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| Author | SHA1 | Date | |
|---|---|---|---|
+44          Laveesh RohraGitHubClaude Opus 4.5CopilotCopilot <175728472+Copilot@…Tao ChenKurtEvan MattsonSergeyMenshykhKorolev Dmitry Mark Wallace Copilot rogerbarretodependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Eduard van Valkenburg Dmytro Struk Chris Jose Luis Latorre Millas Jacob Alber Richard Ortega 刘邦学AI Stephen Toub Nico Möller Chris Gillum Giles Odigwe Phillip Hoff Ege Ozan Özyedek samueljohnsiby Evan Mattson Hao Luo Victor Dibia stephentoub Jacob Viau SuperKenVery Sunil Dutta Sunil Dutta budgetboardingai Syrine Chelly SergeyMenshykh westey takanori-terai claude89757 Gavin Aguiar Sukeesh eavanvalkenburg eavanvalkenburg Ao Chen Dina Suehiro Jones eoindoherty1 Darren Cohen Ben Thomas alliscode TaoChenOSU Shyju Krishnankutty |
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CopilotGitHubSergeyMenshykhCopilotcopilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>SergeyMenshykh |
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CopilotGitHubstephentoubcopilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>Roger Barreto |
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@@ -1,11 +1,15 @@
|
||||
{
|
||||
"name": "C# (.NET)",
|
||||
"image": "mcr.microsoft.com/devcontainers/dotnet:10.0",
|
||||
//"image": "mcr.microsoft.com/devcontainers/dotnet",
|
||||
// Workaround for https://github.com/devcontainers/images/issues/1752
|
||||
"build": {
|
||||
"dockerfile": "dotnet.Dockerfile"
|
||||
},
|
||||
"features": {
|
||||
"ghcr.io/devcontainers/features/dotnet:2.4.0": {},
|
||||
"ghcr.io/devcontainers/features/dotnet:2.4.2": {},
|
||||
"ghcr.io/devcontainers/features/powershell:1.5.1": {},
|
||||
"ghcr.io/devcontainers/features/azure-cli:1.2.8": {},
|
||||
"ghcr.io/devcontainers/features/docker-in-docker:2.12.4": {}
|
||||
"ghcr.io/devcontainers/features/azure-cli:1.2.9": {},
|
||||
"ghcr.io/devcontainers/features/docker-in-docker:2.14.0": {}
|
||||
},
|
||||
"workspaceFolder": "/workspaces/agent-framework/dotnet/",
|
||||
"customizations": {
|
||||
|
||||
@@ -0,0 +1,5 @@
|
||||
FROM mcr.microsoft.com/devcontainers/dotnet
|
||||
|
||||
# Remove Yarn repository with expired GPG key to prevent apt-get update failures
|
||||
# Tracking issue: https://github.com/devcontainers/images/issues/1752
|
||||
RUN rm -f /etc/apt/sources.list.d/yarn.list
|
||||
@@ -12,7 +12,7 @@ runs:
|
||||
docker rm -f dts-emulator
|
||||
fi
|
||||
echo "Starting Durable Task Scheduler Emulator"
|
||||
docker run -d --name dts-emulator -p 8080:8080 -p 8082:8082 mcr.microsoft.com/dts/dts-emulator:latest
|
||||
docker run -d --name dts-emulator -p 8080:8080 -p 8082:8082 -e DTS_USE_DYNAMIC_TASK_HUBS=true mcr.microsoft.com/dts/dts-emulator:latest
|
||||
echo "Waiting for Durable Task Scheduler Emulator to be ready"
|
||||
timeout 30 bash -c 'until curl --silent http://localhost:8080/healthz; do sleep 1; done'
|
||||
echo "Durable Task Scheduler Emulator is ready"
|
||||
|
||||
@@ -14,6 +14,8 @@ Here are some general guidelines that apply to all code.
|
||||
|
||||
- The top of all *.cs files should have a copyright notice: `// Copyright (c) Microsoft. All rights reserved.`
|
||||
- All public methods and classes should have XML documentation comments.
