Merge branch 'main' into javiercn/mapagui-hosting-overloads

2026-06-16 21:04:09 +08:00 · 2025-12-05 13:46:45 +01:00
parent 09c0648486 51721bd9f6
commit 47b8ced5ca
242 changed files with 13019 additions and 6985 deletions
@@ -14,11 +14,6 @@
    <PackageReference Include="Microsoft.Extensions.Hosting" />
  </ItemGroup>

-  <ItemGroup Condition="!$([MSBuild]::IsTargetFrameworkCompatible($(TargetFramework), 'net10.0'))">
-    <PackageReference Include="System.Net.ServerSentEvents" />
-    <PackageReference Include="Microsoft.Bcl.AsyncInterfaces" />
-  </ItemGroup>
-
  <ItemGroup>
    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.A2A\Microsoft.Agents.AI.A2A.csproj" />
    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Abstractions\Microsoft.Agents.AI.Abstractions.csproj" />
@@ -15,11 +15,6 @@
    <PackageReference Include="Microsoft.Extensions.Hosting" />
  </ItemGroup>

-  <ItemGroup Condition="!$([MSBuild]::IsTargetFrameworkCompatible($(TargetFramework), 'net10.0'))">
-    <PackageReference Include="System.Net.ServerSentEvents" />
-    <PackageReference Include="Microsoft.Bcl.AsyncInterfaces" />
-  </ItemGroup>
-
  <ItemGroup>
    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.A2A\Microsoft.Agents.AI.A2A.csproj" />
    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
@@ -11,6 +11,7 @@

  <ItemGroup>
    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Anthropic.Foundry" />
  </ItemGroup>

  <ItemGroup>
@@ -2,10 +2,9 @@

 // This sample shows how to create and use an AI agent with Anthropic as the backend.

-using System.ClientModel;
 using System.Net.Http.Headers;
 using Anthropic;
-using Anthropic.Core;
+using Anthropic.Foundry;
 using Azure.Core;
 using Azure.Identity;
 using Microsoft.Agents.AI;
@@ -15,8 +14,8 @@ var deploymentName = Environment.GetEnvironmentVariable("ANTHROPIC_DEPLOYMENT_NA

 // The resource is the subdomain name / first name coming before '.services.ai.azure.com' in the endpoint Uri
 // ie: https://(resource name).services.ai.azure.com/anthropic/v1/chat/completions
-var resource = Environment.GetEnvironmentVariable("ANTHROPIC_RESOURCE");
-var apiKey = Environment.GetEnvironmentVariable("ANTHROPIC_API_KEY");
+string? resource = Environment.GetEnvironmentVariable("ANTHROPIC_RESOURCE");
+string? apiKey = Environment.GetEnvironmentVariable("ANTHROPIC_API_KEY");

 const string JokerInstructions = "You are good at telling jokes.";
 const string JokerName = "JokerAgent";
@@ -24,8 +23,8 @@ const string JokerName = "JokerAgent";
 AnthropicClient? client = (resource is null)
    ? new AnthropicClient() { APIKey = apiKey ?? throw new InvalidOperationException("ANTHROPIC_API_KEY is required when no ANTHROPIC_RESOURCE is provided") }  // If no resource is provided, use Anthropic public API
    : (apiKey is not null)
-        ? new AnthropicFoundryClient(resource, new ApiKeyCredential(apiKey)) // If an apiKey is provided, use Foundry with ApiKey authentication
-        : new AnthropicFoundryClient(resource, new AzureCliCredential()); // Otherwise, use Foundry with Azure Client authentication
+        ? new AnthropicFoundryClient(new AnthropicFoundryApiKeyCredentials(apiKey, resource)) // If an apiKey is provided, use Foundry with ApiKey authentication
+        : new AnthropicFoundryClient(new AnthropicAzureTokenCredential(new AzureCliCredential(), resource)); // Otherwise, use Foundry with Azure Client authentication

 AIAgent agent = client.CreateAIAgent(model: deploymentName, instructions: JokerInstructions, name: JokerName);

