mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Update 2
This commit is contained in:
Roger Barreto
+1
@@ -15,6 +15,7 @@
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<ItemGroup>
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<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.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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-24
@@ -1,24 +0,0 @@
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<Project Sdk="Microsoft.NET.Sdk">
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<PropertyGroup>
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<OutputType>Exe</OutputType>
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<TargetFramework>net9.0</TargetFramework>
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<Nullable>enable</Nullable>
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<ImplicitUsings>enable</ImplicitUsings>
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<NoWarn>$(NoWarn);CA1812</NoWarn>
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</PropertyGroup>
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<ItemGroup>
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<PackageReference Include="Azure.AI.Agents" />
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<PackageReference Include="Azure.Identity" />
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<PackageReference Include="Microsoft.SemanticKernel.Connectors.InMemory" />
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<PackageReference Include="System.Linq.Async" />
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</ItemGroup>
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<ItemGroup>
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<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
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<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
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</ItemGroup>
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</Project>
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-156
@@ -1,156 +0,0 @@
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// Copyright (c) Microsoft. All rights reserved.
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#pragma warning disable CA1869 // Cache and reuse 'JsonSerializerOptions' instances
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// This sample shows how to create and use a simple AI agent with a conversation that can be persisted to a 3rd party storage.
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using System.Text.Json;
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using Azure.AI.Agents;
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using Azure.Identity;
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using Microsoft.Agents.AI;
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using Microsoft.Extensions.AI;
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using Microsoft.Extensions.VectorData;
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using Microsoft.SemanticKernel.Connectors.InMemory;
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using SampleApp;
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var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
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var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
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const string JokerInstructions = "You are good at telling jokes.";
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const string JokerName = "JokerAgent";
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// Create a vector store to store the chat messages in.
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// Replace this with a vector store implementation of your choice if you want to persist the chat history to disk.
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VectorStore vectorStore = new InMemoryVectorStore();
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// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
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var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
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AIAgent agent = await agentsClient.CreateAIAgentAsync(
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deploymentName,
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new ChatClientAgentOptions
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{
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Instructions = JokerInstructions,
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Name = JokerName,
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ChatMessageStoreFactory = ctx =>
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{
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// Create a new chat message store for this agent that stores the messages in a vector store.
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// Each thread must get its own copy of the VectorChatMessageStore, since the store
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// also contains the id that the thread is stored under.
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return new VectorChatMessageStore(vectorStore, ctx.SerializedState, ctx.JsonSerializerOptions);
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}
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});
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// Start a new thread for the agent conversation.
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AgentThread thread = agent.GetNewThread();
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// Run the agent with the thread that stores conversation history in the vector store.
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Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", thread));
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// Serialize the thread state, so it can be stored for later use.
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// Since the chat history is stored in the vector store, the serialized thread
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// only contains the guid that the messages are stored under in the vector store.
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JsonElement serializedThread = thread.Serialize();
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Console.WriteLine("\n--- Serialized thread ---\n");
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Console.WriteLine(JsonSerializer.Serialize(serializedThread, new JsonSerializerOptions { WriteIndented = true }));
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// The serialized thread can now be saved to a database, file, or any other storage mechanism
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// and loaded again later.
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// Deserialize the thread state after loading from storage.
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AgentThread resumedThread = agent.DeserializeThread(serializedThread);
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// Run the agent with the thread that stores conversation history in the vector store a second time.
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Console.WriteLine(await agent.RunAsync("Now tell the same joke in the voice of a pirate, and add some emojis to the joke.", resumedThread));
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// We can access the VectorChatMessageStore via the thread's GetService method if we need to read the key under which threads are stored.
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var messageStore = resumedThread.GetService<VectorChatMessageStore>()!;
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Console.WriteLine($"\nThread is stored in vector store under key: {messageStore.ThreadDbKey}");
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// Cleanup by agent name removes the agent version created.