|
||||
- After adding, modifying or deleting code, run `dotnet build`, and then fix any reported build errors.
|
||||
- After adding or modifying code, run `dotnet format` to automatically fix any formatting errors.
|
||||
|
||||
### C# Sample Code Guidelines
|
||||
|
||||
|
||||
@@ -83,7 +83,7 @@ jobs:
|
||||
dotnet
|
||||
python
|
||||
workflow-samples
|
||||
|
||||
|
||||
# Start Cosmos DB Emulator for all integration tests and only for unit tests when CosmosDB changes happened)
|
||||
- name: Start Azure Cosmos DB Emulator
|
||||
if: ${{ runner.os == 'Windows' && (needs.paths-filter.outputs.cosmosDbChanges == 'true' || (github.event_name != 'pull_request' && matrix.integration-tests)) }}
|
||||
@@ -95,7 +95,7 @@ jobs:
|
||||
echo "COSMOS_EMULATOR_AVAILABLE=true" >> $env:GITHUB_ENV
|
||||
|
||||
- name: Setup dotnet
|
||||
uses: actions/setup-dotnet@v5.0.1
|
||||
uses: actions/setup-dotnet@v5.1.0
|
||||
with:
|
||||
global-json-file: ${{ github.workspace }}/dotnet/global.json
|
||||
- name: Build dotnet solutions
|
||||
@@ -139,7 +139,7 @@ jobs:
|
||||
popd
|
||||
popd
|
||||
rm -rf "$TEMP_DIR"
|
||||
|
||||
|
||||
- name: Run Unit Tests
|
||||
shell: bash
|
||||
run: |
|
||||
@@ -147,7 +147,7 @@ jobs:
|
||||
for project in $UT_PROJECTS; do
|
||||
# Query the project's target frameworks using MSBuild with the current configuration
|
||||
target_frameworks=$(dotnet msbuild $project -getProperty:TargetFrameworks -p:Configuration=${{ matrix.configuration }} -nologo 2>/dev/null | tr -d '\r')
|
||||
|
||||
|
||||
# Check if the project supports the target framework
|
||||
if [[ "$target_frameworks" == *"${{ matrix.targetFramework }}"* ]]; then
|
||||
if [[ "${{ matrix.targetFramework }}" == "${{ env.COVERAGE_FRAMEWORK }}" ]]; then
|
||||
@@ -165,8 +165,8 @@ jobs:
|
||||
COSMOSDB_KEY: C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw==
|
||||
|
||||
- name: Log event name and matrix integration-tests
|
||||
shell: bash
|
||||
run: echo "github.event_name:${{ github.event_name }} matrix.integration-tests:${{ matrix.integration-tests }} github.event.action:${{ github.event.action }} github.event.pull_request.merged:${{ github.event.pull_request.merged }}"
|
||||
shell: bash
|
||||
run: echo "github.event_name:${{ github.event_name }} matrix.integration-tests:${{ matrix.integration-tests }} github.event.action:${{ github.event.action }} github.event.pull_request.merged:${{ github.event.pull_request.merged }}"
|
||||
|
||||
- name: Azure CLI Login
|
||||
if: github.event_name != 'pull_request' && matrix.integration-tests
|
||||
@@ -192,10 +192,10 @@ jobs:
|
||||
for project in $INTEGRATION_TEST_PROJECTS; do
|
||||
# Query the project's target frameworks using MSBuild with the current configuration
|
||||
target_frameworks=$(dotnet msbuild $project -getProperty:TargetFrameworks -p:Configuration=${{ matrix.configuration }} -nologo 2>/dev/null | tr -d '\r')
|
||||
|
||||
|
||||
# Check if the project supports the target framework
|
||||
if [[ "$target_frameworks" == *"${{ matrix.targetFramework }}"* ]]; then
|
||||
dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx
|
||||
dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx --filter "Category!=IntegrationDisabled"
|
||||
else
|
||||
echo "Skipping $project - does not support target framework ${{ matrix.targetFramework }} (supports: $target_frameworks)"
|
||||
fi
|
||||
|
||||
@@ -29,4 +29,4 @@ jobs:
|
||||
token: ${{ secrets.GITHUB_TOKEN }}
|
||||
