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@@ -0,0 +1,42 @@
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<Project Sdk="Microsoft.NET.Sdk">
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<PropertyGroup>
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<TargetFrameworks>net10.0</TargetFrameworks>
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<AzureFunctionsVersion>v4</AzureFunctionsVersion>
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<OutputType>Exe</OutputType>
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<ImplicitUsings>enable</ImplicitUsings>
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<Nullable>enable</Nullable>
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<!-- The Functions build tools don't like namespaces that start with a number -->
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<AssemblyName>AgentOrchestration_Concurrency</AssemblyName>
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<RootNamespace>AgentOrchestration_Concurrency</RootNamespace>
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</PropertyGroup>
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<ItemGroup>
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<FrameworkReference Include="Microsoft.AspNetCore.App" />
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</ItemGroup>
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<!-- Azure Functions packages -->
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<ItemGroup>
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<PackageReference Include="Microsoft.Azure.Functions.Worker" />
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<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
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<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
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<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
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<PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
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</ItemGroup>
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<ItemGroup>
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<PackageReference Include="Azure.AI.OpenAI" />
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<PackageReference Include="Azure.Identity" />
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</ItemGroup>
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<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
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<!--
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<ItemGroup>
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<PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
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<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
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</ItemGroup>
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-->
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<ItemGroup>
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<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
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<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
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</ItemGroup>
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</Project>
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@@ -0,0 +1,116 @@
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// Copyright (c) Microsoft. All rights reserved.
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using System.Net;
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using System.Text.Json;
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using Microsoft.Agents.AI;
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using Microsoft.Agents.AI.DurableTask;
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using Microsoft.Azure.Functions.Worker;
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using Microsoft.Azure.Functions.Worker.Http;
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using Microsoft.DurableTask;
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using Microsoft.DurableTask.Client;
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namespace AgentOrchestration_Concurrency;
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public static class FunctionsTriggers
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{
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public sealed record TextResponse(string Text);
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[Function(nameof(RunOrchestrationAsync))]
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public static async Task<object> RunOrchestrationAsync([OrchestrationTrigger] TaskOrchestrationContext context)
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{
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// Get the prompt from the orchestration input
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string prompt = context.GetInput<string>() ?? throw new InvalidOperationException("Prompt is required");
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// Get both agents
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DurableAIAgent physicist = context.GetAgent("PhysicistAgent");
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DurableAIAgent chemist = context.GetAgent("ChemistAgent");
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// Start both agent runs concurrently
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Task<AgentResponse<TextResponse>> physicistTask = physicist.RunAsync<TextResponse>(prompt);
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Task<AgentResponse<TextResponse>> chemistTask = chemist.RunAsync<TextResponse>(prompt);
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// Wait for both tasks to complete using Task.WhenAll
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await Task.WhenAll(physicistTask, chemistTask);
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// Get the results
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TextResponse physicistResponse = (await physicistTask).Result;
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TextResponse chemistResponse = (await chemistTask).Result;
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// Return the result as a structured, anonymous type
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return new
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{
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physicist = physicistResponse.Text,
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chemist = chemistResponse.Text,
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};
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}
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// POST /multiagent/run
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[Function(nameof(StartOrchestrationAsync))]
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public static async Task<HttpResponseData> StartOrchestrationAsync(
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[HttpTrigger(AuthorizationLevel.Anonymous, "post", Route = "multiagent/run")] HttpRequestData req,
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[DurableClient] DurableTaskClient client)
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{
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// Read the prompt from the request body
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string? prompt = await req.ReadAsStringAsync();
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if (string.IsNullOrWhiteSpace(prompt))
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{
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HttpResponseData badRequestResponse = req.CreateResponse(HttpStatusCode.BadRequest);
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await badRequestResponse.WriteAsJsonAsync(new { error = "Prompt is required" });
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return badRequestResponse;
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}
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string instanceId = await client.ScheduleNewOrchestrationInstanceAsync(
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orchestratorName: nameof(RunOrchestrationAsync),