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agentsClient.DeleteAgent(agent.Name);
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namespace SampleApp
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{
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/// <summary>
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/// A sample implementation of <see cref="ChatMessageStore"/> that stores chat messages in a vector store.
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/// </summary>
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internal sealed class VectorChatMessageStore : ChatMessageStore
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{
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private readonly VectorStore _vectorStore;
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public VectorChatMessageStore(VectorStore vectorStore, JsonElement serializedStoreState, JsonSerializerOptions? jsonSerializerOptions = null)
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{
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this._vectorStore = vectorStore ?? throw new ArgumentNullException(nameof(vectorStore));
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if (serializedStoreState.ValueKind is JsonValueKind.String)
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{
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// Here we can deserialize the thread id so that we can access the same messages as before the suspension.
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this.ThreadDbKey = serializedStoreState.Deserialize<string>();
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}
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}
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public string? ThreadDbKey { get; private set; }
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public override async Task AddMessagesAsync(IEnumerable<ChatMessage> messages, CancellationToken cancellationToken = default)
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{
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this.ThreadDbKey ??= Guid.NewGuid().ToString("N");
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var collection = this._vectorStore.GetCollection<string, ChatHistoryItem>("ChatHistory");
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await collection.EnsureCollectionExistsAsync(cancellationToken);
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await collection.UpsertAsync(messages.Select(x => new ChatHistoryItem()
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{
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Key = this.ThreadDbKey + x.MessageId,
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Timestamp = DateTimeOffset.UtcNow,
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ThreadId = this.ThreadDbKey,
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SerializedMessage = JsonSerializer.Serialize(x),
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MessageText = x.Text
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}), cancellationToken);
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}
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public override async Task<IEnumerable<ChatMessage>> GetMessagesAsync(CancellationToken cancellationToken = default)
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{
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var collection = this._vectorStore.GetCollection<string, ChatHistoryItem>("ChatHistory");
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await collection.EnsureCollectionExistsAsync(cancellationToken);
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var records = await collection
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.GetAsync(
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x => x.ThreadId == this.ThreadDbKey, 10,
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new() { OrderBy = x => x.Descending(y => y.Timestamp) },
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cancellationToken)
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.ToListAsync(cancellationToken);
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var messages = records.ConvertAll(x => JsonSerializer.Deserialize<ChatMessage>(x.SerializedMessage!)!)
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;
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messages.Reverse();
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return messages;
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}
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public override JsonElement Serialize(JsonSerializerOptions? jsonSerializerOptions = null) =>
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// We have to serialize the thread id, so that on deserialization we can retrieve the messages using the same thread id.
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JsonSerializer.SerializeToElement(this.ThreadDbKey);
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/// <summary>
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/// The data structure used to store chat history items in the vector store.
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/// </summary>
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private sealed class ChatHistoryItem
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{
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[VectorStoreKey]
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public string? Key { get; set; }
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[VectorStoreData]
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public string? ThreadId { get; set; }
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[VectorStoreData]
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public DateTimeOffset? Timestamp { get; set; }
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[VectorStoreData]
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public string? SerializedMessage { get; set; }
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[VectorStoreData]
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public string? MessageText { get; set; }
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}
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}
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}
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+1
-7
@@ -32,13 +32,7 @@ using var tracerProvider = tracerProviderBuilder.Build();
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var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
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// Define the agent you want to create. (Prompt Agent in this case)
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var agentDefinition = new PromptAgentDefinition(model: deploymentName) { Instructions = JokerInstructions };
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// Create a server side agent version with the Azure.AI.Agents SDK client.
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var agentVersion = agentsClient.CreateAgentVersion(agentName: JokerName, definition: agentDefinition);
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// Retrieve an AIAgent for the created server side agent version.
