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.Net - Update and Fixes for AzureAIAgent (#12348)
### Motivation and Context <!-- Thank you for your contribution to the semantic-kernel repo! Please help reviewers and future users, providing the following information: 1. Why is this change required? 2. What problem does it solve? 3. What scenario does it contribute to? 4. If it fixes an open issue, please link to the issue here. --> Address customer input and discovered issues for `AzureAIAgent` ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> Address several issues: - Support image input - Null reference when function calling parameter is null - Null reference when using BingGroundingTool with streaming - Add samples for response-format - Fix connection resolution for declarative bing tool Fixes: #12288 ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [X] The code builds clean without any errors or warnings - [X] The PR follows the [SK Contribution Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) and the [pre-submission formatting script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts) raises no violations - [X] All unit tests pass, and I have added new tests where possible - [X] I didn't break anyone 😄
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‎dotnet/Directory.Packages.props‎

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<PackageVersion Include="Azure.AI.ContentSafety" Version="1.0.0" />
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<PackageVersion Include="Azure.AI.Inference" Version="1.0.0-beta.5" />
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<PackageVersion Include="Azure.AI.OpenAI" Version="[2.2.0-beta.4]" />
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<PackageVersion Include="Azure.AI.Projects" Version="1.0.0-beta.9" />
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<PackageVersion Include="Azure.Identity" Version="1.13.2" />
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<PackageVersion Include="Azure.Monitor.OpenTelemetry.Exporter" Version="1.3.0" />
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<PackageVersion Include="Azure.Search.Documents" Version="11.6.0" />

‎dotnet/samples/Concepts/Agents/AzureAIAgent_Streaming.cs‎

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@@ -199,7 +199,7 @@ public string GetSpecials()
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[KernelFunction, Description("Provides the price of the requested menu item.")]
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public string GetItemPrice(
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[Description("The name of the menu item.")]
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string menuItem)
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string menuItem)
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{
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return "$9.99";
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}

‎dotnet/samples/Concepts/Concepts.csproj‎

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<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
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<PrivateAssets>all</PrivateAssets>
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</PackageReference>
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<PackageReference Include="Azure.AI.Projects" />
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<PackageReference Include="Azure.Identity" />
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<PackageReference Include="Microsoft.Extensions.Configuration" />
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<PackageReference Include="Microsoft.Extensions.AI.AzureAIInference" />

‎dotnet/samples/GettingStartedWithAgents/AzureAIAgent/Step03_AzureAIAgent_Chat.cs‎

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‎dotnet/samples/GettingStartedWithAgents/AzureAIAgent/Step03_AzureAIAgent_Vision.cs‎

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// Copyright (c) Microsoft. All rights reserved.
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using Azure.AI.Agents.Persistent;
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using Microsoft.SemanticKernel;
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using Microsoft.SemanticKernel.Agents.AzureAI;
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using Microsoft.SemanticKernel.ChatCompletion;
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using Resources;
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namespace GettingStarted.AzureAgents;
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/// <summary>
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/// Demonstrate using code-interpreter on <see cref="AzureAIAgent"/> .
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/// </summary>
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public class Step03_AzureAIAgent_Vision(ITestOutputHelper output) : BaseAzureAgentTest(output)
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{
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[Fact]
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public async Task UseImageContentWithAgent()
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{
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// Upload an image
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await using Stream imageStream = EmbeddedResource.ReadStream("cat.jpg")!;
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PersistentAgentFileInfo fileInfo = await this.Client.Files.UploadFileAsync(imageStream, PersistentAgentFilePurpose.Agents, "cat.jpg");
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// Define the agent
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PersistentAgent definition = await this.Client.Administration.CreateAgentAsync(TestConfiguration.AzureAI.ChatModelId);
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AzureAIAgent agent = new(definition, this.Client);
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// Create a thread for the agent conversation.
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AzureAIAgentThread thread = new(this.Client, metadata: SampleMetadata);
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// Respond to user input
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try
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{
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// Refer to public image by url
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await InvokeAgentAsync(CreateMessageWithImageUrl("Describe this image.", "https://upload.wikimedia.org/wikipedia/commons/thumb/4/47/New_york_times_square-terabass.jpg/1200px-New_york_times_square-terabass.jpg"));
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await InvokeAgentAsync(CreateMessageWithImageUrl("What are is the main color in this image?", "https://upload.wikimedia.org/wikipedia/commons/5/56/White_shark.jpg"));
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// Refer to uploaded image by file-id.
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await InvokeAgentAsync(CreateMessageWithImageReference("Is there an animal in this image?", fileInfo.Id));
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}
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finally
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{
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await thread.DeleteAsync();
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await this.Client.Administration.DeleteAgentAsync(agent.Id);
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await this.Client.Files.DeleteFileAsync(fileInfo.Id);
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}
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// Local function to invoke agent and display the conversation messages.
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async Task InvokeAgentAsync(ChatMessageContent input)
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{
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this.WriteAgentChatMessage(input);
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await foreach (ChatMessageContent response in agent.InvokeAsync(input, thread))
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{
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this.WriteAgentChatMessage(response);
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}
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}
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}
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private ChatMessageContent CreateMessageWithImageUrl(string input, string url)
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=> new(AuthorRole.User, [new TextContent(input), new ImageContent(new Uri(url))]);
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private ChatMessageContent CreateMessageWithImageReference(string input, string fileId)
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=> new(AuthorRole.User, [new TextContent(input), new FileReferenceContent(fileId)]);
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}

