Files
agent-framework/dotnet/samples/GettingStarted/A2A/A2AAgent_AsFunctionTools/Program.cs
T

90 lines
4.1 KiB
C#

// 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-4o-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();
}