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AIAgent agent = agentsClient.GetAIAgent(agentVersion)
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AIAgent agent = agentsClient.CreateAIAgent(name: JokerName, model: deploymentName, instructions: JokerInstructions)
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.AsBuilder()
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.UseOpenTelemetry(sourceName: sourceName)
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.Build();
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+4
-8
@@ -20,16 +20,12 @@ const string JokerName = "JokerAgent";
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HostApplicationBuilder builder = Host.CreateApplicationBuilder(args);
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// Add the agents client to the service collection.
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builder.Services.AddSingleton<AgentsClient>((sp) => new AgentsClient(new Uri(endpoint), new AzureCliCredential()));
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builder.Services.AddSingleton((sp) => new AgentsClient(new Uri(endpoint), new AzureCliCredential()));
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// Add the AI agent to the service collection.
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builder.Services.AddSingleton<AIAgent>((sp) =>
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{
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var agentsClient = sp.GetRequiredService<AgentsClient>();
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var agentDefinition = new PromptAgentDefinition(model: deploymentName) { Instructions = JokerInstructions };
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var agentVersion = agentsClient.CreateAgentVersion(agentName: JokerName, definition: agentDefinition);
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return agentsClient.GetAIAgent(agentVersion);
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});
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builder.Services.AddSingleton<AIAgent>((sp)
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=> sp.GetRequiredService<AgentsClient>()
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.CreateAIAgent(name: JokerName, model: deploymentName, instructions: JokerInstructions));
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// Add a sample service that will use the agent to respond to user input.
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builder.Services.AddHostedService<SampleService>();
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+1
-1
@@ -18,7 +18,7 @@
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</ItemGroup>
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<ItemGroup>
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<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI.Persistent\Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
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<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
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<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
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</ItemGroup>
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+14
-10
@@ -2,7 +2,7 @@
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// This sample shows how to expose an AI agent as an MCP tool.
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using Azure.AI.Agents.Persistent;
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using Azure.AI.Agents;
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using Azure.Identity;
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using Microsoft.Agents.AI;
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using Microsoft.Extensions.DependencyInjection;
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@@ -12,17 +12,19 @@ using ModelContextProtocol.Server;
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var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
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var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
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var persistentAgentsClient = new PersistentAgentsClient(endpoint, new AzureCliCredential());
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const string JokerInstructions = "You are good at telling jokes, and you always start each joke with 'Aye aye, captain!'.";
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const string JokerName = "JokerAgent";
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const string JokerDescription = "An agent that tells jokes.";
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// Create a server side persistent agent
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var agentMetadata = await persistentAgentsClient.Administration.CreateAgentAsync(
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// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
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var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
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|
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// Define the agent you want to create. (Prompt Agent in this case)
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AIAgent agent = agentsClient.CreateAIAgent(
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name: JokerName,
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model: deploymentName,
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instructions: "You are good at telling jokes, and you always start each joke with 'Aye aye, captain!'.",
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name: "Joker",
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description: "An agent that tells jokes.");
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// Retrieve the server side persistent agent as an AIAgent.
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AIAgent agent = await persistentAgentsClient.GetAIAgentAsync(agentMetadata.Value.Id);
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instructions: JokerInstructions,
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creationOptions: new() { Description = JokerDescription });
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// Convert the agent to an AIFunction and then to an MCP tool.
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// The agent name and description will be used as the mcp tool name and description.
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@@ -35,4 +37,6 @@ builder.Services
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.WithStdioServerTransport()
|
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.WithTools([tool]);
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|
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Console.WriteLine("Starting MCP Tool server. Press Ctrl+C to exit.");
|
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|
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await builder.Build().RunAsync();
|
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+1
-7
@@ -17,13 +17,7 @@ const string VisionName = "VisionAgent";
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var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
|
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|
||||
// Define the agent you want to create. (Prompt Agent in this case)
|
||||
var agentDefinition = new PromptAgentDefinition(model: deploymentName) { Instructions = VisionInstructions };
|
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|
||||
// Create a server side agent version with the Azure.AI.Agents SDK client.
