Move A2A samples from 04-hosting to 02-agents (#5267)

Move the A2A sample projects (A2AAgent_AsFunctionTools and
A2AAgent_PollingForTaskCompletion) from samples/04-hosting/A2A/ to
samples/02-agents/A2A/ to better align with the sample directory
structure. Update solution file and samples README accordingly.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
This commit is contained in:
SergeyMenshykh
2026-04-15 12:08:21 +01:00
committed by GitHub
Unverified
parent 6173e63f0b
commit c1bbaeb31d
9 changed files with 5 additions and 5 deletions
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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="A2A" />
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
<PackageReference Include="Microsoft.Extensions.Hosting" />
</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" />
</ItemGroup>
</Project>
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// Copyright (c) Microsoft. All rights reserved.
// This sample shows how to represent an A2A agent as a set of function tools, where each function tool
// corresponds to a skill of the A2A agent, and register these function tools with another AI agent so
// it can leverage the A2A agent's skills.
using System.Text.RegularExpressions;
using A2A;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
using OpenAI.Chat;
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-5.4-mini";
var a2aAgentHost = Environment.GetEnvironmentVariable("A2A_AGENT_HOST") ?? throw new InvalidOperationException("A2A_AGENT_HOST is not set.");
// Initialize an A2ACardResolver to get an A2A agent card.
A2ACardResolver agentCardResolver = new(new Uri(a2aAgentHost));
// Get the agent card
AgentCard agentCard = await agentCardResolver.GetAgentCardAsync();
// Create an instance of the AIAgent for an existing A2A agent specified by the agent card.
AIAgent a2aAgent = agentCard.AsAIAgent();
// Create the main agent, and provide the a2a agent skills as a function tools.
// 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.
AIAgent agent = new AzureOpenAIClient(
new Uri(endpoint),
new DefaultAzureCredential())
.GetChatClient(deploymentName)
.AsAIAgent(
instructions: "You are a helpful assistant that helps people with travel planning.",
tools: [.. CreateFunctionTools(a2aAgent, agentCard)]
);
// Invoke the agent and output the text result.
Console.WriteLine(await agent.RunAsync("Plan a route from '1600 Amphitheatre Parkway, Mountain View, CA' to 'San Francisco International Airport' avoiding tolls"));
static IEnumerable<AIFunction> CreateFunctionTools(AIAgent a2aAgent, AgentCard agentCard)
{
foreach (var skill in agentCard.Skills)
{
// A2A agent skills don't have schemas describing the expected shape of their inputs and outputs.
// Schemas can be beneficial for AI models to better understand the skill's contract, generate
// the skill's input accordingly and to know what to expect in the skill's output.
// However, the A2A specification defines properties such as name, description, tags, examples,
// inputModes, and outputModes to provide context about the skill's purpose, capabilities, usage,
// and supported MIME types. These properties are added to the function tool description to help
// the model determine the appropriate shape of the skill's input and output.
AIFunctionFactoryOptions options = new()
{
Name = FunctionNameSanitizer.Sanitize(skill.Name),
Description = $$"""
{
"description": "{{skill.Description}}",
"tags": "[{{string.Join(", ", skill.Tags ?? [])}}]",
"examples": "[{{string.Join(", ", skill.Examples ?? [])}}]",
"inputModes": "[{{string.Join(", ", skill.InputModes ?? [])}}]",
"outputModes": "[{{string.Join(", ", skill.OutputModes ?? [])}}]"
}
""",
};
yield return AIFunctionFactory.Create(RunAgentAsync, options);
}
async Task<string> RunAgentAsync(string input, CancellationToken cancellationToken)
{
var response = await a2aAgent.RunAsync(input, cancellationToken: cancellationToken).ConfigureAwait(false);
return response.Text;
}
}
internal static partial class FunctionNameSanitizer
{
public static string Sanitize(string name)
{
return InvalidNameCharsRegex().Replace(name, "_");
}
[GeneratedRegex("[^0-9A-Za-z]+")]
private static partial Regex InvalidNameCharsRegex();
}
@@ -0,0 +1,22 @@
# A2A Agent as Function Tools
This sample demonstrates how to represent an A2A agent as a set of function tools, where each function tool corresponds to a skill of the A2A agent,
and register these function tools with another AI agent so it can leverage the A2A agent's skills.
