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This commit is contained in:
wehub-resource-sync
2026-07-13 13:39:25 +08:00
commit db620d33df
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<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
<NoWarn>$(NoWarn);OPENAICUA001;MEAI001</NoWarn>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Azure.Identity" />
<PackageReference Include="Microsoft.Extensions.Logging.Console" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Foundry\Microsoft.Agents.AI.Foundry.csproj" />
</ItemGroup>
<ItemGroup>
<None Update="Assets\cua_browser_search.jpg">
<CopyToOutputDirectory>Always</CopyToOutputDirectory>
</None>
<None Update="Assets\cua_search_results.jpg">
<CopyToOutputDirectory>Always</CopyToOutputDirectory>
</None>
<None Update="Assets\cua_search_typed.jpg">
<CopyToOutputDirectory>Always</CopyToOutputDirectory>
</None>
</ItemGroup>
</Project>
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// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Extensions.AI;
using OpenAI.Responses;
namespace Demo.ComputerUse;
/// <summary>
/// Enum for tracking the state of the simulated web search flow.
/// </summary>
internal enum SearchState
{
Initial, // Browser search page
Typed, // Text entered in search box
PressedEnter // Enter key pressed, transitioning to results
}
internal static class ComputerUseUtil
{
internal static async Task<Dictionary<string, string>> UploadScreenshotAssetsAsync(IHostedFileClient fileClient)
{
string assetsDir = Path.Combine(AppDomain.CurrentDomain.BaseDirectory, "Assets");
(string key, string fileName)[] files =
[
("browser_search", "cua_browser_search.jpg"),
("search_typed", "cua_search_typed.jpg"),
("search_results", "cua_search_results.jpg")
];
Dictionary<string, string> screenshots = [];
foreach (var (key, fileName) in files)
{
HostedFileContent result = await fileClient.UploadAsync(
Path.Combine(assetsDir, fileName), new HostedFileClientOptions() { Purpose = "assistants" });
screenshots[key] = result.FileId;
}
return screenshots;
}
internal static async Task EnsureDeleteScreenshotAssetsAsync(IHostedFileClient fileClient, Dictionary<string, string> screenshots)
{
foreach (var (_, fileId) in screenshots)
{
try
{
await fileClient.DeleteAsync(fileId);
}
catch
{
}
}
}
/// <summary>
/// Simulates executing a computer action by advancing the state
/// and returning the screenshot file ID for the new state.
/// </summary>
internal static async Task<(SearchState State, string FileId)> GetScreenshotAsync(
ComputerCallAction action,
SearchState currentState,
Dictionary<string, string> screenshots)
{
if (action.Kind == ComputerCallActionKind.Wait)
{
await Task.Delay(TimeSpan.FromSeconds(5));
}
SearchState nextState = action.Kind switch
{
ComputerCallActionKind.Click when currentState == SearchState.Typed => SearchState.PressedEnter,
ComputerCallActionKind.Type when action.TypeText is not null => SearchState.Typed,
ComputerCallActionKind.KeyPress when IsEnterKey(action) => SearchState.PressedEnter,
_ => currentState
};
string imageKey = nextState switch
{
SearchState.PressedEnter => "search_results",
SearchState.Typed => "search_typed",
_ => "browser_search"
};
return (nextState, screenshots[imageKey]);
}
private static bool IsEnterKey(ComputerCallAction action) =>
action.KeyPressKeyCodes is not null &&
(action.KeyPressKeyCodes.Contains("Return", StringComparer.OrdinalIgnoreCase) ||
action.KeyPressKeyCodes.Contains("Enter", StringComparer.OrdinalIgnoreCase));
}
@@ -0,0 +1,112 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample shows how to use the Computer Use tool with AIProjectClient.AsAIAgent(...).
using Azure.AI.Projects;
using Azure.Identity;
using Demo.ComputerUse;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Foundry;
using Microsoft.Extensions.AI;
using OpenAI.Responses;
string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_COMPUTER_USE_DEPLOYMENT_NAME") ?? "computer-use-preview";
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
AIProjectClient projectClient = new(new Uri(endpoint), new DefaultAzureCredential());
using IHostedFileClient fileClient = projectClient.GetProjectOpenAIClient().AsIHostedFileClient();
AIAgent agent = projectClient.AsAIAgent(
model: deploymentName,
name: "ComputerAgent",
instructions: "You are a computer automation assistant.",
tools: [FoundryAITool.CreateComputerTool(ComputerToolEnvironment.Browser, 1026, 769)]);
Dictionary<string, string> screenshots = [];
try
{
// Upload pre-captured screenshots that simulate browser state transitions.
screenshots = await ComputerUseUtil.UploadScreenshotAssetsAsync(fileClient);
// Enable auto-truncation for the Responses API.
ChatClientAgentRunOptions runOptions = new()
{
ChatOptions = new ChatOptions
{
RawRepresentationFactory = (_) => new CreateResponseOptions() { TruncationMode = ResponseTruncationMode.Auto },
}
};
// Send the initial request with a screenshot of the browser.