@@ -35,67 +34,41 @@ Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));
 namespace Sample
 {
    /// <summary>
-    /// Provides methods for invoking the Azure hosted Anthropic api.
+    /// Provides methods for invoking the Azure hosted Anthropic models using <see cref="TokenCredential"/> types.
    /// </summary>
-    public class AnthropicFoundryClient : AnthropicClient
+    public sealed class AnthropicAzureTokenCredential : IAnthropicFoundryCredentials
    {
        private readonly TokenCredential _tokenCredential;
-        private readonly string _resourceName;
+        private readonly Lock _lock = new();
+        private AccessToken? _cachedAccessToken;
+
+        /// <inheritdoc/>
+        public string ResourceName { get; }

        /// <summary>
-        /// Creates a new instance of the <see cref="AnthropicFoundryClient"/>.
+        /// Creates a new instance of the <see cref="AnthropicAzureTokenCredential"/>.
        /// </summary>
-        /// <param name="resourceName">The service resource subdomain name to use in the anthropic azure endpoint</param>
        /// <param name="tokenCredential">The credential provider. Use any specialization of <see cref="TokenCredential"/> to get your access token in supported environments.</param>
-        /// <param name="options">Set of <see cref="Anthropic.Core.ClientOptions"/> client option configurations</param>
-        /// <exception cref="ArgumentNullException">Resource is null</exception>
-        /// <exception cref="ArgumentNullException">TokenCredential is null</exception>
-        /// <remarks>
-        /// Any <see cref="Anthropic.Core.ClientOptions"/> APIKey or Bearer token provided will be ignored in favor of the <see cref="TokenCredential"/> provided in the constructor
-        /// </remarks>
-        public AnthropicFoundryClient(string resourceName, TokenCredential tokenCredential, Anthropic.Core.ClientOptions? options = null) : base(options ?? new())
+        /// <param name="resourceName">The service resource subdomain name to use in the anthropic azure endpoint</param>
+        internal AnthropicAzureTokenCredential(TokenCredential tokenCredential, string resourceName)
        {
-            this._resourceName = resourceName ?? throw new ArgumentNullException(nameof(resourceName));
+            this.ResourceName = resourceName ?? throw new ArgumentNullException(nameof(resourceName));
            this._tokenCredential = tokenCredential ?? throw new ArgumentNullException(nameof(tokenCredential));
-            this.BaseUrl = new Uri($"https://{this._resourceName}.services.ai.azure.com/anthropic", UriKind.Absolute);
        }

-        /// <summary>
-        /// Creates a new instance of the <see cref="AnthropicFoundryClient"/>.
-        /// </summary>
-        /// <param name="resourceName">The service resource subdomain name to use in the anthropic azure endpoint</param>
-        /// <param name="apiKeyCredential">The api key.</param>
-        /// <param name="options">Set of <see cref="Anthropic.Core.ClientOptions"/> client option configurations</param>
-        /// <exception cref="ArgumentNullException">Resource is null</exception>
-        /// <exception cref="ArgumentNullException">Api key is null</exception>
-        /// <remarks>
-        /// Any <see cref="Anthropic.Core.ClientOptions"/> APIKey or Bearer token provided will be ignored in favor of the <see cref="ApiKeyCredential"/> provided in the constructor
-        /// </remarks>
-        public AnthropicFoundryClient(string resourceName, ApiKeyCredential apiKeyCredential, Anthropic.Core.ClientOptions? options = null) :
-            this(resourceName, apiKeyCredential is null
-                ? throw new ArgumentNullException(nameof(apiKeyCredential))
-                : DelegatedTokenCredential.Create((_, _) =>
-                {
-                    apiKeyCredential.Deconstruct(out string dangerousCredential);
-                    return new AccessToken(dangerousCredential, DateTimeOffset.MaxValue);
-                }),
-                options)
-        { }
-
-        public override IAnthropicClient WithOptions(Func<Anthropic.Core.ClientOptions, Anthropic.Core.ClientOptions> modifier)
-            => this;
-
-        protected override ValueTask BeforeSend<T>(
-            HttpRequest<T> request,
-            HttpRequestMessage requestMessage,
-            CancellationToken cancellationToken
-        )
+        /// <inheritdoc/>
+        public void Apply(HttpRequestMessage requestMessage)
        {
-            var accessToken = this._tokenCredential.GetToken(new TokenRequestContext(scopes: ["https://ai.azure.com/.default"]), cancellationToken);
+            lock (this._lock)
+            {
+                // Add a 5-minute buffer to avoid using tokens that are about to expire
+                if (this._cachedAccessToken is null || this._cachedAccessToken.Value.ExpiresOn <= DateTimeOffset.Now.AddMinutes(5))
+                {
+                    this._cachedAccessToken = this._tokenCredential.GetToken(new TokenRequestContext(scopes: ["https://ai.azure.com/.default"]), CancellationToken.None);
+                }
+            }

