Files
agent-framework/dotnet/samples/01-get-started/04_memory/Program.cs
T
westey 8b191de936 Merge and move scripts (#4308)
* .NET: Add Microsoft Fabric sample #3674 (#4230)

Co-authored-by: Chris <66376200+crickman@users.noreply.github.com>

* Python: Phase 2: Embedding clients for Ollama, Bedrock, and Azure AI Inference (#4207)

* Phase 2: Embedding clients for Ollama, Bedrock, and Azure AI Inference

Add embedding client implementations to existing provider packages:

- OllamaEmbeddingClient: Text embeddings via Ollama's embed API
- BedrockEmbeddingClient: Text embeddings via Amazon Titan on Bedrock
- AzureAIInferenceEmbeddingClient: Text and image embeddings via Azure AI
  Inference, supporting Content | str input with separate model IDs for
  text (AZURE_AI_INFERENCE_EMBEDDING_MODEL_ID) and image
  (AZURE_AI_INFERENCE_IMAGE_EMBEDDING_MODEL_ID) endpoints

Additional changes:
- Rename EmbeddingCoT -> EmbeddingT, EmbeddingOptionsCoT -> EmbeddingOptionsT
- Add otel_provider_name passthrough to all embedding clients
- Register integration pytest marker in all packages
- Add lazy-loading namespace exports for Ollama and Bedrock embeddings
- Add image embedding sample using Cohere-embed-v3-english
- Add azure-ai-inference dependency to azure-ai package

Part of #1188

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Fix mypy duplicate name and ruff lint issues

- Rename second 'vector' variable to 'img_vector' in image embedding loop
- Combine nested with statements in tests
- Remove unused result assignments in tests

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* updates from feedback

* Fix CI failures in embedding usage handling

- Fix Azure AI embedding mypy issues by normalizing vectors to list[float],
  safely accumulating optional usage token fields, and filtering None entries
  before constructing GeneratedEmbeddings
- Avoid Bandit false positive by initializing usage details as an empty dict
- Update OpenAI embedding tests to assert canonical usage keys
  (input_token_count/total_token_count)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* [Purview] Mark responses as responses and fix epoch bug for python long overflow (#4225)

* .NET: Support InvokeMcpTool for declarative workflows (#4204)

* Initial implementation of InvokeMcpTool in declarative workflow

* Cleaned up sample implementation

* Updated sample comments.

* Added missing executor routing attribute

* Fix PR comments.

* Updated based on PR comments.

* Updated based on PR comments.

* Removed unnecessary using statement.

* Update Python package versions to rc2 (#4258)

- Bump core and azure-ai to 1.0.0rc2
- Bump preview packages to 1.0.0b260225
- Update dependencies to >=1.0.0rc2
- Add CHANGELOG entries for changes since rc1
- Update uv.lock

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* .NET: Fixing issue where OpenTelemetry span is never exported in .NET in-process workflow execution (#4196)

* 1. Add reproduction test for issue #4155: workflow.run Activity never stopped in streaming OffThread path

The WorkflowRunActivity_IsStopped_Streaming_OffThread test demonstrates that
the workflow.run OpenTelemetry Activity created in StreamingRunEventStream.RunLoopAsync
is started but never stopped when using the OffThread/Default streaming execution.
The background run loop keeps running after event consumption completes, so the
using Activity? declaration never disposes until explicit StopAsync() is called.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

2. Fix workflow.run Activity never stopped in streaming OffThread execution (#4155)

The workflow.run OpenTelemetry Activity in StreamingRunEventStream.RunLoopAsync
was scoped to the method lifetime via 'using'. Since the run loop only exits on
cancellation, the Activity was never stopped/exported until explicit disposal.

Fix: Remove 'using' and explicitly dispose the Activity when the workflow reaches
Idle status (all supersteps complete). A safety-net disposal in the finally block
handles cancellation and error paths.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Add root-level workflow.session activity spanning run loop lifetime\n\nImplements two-level telemetry hierarchy per PR feedback from lokitoth:\n- workflow.session: spans the entire run loop / stream lifetime\n- workflow_invoke: per input-to-halt cycle, nested within the session\n\nThis ensures the session activity stays open across multiple turns,\nwhile individual run activities are created and disposed per cycle.\n\nAlso fixes linkedSource CancellationTokenSource disposal leak in\nStreamingRunEventStream (added using declaration)."