ChatMessage message = new(ChatRole.User, [
new TextContent("Search for 'OpenAI news'. Type it and submit. Once you see results, the task is complete."),
new AIContent() { RawRepresentation = ResponseContentPart.CreateInputImagePart(imageFileId: screenshots["browser_search"], imageDetailLevel: ResponseImageDetailLevel.High) }
]);
Console.WriteLine("Starting computer use session...");
AgentSession session = await agent.CreateSessionAsync();
AgentResponse response = await agent.RunAsync(message, session: session, options: runOptions);
SearchState currentState = SearchState.Initial;
for (int i = 0; i < 10; i++)
{
// Find the next computer call action.
ComputerCallResponseItem? computerCall = response.Messages
.SelectMany(m => m.Contents)
.Select(c => c.RawRepresentation as ComputerCallResponseItem)
.FirstOrDefault(item => item is not null);
if (computerCall is null)
{
if (currentState == SearchState.PressedEnter)
{
Console.WriteLine("No more computer actions. Done.");
Console.WriteLine(response);
break;
}
// Check if the agent is asking for confirmation to proceed, and if so, respond affirmatively.
TextContent? textContent = response.Messages
.Where(m => m.Role == ChatRole.Assistant)
.SelectMany(m => m.Contents.OfType<TextContent>())
.FirstOrDefault();
if (textContent?.Text is { } text && (
text.Contains("Would you like me") ||
text.Contains("Should I") ||
text.Contains("proceed") ||
text.Contains('?')))
{
response = await agent.RunAsync("Please proceed.", session, runOptions);
continue;
}
break;
}
Console.WriteLine($"[{i + 1}] Action: {computerCall!.Action.Kind}");
// Simulate the action and get the resulting screenshot.
(currentState, string fileId) = await ComputerUseUtil.GetScreenshotAsync(computerCall.Action, currentState, screenshots);
// Send the screenshot back as the computer call output.
AIContent callOutput = new()
{
RawRepresentation = new ComputerCallOutputResponseItem(
computerCall.CallId,
output: ComputerCallOutput.CreateScreenshotOutput(screenshotImageFileId: fileId))
};
response = await agent.RunAsync([new ChatMessage(ChatRole.User, [callOutput])], session: session, options: runOptions);
}
}
finally
{
await ComputerUseUtil.EnsureDeleteScreenshotAssetsAsync(fileClient, screenshots);
}
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# Computer Use with the Responses API
This sample shows how to use the Computer Use tool with `AIProjectClient.AsAIAgent(...)`.
## What this sample demonstrates
- Using `FoundryAITool.CreateComputerTool()` to add computer use capabilities
- Processing computer call actions (click, type, key press)
- Managing the computer use interaction loop with screenshots
For more information, see [Use the computer tool](https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/computer-use?pivots=csharp).
## How the simulation works
In a real computer use scenario, the model controls a virtual keyboard and mouse to interact with a live browser — typing text, clicking buttons, and pressing keys. The host application captures a screenshot after each action and sends it back to the model so it can decide what to do next.
**This sample does not connect to a real browser.** Instead, it intercepts the model's actions and returns pre-captured screenshots as if the actions were actually performed. No real typing, clicking, or key presses happen — the sample fakes the environment so you can explore the computer use protocol without any browser automation setup.
### State transitions
The model receives a screenshot as input, analyzes it, and responds with a computer action as output. The sample maps each action to a new state and returns the corresponding screenshot:
| Step | Model Action | What Happens | Screenshot Sent Back to Model |
|------|-----------------|-------------------------------------------|--------------------------------------------------------------|
| 1 | | Session starts with the user prompt | `cua_browser_search.jpg` — empty search page |
| 2 | Click | Model clicks the search box to focus it | `cua_browser_search.jpg` — same page |
| 3 | Type | Model types the search query into the box | `cua_search_typed.jpg` — search text visible in the box |
| 3a | *(text response)* | Model may ask for confirmation instead of acting | `cua_search_typed.jpg` — same page |
| 4 | KeyPress Enter | Model presses Enter to submit the search | `cua_search_results.jpg` — search results page |
### Interaction loop
1. The user prompt and the initial screenshot (`cua_browser_search.jpg` — an empty search page) are sent to the model as input.
2. The model analyzes the screenshot and responds with a computer action (e.g., click on the search box to focus it, then type search text, then press Enter).
3. The sample intercepts the action, advances the state, and sends back the next pre-captured screenshot as if the action was performed on a real browser.
4. Steps 23 repeat until the model stops requesting actions or the iteration limit is reached.
## Prerequisites
- .NET 10 SDK or later
- Microsoft Foundry service endpoint and deployment configured
- An authenticated Azure identity (for example, sign in with `az login`)
Set the following environment variables:
```powershell
$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
$env:AZURE_AI_COMPUTER_USE_DEPLOYMENT_NAME="computer-use-preview"
```
## Run the sample
```powershell
dotnet run
```