# Prerequisites
Before you begin, ensure you have the following prerequisites:
- .NET 10 SDK or later
- Access to the A2A agent host service
**Note**: These samples need to be run against a valid A2A server. If no A2A server is available, they can be run against the echo-agent that can be
spun up locally by following the guidelines at: https://github.com/a2aproject/a2a-dotnet/blob/main/samples/AgentServer/README.md
Set the following environment variables:
```powershell
$env:A2A_AGENT_HOST="https://your-a2a-agent-host" # Replace with your A2A agent host endpoint
$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini" # Optional, defaults to gpt-5.4-mini
```
@@ -0,0 +1,23 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="A2A" />
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
<PackageReference Include="Microsoft.Extensions.Hosting" />
</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" />
</ItemGroup>
</Project>
@@ -0,0 +1,35 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample demonstrates how to poll for long-running task completion using continuation tokens with an A2A AI agent.
using A2A;
using Microsoft.Agents.AI;
var a2aAgentHost = Environment.GetEnvironmentVariable("A2A_AGENT_HOST") ?? throw new InvalidOperationException("A2A_AGENT_HOST is not set.");
// Initialize an A2ACardResolver to get an A2A agent card.
A2ACardResolver agentCardResolver = new(new Uri(a2aAgentHost));
// Get the agent card
AgentCard agentCard = await agentCardResolver.GetAgentCardAsync();
// Create an instance of the AIAgent for an existing A2A agent specified by the agent card.
AIAgent agent = agentCard.AsAIAgent();
AgentSession session = await agent.CreateSessionAsync();
// Start the initial run with a long-running task.
AgentResponse response = await agent.RunAsync("Conduct a comprehensive analysis of quantum computing applications in cryptography, including recent breakthroughs, implementation challenges, and future roadmap. Please include diagrams and visual representations to illustrate complex concepts.", session);
// Poll until the response is complete.
while (response.ContinuationToken is { } token)
{
// Wait before polling again.
await Task.Delay(TimeSpan.FromSeconds(2));
// Continue with the token.
response = await agent.RunAsync(session, options: new AgentRunOptions { ContinuationToken = token });
}
// Display the result
Console.WriteLine(response);
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# Polling for A2A Agent Task Completion
This sample demonstrates how to poll for long-running task completion using continuation tokens with an A2A AI agent, following the background responses pattern.
The sample:
- Connects to an A2A agent server specified in the `A2A_AGENT_HOST` environment variable
- Sends a request to the agent that may take time to complete
- Polls the agent at regular intervals using continuation tokens until a final response is received
- Displays the final result
This pattern is useful when an AI model cannot complete a complex task in a single response and needs multiple rounds of processing.
# Prerequisites
Before you begin, ensure you have the following prerequisites:
- .NET 10.0 SDK or later
- An A2A agent server running and accessible via HTTP
Set the following environment variable:
```powershell
$env:A2A_AGENT_HOST="http://localhost:5000" # Replace with your A2A agent server host
```
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# Agent-to-Agent (A2A) Samples
These samples demonstrate how to work with Agent-to-Agent (A2A) specific features in the Agent Framework.
For other samples that demonstrate how to use AIAgent instances,
see the [Getting Started With Agents](../../02-agents/Agents/README.md) samples.
## Prerequisites
See the README.md for each sample for the prerequisites for that sample.
## Samples
|Sample|Description|
|---|---|
|[A2A Agent As Function Tools](./A2AAgent_AsFunctionTools/)|This sample demonstrates how to represent an A2A agent as a set of function tools, where each function tool corresponds to a skill of the A2A agent, and register these function tools with another AI agent so it can leverage the A2A agent's skills.|
|[A2A Agent Polling For Task Completion](./A2AAgent_PollingForTaskCompletion/)|This sample demonstrates how to poll for long-running task completion using continuation tokens with an A2A agent.|
## Running the samples from the console
To run the samples, navigate to the desired sample directory, e.g.
```powershell
cd A2AAgent_AsFunctionTools
```
Set the required environment variables as documented in the sample readme.
If the variables are not set, you will be prompted for the values when running the samples.
Execute the following command to build the sample:
```powershell
dotnet build
```
Execute the following command to run the sample:
```powershell
dotnet run --no-build
```
Or just build and run in one step:
```powershell
dotnet run
```
## Running the samples from Visual Studio
Open the solution in Visual Studio and set the desired sample project as the startup project. Then, run the project using the built-in debugger or by pressing `F5`.
You will be prompted for any required environment variables if they are not already set.