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input: prompt);
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HttpResponseData response = req.CreateResponse(HttpStatusCode.Accepted);
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await response.WriteAsJsonAsync(new
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{
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message = "Multi-agent concurrent orchestration started.",
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prompt,
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instanceId,
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statusQueryGetUri = GetStatusQueryGetUri(req, instanceId),
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});
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return response;
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}
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// GET /multiagent/status/{instanceId}
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[Function(nameof(GetOrchestrationStatusAsync))]
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public static async Task<HttpResponseData> GetOrchestrationStatusAsync(
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[HttpTrigger(AuthorizationLevel.Anonymous, "get", Route = "multiagent/status/{instanceId}")] HttpRequestData req,
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string instanceId,
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[DurableClient] DurableTaskClient client)
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{
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OrchestrationMetadata? status = await client.GetInstanceAsync(
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instanceId,
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getInputsAndOutputs: true,
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req.FunctionContext.CancellationToken);
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if (status is null)
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{
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HttpResponseData notFound = req.CreateResponse(HttpStatusCode.NotFound);
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await notFound.WriteAsJsonAsync(new { error = "Instance not found" });
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return notFound;
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}
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HttpResponseData response = req.CreateResponse(HttpStatusCode.OK);
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await response.WriteAsJsonAsync(new
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{
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instanceId = status.InstanceId,
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runtimeStatus = status.RuntimeStatus.ToString(),
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input = status.SerializedInput is not null ? (object)status.ReadInputAs<JsonElement>() : null,
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output = status.SerializedOutput is not null ? (object)status.ReadOutputAs<JsonElement>() : null,
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failureDetails = status.FailureDetails
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});
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return response;
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}
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private static string GetStatusQueryGetUri(HttpRequestData req, string instanceId)
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{
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// NOTE: This can be made more robust by considering the value of
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// request headers like "X-Forwarded-Host" and "X-Forwarded-Proto".
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string authority = $"{req.Url.Scheme}://{req.Url.Authority}";
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return $"{authority}/api/multiagent/status/{instanceId}";
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}
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}
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@@ -0,0 +1,45 @@
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// Copyright (c) Microsoft. All rights reserved.
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using Azure;
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using Azure.AI.OpenAI;
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using Azure.Identity;
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using Microsoft.Agents.AI;
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using Microsoft.Agents.AI.Hosting.AzureFunctions;
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using Microsoft.Azure.Functions.Worker.Builder;
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using Microsoft.Extensions.Hosting;
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using OpenAI.Chat;
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// Get the Azure OpenAI endpoint and deployment name from environment variables.
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string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
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?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
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string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
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?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
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// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
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string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
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AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
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? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
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: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
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// Two agents used by the orchestration to demonstrate concurrent execution.
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const string PhysicistName = "PhysicistAgent";
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const string PhysicistInstructions = "You are an expert in physics. You answer questions from a physics perspective.";
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const string ChemistName = "ChemistAgent";
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const string ChemistInstructions = "You are an expert in chemistry. You answer questions from a chemistry perspective.";
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AIAgent physicistAgent = client.GetChatClient(deploymentName).AsAIAgent(PhysicistInstructions, PhysicistName);
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AIAgent chemistAgent = client.GetChatClient(deploymentName).AsAIAgent(ChemistInstructions, ChemistName);
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using IHost app = FunctionsApplication
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.CreateBuilder(args)
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.ConfigureFunctionsWebApplication()
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.ConfigureDurableAgents(options =>
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{
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options
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.AddAIAgent(physicistAgent)
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.AddAIAgent(chemistAgent);
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})
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.Build();
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app.Run();
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@@ -0,0 +1,65 @@
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# Multi-Agent Concurrent Orchestration Sample
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This sample demonstrates how to use the Durable Agent Framework (DAFx) to create an Azure Functions app that orchestrates concurrent execution of multiple AI agents, each with specialized expertise, to provide comprehensive answers to complex questions.