timeout: 3600
|
||||
interval: 30
|
||||
ignored: CodeQL
|
||||
ignored: CodeQL,CodeQL analysis (csharp)
|
||||
|
||||
@@ -34,9 +34,16 @@ jobs:
|
||||
# because the workflow_run event does not have access to the PR number
|
||||
# The PR number is needed to post the comment on the PR
|
||||
run: |
|
||||
PR_NUMBER=$(cat pr_number)
|
||||
echo "PR number: $PR_NUMBER"
|
||||
echo "PR_NUMBER=$PR_NUMBER" >> $GITHUB_ENV
|
||||
if [ ! -s pr_number ]; then
|
||||
echo "PR number file 'pr_number' is missing or empty"
|
||||
exit 1
|
||||
fi
|
||||
PR_NUMBER=$(head -1 pr_number | tr -dc '0-9')
|
||||
if [ -z "$PR_NUMBER" ]; then
|
||||
echo "PR number file 'pr_number' does not contain a valid PR number"
|
||||
exit 1
|
||||
fi
|
||||
echo "PR_NUMBER=$PR_NUMBER" >> "$GITHUB_ENV"
|
||||
- name: Pytest coverage comment
|
||||
id: coverageComment
|
||||
uses: MishaKav/pytest-coverage-comment@v1.2.0
|
||||
|
||||
+6
-5
@@ -209,13 +209,14 @@ WARP.md
|
||||
**/tmpclaude*
|
||||
|
||||
# Azurite storage emulator files
|
||||
*/__azurite_db_blob__.json
|
||||
*/__azurite_db_blob_extent__.json
|
||||
*/__azurite_db_queue__.json
|
||||
*/__azurite_db_queue_extent__.json
|
||||
*/__azurite_db_table__.json
|
||||
*/__azurite_db_blob__.json*
|
||||
*/__azurite_db_blob_extent__.json*
|
||||
*/__azurite_db_queue__.json*
|
||||
*/__azurite_db_queue_extent__.json*
|
||||
*/__azurite_db_table__.json*
|
||||
*/__blobstorage__/
|
||||
*/__queuestorage__/
|
||||
*/AzuriteConfig
|
||||
|
||||
# Azure Functions local settings
|
||||
local.settings.json
|
||||
|
||||
@@ -0,0 +1,423 @@
|
||||
---
|
||||
status: accepted
|
||||
contact: westey-m
|
||||
date: 2025-01-21
|
||||
deciders: sergeymenshykh, markwallace, rbarreto, westey-m, stephentoub
|
||||
consulted: reubenbond
|
||||
informed:
|
||||
---
|
||||
|
||||
# Feature Collections
|
||||
|
||||
## Context and Problem Statement
|
||||
|
||||
When using agents, we often have cases where we want to pass some arbitrary services or data to an agent or some component in the agent execution stack.
|
||||
These services or data are not necessarily known at compile time and can vary by the agent stack that the user has built.
|
||||
E.g., there may be an agent decorator or chat client decorator that was added to the stack by the user, and an arbitrary payload needs to be passed to that decorator.
|
||||
|
||||
Since these payloads are related to components that are not integral parts of the agent framework, they cannot be added as strongly typed settings to the agent run options.
|
||||
However, the payloads could be added to the agent run options as loosely typed 'features', that can be retrieved as needed.
|
||||
|
||||
In some cases certain classes of agents may support the same capability, but not all agents do.
|
||||
Having the configuration for such a capability on the main abstraction would advertise the functionality to all users, even if their chosen agent does not support it.
|
||||
The user may type test for certain agent types, and call overloads on the appropriate agent types, with the strongly typed configuration.
|
||||
Having a feature collection though, would be an alternative way of passing such configuration, without needing to type check the agent type.
|
||||
All agents that support the functionality would be able to check for the configuration and use it, simplifying the user code.
|
||||
If the agent does not support the capability, that configuration would be ignored.