* Address Copilot review: fix Activity/CTS disposal, rename activity, add error tag\n\n1. LockstepRunEventStream: Remove 'using' from Activity in async iterator\n   and manually dispose in finally block (fixes #4155 pattern). Also dispose\n   linkedSource CTS in finally to prevent leak.\n2. Tags.cs: Add ErrorMessage (\"error.message\") tag for runtime errors,\n   distinct from BuildErrorMessage (\"build.error.message\").\n3. ActivityNames: Rename WorkflowRun from \"workflow_invoke\" to \"workflow.run\"\n   for cross-language consistency.\n4. WorkflowTelemetryContext: Fix XML doc to say \"outer/parent span\" instead\n   of \"root-level span\".\n5. ObservabilityTests: Assert WorkflowSession absence when DisableWorkflowRun\n   is true.\n6. WorkflowRunActivityStopTests: Fix streaming test race by disposing\n   StreamingRun before asserting activities are stopped.\n7. StreamingRunEventStream/LockstepRunEventStream: Use Tags.ErrorMessage\n   instead of Tags.BuildErrorMessage for runtime error events."

* Review fixes: revert workflow_invoke rename, use 'using' for linkedSource, move SessionStarted earlier\n\n- Revert ActivityNames.WorkflowRun back to \"workflow_invoke\" (OTEL semantic convention contract)\n- Use 'using' declaration for linkedSource CTS in LockstepRunEventStream (no timing sensitivity)\n- Move SessionStarted event before WaitForInputAsync in StreamingRunEventStream to match Lockstep behavior"

* Improve naming and comments in WorkflowRunActivityStopTests"

* Prevent session Activity.Current leak in lockstep mode, add nesting test

Save and restore Activity.Current in LockstepRunEventStream.Start() so the
session activity doesn't leak into caller code via AsyncLocal. Re-establish
Activity.Current = sessionActivity before creating the run activity in
TakeEventStreamAsync to preserve parent-child nesting.

Add test verifying app activities after RunAsync are not parented under the
session, and that the workflow_invoke activity nests under the session."

* Fix stale XML doc: WorkflowRun -> WorkflowInvoke in ObservabilityTests

---------

Co-authored-by: alliscode <bentho@microsoft.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Python / .NET Samples - Restructure and Improve Samples (Feature Branc… (#4092)

* Python: .NET Samples - Restructure and Improve Samples (Feature Branch) (#4091)

* Moved by agent (#4094)

* Fix readme links

* .NET Samples - Create `04-hosting` learning path step (#4098)

* Agent move

* Agent reorderd

* Remove A2A section from README 

Removed A2A section from the Getting Started README.

* Agent fixed links

* Fix broken sample links in durable-agents README (#4101)

* Initial plan

* Fix broken internal links in documentation

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* Revert template link changes; keep only durable-agents README fix

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* .NET Samples - Create `03-workflows` learning path step (#4102)

* Fix solution project path

* Python: Fix broken markdown links to repo resources (outside /docs) (#4105)

* Initial plan

* Fix broken markdown links to repo resources

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* Update README to rename .NET Workflows Samples section

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* .NET Samples - Create `02-agents` learning path step (#4107)

* .NET: Fix broken relative link in GroupChatToolApproval README (#4108)

* Initial plan

* Fix broken link in GroupChatToolApproval README

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* Update labeler configuration for workflow samples

* .NET - Reorder Agents samples to start from Step01 instead of Step04 (#4110)

* Fix solution

* Resolve new sample paths

* Move new AgentSkills and AgentWithMemory_Step04 samples

* Fix link

* Fix readme path

* fix: update stale dotnet/samples/Durable path reference in AGENTS.md

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* Moved new sample

* Update solution

* Resolve merge (new sample)

* Sync to new sample - FoundryAgents_Step21_BingCustomSearch

* Updated README

* .NET Samples - Configuration Naming Update (#4149)

* .NET: Restore AzureFunctions index parity with ConsoleApps under DurableAgents samples (#4221)

* Clean-up `05_host_your_agent`

* Config setting consistency

* Refine samples

* AGENTS.md

* Move new samples

* Re-order samples

* Move new project and fixup solution

* Fixup model config

* Fix up new UT project

---------

Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com>

* Python: Fix Bedrock embedding test stub missing meta attribute (#4287)

* Fix Bedrock embedding test stub missing meta attribute

* Increase test coverage so gate passes

* Python: (ag-ui): fix approval payloads being re-processed on subsequent conversation turns (#4232)

* Fix ag-ui tool call issue

* Safe json fix

* Python: Update workflow orchestration samples to use AzureOpenAIResponsesClient (#4285)

