -0,0 +1,20 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
+45
@@ -0,0 +1,45 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample shows how to create and use a simple AI agent with a multi-turn conversation.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
|
||||
|
||||
const string JokerInstructions = "You are good at telling jokes.";
|
||||
const string JokerName = "JokerAgent";
|
||||
|
||||
// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
|
||||
AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Define the agent you want to create. (Prompt Agent in this case)
|
||||
AgentVersionCreationOptions options = new(new PromptAgentDefinition(model: deploymentName) { Instructions = JokerInstructions });
|
||||
|
||||
// Create a server side agent version with the Azure.AI.Agents SDK client.
|
||||
AgentVersion agentVersion = aiProjectClient.Agents.CreateAgentVersion(agentName: JokerName, options);
|
||||
|
||||
// Retrieve an AIAgent for the created server side agent version.
|
||||
AIAgent jokerAgent = aiProjectClient.GetAIAgent(agentVersion);
|
||||
|
||||
// Invoke the agent with a multi-turn conversation, where the context is preserved in the thread object.
|
||||
AgentThread thread = jokerAgent.GetNewThread();
|
||||
Console.WriteLine(await jokerAgent.RunAsync("Tell me a joke about a pirate.", thread));
|
||||
Console.WriteLine(await jokerAgent.RunAsync("Now add some emojis to the joke and tell it in the voice of a pirate's parrot.", thread));
|
||||
|
||||
// Invoke the agent with a multi-turn conversation and streaming, where the context is preserved in the thread object.
|
||||
thread = jokerAgent.GetNewThread();
|
||||
await foreach (AgentRunResponseUpdate update in jokerAgent.RunStreamingAsync("Tell me a joke about a pirate.", thread))
|
||||
{
|
||||
Console.WriteLine(update);
|
||||
}
|
||||
await foreach (AgentRunResponseUpdate update in jokerAgent.RunStreamingAsync("Now add some emojis to the joke and tell it in the voice of a pirate's parrot.", thread))
|
||||
{
|
||||
Console.WriteLine(update);
|
||||
}
|
||||
|
||||
// Cleanup by agent name removes the agent version created.
|
||||
await aiProjectClient.Agents.DeleteAgentAsync(jokerAgent.Name);
|
||||
+50
@@ -0,0 +1,50 @@
|
||||
# Multi-turn Conversation with AI Agents
|
||||
|
||||
This sample demonstrates how to implement multi-turn conversations with AI agents, where context is preserved across multiple agent runs using threads.
|
||||
|
||||
## What this sample demonstrates
|
||||
|
||||
- Creating an AI agent with instructions
|
||||
- Using threads to maintain conversation context
|
||||
- Running multi-turn conversations with text output
|
||||
- Running multi-turn conversations with streaming output
|
||||
- Managing agent lifecycle (creation and deletion)
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 10 SDK or later
|
||||
- Azure 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).
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
$env:AZURE_FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
|
||||
$env:AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME="gpt-4o-mini" # Optional, defaults to gpt-4o-mini
|
||||
```
|
||||
|
||||
## Run the sample
|
||||
|
||||
Navigate to the FoundryAgents sample directory and run:
|
||||
|
||||
```powershell
|
||||
cd dotnet/samples/GettingStarted/FoundryAgents
|
||||
dotnet run --project .\FoundryAgents_Step02_MultiturnConversation
|
||||
```
|
||||
|
||||
## Expected behavior
|
||||
|
||||
The sample will:
|
||||
|
||||
1. Create an agent named "JokerAgent" with instructions to tell jokes
|
||||
2. Create a thread for conversation context
|
||||
3. Run the agent with a text prompt and display the response
|
||||
4. Send a follow-up message to the same thread, demonstrating context preservation
|
||||
5. Create a new thread and run the agent with streaming
|
||||
6. Send a follow-up streaming message to demonstrate multi-turn streaming
|
||||
7. Clean up resources by deleting the agent
|
||||
|
||||
+20
@@ -0,0 +1,20 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
+51
@@ -0,0 +1,51 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample demonstrates how to use an agent with function tools.
|
||||
// It shows both non-streaming and streaming agent interactions using weather-related tools.
|
||||
|
||||
using System.ComponentModel;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
|
||||
|
||||
[Description("Get the weather for a given location.")]
|
||||
static string GetWeather([Description("The location to get the weather for.")] string location)
|
||||
=> $"The weather in {location} is cloudy with a high of 15°C.";
|
||||
|
||||
const string AssistantInstructions = "You are a helpful assistant that can get weather information.";
|
||||
const string AssistantName = "WeatherAssistant";
|
||||
|
||||
// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
|
||||
AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Define the agent with function tools.
