.NET: Chathistory memory provider add (#1867)

* Add ChatHistoryMemoryProvider with unit tests

* Set new project to not packable.

* Fix bugs

* Add serialization support.

* Update dotnet/src/Microsoft.Agents.AI.VectorDataMemory/ChatHistoryMemoryProvider.cs

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Remove unnecessary line

* Convert ChatHistoryMemoryProvider to use Dynamic collections.

* Sealing options and scope classes.

* Add sample, add scope to logs and improve scope validation

* Move ChatHistoryMemoryProvider to MAAI project.

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
This commit is contained in:
westey
2025-11-07 11:46:35 +00:00
committed by GitHub
Unverified
parent 64826b8f56
commit e5d9d74c2d
11 changed files with 1081 additions and 6 deletions
@@ -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));