|
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var agentVersion = agentsClient.CreateAgentVersion(agentName: VisionName, definition: agentDefinition);
|
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|
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// Retrieve an AIAgent for the created server side agent version.
|
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AIAgent agent = agentsClient.GetAIAgent(agentVersion);
|
||||
AIAgent agent = agentsClient.CreateAIAgent(name: VisionName, model: deploymentName, instructions: VisionInstructions);
|
||||
|
||||
ChatMessage message = new(ChatRole.User, [
|
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new TextContent("What do you see in this image?"),
|
||||
+10
-16
@@ -7,7 +7,6 @@ using Azure.AI.Agents;
|
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using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
using OpenAI.Responses;
|
||||
|
||||
var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
|
||||
var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
|
||||
@@ -25,24 +24,19 @@ static string GetWeather([Description("The location to get the weather for.")] s
|
||||
var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Create the weather agent with function tools.
|
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var weatherAgentDefinition = new PromptAgentDefinition(model: deploymentName)
|
||||
{
|
||||
Instructions = WeatherInstructions
|
||||
};
|
||||
var weatherTool = AIFunctionFactory.Create(GetWeather);
|
||||
weatherAgentDefinition.Tools.Add(weatherTool.GetService<ResponseTool>() ?? weatherTool.AsOpenAIResponseTool()!);
|
||||
var weatherAgentVersion = agentsClient.CreateAgentVersion(agentName: WeatherName, definition: weatherAgentDefinition);
|
||||
AIAgent weatherAgent = agentsClient.GetAIAgent(weatherAgentVersion);
|
||||
AIAgent weatherAgent = agentsClient.CreateAIAgent(
|
||||
name: WeatherName,
|
||||
model: deploymentName,
|
||||
instructions: WeatherInstructions,
|
||||
tools: [weatherTool]);
|
||||
|
||||
// Create the main agent, and provide the weather agent as a function tool.
|
||||
var mainAgentDefinition = new PromptAgentDefinition(model: deploymentName)
|
||||
{
|
||||
Instructions = MainInstructions
|
||||
};
|
||||
var agentTool = weatherAgent.AsAIFunction();
|
||||
mainAgentDefinition.Tools.Add(agentTool.GetService<ResponseTool>() ?? agentTool.AsOpenAIResponseTool()!);
|
||||
var mainAgentVersion = agentsClient.CreateAgentVersion(agentName: MainName, definition: mainAgentDefinition);
|
||||
AIAgent agent = agentsClient.GetAIAgent(mainAgentVersion);
|
||||
AIAgent agent = agentsClient.CreateAIAgent(
|
||||
name: MainName,
|
||||
model: deploymentName,
|
||||
instructions: MainInstructions,
|
||||
tools: [weatherAgent.AsAIFunction()]);
|
||||
|
||||
// Invoke the agent and output the text result.
|
||||
AgentThread thread = agent.GetNewThread();
|
||||
+19
-40
@@ -11,7 +11,6 @@ using Azure.AI.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
using OpenAI.Responses;
|
||||
|
||||
// Get Azure AI Foundry configuration from environment variables
|
||||
var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
|
||||
@@ -31,19 +30,15 @@ static string GetWeather([Description("The location to get the weather for.")] s
|
||||
static string GetDateTime()
|
||||
=> DateTimeOffset.Now.ToString();
|
||||
|
||||
// Define the agent with tools
|
||||
var agentDefinition = new PromptAgentDefinition(model: deploymentName)
|
||||
{
|
||||
Instructions = AssistantInstructions
|
||||
};
|
||||
var dateTimeTool = AIFunctionFactory.Create(GetDateTime, name: nameof(GetDateTime));
|
||||
agentDefinition.Tools.Add(dateTimeTool.GetService<ResponseTool>() ?? dateTimeTool.AsOpenAIResponseTool()!);
|
||||
var getWeatherTool = AIFunctionFactory.Create(GetWeather, name: nameof(GetWeather));
|
||||
|
||||
// Create a server side agent version with the Azure.AI.Agents SDK client.