‎dotnet/samples/GettingStartedWithAgents/AzureAIAgent/Step08_AzureAIAgent_Declarative.cs‎

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public async Task AzureAIAgentWithBingGrounding()
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{
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var text =
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$"""
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"""
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type: foundry_agent
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name: BingAgent
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instructions: Answer questions using Bing to provide grounding context.
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description: This agent answers questions using Bing to provide grounding context.
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model:
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id: ${TestConfiguration.AzureAI:ChatModelId}
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id: ${AzureAI:ChatModelId}
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options:
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temperature: 0.4
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tools:
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- type: bing_grounding
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options:
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tool_connections:
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- {TestConfiguration.AzureAI.BingConnectionId}
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- ${AzureAI:BingConnectionId}
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""";
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AzureAIAgentFactory factory = new();
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public async Task AzureAIAgentWithFileSearch()
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{
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var text =
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$"""
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"""
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type: foundry_agent
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name: FileSearchAgent
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instructions: Answer questions using available files to provide grounding context.
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description: This agent answers questions using available files to provide grounding context.
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model:
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id: ${TestConfiguration.AzureAI:ChatModelId}
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options:
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id: ${AzureAI:ChatModelId}
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optisons:
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temperature: 0.4
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tools:
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- type: file_search
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description: Grounding with available files.
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options:
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vector_store_ids:
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- {TestConfiguration.AzureAI.VectorStoreId}
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- ${AzureAI.VectorStoreId}
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""";
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AzureAIAgentFactory factory = new();
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{
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var builder = Kernel.CreateBuilder();
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builder.Services.AddSingleton(this.Client);
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builder.Services.AddSingleton(this.CreateFoundryProjectClient());
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this._kernel = builder.Build();
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}
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WriteAgentChatMessage(response);
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}
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}
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catch (Exception e)
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{
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Console.WriteLine($"Error invoking agent: {e.Message}");
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}
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finally
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{
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if (deleteAgent ?? true)

‎dotnet/samples/GettingStartedWithAgents/AzureAIAgent/Step09_AzureAIAgent_BingGrounding.cs‎

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@@ -16,7 +16,8 @@ public class Step09_AzureAIAgent_BingGrounding(ITestOutputHelper output) : BaseA
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public async Task UseBingGroundingToolWithAgent()
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{
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// Access the BingGrounding connection
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BingGroundingSearchConfiguration bingToolConfiguration = new(TestConfiguration.AzureAI.BingConnectionId);
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string connectionId = await this.GetConnectionId(TestConfiguration.AzureAI.BingConnectionId);
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BingGroundingSearchConfiguration bingToolConfiguration = new(connectionId);
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BingGroundingSearchToolParameters bingToolParameters = new([bingToolConfiguration]);
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PersistentAgent definition = await this.Client.Administration.CreateAgentAsync(
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TestConfiguration.AzureAI.ChatModelId,
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public async Task UseBingGroundingToolWithStreaming()
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{
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// Access the BingGrounding connection
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BingGroundingSearchConfiguration bingToolConfiguration = new(TestConfiguration.AzureAI.BingConnectionId);
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string connectionId = await this.GetConnectionId(TestConfiguration.AzureAI.BingConnectionId);
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BingGroundingSearchConfiguration bingToolConfiguration = new(connectionId);
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BingGroundingSearchToolParameters bingToolParameters = new([bingToolConfiguration]);
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// Define the agent