|
||||
|
||||
### Sample Scenario 1 - Per Run ChatMessageStore Override for hosting Libraries
|
||||
|
||||
We are building an agent hosting library, that can host any agent built using the agent framework.
|
||||
Where an agent is not built on a service that uses in-service chat history storage, the hosting library wants to force the agent to use
|
||||
the hosting library's chat history storage implementation.
|
||||
This chat history storage implementation may be specifically tailored to the type of protocol that the hosting library uses, e.g. conversation id based storage or response id based storage.
|
||||
The hosting library does not know what type of agent it is hosting, so it cannot provide a strongly typed parameter on the agent.
|
||||
Instead, it adds the chat history storage implementation to a feature collection, and if the agent supports custom chat history storage, it retrieves the implementation from the feature collection and uses it.
|
||||
|
||||
```csharp
|
||||
// Pseudo-code for an agent hosting library that supports conversation id based hosting.
|
||||
public async Task<string> HandleConversationsBasedRequestAsync(AIAgent agent, string conversationId, string userInput)
|
||||
{
|
||||
var thread = await this._threadStore.GetOrCreateThread(conversationId);
|
||||
|
||||
// The hosting library can set a per-run chat message store via Features that only applies for that run.
|
||||
// This message store will load and save messages under the conversation id provided.
|
||||
ConversationsChatMessageStore messageStore = new(this._dbClient, conversationId);
|
||||
var response = await agent.RunAsync(
|
||||
userInput,
|
||||
thread,
|
||||
options: new AgentRunOptions()
|
||||
{
|
||||
Features = new AgentFeatureCollection().WithFeature<ChatMessageStore>(messageStore)
|
||||
});
|
||||
|
||||
await this._threadStore.SaveThreadAsync(conversationId, thread);
|
||||
return response.Text;
|
||||
}
|
||||
|
||||
// Pseudo-code for an agent hosting library that supports response id based hosting.
|
||||
public async Task<(string responseMessage, string responseId)> HandleResponseIdBasedRequestAsync(AIAgent agent, string previousResponseId, string userInput)
|
||||
{
|
||||
var thread = await this._threadStore.GetOrCreateThreadAsync(previousResponseId);
|
||||
|
||||
// The hosting library can set a per-run chat message store via Features that only applies for that run.
|
||||
// This message store will buffer newly added messages until explicitly saved after the run.
|
||||
ResponsesChatMessageStore messageStore = new(this._dbClient, previousResponseId);
|
||||
|
||||
var response = await agent.RunAsync(
|
||||
userInput,
|
||||
thread,
|
||||
options: new AgentRunOptions()
|
||||
{
|
||||
Features = new AgentFeatureCollection().WithFeature<ChatMessageStore>(messageStore)
|
||||
});
|
||||
|
||||
// Since the message store may not actually have been used at all (if the agent's underlying chat client requires service-based chat history storage),
|
||||
// we may not have anything to save back to the database.
|
||||
// We still want to generate a new response id though, so that we can save the updated thread state under that id.
|
||||
// We should also use the same id to save any buffered messages in the message store if there are any.
|
||||
var newResponseId = this.GenerateResponseId();
|
||||
if (messageStore.HasBufferedMessages)
|
||||
{
|
||||
await messageStore.SaveBufferedMessagesAsync(newResponseId);
|
||||
}
|
||||
|
||||
// Save the updated thread state under the new response id that was generated by the store.
|
||||
await this._threadStore.SaveThreadAsync(newResponseId, thread);
|
||||
return (response.Text, newResponseId);
|
||||
}
|
||||
```
|
||||
|
||||
### Sample Scenario 2 - Structured output
|
||||
|
||||
Currently our base abstraction does not support structured output, since the capability is not supported by all agents.
|
||||
For those agents that don't support structured output, we could add an agent decorator that takes the response from the underlying agent, and applies structured output parsing on top of it via an additional LLM call.
|
||||
|
||||
If we add structured output configuration as a feature, then any agent that supports structured output could retrieve the configuration from the feature collection and apply it, and where it is not supported, the configuration would simply be ignored.
|
||||
|
||||
We could add a simple StructuredOutputAgentFeature that can be added to the list of features and also be used to return the generated structured output.
