Merge branch 'main' into feature-foundry-agents

This commit is contained in:
Chris
2025-11-07 09:14:33 -08:00
committed by GitHub
50 changed files with 3808 additions and 284 deletions
@@ -1,4 +1,4 @@
<Project Sdk="Microsoft.NET.Sdk.Web">
<Project Sdk="Microsoft.NET.Sdk.Web">
<PropertyGroup>
<TargetFramework>net9.0</TargetFramework>
@@ -13,7 +13,7 @@
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting\Microsoft.Agents.AI.Hosting.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.A2A.AspNetCore\Microsoft.Agents.AI.Hosting.A2A.AspNetCore.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.OpenAI\Microsoft.Agents.AI.Hosting.OpenAI.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.OpenAI\Microsoft.Agents.AI.Hosting.OpenAI.csproj" />
<ProjectReference Include="..\AgentWebChat.ServiceDefaults\AgentWebChat.ServiceDefaults.csproj" />
</ItemGroup>
@@ -37,4 +37,4 @@
</ItemGroup>
<!-- A2A dependency -->
</Project>
</Project>
@@ -0,0 +1,17 @@
// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Extensions.AI;
namespace AgentWebChat.AgentHost.Custom;
public class CustomAITool : AITool
{
}
public class CustomFunctionTool : AIFunction
{
protected override ValueTask<object?> InvokeCoreAsync(AIFunctionArguments arguments, CancellationToken cancellationToken)
{
return new ValueTask<object?>(arguments.Context?.Count ?? 0);
}
}
@@ -2,6 +2,7 @@
using A2A.AspNetCore;
using AgentWebChat.AgentHost;
using AgentWebChat.AgentHost.Custom;
using AgentWebChat.AgentHost.Utilities;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Hosting;
@@ -25,6 +26,8 @@ var pirateAgentBuilder = builder.AddAIAgent(
instructions: "You are a pirate. Speak like a pirate",
description: "An agent that speaks like a pirate.",
chatClientServiceKey: "chat-model")
.WithAITool(new CustomAITool())
.WithAITool(new CustomFunctionTool())
.WithInMemoryThreadStore();
var knightsKnavesAgentBuilder = builder.AddAIAgent("knights-and-knaves", (sp, key) =>
@@ -78,8 +81,19 @@ var literatureAgent = builder.AddAIAgent("literator",
description: "An agent that helps with literature.",
chatClientServiceKey: "chat-model");
builder.AddSequentialWorkflow("science-sequential-workflow", [chemistryAgent, mathsAgent, literatureAgent]).AddAsAIAgent();
builder.AddConcurrentWorkflow("science-concurrent-workflow", [chemistryAgent, mathsAgent, literatureAgent]).AddAsAIAgent();
var scienceSequentialWorkflow = builder.AddWorkflow("science-sequential-workflow", (sp, key) =>
{
List<IHostedAgentBuilder> usedAgents = [chemistryAgent, mathsAgent, literatureAgent];
var agents = usedAgents.Select(ab => sp.GetRequiredKeyedService<AIAgent>(ab.Name));
return AgentWorkflowBuilder.BuildSequential(workflowName: key, agents: agents);
}).AddAsAIAgent();
var scienceConcurrentWorkflow = builder.AddWorkflow("science-concurrent-workflow", (sp, key) =>
{
List<IHostedAgentBuilder> usedAgents = [chemistryAgent, mathsAgent, literatureAgent];
var agents = usedAgents.Select(ab => sp.GetRequiredKeyedService<AIAgent>(ab.Name));
return AgentWorkflowBuilder.BuildConcurrent(workflowName: key, agents: agents);
}).AddAsAIAgent();
builder.AddOpenAIChatCompletions();
builder.AddOpenAIResponses();
@@ -4,6 +4,8 @@
// capabilities to an AI agent. The provider runs a search against an external knowledge base
// before each model invocation and injects the results into the model context.
// Also see the AgentWithRAG folder for more advanced RAG scenarios.
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
@@ -0,0 +1,23 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFramework>net9.0</TargetFramework>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
<PackageReference Include="Microsoft.SemanticKernel.Connectors.InMemory" />
<PackageReference Include="System.Linq.Async" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
</ItemGroup>
</Project>
@@ -0,0 +1,60 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample shows how to create and use a simple AI agent that stores chat messages in a vector store using the ChatHistoryMemoryProvider.
// It can then use the chat history from prior conversations to inform responses in new conversations.
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
using Microsoft.Extensions.VectorData;
using Microsoft.SemanticKernel.Connectors.InMemory;
using OpenAI;
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 embeddingDeploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-3-large";
// Create a vector store to store the chat messages in.
// For demonstration purposes, we are using an in-memory vector store.
// Replace this with a vector store implementation of your choice that can persist the chat history long term.
VectorStore vectorStore = new InMemoryVectorStore(new InMemoryVectorStoreOptions()
{
EmbeddingGenerator = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
.GetEmbeddingClient(embeddingDeploymentName)
.AsIEmbeddingGenerator()
});
// Create the agent and add the ChatHistoryMemoryProvider to store chat messages in the vector store.
AIAgent agent = new AzureOpenAIClient(
new Uri(endpoint),
new AzureCliCredential())
.GetChatClient(deploymentName)
.CreateAIAgent(new ChatClientAgentOptions
{
Instructions = "You are good at telling jokes.",
Name = "Joker",
AIContextProviderFactory = (ctx) => new ChatHistoryMemoryProvider(
vectorStore,
collectionName: "chathistory",
vectorDimensions: 3072,
// Configure the scope values under which chat messages will be stored.
// In this case, we are using a fixed user ID and a unique thread ID for each new thread.
storageScope: new() { UserId = "UID1", ThreadId = new Guid().ToString() },
// Configure the scope which would be used to search for relevant prior messages.
// In this case, we are searching for any messages for the user across all threads.
searchScope: new() { UserId = "UID1" })
});
// Start a new thread for the agent conversation.
AgentThread thread = agent.GetNewThread();
// Run the agent with the thread that stores conversation history in the vector store.
Console.WriteLine(await agent.RunAsync("I like jokes about Pirates. Tell me a joke about a pirate.", thread));
// Start a second thread. Since we configured the search scope to be across all threads for the user,
// the agent should remember that the user likes pirate jokes.
AgentThread thread2 = agent.GetNewThread();
// Run the agent with the second thread.
Console.WriteLine(await agent.RunAsync("Tell me a joke that I might like.", thread2));
@@ -4,8 +4,10 @@
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.DevUI;
using Microsoft.Agents.AI.Hosting;
using Microsoft.Agents.AI.Workflows;
using Microsoft.Extensions.AI;
namespace DevUI_Step01_BasicUsage;
@@ -56,10 +58,11 @@ internal static class Program
// Register sample workflows
var assistantBuilder = builder.AddAIAgent("workflow-assistant", "You are a helpful assistant in a workflow.");
var reviewerBuilder = builder.AddAIAgent("workflow-reviewer", "You are a reviewer. Review and critique the previous response.");
builder.AddSequentialWorkflow(
"review-workflow",
[assistantBuilder, reviewerBuilder])
.AddAsAIAgent();
builder.AddWorkflow("review-workflow", (sp, key) =>
{
var agents = new List<IHostedAgentBuilder>() { assistantBuilder, reviewerBuilder }.Select(ab => sp.GetRequiredKeyedService<AIAgent>(ab.Name));
return AgentWorkflowBuilder.BuildSequential(workflowName: key, agents: agents);
}).AddAsAIAgent();
if (builder.Environment.IsDevelopment())
{