‎dotnet/samples/GettingStartedWithAgents/AzureAIAgent/Step10_JsonResponse.cs‎

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// Copyright (c) Microsoft. All rights reserved.
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using Azure.AI.Agents.Persistent;
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using Microsoft.SemanticKernel;
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using Microsoft.SemanticKernel.Agents.AzureAI;
5+
using Microsoft.SemanticKernel.ChatCompletion;
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namespace GettingStarted.AzureAgents;
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9+
/// <summary>
10+
/// Demonstrate parsing JSON response.
11+
/// </summary>
12+
public class Step10_JsonResponse(ITestOutputHelper output) : BaseAzureAgentTest(output)
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{
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private const string TutorInstructions =
15+
"""
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Think step-by-step and rate the user input on creativity and expressiveness from 1-100.
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Respond in JSON format with the following JSON schema:
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{
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"score": "integer (1-100)",
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"notes": "the reason for your score"
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}
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""";
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[Fact]
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public async Task UseJsonObjectResponse()
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{
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PersistentAgent definition =
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await this.Client.Administration.CreateAgentAsync(
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TestConfiguration.AzureAI.ChatModelId,
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instructions: TutorInstructions,
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responseFormat:
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BinaryData.FromString(
35+
"""
36+
{
37+
"type": "json_object"
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}
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"""));
40+
41+
AzureAIAgent agent = new(definition, this.Client);
42+
43+
await ExecuteAgent(agent);
44+
}
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[Fact]
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public async Task UseJsonSchemaResponse()
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{
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PersistentAgent definition =
50+
await this.Client.Administration.CreateAgentAsync(
51+
TestConfiguration.AzureAI.ChatModelId,
52+
instructions: TutorInstructions,
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responseFormat: BinaryData.FromString(
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"""
55+
{
56+
"type": "json_schema",
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"json_schema":
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{
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"type": "object",
60+
"name": "scoring",
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"schema": {
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"type": "object",
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"properties": {
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"score": {
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"type": "number"
66+
},
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"notes": {
68+
"type": "string"
69+
}
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},
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"required": [
72+
"score",
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"notes"
74+
],
75+
"additionalProperties": false
76+
},
77+
"strict": true
78+
}
79+
}
80+
"""));
81+
82+
AzureAIAgent agent = new(definition, this.Client);
83+
84+
await ExecuteAgent(agent);
85+
}
86+
87+
private async Task ExecuteAgent(AzureAIAgent agent)
88+
{
89+
AzureAIAgentThread thread = new(agent.Client);
90+
91+
await InvokeAgentAsync("The sunset is very colorful.");
92+
await InvokeAgentAsync("The sunset is setting over the mountains.");
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await InvokeAgentAsync("The sunset is setting over the mountains and filled the sky with a deep red flame, setting the clouds ablaze.");
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95+
// Local function to invoke agent and display the conversation messages.
96+
async Task InvokeAgentAsync(string input)
97+
{
98+
ChatMessageContent message = new(AuthorRole.User, input);
99+
this.WriteAgentChatMessage(message);
100+
101+
await foreach (ChatMessageContent response in agent.InvokeAsync(message, thread))
102+
{
103+
this.WriteAgentChatMessage(response);
104+
}
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}
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}
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}

‎dotnet/samples/GettingStartedWithAgents/GettingStartedWithAgents.csproj‎

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</PropertyGroup>
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<ItemGroup>
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<PackageReference Include="Azure.AI.Projects" />
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<PackageReference Include="Azure.Identity" />
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<PackageReference Include="Azure.Monitor.OpenTelemetry.Exporter" />
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<PackageReference Include="Microsoft.Extensions.AI.OpenAI" />

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