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Extensions, integrations, and deployment options for AutoGen .NET applications.

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Microsoft.Extensions.AI Integration

Microsoft.Extensions.AI chat client interface.
using Microsoft.Extensions.AI;
using Microsoft.Extensions.DependencyInjection;

var services = new ServiceCollection();

// Add OpenAI chat client
services.AddChatClient(builder => builder
    .UseOpenAI("gpt-4", apiKey));

var chatClient = services.BuildServiceProvider()
    .GetRequiredService<IChatClient>();

// Use with InferenceAgent
var agent = new InferenceAgent<TaskMessage>(
    id,
    runtime,
    "Assistant",
    logger,
    chatClient
);
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GetResponseAsync
Task<ChatResponse>
Generate a chat completion
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messages
IList<ChatMessage>
required
Conversation messages
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options
ChatOptions?
Generation options (temperature, max tokens, etc.)
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cancellationToken
CancellationToken
Cancellation token
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GetStreamingResponseAsync
IAsyncEnumerable<ChatResponseUpdate>
Stream chat completion updates
Configuration for chat completions.
var options = new ChatOptions
{
    Temperature = 0.7f,
    MaxTokens = 2000,
    TopP = 0.9f,
    FrequencyPenalty = 0.5f,
    PresencePenalty = 0.5f,
    StopSequences = new[] { "STOP", "END" },
    ModelId = "gpt-4"
};

var response = await chatClient.GetResponseAsync(messages, options);
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Temperature
float?
Sampling temperature (0.0 to 2.0)
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MaxTokens
int?
Maximum tokens in response
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TopP
float?
Nucleus sampling parameter
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FrequencyPenalty
float?
Frequency penalty (-2.0 to 2.0)
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PresencePenalty
float?
Presence penalty (-2.0 to 2.0)
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StopSequences
IList<string>?
Stop sequences
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ModelId
string?
Override model identifier
Message in a conversation.
using Microsoft.Extensions.AI;

var messages = new List<ChatMessage>
{
    new ChatMessage(ChatRole.System, "You are helpful."),
    new ChatMessage(ChatRole.User, "Hello!"),
    new ChatMessage(ChatRole.Assistant, "Hi! How can I help?"),
    new ChatMessage(ChatRole.User, "Tell me a joke.")
};
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Role
ChatRole
required
Message role (System, User, Assistant, Tool)
​
Content
string
required
Message content

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Semantic Kernel Integration

Integration with Semantic Kernel.
using Microsoft.AutoGen.Extensions.SemanticKernel;
using Microsoft.Extensions.DependencyInjection;
using Microsoft.SemanticKernel;

var builder = Host.CreateApplicationBuilder();

// Add Semantic Kernel
builder.Services.AddSemanticKernel()
    .AddOpenAIChatCompletion("gpt-4", apiKey);

// Add SK-powered agents
builder.Services.AddSemanticKernelAgents();

var host = builder.Build();
Configuration for Qdrant vector database.
using Microsoft.AutoGen.Extensions.SemanticKernel.Options;

builder.Services.Configure<QdrantOptions>(options =>
{
    options.Endpoint = "http://localhost:6333";
    options.ApiKey = "your-api-key";
    options.CollectionName = "agent_memory";
    options.VectorSize = 1536;
});
​
Endpoint
string
required
Qdrant server endpoint
​
ApiKey
string?
API key for authentication
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CollectionName
string
required
Collection name for vectors
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VectorSize
int
required
Dimension of embedding vectors

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Microsoft.Extensions.AI (MEAI)

Hosting extensions for Microsoft.Extensions.AI.
using Microsoft.AutoGen.Extensions.MEAI;
using Microsoft.Extensions.DependencyInjection;

var builder = Host.CreateApplicationBuilder();

// Configure chat completion services
builder.Services.AddChatClient(config =>
{
    config.UseOpenAI("gpt-4", apiKey);
    config.UseLogging();
    config.UseDistributedCaching();
});

var host = builder.Build();
Configuration for AI clients.
using Microsoft.AutoGen.Extensions.MEAI.Options;

builder.Services.Configure<AIClientOptions>(options =>
{
    options.Endpoint = "https://api.openai.com";
    options.ApiKey = "sk-...";
    options.DefaultModel = "gpt-4";
    options.Timeout = TimeSpan.FromSeconds(30);
    options.MaxRetries = 3;
});
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Endpoint
string
required
API endpoint URL
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ApiKey
string
required
API key for authentication
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DefaultModel
string
required
Default model identifier
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Timeout
TimeSpan
Request timeout
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MaxRetries
int
Maximum retry attempts
Extension methods for adding chat completion services.
services.AddChatCompletionClient<OpenAIChatClient>(config =>
{
    config.ApiKey = "sk-...";
    config.Model = "gpt-4";
});

