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This commit is contained in:
2026-01-24 03:05:12 +11:00
parent f78f2388b3
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<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.OpenAI" />
<PackageReference Include="Azure.Identity" />
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
</ItemGroup>
</Project>

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// Copyright (c) Microsoft. All rights reserved.
// This sample shows how to configure ChatClientAgent to produce structured output.
using System.ComponentModel;
using System.Text.Json;
using System.Text.Json.Serialization;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using OpenAI.Chat;
using SampleApp;
var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
// Create chat client to be used by chat client agents.
ChatClient chatClient = new AzureOpenAIClient(
new Uri(endpoint),
new AzureCliCredential())
.GetChatClient(deploymentName);
// Create the ChatClientAgent with the specified name and instructions.
ChatClientAgent agent = chatClient.AsAIAgent(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.
AgentResponse<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($"Occupation: {response.Result.Occupation}");
// Create the ChatClientAgent with the specified name, instructions, and expected structured output the agent should produce.
ChatClientAgent agentWithPersonInfo = chatClient.AsAIAgent(new ChatClientAgentOptions()
{
Name = "HelpfulAssistant",
ChatOptions = new() { Instructions = "You are a helpful assistant.", ResponseFormat = Microsoft.Extensions.AI.ChatResponseFormat.ForJsonSchema<PersonInfo>() }
});
// Invoke the agent with some unstructured input while streaming, to extract the structured information from.
var updates = agentWithPersonInfo.RunStreamingAsync("Please provide information about John Smith, who is a 35-year-old software engineer.");
// Assemble all the parts of the streamed output, since we can only deserialize once we have the full json,
// then deserialize the response into the PersonInfo class.
PersonInfo personInfo = (await updates.ToAgentResponseAsync()).Deserialize<PersonInfo>(JsonSerializerOptions.Web);
Console.WriteLine("Assistant Output:");
Console.WriteLine($"Name: {personInfo.Name}");
Console.WriteLine($"Age: {personInfo.Age}");
Console.WriteLine($"Occupation: {personInfo.Occupation}");
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; }
}
}