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// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json;
using System.Text.Json.Serialization;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Workflows;
using Microsoft.Agents.AI.Workflows.Reflection;
using Microsoft.Extensions.AI;
namespace WorkflowMultiSelectionSample;
/// <summary>
/// This sample introduces multi-selection routing where one executor can trigger multiple downstream executors.
///
/// Extending the switch-case pattern from the previous sample, the workflow can now
/// trigger multiple executors simultaneously when certain conditions are met.
///
/// Key features:
/// - For legitimate emails: triggers Email Assistant (always) + Email Summary (if email is long)
/// - For spam emails: triggers Handle Spam executor only
/// - For uncertain emails: triggers Handle Uncertain executor only
/// - Database logging happens for both short emails and summarized long emails
///
/// This pattern is powerful for workflows that need parallel processing based on data characteristics,
/// such as triggering different analytics pipelines or multiple notification systems.
/// </summary>
/// <remarks>
/// Pre-requisites:
/// - Foundational samples should be completed first.
/// - Shared state is used in this sample to persist email data between executors.
/// - An Azure OpenAI chat completion deployment that supports structured outputs must be configured.
/// </remarks>
public static class Program
{
private const int LongEmailThreshold = 100;
private static async Task Main()
{
// Set up the Azure OpenAI client
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 chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential()).GetChatClient(deploymentName).AsIChatClient();
// Create agents
AIAgent emailAnalysisAgent = GetEmailAnalysisAgent(chatClient);
AIAgent emailAssistantAgent = GetEmailAssistantAgent(chatClient);
AIAgent emailSummaryAgent = GetEmailSummaryAgent(chatClient);
// Create executors
var emailAnalysisExecutor = new EmailAnalysisExecutor(emailAnalysisAgent);
var emailAssistantExecutor = new EmailAssistantExecutor(emailAssistantAgent);
var emailSummaryExecutor = new EmailSummaryExecutor(emailSummaryAgent);
var sendEmailExecutor = new SendEmailExecutor();
var handleSpamExecutor = new HandleSpamExecutor();
var handleUncertainExecutor = new HandleUncertainExecutor();
var databaseAccessExecutor = new DatabaseAccessExecutor();
// Build the workflow by adding executors and connecting them
WorkflowBuilder builder = new(emailAnalysisExecutor);
builder.AddFanOutEdge(
emailAnalysisExecutor,
targets: [
handleSpamExecutor,
emailAssistantExecutor,
emailSummaryExecutor,
handleUncertainExecutor,
],
partitioner: GetPartitioner()
)
// After the email assistant writes a response, it will be sent to the send email executor
.AddEdge(emailAssistantExecutor, sendEmailExecutor)
// Save the analysis result to the database if summary is not needed
.AddEdge<AnalysisResult>(
emailAnalysisExecutor,
databaseAccessExecutor,
condition: analysisResult => analysisResult?.EmailLength <= LongEmailThreshold)
// Save the analysis result to the database with summary
.AddEdge(emailSummaryExecutor, databaseAccessExecutor)
.WithOutputFrom(handleUncertainExecutor, handleSpamExecutor, sendEmailExecutor);
var workflow = builder.Build();
// Read a email from a text file
string email = Resources.Read("email.txt");
// Execute the workflow
StreamingRun run = await InProcessExecution.StreamAsync(workflow, new ChatMessage(ChatRole.User, email));
await run.TrySendMessageAsync(new TurnToken(emitEvents: true));
await foreach (WorkflowEvent evt in run.WatchStreamAsync().ConfigureAwait(false))
{
if (evt is WorkflowOutputEvent outputEvent)
{
Console.WriteLine($"{outputEvent}");
}
if (evt is DatabaseEvent databaseEvent)
{
Console.WriteLine($"{databaseEvent}");
}
}
}
/// <summary>
/// Creates a partitioner for routing messages based on the analysis result.
/// </summary>
/// <returns>A function that takes an analysis result and returns the target partitions.</returns>
private static Func<AnalysisResult?, int, IEnumerable<int>> GetPartitioner()
{
return (analysisResult, targetCount) =>
{
if (analysisResult is not null)
{
if (analysisResult.spamDecision == SpamDecision.Spam)
{
return [0]; // Route to spam handler
}
else if (analysisResult.spamDecision == SpamDecision.NotSpam)
{
List<int> targets = [1]; // Route to the email assistant
if (analysisResult.EmailLength > LongEmailThreshold)
{
targets.Add(2); // Route to the email summarizer too
}
return targets;
}
else
{
return [3];
}
}
throw new InvalidOperationException("Invalid analysis result.");
};
}
/// <summary>
/// Create an email analysis agent.
/// </summary>
/// <returns>A ChatClientAgent configured for email analysis</returns>
private static ChatClientAgent GetEmailAnalysisAgent(IChatClient chatClient) =>
new(chatClient, new ChatClientAgentOptions(instructions: "You are a spam detection assistant that identifies spam emails.")