|
||||
var agentVersion = agentsClient.CreateAgentVersion(agentName: AssistantName, definition: agentDefinition);
|
||||
|
||||
// Retrieve an AIAgent for the created server side agent version.
|
||||
var originalAgent = agentsClient.GetAIAgent(agentVersion);
|
||||
// Define the agent you want to create. (Prompt Agent in this case)
|
||||
AIAgent originalAgent = agentsClient.CreateAIAgent(
|
||||
name: AssistantName,
|
||||
model: deploymentName,
|
||||
instructions: AssistantInstructions,
|
||||
tools: [getWeatherTool, dateTimeTool]);
|
||||
|
||||
// Adding middleware to the agent level
|
||||
var middlewareEnabledAgent = originalAgent
|
||||
@@ -68,33 +63,28 @@ Console.WriteLine("\n\n=== Example 3: Agent function middleware ===");
|
||||
|
||||
// Agent function middleware support is limited to agents that wraps a upstream ChatClientAgent or derived from it.
|
||||
|
||||
// Add Per-request tools
|
||||
var options = new ChatClientAgentRunOptions(new()
|
||||
{
|
||||
Tools = [AIFunctionFactory.Create(GetWeather, name: nameof(GetWeather))]
|
||||
});
|
||||
|
||||
var functionCallResponse = await middlewareEnabledAgent.RunAsync("What's the current time and the weather in Seattle?", thread, options);
|
||||
var functionCallResponse = await middlewareEnabledAgent.RunAsync("What's the current time and the weather in Seattle?", thread);
|
||||
Console.WriteLine($"Function calling response: {functionCallResponse}");
|
||||
|
||||
// Special per-request middleware agent.
|
||||
Console.WriteLine("\n\n=== Example 4: Per-request middleware with human in the loop function approval ===");
|
||||
Console.WriteLine("\n\n=== Example 4: Middleware with human in the loop function approval ===");
|
||||
|
||||
AIAgent humamInTheLoopAgent = agentsClient.CreateAIAgent(
|
||||
name: "HumanInTheLoopAgent",
|
||||
model: deploymentName,
|
||||
instructions: "You are an Human in the loop testing AI assistant that helps people find information.",
|
||||
|
||||
var optionsWithApproval = new ChatClientAgentRunOptions(new()
|
||||
{
|
||||
// Adding a function with approval required
|
||||
Tools = [new ApprovalRequiredAIFunction(AIFunctionFactory.Create(GetWeather, name: nameof(GetWeather)))],
|
||||
});
|
||||
tools: [new ApprovalRequiredAIFunction(AIFunctionFactory.Create(GetWeather, name: nameof(GetWeather)))]);
|
||||
|
||||
// var response = middlewareAgent // Using per-request middleware pipeline in addition to existing agent-level middleware
|
||||
var response = await originalAgent // Using per-request middleware pipeline without existing agent-level middleware
|
||||
// Using the ConsolePromptingApprovalMiddleware for a specific request to handle user approval during function calls.
|
||||
var response = await humamInTheLoopAgent
|
||||
.AsBuilder()
|
||||
.Use(PerRequestFunctionCallingMiddleware)
|
||||
.Use(ConsolePromptingApprovalMiddleware, null)
|
||||
.Build()
|
||||
.RunAsync("What's the current time and the weather in Seattle?", thread, optionsWithApproval);
|
||||
.RunAsync("What's the current time and the weather in Seattle?");
|
||||
|
||||
Console.WriteLine($"Per-request middleware response: {response}");
|
||||
Console.WriteLine($"HumamInTheLoopAgent agent middleware response: {response}");
|
||||
|
||||
// Function invocation middleware that logs before and after function calls.