|
||||
AITool tool = AIFunctionFactory.Create(GetWeather);
|
||||
|
||||
// Create AIAgent directly
|
||||
var newAgent = await aiProjectClient.CreateAIAgentAsync(name: AssistantName, model: deploymentName, instructions: AssistantInstructions, tools: [tool]);
|
||||
|
||||
// Getting an already existing agent by name with tools.
|
||||
/*
|
||||
* IMPORTANT: Since agents that are stored in the server only know the definition of the function tools (JSON Schema),
|
||||
* you need to provided all invocable function tools when retrieving the agent so it can invoke them automatically.
|
||||
* If no invocable tools are provided, the function calling needs to handled manually.
|
||||
*/
|
||||
var existingAgent = await aiProjectClient.GetAIAgentAsync(name: AssistantName, tools: [tool]);
|
||||
|
||||
// Non-streaming agent interaction with function tools.
|
||||
AgentThread thread = existingAgent.GetNewThread();
|
||||
Console.WriteLine(await existingAgent.RunAsync("What is the weather like in Amsterdam?", thread));
|
||||
|
||||
// Streaming agent interaction with function tools.
|
||||
thread = existingAgent.GetNewThread();
|
||||
await foreach (AgentRunResponseUpdate update in existingAgent.RunStreamingAsync("What is the weather like in Amsterdam?", thread))
|
||||
{
|
||||
Console.WriteLine(update);
|
||||
}
|
||||
|
||||
// Cleanup by agent name removes the agent version created.
|
||||
await aiProjectClient.Agents.DeleteAgentAsync(existingAgent.Name);
|
||||
+48
@@ -0,0 +1,48 @@
|
||||
# Using Function Tools with AI Agents
|
||||
|
||||
This sample demonstrates how to use function tools with AI agents, allowing agents to call custom functions to retrieve information.
|
||||
|
||||
## What this sample demonstrates
|
||||
|
||||
- Creating function tools using AIFunctionFactory
|
||||
- Passing function tools to an AI agent
|
||||
- Running agents with function tools (text output)
|
||||
- Running agents with function tools (streaming output)
|
||||
- Managing agent lifecycle (creation and deletion)
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 10 SDK or later
|
||||
- Azure 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).
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
$env:AZURE_FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
|
||||
$env:AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME="gpt-4o-mini" # Optional, defaults to gpt-4o-mini
|
||||
```
|
||||
|
||||
## Run the sample
|
||||
|
||||
Navigate to the FoundryAgents sample directory and run:
|
||||
|
||||
```powershell
|
||||
cd dotnet/samples/GettingStarted/FoundryAgents
|
||||
dotnet run --project .\FoundryAgents_Step03.1_UsingFunctionTools
|
||||
```
|
||||
|
||||
## Expected behavior
|
||||
|
||||
The sample will:
|
||||
|
||||
1. Create an agent named "WeatherAssistant" with a GetWeather function tool
|
||||
2. Run the agent with a text prompt asking about weather
|
||||
3. The agent will invoke the GetWeather function tool to retrieve weather information
|
||||
4. Run the agent again with streaming to display the response as it's generated
|
||||
5. Clean up resources by deleting the agent
|
||||
|
||||
+20
@@ -0,0 +1,20 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
+64
@@ -0,0 +1,64 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample demonstrates how to use an agent with function tools that require a human in the loop for approvals.
|
||||
// It shows both non-streaming and streaming agent interactions using weather-related tools.
|
||||
// If the agent is hosted in a service, with a remote user, combine this sample with the Persisted Conversations sample to persist the chat history
|
||||
// while the agent is waiting for user input.
|
||||
|
||||
using System.ComponentModel;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
|
||||
|
||||
// Create a sample function tool that the agent can use.
|
||||
[Description("Get the weather for a given location.")]
|
||||
static string GetWeather([Description("The location to get the weather for.")] string location)
|
||||
=> $"The weather in {location} is cloudy with a high of 15°C.";
|
||||
|
||||
const string AssistantInstructions = "You are a helpful assistant that can get weather information.";
|
||||
const string AssistantName = "WeatherAssistant";
|
||||
|
||||
// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
|
||||
AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
ApprovalRequiredAIFunction approvalTool = new(AIFunctionFactory.Create(GetWeather, name: nameof(GetWeather)));
|
||||
|
||||
// Create AIAgent directly
|
||||
AIAgent agent = await aiProjectClient.CreateAIAgentAsync(name: AssistantName, model: deploymentName, instructions: AssistantInstructions, tools: [approvalTool]);
|
||||
|
||||
// Call the agent with approval-required function tools.
|
||||
// The agent will request approval before invoking the function.