|
||||
|
||||
```csharp
|
||||
internal class StructuredOutputAgentFeature
|
||||
{
|
||||
public Type? OutputType { get; set; }
|
||||
|
||||
public JsonSerializerOptions? SerializerOptions { get; set; }
|
||||
|
||||
public bool? UseJsonSchemaResponseFormat { get; set; }
|
||||
|
||||
// Contains the result of the structured output parsing request.
|
||||
public ChatResponse? ChatResponse { get; set; }
|
||||
}
|
||||
```
|
||||
|
||||
We can add a simple decorator class that does the chat client invocation.
|
||||
|
||||
```csharp
|
||||
public class StructuredOutputAgent : DelegatingAIAgent
|
||||
{
|
||||
private readonly IChatClient _chatClient;
|
||||
public StructuredOutputAgent(AIAgent innerAgent, IChatClient chatClient)
|
||||
: base(innerAgent)
|
||||
{
|
||||
this._chatClient = Throw.IfNull(chatClient);
|
||||
}
|
||||
|
||||
public override async Task<AgentRunResponse> RunAsync(
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentRunOptions? options = null,
|
||||
CancellationToken cancellationToken = default)
|
||||
{
|
||||
// Run the inner agent first, to get back the text response we want to convert.
|
||||
var response = await base.RunAsync(messages, thread, options, cancellationToken).ConfigureAwait(false);
|
||||
|
||||
if (options?.Features?.TryGet<StructuredOutputAgentFeature>(out var responseFormatFeature) is true
|
||||
&& responseFormatFeature.OutputType is not null)
|
||||
{
|
||||
// Create the chat options to request structured output.
|
||||
ChatOptions chatOptions = new()
|
||||
{
|
||||
ResponseFormat = ChatResponseFormat.ForJsonSchema(responseFormatFeature.OutputType, responseFormatFeature.SerializerOptions)
|
||||
};
|
||||
|
||||
// Invoke the chat client to transform the text output into structured data.
|
||||
// The feature is updated with the result.
|
||||
// The code can be simplified by adding a non-generic structured output GetResponseAsync
|
||||
// overload that takes Type as input.
|
||||
responseFormatFeature.ChatResponse = await this._chatClient.GetResponseAsync(
|
||||
messages: new[]
|
||||
{
|
||||
new ChatMessage(ChatRole.System, "You are a json expert and when provided with any text, will convert it to the requested json format."),
|
||||
new ChatMessage(ChatRole.User, response.Text)
|
||||
},
|
||||
options: chatOptions,
|
||||
cancellationToken: cancellationToken).ConfigureAwait(false);
|
||||
}
|
||||
|
||||
return response;
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
Finally, we can add an extension method on `AIAgent` that can add the feature to the run options and check the feature for the structured output result and add the deserialized result to the response.
|
||||
|
||||
```csharp
|
||||
public static async Task<AgentRunResponse<T>> RunAsync<T>(
|
||||
this AIAgent agent,
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
JsonSerializerOptions? serializerOptions = null,
|
||||
AgentRunOptions? options = null,
|
||||
bool? useJsonSchemaResponseFormat = null,
|
||||
CancellationToken cancellationToken = default)
|
||||
{
|
||||
// Create the structured output feature.
|
||||
var structuredOutputFeature = new StructuredOutputAgentFeature();
|
||||
structuredOutputFeature.OutputType = typeof(T);
|
||||
structuredOutputFeature.UseJsonSchemaResponseFormat = useJsonSchemaResponseFormat;
|
||||
|
||||
// Run the agent.
|
||||
options ??= new AgentRunOptions();
|
||||
options.Features ??= new AgentFeatureCollection();
|
||||
options.Features.Set(structuredOutputFeature);
|
||||
|
||||
var response = await agent.RunAsync(messages, thread, options, cancellationToken).ConfigureAwait(false);
|
||||
|
||||
// Deserialize the JSON output.