|
||||
async ValueTask<object?> FunctionCallMiddleware(AIAgent agent, FunctionInvocationContext context, Func<FunctionInvocationContext, CancellationToken, ValueTask<object?>> next, CancellationToken cancellationToken)
|
||||
@@ -122,17 +112,6 @@ async ValueTask<object?> FunctionCallOverrideWeather(AIAgent agent, FunctionInvo
|
||||
return result;
|
||||
}
|
||||
|
||||
// There's no difference per-request middleware, except it's added to the agent and used for a single agent run.
|
||||
// This middleware logs function names before and after they are invoked.
|
||||
async ValueTask<object?> PerRequestFunctionCallingMiddleware(AIAgent agent, FunctionInvocationContext context, Func<FunctionInvocationContext, CancellationToken, ValueTask<object?>> next, CancellationToken cancellationToken)
|
||||
{
|
||||
Console.WriteLine($"Agent Id: {agent.Id}");
|
||||
Console.WriteLine($"Function Name: {context!.Function.Name} - Per-Request Pre-Invoke");
|
||||
var result = await next(context, cancellationToken);
|
||||
Console.WriteLine($"Function Name: {context!.Function.Name} - Per-Request Post-Invoke");
|
||||
return result;
|
||||
}
|
||||
|
||||
// This middleware redacts PII information from input and output messages.
|
||||
async Task<AgentRunResponse> PIIMiddleware(IEnumerable<ChatMessage> messages, AgentThread? thread, AgentRunOptions? options, AIAgent innerAgent, CancellationToken cancellationToken)
|
||||
{
|
||||
-22
@@ -1,22 +0,0 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net9.0</TargetFramework>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<NoWarn>$(NoWarn);CA1812</NoWarn>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Agents" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
-156
@@ -1,156 +0,0 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample shows how to add a basic custom memory component to an agent.
|
||||
// The memory component subscribes to all messages added to the conversation and
|
||||
// extracts the user's name and age if provided.
|
||||
// The component adds a prompt to ask for this information if it is not already known
|
||||
// and provides it to the model before each invocation if known.
|
||||
|
||||
using System.Text;
|
||||
using System.Text.Json;
|
||||
using Azure.AI.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
using SampleApp;
|
||||
|
||||
var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
|
||||
var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
|
||||
|
||||
const string AssistantInstructions = "You are a friendly assistant. Always address the user by their name.";
|
||||
const string AssistantName = "FriendlyAssistant";
|
||||
|
||||
// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
|
||||
var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Define the agent you want to create. (Prompt Agent in this case)
|
||||
var agentDefinition = new PromptAgentDefinition(model: deploymentName) { Instructions = AssistantInstructions };
|
||||
|
||||
// Create a server side agent version with the Azure.AI.Agents SDK client.
|
||||
var agentVersion = agentsClient.CreateAgentVersion(agentName: AssistantName, definition: agentDefinition);
|
||||
|
||||
// Retrieve an AIAgent for the created server side agent version.
|
||||
AIAgent agent = agentsClient.GetAIAgent(agentVersion);
|
||||
|
||||
// Create a new thread for the conversation.
|
||||
AgentThread thread = agent.GetNewThread();
|
||||
|
||||
Console.WriteLine(">> Use thread with blank memory\n");
|
||||
|
||||
// Invoke the agent and output the text result.
|
||||
Console.WriteLine(await agent.RunAsync("Hello, what is the square root of 9?", thread));
|
||||
Console.WriteLine(await agent.RunAsync("My name is Ruaidhrí", thread));
|
||||
Console.WriteLine(await agent.RunAsync("I am 20 years old", thread));
|
||||
|
||||
// We can serialize the thread. The serialized state will include the state of the memory component.
|
||||
var threadElement = thread.Serialize();
|
||||
|
||||
Console.WriteLine("\n>> Use deserialized thread with previously created memories\n");
|
||||
|
||||
// Later we can deserialize the thread and continue the conversation with the previous memory component state.