|
||||
AgentThread thread = agent.GetNewThread();
|
||||
AgentRunResponse response = await agent.RunAsync("What is the weather like in Amsterdam?", thread);
|
||||
|
||||
// Check if there are any user input requests (approvals needed).
|
||||
List<UserInputRequestContent> userInputRequests = response.UserInputRequests.ToList();
|
||||
|
||||
while (userInputRequests.Count > 0)
|
||||
{
|
||||
// Ask the user to approve each function call request.
|
||||
// For simplicity, we are assuming here that only function approval requests are being made.
|
||||
List<ChatMessage> userInputMessages = userInputRequests
|
||||
.OfType<FunctionApprovalRequestContent>()
|
||||
.Select(functionApprovalRequest =>
|
||||
{
|
||||
Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {functionApprovalRequest.FunctionCall.Name}");
|
||||
bool approved = Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false;
|
||||
return new ChatMessage(ChatRole.User, [functionApprovalRequest.CreateResponse(approved)]);
|
||||
})
|
||||
.ToList();
|
||||
|
||||
// Pass the user input responses back to the agent for further processing.
|
||||
response = await agent.RunAsync(userInputMessages, thread);
|
||||
|
||||
userInputRequests = response.UserInputRequests.ToList();
|
||||
}
|
||||
|
||||
Console.WriteLine($"\nAgent: {response}");
|
||||
|
||||
// Cleanup by agent name removes the agent version created.
|
||||
await aiProjectClient.Agents.DeleteAgentAsync(agent.Name);
|
||||
+51
@@ -0,0 +1,51 @@
|
||||
# Using Function Tools with Approvals (Human-in-the-Loop)
|
||||
|
||||
This sample demonstrates how to use function tools that require human approval before execution, implementing a human-in-the-loop workflow.
|
||||
|
||||
## What this sample demonstrates
|
||||
|
||||
- Creating approval-required function tools using ApprovalRequiredAIFunction
|
||||
- Handling user input requests for function approvals
|
||||
- Implementing human-in-the-loop approval workflows
|
||||
- Processing agent responses with pending approvals
|
||||
- Managing agent lifecycle (creation and deletion)
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 10 SDK or later
|
||||
- Azure 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).
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
$env:AZURE_FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
|
||||
$env:AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME="gpt-4o-mini" # Optional, defaults to gpt-4o-mini
|
||||
```
|
||||
|
||||
## Run the sample
|
||||
|
||||
Navigate to the FoundryAgents sample directory and run:
|
||||
|
||||
```powershell
|
||||
cd dotnet/samples/GettingStarted/FoundryAgents
|
||||
dotnet run --project .\FoundryAgents_Step04_UsingFunctionToolsWithApprovals
|
||||
```
|
||||
|
||||
## Expected behavior
|
||||
|
||||
The sample will:
|
||||
|
||||
1. Create an agent named "WeatherAssistant" with an approval-required GetWeather function tool
|
||||
2. Run the agent with a prompt asking about weather
|
||||
3. The agent will request approval before invoking the GetWeather function
|
||||
4. The sample will prompt the user to approve or deny the function call (enter 'Y' to approve)
|
||||
5. After approval, the function will be executed and the result returned to the agent
|
||||
6. Clean up resources by deleting the agent
|
||||
|
||||
**Note**: For hosted agents with remote users, combine this sample with the Persisted Conversations sample to persist chat history while waiting for user approval.
|
||||
|
||||
+20
@@ -0,0 +1,20 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
+87
@@ -0,0 +1,87 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample shows how to configure an agent to produce structured output.
|
||||
|
||||
using System.ComponentModel;
|
||||
using System.Text.Json;
|
||||
using System.Text.Json.Serialization;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using SampleApp;
|
||||
|
||||
#pragma warning disable CA5399
|
||||
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
|
||||
|
||||
const string AssistantInstructions = "You are a helpful assistant that extracts structured information about people.";
|
||||
const string AssistantName = "StructuredOutputAssistant";
|
||||
|
||||
// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
|
||||
AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Create ChatClientAgent directly
|
||||
ChatClientAgent agent = await aiProjectClient.CreateAIAgentAsync(
|
||||
model: deploymentName,
|
||||
new ChatClientAgentOptions(name: AssistantName, instructions: AssistantInstructions)
|
||||
{
|
||||
ChatOptions = new()
|
||||
{
|
||||
ResponseFormat = Microsoft.Extensions.AI.ChatResponseFormat.ForJsonSchema<PersonInfo>()
|
||||
}
|
||||
});
|
||||
|
||||
// Set PersonInfo as the type parameter of RunAsync method to specify the expected structured output from the agent and invoke the agent with some unstructured input.