|
||||
if (structuredOutputFeature.ChatResponse is not null)
|
||||
{
|
||||
var typed = new ChatResponse<T>(structuredOutputFeature.ChatResponse, serializerOptions ?? AgentJsonUtilities.DefaultOptions);
|
||||
return new AgentRunResponse<T>(response, typed.Result);
|
||||
}
|
||||
|
||||
throw new InvalidOperationException("No structured output response was generated by the agent.");
|
||||
}
|
||||
```
|
||||
|
||||
We can then use the extension method with any agent that supports structured output or that has
|
||||
been decorated with the `StructuredOutputAgent` decorator.
|
||||
|
||||
```csharp
|
||||
agent = new StructuredOutputAgent(agent, chatClient);
|
||||
|
||||
AgentRunResponse<PersonInfo> response = await agent.RunAsync<PersonInfo>([new ChatMessage(
|
||||
ChatRole.User,
|
||||
"Please provide information about John Smith, who is a 35-year-old software engineer.")]);
|
||||
```
|
||||
|
||||
## Implementation Options
|
||||
|
||||
Three options were considered for implementing feature collections:
|
||||
|
||||
- **Option 1**: FeatureCollections similar to ASP.NET Core
|
||||
- **Option 2**: AdditionalProperties Dictionary
|
||||
- **Option 3**: IServiceProvider
|
||||
|
||||
Here are some comparisons about their suitability for our use case:
|
||||
|
||||
| Criteria | Feature Collection | Additional Properties | IServiceProvider |
|
||||
|------------------|--------------------|-----------------------|------------------|
|
||||
|Ease of use |✅ Good |❌ Bad |✅ Good |
|
||||
|User familiarity |❌ Bad |✅ Good |✅ Good |
|
||||
|Type safety |✅ Good |❌ Bad |✅ Good |
|
||||
|Ability to modify registered options when progressing down the stack|✅ Supported|✅ Supported|❌ Not-Supported (IServiceProvider is read-only)|
|
||||
|Already available in MEAI stack|❌ No|✅ Yes|❌ No|
|
||||
|Ambiguity with existing AdditionalProperties|❌ Yes|✅ No|❌ Yes|
|
||||
|
||||
## IServiceProvider
|
||||
|
||||
Service Collections and Service Providers provide a very popular way to register and retrieve services by type and could be used as a way to pass features to agents and chat clients.
|
||||
|
||||
However, since IServiceProvider is read-only, it is not possible to modify the registered services when progressing down the execution stack.
|
||||
E.g. an agent decorator cannot add additional services to the IServiceProvider passed to it when calling into the inner agent.
|
||||
|
||||
IServiceProvider also does not expose a way to list all services contained in it, making it difficult to copy services from one provider to another.
|
||||
|
||||
This lack of mutability makes IServiceProvider unsuitable for our use case, since we will not be able to use it to build sample scenario 2.
|
||||
|
||||
## AdditionalProperties dictionary
|
||||
|
||||
The AdditionalProperties dictionary is already available on various options classes in the agent framework as well as in the MEAI stack and
|
||||
allows storing arbitrary key/value pairs, where the key is a string and the value is an object.
|
||||
|
||||
While FeatureCollection uses Type as a key, AdditionalProperties uses string keys.
|
||||
This means that users need to agree on string keys to use for specific features, however it is also possible to use Type.FullName as a key by convention
|
||||
to avoid key collisions, which is an easy convention to follow.
|
||||
|
||||
Since the value of AdditionalProperties is of type object, users need to cast the value to the expected type when retrieving it, which is also
|
||||
a drawback, but when using the convention of using Type.FullName as a key, there is at least a clear expectation of what type to cast to.
|
||||
|
||||
```csharp
|
||||
// Setting a feature
|
||||
options.AdditionalProperties[typeof(MyFeature).FullName] = new MyFeature();
|
||||
|
||||
// Retrieving a feature
|
||||
if (options.AdditionalProperties.TryGetValue(typeof(MyFeature).FullName, out var featureObj)
|
||||
&& featureObj is MyFeature myFeature)
|
||||
{
|
||||
// Use myFeature
|
||||
}
|
||||
```
|
||||
|
||||
It would also be possible to add extension methods to simplify setting and getting features from AdditionalProperties.