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## Key Concepts Demonstrated
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- Multi-agent orchestration with specialized AI agents (physics and chemistry)
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- Concurrent execution using the fan-out/fan-in pattern for improved performance and distributed processing
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- Response aggregation from multiple agents into a unified result
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- Durable orchestration with automatic checkpointing and resumption from failures
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## Environment Setup
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See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
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## Running the Sample
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With the environment setup and function app running, you can test the sample by sending an HTTP request with a custom prompt to the orchestration.
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You can use the `demo.http` file to send a message to the agents, or a command line tool like `curl` as shown below:
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Bash (Linux/macOS/WSL):
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```bash
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curl -X POST http://localhost:7071/api/multiagent/run \
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-H "Content-Type: text/plain" \
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-d "What is temperature?"
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```
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PowerShell:
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```powershell
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Invoke-RestMethod -Method Post `
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-Uri http://localhost:7071/api/multiagent/run `
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-ContentType text/plain `
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-Body "What is temperature?"
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```
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The response will be a JSON object that looks something like the following, which indicates that the orchestration has started.
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```json
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{
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"message": "Multi-agent concurrent orchestration started.",
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"prompt": "What is temperature?",
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"instanceId": "e7e29999b6b8424682b3539292afc9ed",
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"statusQueryGetUri": "http://localhost:7071/api/multiagent/status/e7e29999b6b8424682b3539292afc9ed"
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}
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```
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The orchestration will run both the PhysicistAgent and ChemistAgent concurrently, asking them the same question. Their responses will be combined to provide a comprehensive answer covering both physical and chemical aspects.
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Once the orchestration has completed, you can get the status of the orchestration by sending a GET request to the `statusQueryGetUri` URL. The response will be a JSON object that looks something like the following:
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```json
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{
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"failureDetails": null,
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"input": "What is temperature?",
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"instanceId": "e7e29999b6b8424682b3539292afc9ed",
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"output": {
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"physicist": "Temperature is a measure of the average kinetic energy of particles in a system. From a physics perspective, it represents the thermal energy and determines the direction of heat flow between objects.",
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"chemist": "From a chemistry perspective, temperature is crucial for chemical reactions as it affects reaction rates through the Arrhenius equation. It influences the equilibrium position of reversible reactions and determines the physical state of substances."
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},
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"runtimeStatus": "Completed"
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||||
}
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```
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@@ -0,0 +1,5 @@
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||||
### Start the multi-agent concurrent orchestration
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POST http://localhost:7071/api/multiagent/run
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Content-Type: text/plain
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What is temperature?
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@@ -0,0 +1,20 @@
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||||
{
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||||
"version": "2.0",
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"logging": {
|
||||
"logLevel": {
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"Microsoft.Agents.AI.DurableTask": "Information",
|
||||
"Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
|
||||
"DurableTask": "Information",
|
||||
"Microsoft.DurableTask": "Information"
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||||
}
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||||
},
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||||
"extensions": {
|
||||
"durableTask": {
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||||
"hubName": "default",
|
||||
"storageProvider": {
|
||||
"type": "AzureManaged",
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||||
"connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
|
||||
}
|
||||
}
|
||||
}
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||||
}
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||||
@@ -0,0 +1,10 @@
|
||||
{
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||||
"IsEncrypted": false,
|
||||
"Values": {
|
||||
"FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated",
|
||||
"AzureWebJobsStorage": "UseDevelopmentStorage=true",
|
||||
"DURABLE_TASK_SCHEDULER_CONNECTION_STRING": "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None",
|
||||
"AZURE_OPENAI_ENDPOINT": "<AZURE_OPENAI_ENDPOINT>",
|
||||
"AZURE_OPENAI_DEPLOYMENT": "<AZURE_OPENAI_DEPLOYMENT>"
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user