|
||||
AgentRunResponse<PersonInfo> response = await agent.RunAsync<PersonInfo>("Please provide information about John Smith, who is a 35-year-old software engineer.");
|
||||
|
||||
// Access the structured output via the Result property of the agent response.
|
||||
Console.WriteLine("Assistant Output:");
|
||||
Console.WriteLine($"Name: {response.Result.Name}");
|
||||
Console.WriteLine($"Age: {response.Result.Age}");
|
||||
Console.WriteLine($"Occupation: {response.Result.Occupation}");
|
||||
|
||||
// Create the ChatClientAgent with the specified name, instructions, and expected structured output the agent should produce.
|
||||
ChatClientAgent agentWithPersonInfo = aiProjectClient.CreateAIAgent(
|
||||
model: deploymentName,
|
||||
new ChatClientAgentOptions(name: AssistantName, instructions: AssistantInstructions)
|
||||
{
|
||||
ChatOptions = new()
|
||||
{
|
||||
ResponseFormat = Microsoft.Extensions.AI.ChatResponseFormat.ForJsonSchema<PersonInfo>()
|
||||
}
|
||||
});
|
||||
|
||||
// Invoke the agent with some unstructured input while streaming, to extract the structured information from.
|
||||
IAsyncEnumerable<AgentRunResponseUpdate> updates = agentWithPersonInfo.RunStreamingAsync("Please provide information about John Smith, who is a 35-year-old software engineer.");
|
||||
|
||||
// Assemble all the parts of the streamed output, since we can only deserialize once we have the full json,
|
||||
// then deserialize the response into the PersonInfo class.
|
||||
PersonInfo personInfo = (await updates.ToAgentRunResponseAsync()).Deserialize<PersonInfo>(JsonSerializerOptions.Web);
|
||||
|
||||
Console.WriteLine("Assistant Output:");
|
||||
Console.WriteLine($"Name: {personInfo.Name}");
|
||||
Console.WriteLine($"Age: {personInfo.Age}");
|
||||
Console.WriteLine($"Occupation: {personInfo.Occupation}");
|
||||
|
||||
// Cleanup by agent name removes the agent version created.
|
||||
await aiProjectClient.Agents.DeleteAgentAsync(agent.Name);
|
||||
|
||||
namespace SampleApp
|
||||
{
|
||||
/// <summary>
|
||||
/// Represents information about a person, including their name, age, and occupation, matched to the JSON schema used in the agent.
|
||||
/// </summary>
|
||||
[Description("Information about a person including their name, age, and occupation")]
|
||||
public class PersonInfo
|
||||
{
|
||||
[JsonPropertyName("name")]
|
||||
public string? Name { get; set; }
|
||||
|
||||
[JsonPropertyName("age")]
|
||||
public int? Age { get; set; }
|
||||
|
||||
[JsonPropertyName("occupation")]
|
||||
public string? Occupation { get; set; }
|
||||
}
|
||||
}
|
||||
+49
@@ -0,0 +1,49 @@
|
||||
# Structured Output with AI Agents
|
||||
|
||||
This sample demonstrates how to configure AI agents to produce structured output in JSON format using JSON schemas.
|
||||
|
||||
## What this sample demonstrates
|
||||
|
||||
- Configuring agents with JSON schema response formats
|
||||
- Using generic RunAsync<T> method for structured output
|
||||
- Deserializing structured responses into typed objects
|
||||
- Running agents with streaming and structured output
|
||||
- Managing agent lifecycle (creation and deletion)
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 10 SDK or later
|
||||
- Azure 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).
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
$env:AZURE_FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
|
||||
$env:AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME="gpt-4o-mini" # Optional, defaults to gpt-4o-mini
|
||||
```
|
||||
|
||||
## Run the sample
|
||||
|
||||
Navigate to the FoundryAgents sample directory and run:
|
||||
|
||||
```powershell
|
||||
cd dotnet/samples/GettingStarted/FoundryAgents
|
||||
dotnet run --project .\FoundryAgents_Step05_StructuredOutput
|
||||
```
|
||||
|
||||
## Expected behavior
|
||||
|
||||
The sample will:
|
||||
|
||||
1. Create an agent named "StructuredOutputAssistant" configured to produce JSON output
|
||||
2. Run the agent with a prompt to extract person information
|
||||
3. Deserialize the JSON response into a PersonInfo object
|
||||
4. Display the structured data (Name, Age, Occupation)
|
||||
5. Run the agent again with streaming and deserialize the streamed JSON response
|
||||
6. Clean up resources by deleting the agent
|
||||
|
||||
+20
@@ -0,0 +1,20 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user