|
||||
Having a base class for features should help make this more feature rich.
|
||||
|
||||
```csharp
|
||||
// Setting a feature, this can use Type.FullName as the key.
|
||||
options.AdditionalProperties
|
||||
.WithFeature(new MyFeature());
|
||||
|
||||
// Retrieving a feature, this can use Type.FullName as the key.
|
||||
if (options.AdditionalProperties.TryGetFeature<MyFeature>(out var myFeature))
|
||||
{
|
||||
// Use myFeature
|
||||
}
|
||||
```
|
||||
|
||||
It would also be possible to add extension methods for a feature to simplify setting and getting features from AdditionalProperties.
|
||||
|
||||
```csharp
|
||||
// Setting a feature
|
||||
options.AdditionalProperties
|
||||
.WithMyFeature(new MyFeature());
|
||||
// Retrieving a feature
|
||||
if (options.AdditionalProperties.TryGetMyFeature(out var myFeature))
|
||||
{
|
||||
// Use myFeature
|
||||
}
|
||||
```
|
||||
|
||||
## Feature Collection
|
||||
|
||||
If we choose the feature collection option, we need to decide on the design of the feature collection itself.
|
||||
|
||||
### Feature Collections extension points
|
||||
|
||||
We need to decide the set of actions that feature collections would be supported for. Here is the suggested list of actions:
|
||||
|
||||
**MAAI.AIAgent:**
|
||||
|
||||
1. GetNewThread
|
||||
1. E.g. this would allow passing an already existing storage id for the thread to use, or an initialized custom chat message store to use.
|
||||
1. DeserializeThread
|
||||
1. E.g. this would allow passing an already existing storage id for the thread to use, or an initialized custom chat message store to use.
|
||||
1. Run / RunStreaming
|
||||
1. E.g. this would allow passing an override chat message store just for that run, or a desired schema for a structured output middleware component.
|
||||
|
||||
**MEAI.ChatClient:**
|
||||
|
||||
1. GetResponse / GetStreamingResponse
|
||||
|
||||
### Reconciling with existing AdditionalProperties
|
||||
|
||||
If we decide to add feature collections, separately from the existing AdditionalProperties dictionaries, we need to consider how to explain to users when to use each one.
|
||||
One possible approach though is to have the one use the other under the hood.
|
||||
AdditionalProperties could be stored as a feature in the feature collection.
|
||||
|
||||
Users would be able to retrieve additional properties from the feature collection, in addition to retrieving it via a dedicated AdditionalProperties property.
|
||||
E.g. `features.Get<AdditionalPropertiesDictionary>()`
|
||||
|
||||
One challenge with this approach is that when setting a value in the AdditionalProperties dictionary, the feature collection would need to be created first if it does not already exist.
|
||||
|
||||
```csharp
|
||||
public class AgentRunOptions
|
||||
{
|
||||
public AdditionalPropertiesDictionary? AdditionalProperties { get; set; }
|
||||
public IAgentFeatureCollection? Features { get; set; }
|
||||
}
|
||||
|
||||
var options = new AgentRunOptions();
|
||||
// This would need to create the feature collection first, if it does not already exist.
|
||||
options.AdditionalProperties ??= new AdditionalPropertiesDictionary();
|
||||
```
|
||||
|
||||
Since IAgentFeatureCollection is an interface, AgentRunOptions would need to have a concrete implementation of the interface to create, meaning that the user cannot decide.
|
||||
It also means that if the user doesn't realise that AdditionalProperties is implemented using feature collections, they may set a value on AdditionalProperties, and then later overwrite the entire feature collection, losing the AdditionalProperties feature.
|
||||
|
||||
Options to avoid these issues:
|
||||
|
||||
1. Make `Features` readonly.
|
||||
1. This would prevent the user from overwriting the feature collection after setting AdditionalProperties.
|
||||
1. Since the user cannot set their own implementation of IAgentFeatureCollection, having an interface for it may not be necessary.