-            requestMessage.Headers.Authorization = new AuthenticationHeaderValue("bearer", accessToken.Token);
-
-            return default;
+            requestMessage.Headers.Authorization = new AuthenticationHeaderValue("bearer", this._cachedAccessToken.Value.Token);
        }
    }
 }
@@ -2,11 +2,11 @@

  <PropertyGroup>
    <OutputType>Exe</OutputType>
-    <TargetFrameworks>net10.0</TargetFrameworks>
+    <TargetFrameworks>net8.0;net9.0;net10.0</TargetFrameworks>

    <Nullable>enable</Nullable>
    <ImplicitUsings>enable</ImplicitUsings>
-    <NoWarn>$(NoWarn);IDE0059</NoWarn>
+    <NoWarn>$(NoWarn);IDE0059;NU1510</NoWarn>
  </PropertyGroup>

  <ItemGroup>
@@ -14,6 +14,10 @@
    <PackageReference Include="Mscc.GenerativeAI.Microsoft" />
  </ItemGroup>

+  <ItemGroup Condition="'$(TargetFramework)' == 'net8.0' or '$(TargetFramework)' == 'net9.0'">
+    <PackageReference Include="System.Net.Security" />
+  </ItemGroup>
+  
  <ItemGroup>
    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
  </ItemGroup>
@@ -32,7 +32,7 @@ AIAgent agent = new AzureOpenAIClient(
    .GetChatClient(deploymentName)
    .CreateAIAgent(new ChatClientAgentOptions
    {
-        Instructions = "You are good at telling jokes.",
+        ChatOptions = new() { Instructions = "You are good at telling jokes." },
        Name = "Joker",
        AIContextProviderFactory = (ctx) => new ChatHistoryMemoryProvider(
            vectorStore,
@@ -30,7 +30,7 @@ AIAgent agent = new AzureOpenAIClient(
    .GetChatClient(deploymentName)
    .CreateAIAgent(new ChatClientAgentOptions()
    {
-        Instructions = "You are a friendly travel assistant. Use known memories about the user when responding, and do not invent details.",
+        ChatOptions = new() { 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 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() })
@@ -33,7 +33,7 @@ ChatClient chatClient = new AzureOpenAIClient(
 // and its storage to that user id.
 AIAgent agent = chatClient.CreateAIAgent(new ChatClientAgentOptions()
 {
-    Instructions = "You are a friendly assistant. Always address the user by their name.",
+    ChatOptions = new() { Instructions = "You are a friendly assistant. Always address the user by their name." },
    AIContextProviderFactory = ctx => new UserInfoMemory(chatClient.AsIChatClient(), ctx.SerializedState, ctx.JsonSerializerOptions)
 });