{
ChatOptions = new()
{
ResponseFormat = ChatResponseFormat.ForJsonSchema<AnalysisResult>()
}
});
/// <summary>
/// Creates an email assistant agent.
/// </summary>
/// <returns>A ChatClientAgent configured for email assistance</returns>
private static ChatClientAgent GetEmailAssistantAgent(IChatClient chatClient) =>
new(chatClient, new ChatClientAgentOptions(instructions: "You are an email assistant that helps users draft responses to emails with professionalism.")
{
ChatOptions = new()
{
ResponseFormat = ChatResponseFormat.ForJsonSchema<EmailResponse>()
}
});
/// <summary>
/// Creates an agent that summarizes emails.
/// </summary>
/// <returns>A ChatClientAgent configured for email summarization</returns>
private static ChatClientAgent GetEmailSummaryAgent(IChatClient chatClient) =>
new(chatClient, new ChatClientAgentOptions(instructions: "You are an assistant that helps users summarize emails.")
{
ChatOptions = new()
{
ResponseFormat = ChatResponseFormat.ForJsonSchema<EmailSummary>()
}
});
}
internal static class EmailStateConstants
{
public const string EmailStateScope = "EmailState";
}
/// <summary>
/// Represents the possible decisions for spam detection.
/// </summary>
public enum SpamDecision
{
NotSpam,
Spam,
Uncertain
}
/// <summary>
/// Represents the result of email analysis.
/// </summary>
public sealed class AnalysisResult
{
[JsonPropertyName("spam_decision")]
[JsonConverter(typeof(JsonStringEnumConverter))]
public SpamDecision spamDecision { get; set; }
[JsonPropertyName("reason")]
public string Reason { get; set; } = string.Empty;
[JsonIgnore]
public int EmailLength { get; set; }
[JsonIgnore]
public string EmailSummary { get; set; } = string.Empty;
[JsonIgnore]
public string EmailId { get; set; } = string.Empty;
}
/// <summary>
/// Represents an email.
/// </summary>
internal sealed class Email
{
[JsonPropertyName("email_id")]
public string EmailId { get; set; } = string.Empty;
[JsonPropertyName("email_content")]
public string EmailContent { get; set; } = string.Empty;
}
/// <summary>
/// Executor that analyzes emails using an AI agent.
/// </summary>
internal sealed class EmailAnalysisExecutor : ReflectingExecutor<EmailAnalysisExecutor>, IMessageHandler<ChatMessage, AnalysisResult>
{
private readonly AIAgent _emailAnalysisAgent;
/// <summary>
/// Creates a new instance of the <see cref="EmailAnalysisExecutor"/> class.
/// </summary>
/// <param name="emailAnalysisAgent">The AI agent used for email analysis</param>
public EmailAnalysisExecutor(AIAgent emailAnalysisAgent) : base("EmailAnalysisExecutor")
{
this._emailAnalysisAgent = emailAnalysisAgent;
}
public async ValueTask<AnalysisResult> HandleAsync(ChatMessage message, IWorkflowContext context)
{
// Generate a random email ID and store the email content
var newEmail = new Email
{
EmailId = Guid.NewGuid().ToString("N"),
EmailContent = message.Text
};
await context.QueueStateUpdateAsync(newEmail.EmailId, newEmail, scopeName: EmailStateConstants.EmailStateScope);
// Invoke the agent
var response = await this._emailAnalysisAgent.RunAsync(message);
var AnalysisResult = JsonSerializer.Deserialize<AnalysisResult>(response.Text);
AnalysisResult!.EmailId = newEmail.EmailId;
AnalysisResult!.EmailLength = newEmail.EmailContent.Length;
return AnalysisResult;
}
}
/// <summary>
/// Represents the response from the email assistant.
/// </summary>
public sealed class EmailResponse
{
[JsonPropertyName("response")]
public string Response { get; set; } = string.Empty;
}
/// <summary>
/// Executor that assists with email responses using an AI agent.
/// </summary>
internal sealed class EmailAssistantExecutor : ReflectingExecutor<EmailAssistantExecutor>, IMessageHandler<AnalysisResult, EmailResponse>
{
private readonly AIAgent _emailAssistantAgent;
/// <summary>
/// Creates a new instance of the <see cref="EmailAssistantExecutor"/> class.
/// </summary>
/// <param name="emailAssistantAgent">The AI agent used for email assistance</param>
public EmailAssistantExecutor(AIAgent emailAssistantAgent) : base("EmailAssistantExecutor")
{
this._emailAssistantAgent = emailAssistantAgent;
}
public async ValueTask<EmailResponse> HandleAsync(AnalysisResult message, IWorkflowContext context)
{
if (message.spamDecision == SpamDecision.Spam)
{
throw new InvalidOperationException("This executor should only handle non-spam messages.");
}
// Retrieve the email content from the context
var email = await context.ReadStateAsync<Email>(message.EmailId, scopeName: EmailStateConstants.EmailStateScope);
// Invoke the agent
var response = await this._emailAssistantAgent.RunAsync(email!.EmailContent);
var emailResponse = JsonSerializer.Deserialize<EmailResponse>(response.Text);
return emailResponse!;
}
}
/// <summary>
/// Executor that sends emails.