|
||||
var deserializedThread = agent.DeserializeThread(threadElement);
|
||||
Console.WriteLine(await agent.RunAsync("What is my name and age?", deserializedThread));
|
||||
|
||||
Console.WriteLine("\n>> Read memories from memory component\n");
|
||||
|
||||
// It's possible to access the memory component via the thread's GetService method.
|
||||
var userInfo = deserializedThread.GetService<UserInfoMemory>()?.UserInfo;
|
||||
|
||||
// Output the user info that was captured by the memory component.
|
||||
Console.WriteLine($"MEMORY - User Name: {userInfo?.UserName}");
|
||||
Console.WriteLine($"MEMORY - User Age: {userInfo?.UserAge}");
|
||||
|
||||
Console.WriteLine("\n>> Use new thread with previously created memories\n");
|
||||
|
||||
// It is also possible to set the memories in a memory component on an individual thread.
|
||||
// This is useful if we want to start a new thread, but have it share the same memories as a previous thread.
|
||||
var newThread = agent.GetNewThread();
|
||||
if (userInfo is not null && newThread.GetService<UserInfoMemory>() is UserInfoMemory newThreadMemory)
|
||||
{
|
||||
newThreadMemory.UserInfo = userInfo;
|
||||
}
|
||||
|
||||
// Invoke the agent and output the text result.
|
||||
// This time the agent should remember the user's name and use it in the response.
|
||||
Console.WriteLine(await agent.RunAsync("What is my name and age?", newThread));
|
||||
|
||||
// Cleanup by agent name removes the agent version created.
|
||||
agentsClient.DeleteAgent(agent.Name);
|
||||
|
||||
namespace SampleApp
|
||||
{
|
||||
/// <summary>
|
||||
/// Sample memory component that can remember a user's name and age.
|
||||
/// </summary>
|
||||
internal sealed class UserInfoMemory : AIContextProvider
|
||||
{
|
||||
private readonly IChatClient _chatClient;
|
||||
|
||||
public UserInfoMemory(IChatClient chatClient, UserInfo? userInfo = null)
|
||||
{
|
||||
this._chatClient = chatClient;
|
||||
this.UserInfo = userInfo ?? new UserInfo();
|
||||
}
|
||||
|
||||
public UserInfoMemory(IChatClient chatClient, JsonElement serializedState, JsonSerializerOptions? jsonSerializerOptions = null)
|
||||
{
|
||||
this._chatClient = chatClient;
|
||||
|
||||
this.UserInfo = serializedState.ValueKind == JsonValueKind.Object ?
|
||||
serializedState.Deserialize<UserInfo>(jsonSerializerOptions)! :
|
||||
new UserInfo();
|
||||
}
|
||||
|
||||
public UserInfo UserInfo { get; set; }
|
||||
|
||||
public override async ValueTask InvokedAsync(InvokedContext context, CancellationToken cancellationToken = default)
|
||||
{
|
||||
// Try and extract the user name and age from the message if we don't have it already and it's a user message.
|
||||
if ((this.UserInfo.UserName is null || this.UserInfo.UserAge is null) && context.RequestMessages.Any(x => x.Role == ChatRole.User))
|
||||
{
|
||||
var result = await this._chatClient.GetResponseAsync<UserInfo>(
|
||||
context.RequestMessages,
|
||||
new ChatOptions()
|
||||
{
|
||||
Instructions = "Extract the user's name and age from the message if present. If not present return nulls."
|
||||
},
|
||||
cancellationToken: cancellationToken);
|
||||
|
||||
this.UserInfo.UserName ??= result.Result.UserName;
|
||||
this.UserInfo.UserAge ??= result.Result.UserAge;
|
||||
}
|
||||
}
|
||||
|
||||
public override ValueTask<AIContext> InvokingAsync(InvokingContext context, CancellationToken cancellationToken = default)
|
||||
{
|
||||
StringBuilder instructions = new();
|
||||
|
||||
// If we don't already know the user's name and age, add instructions to ask for them, otherwise just provide what we have to the context.