@@ -0,0 +1,15 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,31 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to create an AI agent directly from an OpenAI.Chat.ChatClient instance using OpenAIChatClientAgent.
+
+using OpenAI;
+using OpenAI.Chat;
+
+string apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
+string model = Environment.GetEnvironmentVariable("OPENAI_MODEL") ?? "gpt-4o-mini";
+
+// Create a ChatClient directly from OpenAIClient
+ChatClient chatClient = new OpenAIClient(apiKey).GetChatClient(model);
+
+// Create an agent directly from the ChatClient using OpenAIChatClientAgent
+OpenAIChatClientAgent agent = new(chatClient, instructions: "You are good at telling jokes.", name: "Joker");
+
+UserChatMessage chatMessage = new("Tell me a joke about a pirate.");
+
+// Invoke the agent and output the text result.
+ChatCompletion chatCompletion = await agent.RunAsync([chatMessage]);
+Console.WriteLine(chatCompletion.Content.Last().Text);
+
+// Invoke the agent with streaming support.
+IAsyncEnumerable<StreamingChatCompletionUpdate> completionUpdates = agent.RunStreamingAsync([chatMessage]);
+await foreach (StreamingChatCompletionUpdate completionUpdate in completionUpdates)
+{
+    if (completionUpdate.ContentUpdate.Count > 0)
+    {
+        Console.WriteLine(completionUpdate.ContentUpdate[0].Text);
+    }
+}
@@ -0,0 +1,22 @@
+# Creating an Agent from a ChatClient
+
+This sample demonstrates how to create an AI agent directly from an `OpenAI.Chat.ChatClient` instance using the `OpenAIChatClientAgent` class.
+
+## What This Sample Shows
+
+- **Direct ChatClient Creation**: Shows how to create an `OpenAI.Chat.ChatClient` from `OpenAI.OpenAIClient` and then use it to instantiate an agent
+- **OpenAIChatClientAgent**: Demonstrates using the OpenAI SDK primitives instead of the ones from Microsoft.Extensions.AI and Microsoft.Agents.AI abstractions
+- **Full Agent Capabilities**: Shows both regular and streaming invocation of the agent
+
+## Running the Sample
+
+1. Set the required environment variables:
+   ```bash
+   set OPENAI_API_KEY=your_api_key_here
+   set OPENAI_MODEL=gpt-4o-mini
+   ```
+
+2. Run the sample:
+   ```bash
+   dotnet run
+   ```
@@ -0,0 +1,15 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,31 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to create OpenAIResponseClientAgent directly from an OpenAIResponseClient instance.
+
+using OpenAI;
+using OpenAI.Responses;
+
+var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
+var model = Environment.GetEnvironmentVariable("OPENAI_MODEL") ?? "gpt-4o-mini";
+
+// Create an OpenAIResponseClient directly from OpenAIClient
+OpenAIResponseClient responseClient = new OpenAIClient(apiKey).GetOpenAIResponseClient(model);
+
+// Create an agent directly from the OpenAIResponseClient using OpenAIResponseClientAgent
+OpenAIResponseClientAgent agent = new(responseClient, instructions: "You are good at telling jokes.", name: "Joker");
+
+ResponseItem userMessage = ResponseItem.CreateUserMessageItem("Tell me a joke about a pirate.");
+
+// Invoke the agent and output the text result.
+OpenAIResponse response = await agent.RunAsync([userMessage]);
+Console.WriteLine(response.GetOutputText());
+
+// Invoke the agent with streaming support.
+IAsyncEnumerable<StreamingResponseUpdate> responseUpdates = agent.RunStreamingAsync([userMessage]);
+await foreach (StreamingResponseUpdate responseUpdate in responseUpdates)
+{
+    if (responseUpdate is StreamingResponseOutputTextDeltaUpdate textUpdate)
+    {
+        Console.WriteLine(textUpdate.Delta);
+    }
+}
@@ -0,0 +1,22 @@
+# Creating an Agent from an OpenAIResponseClient
+
+This sample demonstrates how to create an AI agent directly from an `OpenAI.Responses.OpenAIResponseClient` instance using the `OpenAIResponseClientAgent` class.
+
+## What This Sample Shows
+
+- **Direct OpenAIResponseClient Creation**: Shows how to create an `OpenAI.Responses.OpenAIResponseClient` from `OpenAI.OpenAIClient` and then use it to instantiate an agent
+- **OpenAIResponseClientAgent**: Demonstrates using the OpenAI SDK primitives instead of the ones from Microsoft.Extensions.AI and Microsoft.Agents.AI abstractions
+- **Full Agent Capabilities**: Shows both regular and streaming invocation of the agent
+
+## Running the Sample
+
+1. Set the required environment variables:
+   ```bash
+   set OPENAI_API_KEY=your_api_key_here
+   set OPENAI_MODEL=gpt-4o-mini
+   ```
+
+2. Run the sample:
+   ```bash
+   dotnet run
+   ```
@@ -10,5 +10,7 @@ Agent Framework provides additional support to allow OpenAI developers to use th