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Aspire Integration

.NET Aspire integration for cloud-native deployment.
using Microsoft.AutoGen.Extensions.Aspire;

var builder = DistributedApplication.CreateBuilder(args);

// Add AutoGen runtime
var runtime = builder.AddAutoGenRuntime("runtime")
    .WithReplicas(3);

// Add agent services
builder.AddProject<Projects.WorkerAgents>("workers")
    .WithReference(runtime);

builder.AddProject<Projects.AgentGateway>("gateway")
    .WithReference(runtime)
    .WithExternalHttpEndpoints();

var app = builder.Build();
await app.RunAsync();
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AddAutoGenRuntime
method
Add AutoGen runtime to the application model
​
name
string
required
Runtime service name
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WithReplicas
method
Configure number of runtime replicas
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count
int
required
Number of replicas

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gRPC Runtime

Distributed runtime using gRPC for inter-process communication.
using Microsoft.AutoGen.Core.Grpc;

// Server side
var builder = WebApplication.CreateBuilder();
builder.Services.AddGrpc();
builder.Services.AddAutoGenGrpcRuntime();

var app = builder.Build();
app.MapGrpcService<GrpcGatewayService>();
await app.RunAsync();

// Client side
var channel = GrpcChannel.ForAddress("http://localhost:50051");
var runtime = new GrpcAgentRuntime(channel);

await runtime.SendMessageAsync(
    message: "Task",
    recipient: new AgentId("worker", "instance1")
);
Gateway service for gRPC-based agent communication.
using Microsoft.AutoGen.RuntimeGateway.Grpc;

var builder = WebApplication.CreateBuilder();
builder.Services.AddGrpcGateway();

var app = builder.Build();
app.MapGrpcGateway();
await app.RunAsync();
Extension methods for agent runtime.
using Microsoft.AutoGen.Core.Grpc;

// Send and wait for response
var result = await runtime.SendAndAwaitResponseAsync(
    message: request,
    recipient: agentId,
    timeout: TimeSpan.FromSeconds(30)
);

// Broadcast to all agents of a type
await runtime.BroadcastAsync(
    message: notification,
    agentType: "worker"
);

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Orleans Integration

Microsoft Orleans integration for distributed agents.
using Microsoft.AutoGen.RuntimeGateway.Grpc.Services.Orleans;

var builder = WebApplication.CreateBuilder();

builder.Services.AddOrleansAgentRuntime(siloBuilder =>
{
    siloBuilder.UseLocalhostClustering();
    siloBuilder.AddMemoryGrainStorage("PubSubStore");
});

var app = builder.Build();
await app.RunAsync();
Orleans grain for agent registry.
// Automatic registration via Orleans
// Tracks all active agents in the cluster

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Serialization

Protocol Buffers serialization for messages.
using Microsoft.AutoGen.Core.Grpc;

var serializer = new ProtobufMessageSerializer();

// Serialize
var bytes = serializer.Serialize(message);

// Deserialize
var message = serializer.Deserialize<TaskMessage>(bytes);
CloudEvents format support.
using Microsoft.AutoGen.Core.Grpc;

var cloudEvent = message.ToCloudEvent(
    source: "agent/worker",
    type: "autogen.task"
);

var message = cloudEvent.ToMessage<TaskMessage>();

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Example: Complete gRPC Setup

using Microsoft.AutoGen.Core;
using Microsoft.AutoGen.Core.Grpc;
using Microsoft.AutoGen.Contracts;
using Microsoft.Extensions.DependencyInjection;
using Microsoft.Extensions.Hosting;
using Grpc.Net.Client;

// Server (Gateway)
var serverBuilder = WebApplication.CreateBuilder();
serverBuilder.Services.AddGrpc();
serverBuilder.Services.AddAutoGenGrpcRuntime();

var server = serverBuilder.Build();
server.MapGrpcService<GrpcGatewayService>();
await server.StartAsync();

// Worker (Agent Host)
var workerBuilder = Host.CreateApplicationBuilder();
var channel = GrpcChannel.ForAddress("http://localhost:50051");
var runtime = new GrpcAgentRuntime(channel);

workerBuilder.Services.AddSingleton<IAgentRuntime>(runtime);
workerBuilder.Services.AddTransient<WorkerAgent>();

var worker = workerBuilder.Build();

await runtime.RegisterAgentFactoryAsync(
    new AgentType("worker"),
    async (id, rt) => new WorkerAgent(id, rt)
);

await worker.RunAsync();

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See Also

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