|
||||
instructions
|
||||
.AppendLine(
|
||||
this.UserInfo.UserName is null ?
|
||||
"Ask the user for their name and politely decline to answer any questions until they provide it." :
|
||||
$"The user's name is {this.UserInfo.UserName}.")
|
||||
.AppendLine(
|
||||
this.UserInfo.UserAge is null ?
|
||||
"Ask the user for their age and politely decline to answer any questions until they provide it." :
|
||||
$"The user's age is {this.UserInfo.UserAge}.");
|
||||
|
||||
return new ValueTask<AIContext>(new AIContext
|
||||
{
|
||||
Instructions = instructions.ToString()
|
||||
});
|
||||
}
|
||||
|
||||
public override JsonElement Serialize(JsonSerializerOptions? jsonSerializerOptions = null)
|
||||
{
|
||||
return JsonSerializer.SerializeToElement(this.UserInfo, jsonSerializerOptions);
|
||||
}
|
||||
}
|
||||
|
||||
internal sealed class UserInfo
|
||||
{
|
||||
public string? UserName { get; set; }
|
||||
public int? UserAge { get; set; }
|
||||
}
|
||||
}
|
||||
+7
-15
@@ -14,7 +14,6 @@ using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
using Microsoft.Extensions.DependencyInjection;
|
||||
using OpenAI.Responses;
|
||||
|
||||
var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
|
||||
var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
|
||||
@@ -34,20 +33,13 @@ IServiceProvider serviceProvider = services.BuildServiceProvider();
|
||||
var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Define the agent with plugin tools
|
||||
var agentDefinition = new PromptAgentDefinition(model: deploymentName)
|
||||
{
|
||||
Instructions = AssistantInstructions
|
||||
};
|
||||
foreach (var tool in serviceProvider.GetRequiredService<AgentPlugin>().AsAITools())
|
||||
{
|
||||
agentDefinition.Tools.Add(tool.GetService<ResponseTool>() ?? tool.AsOpenAIResponseTool()!);
|
||||
}
|
||||
|
||||
// Create a server side agent version with the Azure.AI.Agents SDK client.
|
||||
var agentVersion = agentsClient.CreateAgentVersion(agentName: AssistantName, definition: agentDefinition);
|
||||
|
||||
// Retrieve an AIAgent for the created server side agent version.
|
||||
AIAgent agent = agentsClient.GetAIAgent(agentVersion);
|
||||
// Define the agent you want to create. (Prompt Agent in this case)
|
||||
AIAgent agent = agentsClient.CreateAIAgent(
|
||||
name: AssistantName,
|
||||
model: deploymentName,
|
||||
instructions: AssistantInstructions,
|
||||
tools: serviceProvider.GetRequiredService<AgentPlugin>().AsAITools().ToList(),
|
||||
services: serviceProvider);
|
||||
|
||||
// Invoke the agent and output the text result.
|
||||
AgentThread thread = agent.GetNewThread();
|
||||
+1
-7
@@ -18,13 +18,7 @@ const string JokerName = "JokerAgent";
|
||||
var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Define the agent you want to create. (Prompt Agent in this case)
|
||||
var agentDefinition = new PromptAgentDefinition(model: deploymentName) { Instructions = JokerInstructions };
|
||||
|
||||
// Create a server side agent version with the Azure.AI.Agents SDK client.
|
||||
var agentVersion = agentsClient.CreateAgentVersion(agentName: JokerName, definition: agentDefinition);
|
||||
|
||||
// Retrieve an AIAgent for the created server side agent version.
|
||||
AIAgent agent = agentsClient.GetAIAgent(agentVersion);
|
||||
AIAgent agent = agentsClient.CreateAIAgent(name: JokerName, model: deploymentName, instructions: JokerInstructions);
|
||||
|
||||
AgentThread thread = agent.GetNewThread();
|
||||
|
||||
|
||||
Reference in New Issue
Block a user