 |Sample|Description|
 |---|---|
-|[Creating an AIAgent](./Agent_OpenAI_Step01_Running/)|This sample demonstrates how to create and run a basic agent instructions with native OpenAI SDK types.|
-
+|[Creating an AIAgent](./Agent_OpenAI_Step01_Running/)|This sample demonstrates how to create and run a basic agent with native OpenAI SDK types. Shows both regular and streaming invocation of the agent.|
+|[Using Reasoning Capabilities](./Agent_OpenAI_Step02_Reasoning/)|This sample demonstrates how to create an AI agent with reasoning capabilities using OpenAI's reasoning models and response types.|
+|[Creating an Agent from a ChatClient](./Agent_OpenAI_Step03_CreateFromChatClient/)|This sample demonstrates how to create an AI agent directly from an OpenAI.Chat.ChatClient instance using OpenAIChatClientAgent.|
+|[Creating an Agent from an OpenAIResponseClient](./Agent_OpenAI_Step04_CreateFromOpenAIResponseClient/)|This sample demonstrates how to create an AI agent directly from an OpenAI.Responses.OpenAIResponseClient instance using OpenAIResponseClientAgent.|
@@ -8,7 +8,6 @@
 using Azure.AI.OpenAI;
 using Azure.Identity;
 using Microsoft.Agents.AI;
-using Microsoft.Agents.AI.Data;
 using Microsoft.Agents.AI.Samples;
 using Microsoft.Extensions.AI;
 using Microsoft.Extensions.VectorData;
@@ -62,7 +61,7 @@ AIAgent agent = azureOpenAIClient
    .GetChatClient(deploymentName)
    .CreateAIAgent(new ChatClientAgentOptions
    {
-        Instructions = "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available.",
+        ChatOptions = new() { Instructions = "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available." },
        AIContextProviderFactory = ctx => new TextSearchProvider(SearchAdapter, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions)
    });

@@ -7,7 +7,6 @@
 using Azure.AI.OpenAI;
 using Azure.Identity;
 using Microsoft.Agents.AI;
-using Microsoft.Agents.AI.Data;
 using Microsoft.Extensions.AI;
 using Microsoft.Extensions.VectorData;
 using Microsoft.SemanticKernel.Connectors.Qdrant;
@@ -71,7 +70,7 @@ AIAgent agent = azureOpenAIClient
    .GetChatClient(deploymentName)
    .CreateAIAgent(new ChatClientAgentOptions
    {
-        Instructions = "You are a helpful support specialist for the Microsoft Agent Framework. Answer questions using the provided context and cite the source document when available. Keep responses brief.",
+        ChatOptions = new() { Instructions = "You are a helpful support specialist for the Microsoft Agent Framework. Answer questions using the provided context and cite the source document when available. Keep responses brief." },
        AIContextProviderFactory = ctx => new TextSearchProvider(SearchAdapter, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions)
    });

@@ -9,7 +9,6 @@
 using Azure.AI.OpenAI;
 using Azure.Identity;
 using Microsoft.Agents.AI;
-using Microsoft.Agents.AI.Data;
 using Microsoft.Extensions.AI;
 using OpenAI;

@@ -29,7 +28,7 @@ AIAgent agent = new AzureOpenAIClient(
    .GetChatClient(deploymentName)
    .CreateAIAgent(new ChatClientAgentOptions
    {
-        Instructions = "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available.",
+        ChatOptions = new() { Instructions = "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available." },
        AIContextProviderFactory = ctx => new TextSearchProvider(MockSearchAsync, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions)
    });

@@ -22,7 +22,7 @@ ChatClient chatClient = new AzureOpenAIClient(
        .GetChatClient(deploymentName);

 // Create the ChatClientAgent with the specified name and instructions.
-ChatClientAgent agent = chatClient.CreateAIAgent(new ChatClientAgentOptions(name: "HelpfulAssistant", instructions: "You are a helpful assistant."));
+ChatClientAgent agent = chatClient.CreateAIAgent(name: "HelpfulAssistant", instructions: "You are a helpful assistant.");