/// </summary>
internal sealed class SendEmailExecutor() : ReflectingExecutor<SendEmailExecutor>("SendEmailExecutor"), IMessageHandler<EmailResponse>
{
/// <summary>
/// Simulate the sending of an email.
/// </summary>
public async ValueTask HandleAsync(EmailResponse message, IWorkflowContext context) =>
await context.YieldOutputAsync($"Email sent: {message.Response}");
}
/// <summary>
/// Executor that handles spam messages.
/// </summary>
internal sealed class HandleSpamExecutor() : ReflectingExecutor<HandleSpamExecutor>("HandleSpamExecutor"), IMessageHandler<AnalysisResult>
{
/// <summary>
/// Simulate the handling of a spam message.
/// </summary>
public async ValueTask HandleAsync(AnalysisResult message, IWorkflowContext context)
{
if (message.spamDecision == SpamDecision.Spam)
{
await context.YieldOutputAsync($"Email marked as spam: {message.Reason}");
}
else
{
throw new InvalidOperationException("This executor should only handle spam messages.");
}
}
}
/// <summary>
/// Executor that handles uncertain messages.
/// </summary>
internal sealed class HandleUncertainExecutor() : ReflectingExecutor<HandleUncertainExecutor>("HandleUncertainExecutor"), IMessageHandler<AnalysisResult>
{
/// <summary>
/// Simulate the handling of an uncertain spam decision.
/// </summary>
public async ValueTask HandleAsync(AnalysisResult message, IWorkflowContext context)
{
if (message.spamDecision == SpamDecision.Uncertain)
{
var email = await context.ReadStateAsync<Email>(message.EmailId, scopeName: EmailStateConstants.EmailStateScope);
await context.YieldOutputAsync($"Email marked as uncertain: {message.Reason}. Email content: {email?.EmailContent}");
}
else
{
throw new InvalidOperationException("This executor should only handle uncertain spam decisions.");
}
}
}
/// <summary>
/// Represents the response from the email summary agent.
/// </summary>
public sealed class EmailSummary
{
[JsonPropertyName("summary")]
public string Summary { get; set; } = string.Empty;
}
/// <summary>
/// Executor that summarizes emails using an AI agent.
/// </summary>
internal sealed class EmailSummaryExecutor : ReflectingExecutor<EmailSummaryExecutor>, IMessageHandler<AnalysisResult, AnalysisResult>
{
private readonly AIAgent _emailSummaryAgent;
/// <summary>
/// Creates a new instance of the <see cref="EmailSummaryExecutor"/> class.
/// </summary>
/// <param name="emailSummaryAgent">The AI agent used for email summarization</param>
public EmailSummaryExecutor(AIAgent emailSummaryAgent) : base("EmailSummaryExecutor")
{
this._emailSummaryAgent = emailSummaryAgent;
}
public async ValueTask<AnalysisResult> HandleAsync(AnalysisResult message, IWorkflowContext context)
{
// Read the email content from the shared states
var email = await context.ReadStateAsync<Email>(message.EmailId, scopeName: EmailStateConstants.EmailStateScope);
// Invoke the agent
var response = await this._emailSummaryAgent.RunAsync(email!.EmailContent);
var emailSummary = JsonSerializer.Deserialize<EmailSummary>(response.Text);
message.EmailSummary = emailSummary!.Summary;
return message;
}
}
/// <summary>
/// A custom workflow event for database operations.
/// </summary>
/// <param name="message">The message associated with the event</param>
internal sealed class DatabaseEvent(string message) : WorkflowEvent(message) { }
/// <summary>
/// Executor that handles database access.
/// </summary>
internal sealed class DatabaseAccessExecutor() : ReflectingExecutor<DatabaseAccessExecutor>("DatabaseAccessExecutor"), IMessageHandler<AnalysisResult>
{
public async ValueTask HandleAsync(AnalysisResult message, IWorkflowContext context)
{
// 1. Save the email content
await context.ReadStateAsync<Email>(message.EmailId, scopeName: EmailStateConstants.EmailStateScope);
await Task.Delay(100); // Simulate database access delay
// 2. Save the analysis result
await Task.Delay(100); // Simulate database access delay
// Not using the `WorkflowCompletedEvent` because this is not the end of the workflow.
// The end of the workflow is signaled by the `SendEmailExecutor` or the `HandleUnknownExecutor`.
await context.AddEventAsync(new DatabaseEvent($"Email {message.EmailId} saved to database."));
}
}