Files
microsoft--semantic-kernel/dotnet/samples/GettingStartedWithAgents/OpenAIResponse/Step04_OpenAIResponseAgent_Tools.cs
T
wehub-resource-sync b957a53def
CodeQL / Analyze (csharp) (push) Has been cancelled
CodeQL / Analyze (python) (push) Has been cancelled
chore: import upstream snapshot with attribution
2026-07-13 13:21:23 +08:00

169 lines
6.1 KiB
C#

// Copyright (c) Microsoft. All rights reserved.
using System.ClientModel;
using System.ClientModel.Primitives;
using Microsoft.SemanticKernel;
using Microsoft.SemanticKernel.Agents.OpenAI;
using Microsoft.SemanticKernel.ChatCompletion;
using OpenAI.Files;
using OpenAI.Responses;
using OpenAI.VectorStores;
using Plugins;
using Resources;
namespace GettingStarted.OpenAIResponseAgents;
/// <summary>
/// This example demonstrates how to use tools during a model interaction using <see cref="OpenAIResponseAgent"/>.
/// </summary>
public class Step04_OpenAIResponseAgent_Tools(ITestOutputHelper output) : BaseResponsesAgentTest(output)
{
[Fact]
public async Task InvokeAgentWithFunctionToolsAsync()
{
// Define the agent
OpenAIResponseAgent agent = new(this.Client, this.ModelId)
{
StoreEnabled = false,
};
// Create a plugin that defines the tools to be used by the agent.
KernelPlugin plugin = KernelPluginFactory.CreateFromType<MenuPlugin>();
agent.Kernel.Plugins.Add(plugin);
ICollection<ChatMessageContent> messages =
[
new ChatMessageContent(AuthorRole.User, "What is the special soup and its price?"),
new ChatMessageContent(AuthorRole.User, "What is the special drink and its price?"),
];
foreach (ChatMessageContent message in messages)
{
WriteAgentChatMessage(message);
}
// Invoke the agent and output the response
var responseItems = agent.InvokeAsync(messages);
await foreach (ChatMessageContent responseItem in responseItems)
{
WriteAgentChatMessage(responseItem);
}
}
[Fact]
public async Task InvokeAgentWithWebSearchAsync()
{
// Define the agent
OpenAIResponseAgent agent = new(this.Client, this.ModelId)
{
StoreEnabled = false,
};
// ResponseCreationOptions allows you to specify tools for the agent.
CreateResponseOptions creationOptions = new();
creationOptions.Tools.Add(ResponseTool.CreateWebSearchTool());
OpenAIResponseAgentInvokeOptions invokeOptions = new()
{
ResponseCreationOptions = creationOptions,
};
// Invoke the agent and output the response
var responseItems = agent.InvokeAsync("What was a positive news story from today?", options: invokeOptions);
await foreach (ChatMessageContent responseItem in responseItems)
{
WriteAgentChatMessage(responseItem);
}
}
[Fact]
public async Task InvokeAgentWithFileSearchAsync()
{
// Upload a file to the OpenAI File API
await using Stream stream = EmbeddedResource.ReadStream("employees.pdf")!;
OpenAIFile file = await this.FileClient.UploadFileAsync(stream, filename: "employees.pdf", purpose: FileUploadPurpose.UserData);
// Create a vector store for the file
ClientResult<VectorStore> createStoreOp = await this.VectorStoreClient.CreateVectorStoreAsync(
new VectorStoreCreationOptions()
{
FileIds = { file.Id },
});
// Define the agent
OpenAIResponseAgent agent = new(this.Client, this.ModelId)
{
StoreEnabled = false,
};
// ResponseCreationOptions allows you to specify tools for the agent.
CreateResponseOptions creationOptions = new();
creationOptions.Tools.Add(ResponseTool.CreateFileSearchTool([createStoreOp.Value.Id], null));
OpenAIResponseAgentInvokeOptions invokeOptions = new()
{
ResponseCreationOptions = creationOptions,
};
// Invoke the agent and output the response
ICollection<ChatMessageContent> messages =
[
new ChatMessageContent(AuthorRole.User, "Who is the youngest employee?"),
new ChatMessageContent(AuthorRole.User, "Who works in sales?"),
new ChatMessageContent(AuthorRole.User, "I have a customer request, who can help me?"),
];
foreach (ChatMessageContent message in messages)
{
WriteAgentChatMessage(message);
}
// Invoke the agent and output the response
var responseItems = agent.InvokeAsync(messages, options: invokeOptions);
await foreach (ChatMessageContent responseItem in responseItems)
{
WriteAgentChatMessage(responseItem);
}
// Clean up resources
RequestOptions noThrowOptions = new() { ErrorOptions = ClientErrorBehaviors.NoThrow };
this.FileClient.DeleteFile(file.Id, noThrowOptions);
this.VectorStoreClient.DeleteVectorStore(createStoreOp.Value.Id, noThrowOptions);
}
[Fact]
public async Task InvokeAgentWithMultipleToolsAsync()
{
// Define the agent
OpenAIResponseAgent agent = new(this.Client, this.ModelId)
{
StoreEnabled = false,
};
// Create a plugin that defines the tools to be used by the agent.
KernelPlugin plugin = KernelPluginFactory.CreateFromType<MenuPlugin>();
agent.Kernel.Plugins.Add(plugin);
ICollection<ChatMessageContent> messages =
[
new ChatMessageContent(AuthorRole.User, "What is the special soup and its price?"),
new ChatMessageContent(AuthorRole.User, "What is the special drink and its price?"),
];
foreach (ChatMessageContent message in messages)
{
WriteAgentChatMessage(message);
}
// ResponseCreationOptions allows you to specify tools for the agent.
CreateResponseOptions creationOptions = new();
creationOptions.Tools.Add(ResponseTool.CreateWebSearchTool());
OpenAIResponseAgentInvokeOptions invokeOptions = new()
{
ResponseCreationOptions = creationOptions,
};
// Invoke the agent and output the response
var responseItems = agent.InvokeAsync(messages, options: invokeOptions);
await foreach (ChatMessageContent responseItem in responseItems)
{
WriteAgentChatMessage(responseItem);
}
}
}