 // 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.");
@@ -34,12 +34,10 @@ 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 = chatClient.CreateAIAgent(new ChatClientAgentOptions(name: "HelpfulAssistant", instructions: "You are a helpful assistant.")
+ChatClientAgent agentWithPersonInfo = chatClient.CreateAIAgent(new ChatClientAgentOptions()
 {
-    ChatOptions = new()
-    {
-        ResponseFormat = Microsoft.Extensions.AI.ChatResponseFormat.ForJsonSchema<PersonInfo>()
-    }
+    Name = "HelpfulAssistant",
+    ChatOptions = new() { Instructions = "You are a helpful assistant.", ResponseFormat = Microsoft.Extensions.AI.ChatResponseFormat.ForJsonSchema<PersonInfo>() }
 });

 // Invoke the agent with some unstructured input while streaming, to extract the structured information from.
@@ -28,7 +28,7 @@ AIAgent agent = new AzureOpenAIClient(
    .GetChatClient(deploymentName)
    .CreateAIAgent(new ChatClientAgentOptions
    {
-        Instructions = "You are good at telling jokes.",
+        ChatOptions = new() { Instructions = "You are good at telling jokes." },
        Name = "Joker",
        ChatMessageStoreFactory = ctx =>
        {
@@ -18,8 +18,7 @@ var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT
 HostApplicationBuilder builder = Host.CreateApplicationBuilder(args);

 // Add agent options to the service collection.
-builder.Services.AddSingleton(
-    new ChatClientAgentOptions(instructions: "You are good at telling jokes.", name: "Joker"));
+builder.Services.AddSingleton(new ChatClientAgentOptions() { Name = "Joker", ChatOptions = new() { Instructions = "You are good at telling jokes." } });

 // Add a chat client to the service collection.
 builder.Services.AddKeyedChatClient("AzureOpenAI", (sp) => new AzureOpenAIClient(
@@ -16,10 +16,6 @@
    <PackageReference Include="ModelContextProtocol" />
  </ItemGroup>

-  <ItemGroup Condition="!$([MSBuild]::IsTargetFrameworkCompatible($(TargetFramework), 'net10.0'))">
-    <PackageReference Include="System.Net.ServerSentEvents" />
-  </ItemGroup>
-
  <ItemGroup>
    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI.Persistent\Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
  </ItemGroup>
@@ -21,7 +21,7 @@ AIAgent agent = new AzureOpenAIClient(
    .GetChatClient(deploymentName)
    .CreateAIAgent(new ChatClientAgentOptions
    {
-        Instructions = "You are good at telling jokes.",
+        ChatOptions = new() { Instructions = "You are good at telling jokes." },
        Name = "Joker",
        ChatMessageStoreFactory = ctx => new InMemoryChatMessageStore(new MessageCountingChatReducer(2), ctx.SerializedState, ctx.JsonSerializerOptions)
    });
@@ -24,10 +24,12 @@ AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential(
 // Create ChatClientAgent directly
 ChatClientAgent agent = await aiProjectClient.CreateAIAgentAsync(
    model: deploymentName,
-    new ChatClientAgentOptions(name: AssistantName, instructions: AssistantInstructions)
+    new ChatClientAgentOptions()
    {
+        Name = AssistantName,
        ChatOptions = new()
        {
+            Instructions = AssistantInstructions,
            ResponseFormat = Microsoft.Extensions.AI.ChatResponseFormat.ForJsonSchema<PersonInfo>()
        }
    });
@@ -44,10 +46,12 @@ 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)
+    new ChatClientAgentOptions()
    {
+        Name = AssistantName,
        ChatOptions = new()
        {
+            Instructions = AssistantInstructions,
            ResponseFormat = Microsoft.Extensions.AI.ChatResponseFormat.ForJsonSchema<PersonInfo>()
        }
    });
@@ -17,10 +17,6 @@
    <PackageReference Include="ModelContextProtocol" />
  </ItemGroup>