* Update workflow orchestration samples to use AzureOpenAIResponsesClient

* Fix broken link

* Move scripts to scripts folder

---------

Co-authored-by: Roger Barreto <19890735+rogerbarreto@users.noreply.github.com>
Co-authored-by: Chris <66376200+crickman@users.noreply.github.com>
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Rishabh Chawla <rishabhchawla1995@gmail.com>
Co-authored-by: Peter Ibekwe <109177538+peibekwe@users.noreply.github.com>
Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com>
Co-authored-by: Ben Thomas <ben.thomas@microsoft.com>
Co-authored-by: alliscode <bentho@microsoft.com>
Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
2026-02-26 10:49:07 +00:00

163 lines
7.5 KiB
C#

// 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.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
using OpenAI.Chat;
using SampleApp;
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";
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
ChatClient chatClient = new AzureOpenAIClient(
new Uri(endpoint),
new DefaultAzureCredential())
.GetChatClient(deploymentName);
// Create the agent and provide a factory to add our custom memory component to
// all sessions created by the agent. Here each new memory component will have its own
// user info object, so each session will have its own memory.
// In real world applications/services, where the user info would be persisted in a database,
// and preferably shared between multiple sessions used by the same user, ensure that the
// factory reads the user id from the current context and scopes the memory component
// and its storage to that user id.
AIAgent agent = chatClient.AsAIAgent(new ChatClientAgentOptions()
{
ChatOptions = new() { Instructions = "You are a friendly assistant. Always address the user by their name." },
AIContextProviders = [new UserInfoMemory(chatClient.AsIChatClient())]
});
// Create a new session for the conversation.
AgentSession session = await agent.CreateSessionAsync();
Console.WriteLine(">> Use session 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?", session));
Console.WriteLine(await agent.RunAsync("My name is RuaidhrĂ­", session));
Console.WriteLine(await agent.RunAsync("I am 20 years old", session));
// We can serialize the session. The serialized state will include the state of the memory component.
JsonElement sesionElement = await agent.SerializeSessionAsync(session);
Console.WriteLine("\n>> Use deserialized session with previously created memories\n");
// Later we can deserialize the session and continue the conversation with the previous memory component state.
var deserializedSession = await agent.DeserializeSessionAsync(sesionElement);
Console.WriteLine(await agent.RunAsync("What is my name and age?", deserializedSession));
Console.WriteLine("\n>> Read memories using memory component\n");
// It's possible to access the memory component via the agent's GetService method.
var userInfo = agent.GetService<UserInfoMemory>()?.GetUserInfo(deserializedSession);
// 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 session with previously created memories\n");
// It is also possible to set the memories using a memory component on an individual session.
// This is useful if we want to start a new session, but have it share the same memories as a previous session.
var newSession = await agent.CreateSessionAsync();
if (userInfo is not null && agent.GetService<UserInfoMemory>() is UserInfoMemory newSessionMemory)
{
newSessionMemory.SetUserInfo(newSession, 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?", newSession));
namespace SampleApp
{
/// <summary>
/// Sample memory component that can remember a user's name and age.
/// </summary>
internal sealed class UserInfoMemory : AIContextProvider
{
private readonly ProviderSessionState<UserInfo> _sessionState;
private readonly IChatClient _chatClient;
public UserInfoMemory(IChatClient chatClient, Func<AgentSession?, UserInfo>? stateInitializer = null)
: base(null, null)
{
this._sessionState = new ProviderSessionState<UserInfo>(
stateInitializer ?? (_ => new UserInfo()),
this.GetType().Name);
this._chatClient = chatClient;
}
public override string StateKey => this._sessionState.StateKey;
public UserInfo GetUserInfo(AgentSession session)
=> this._sessionState.GetOrInitializeState(session);
public void SetUserInfo(AgentSession session, UserInfo userInfo)
=> this._sessionState.SaveState(session, userInfo);
protected override async ValueTask StoreAIContextAsync(InvokedContext context, CancellationToken cancellationToken = default)
{
var userInfo = this._sessionState.GetOrInitializeState(context.Session);
// 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 ((userInfo.UserName is null || 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);
userInfo.UserName ??= result.Result.UserName;
userInfo.UserAge ??= result.Result.UserAge;
}
this._sessionState.SaveState(context.Session, userInfo);
}
protected override ValueTask<AIContext> ProvideAIContextAsync(InvokingContext context, CancellationToken cancellationToken = default)
{
var userInfo = this._sessionState.GetOrInitializeState(context.Session);
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(
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 {userInfo.UserName}.")
.AppendLine(
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 {userInfo.UserAge}.");
return new ValueTask<AIContext>(new AIContext
{
Instructions = instructions.ToString()
});
}
}
internal sealed class UserInfo
{
public string? UserName { get; set; }
public int? UserAge { get; set; }
}
}