-  <ItemGroup Condition="!$([MSBuild]::IsTargetFrameworkCompatible($(TargetFramework), 'net10.0'))">
-    <PackageReference Include="System.Net.ServerSentEvents" />
-  </ItemGroup>
-
  <ItemGroup>
    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
  </ItemGroup>
@@ -34,9 +34,9 @@ AIAgent agent = await persistentAgentsClient.CreateAIAgentAsync(
    options: new()
    {
        Name = "MicrosoftLearnAgent",
-        Instructions = "You answer questions by searching the Microsoft Learn content only.",
        ChatOptions = new()
        {
+            Instructions = "You answer questions by searching the Microsoft Learn content only.",
            Tools = [mcpTool]
        },
    });
@@ -67,9 +67,9 @@ AIAgent agentWithRequiredApproval = await persistentAgentsClient.CreateAIAgentAs
    options: new()
    {
        Name = "MicrosoftLearnAgentWithApproval",
-        Instructions = "You answer questions by searching the Microsoft Learn content only.",
        ChatOptions = new()
        {
+            Instructions = "You answer questions by searching the Microsoft Learn content only.",
            Tools = [mcpToolWithApproval]
        },
    });
@@ -118,10 +118,11 @@ internal sealed class SloganWriterExecutor : Executor
    /// <param name="chatClient">The chat client to use for the AI agent.</param>
    public SloganWriterExecutor(string id, IChatClient chatClient) : base(id)
    {
-        ChatClientAgentOptions agentOptions = new(instructions: "You are a professional slogan writer. You will be given a task to create a slogan.")
+        ChatClientAgentOptions agentOptions = new()
        {
            ChatOptions = new()
            {
+                Instructions = "You are a professional slogan writer. You will be given a task to create a slogan.",
                ResponseFormat = ChatResponseFormat.ForJsonSchema<SloganResult>()
            }
        };
@@ -193,10 +194,11 @@ internal sealed class FeedbackExecutor : Executor<SloganResult>
    /// <param name="chatClient">The chat client to use for the AI agent.</param>
    public FeedbackExecutor(string id, IChatClient chatClient) : base(id)
    {
-        ChatClientAgentOptions agentOptions = new(instructions: "You are a professional editor. You will be given a slogan and the task it is meant to accomplish.")
+        ChatClientAgentOptions agentOptions = new()
        {
            ChatOptions = new()
            {
+                Instructions = "You are a professional editor. You will be given a slogan and the task it is meant to accomplish.",
                ResponseFormat = ChatResponseFormat.ForJsonSchema<FeedbackResult>()
            }
        };
@@ -85,10 +85,11 @@ public static class Program
    /// </summary>
    /// <returns>A ChatClientAgent configured for spam detection</returns>
    private static ChatClientAgent GetSpamDetectionAgent(IChatClient chatClient) =>
-        new(chatClient, new ChatClientAgentOptions(instructions: "You are a spam detection assistant that identifies spam emails.")
+        new(chatClient, new ChatClientAgentOptions()
        {
            ChatOptions = new()
            {
+                Instructions = "You are a spam detection assistant that identifies spam emails.",
                ResponseFormat = ChatResponseFormat.ForJsonSchema<DetectionResult>()
            }
        });
@@ -98,10 +99,11 @@ public static class Program
    /// </summary>
    /// <returns>A ChatClientAgent configured for email assistance</returns>
    private static ChatClientAgent GetEmailAssistantAgent(IChatClient chatClient) =>
-        new(chatClient, new ChatClientAgentOptions(instructions: "You are an email assistant that helps users draft responses to emails with professionalism.")
+        new(chatClient, new ChatClientAgentOptions()
        {
            ChatOptions = new()
            {
+                Instructions = "You are an email assistant that helps users draft responses to emails with professionalism.",
                ResponseFormat = ChatResponseFormat.ForJsonSchema<EmailResponse>()
            }
        });
@@ -100,10 +100,11 @@ public static class Program
    /// </summary>
    /// <returns>A ChatClientAgent configured for spam detection</returns>
    private static ChatClientAgent GetSpamDetectionAgent(IChatClient chatClient) =>
-        new(chatClient, new ChatClientAgentOptions(instructions: "You are a spam detection assistant that identifies spam emails. Be less confident in your assessments.")
+        new(chatClient, new ChatClientAgentOptions()
        {
            ChatOptions = new()
            {
+                Instructions = "You are a spam detection assistant that identifies spam emails. Be less confident in your assessments.",
                ResponseFormat = ChatResponseFormat.ForJsonSchema<DetectionResult>()
            }
        });
@@ -113,10 +114,11 @@ public static class Program
    /// </summary>
    /// <returns>A ChatClientAgent configured for email assistance</returns>
    private static ChatClientAgent GetEmailAssistantAgent(IChatClient chatClient) =>
-        new(chatClient, new ChatClientAgentOptions(instructions: "You are an email assistant that helps users draft responses to emails with professionalism.")
+        new(chatClient, new ChatClientAgentOptions()
        {
            ChatOptions = new()
            {
+                Instructions = "You are an email assistant that helps users draft responses to emails with professionalism.",
                ResponseFormat = ChatResponseFormat.ForJsonSchema<EmailResponse>()
            }
        });
@@ -140,10 +140,11 @@ public static class Program
    /// </summary>
    /// <returns>A ChatClientAgent configured for email analysis</returns>
    private static ChatClientAgent GetEmailAnalysisAgent(IChatClient chatClient) =>
-        new(chatClient, new ChatClientAgentOptions(instructions: "You are a spam detection assistant that identifies spam emails.")
+        new(chatClient, new ChatClientAgentOptions()
        {
            ChatOptions = new()
            {
+                Instructions = "You are a spam detection assistant that identifies spam emails.",
                ResponseFormat = ChatResponseFormat.ForJsonSchema<AnalysisResult>()
            }
        });
@@ -153,10 +154,11 @@ public static class Program
    /// </summary>
    /// <returns>A ChatClientAgent configured for email assistance</returns>
    private static ChatClientAgent GetEmailAssistantAgent(IChatClient chatClient) =>
-        new(chatClient, new ChatClientAgentOptions(instructions: "You are an email assistant that helps users draft responses to emails with professionalism.")
+        new(chatClient, new ChatClientAgentOptions()
        {
            ChatOptions = new()
            {
+                Instructions = "You are an email assistant that helps users draft responses to emails with professionalism.",
                ResponseFormat = ChatResponseFormat.ForJsonSchema<EmailResponse>()
            }
        });
@@ -166,10 +168,11 @@ public static class Program
    /// </summary>
    /// <returns>A ChatClientAgent configured for email summarization</returns>
    private static ChatClientAgent GetEmailSummaryAgent(IChatClient chatClient) =>
-        new(chatClient, new ChatClientAgentOptions(instructions: "You are an assistant that helps users summarize emails.")
+        new(chatClient, new ChatClientAgentOptions()
        {
            ChatOptions = new()
            {
+                Instructions = "You are an assistant that helps users summarize emails.",
                ResponseFormat = ChatResponseFormat.ForJsonSchema<EmailSummary>()
            }
        });
@@ -285,19 +285,19 @@ internal sealed class CriticExecutor : Executor<ChatMessage, CriticDecision>
        this._agent = new ChatClientAgent(chatClient, new ChatClientAgentOptions
        {
            Name = "Critic",
-            Instructions = """
-                You are a constructive critic. Review the content and provide specific feedback.
-                Always try to provide actionable suggestions for improvement and strive to identify improvement points.
-                Only approve if the content is high quality, clear, and meets the original requirements and you see no improvement points.
-                
-                Provide your decision as structured output with:
-                - approved: true if content is good, false if revisions needed
-                - feedback: specific improvements needed (empty if approved)
-                
-                Be concise but specific in your feedback.
-                """,
            ChatOptions = new()
            {
+                Instructions = """
+                    You are a constructive critic. Review the content and provide specific feedback.
+                    Always try to provide actionable suggestions for improvement and strive to identify improvement points.
+                    Only approve if the content is high quality, clear, and meets the original requirements and you see no improvement points.
+                
+                    Provide your decision as structured output with:
+                    - approved: true if content is good, false if revisions needed
+                    - feedback: specific improvements needed (empty if approved)
+                
+                    Be concise but specific in your feedback.
+                    """,
                ResponseFormat = ChatResponseFormat.ForJsonSchema<CriticDecision>()
            }
        });
@@ -33,9 +33,9 @@ public class WeatherForecastAgent : DelegatingAIAgent
            new ChatClientAgentOptions()
            {
                Name = AgentName,
-                Instructions = AgentInstructions,
                ChatOptions = new ChatOptions()
                {
+                    Instructions = AgentInstructions,
                    Tools = [new ApprovalRequiredAIFunction(AIFunctionFactory.Create(GetWeather))],
                    // We want the agent to return structured output in a known format
                    // so that we can easily create adaptive cards from the response.