|
||||
|
||||
### Feature Collection Implementation
|
||||
|
||||
We have two options for implementing feature collections:
|
||||
|
||||
1. Create our own [IAgentFeatureCollection interface](https://github.com/microsoft/agent-framework/pull/2354/files#diff-9c42f3e60d70a791af9841d9214e038c6de3eebfc10e3997cb4cdffeb2f1246d) and [implementation](https://github.com/microsoft/agent-framework/pull/2354/files#diff-a435cc738baec500b8799f7f58c1538e3bb06c772a208afc2615ff90ada3f4ca).
|
||||
2. Reuse the asp.net [IFeatureCollection interface](https://github.com/dotnet/aspnetcore/blob/main/src/Extensions/Features/src/IFeatureCollection.cs) and [implementation](https://github.com/dotnet/aspnetcore/blob/main/src/Extensions/Features/src/FeatureCollection.cs).
|
||||
|
||||
#### Roll our own
|
||||
|
||||
Advantages:
|
||||
|
||||
Creating our own IAgentFeatureCollection interface and implementation has the advantage of being more clearly associated with the agent framework and allows us to
|
||||
improve on some of the design decisions made in asp.net core's IFeatureCollection.
|
||||
|
||||
Drawbacks:
|
||||
|
||||
It would mean a different implementation to maintain and test.
|
||||
|
||||
#### Reuse asp.net IFeatureCollection
|
||||
|
||||
Advantages:
|
||||
|
||||
Reusing the asp.net IFeatureCollection has the advantage of being able to reuse the well-established and tested implementation from asp.net
|
||||
core. Users who are using agents in an asp.net core application may be able to pass feature collections from asp.net core to the agent framework directly.
|
||||
|
||||
Drawbacks:
|
||||
|
||||
While the package name is `Microsoft.Extensions.Features`, the namespaces of the types are `Microsoft.AspNetCore.Http.Features`, which may create confusion for users of agent framework who are not building web applications or services.
|
||||
Users may rightly ask: Why do I need to use a class from asp.net core when I'm not building a web application / service?
|
||||
|
||||
The current design has some design issues that would be good to avoid. E.g. it does not distinguish between a feature being "not set" and "null". Get returns both as null and there is no tryget method.
|
||||
Since the [default implementation](https://github.com/dotnet/aspnetcore/blob/main/src/Extensions/Features/src/FeatureCollection.cs) also supports value types, it throws for null values of value types.
|
||||
A TryGet method would be more appropriate.
|
||||
|
||||
## Feature Layering
|
||||
|
||||
One possible scenario when adding support for feature collections is to allow layering of features by scope.
|
||||
|
||||
The following levels of scope could be supported:
|
||||
|
||||
1. Application - Application wide features that apply to all agents / chat clients
|
||||
2. Artifact (Agent / ChatClient) - Features that apply to all runs of a specific agent or chat client instance
|
||||
3. Action (GetNewThread / Run / GetResponse) - Feature that apply to a single action only
|
||||
|
||||
When retrieving a feature from the collection, the search would start from the most specific scope (Action) and progress to the least specific scope (Application), returning the first matching feature found.
|
||||
|
||||
Introducing layering adds some challenges:
|
||||
|
||||
- There may be multiple feature collections at the same scope level, e.g. an Agent that uses a ChatClient where both have their own feature collections.
|
||||
- Do we layer the agent feature collection over the chat client feature collection (Application -> ChatClient -> Agent -> Run), or only use the agent feature collection in the agent (Application -> Agent -> Run), and the chat client feature collection in the chat client (Application -> ChatClient -> Run)?
|
||||
- The appropriate base feature collection may change when progressing down the stack, e.g. when an Agent calls a ChatClient, the action feature collection stays the same, but the artifact feature collection changes.
|
||||
- Who creates the feature collection hierarchy?
|
||||
- Since the hierarchy changes as it progresses down the execution stack, and the caller can only pass in the action level feature collection, the callee needs to combine it with its own artifact level feature collection and the application level feature collection. Each action will need to build the appropriate feature collection hierarchy, at the start of its execution.
|
||||
- For Artifact level features, it seems odd to pass them in as a bag of untyped features, when we are constructing a known artifact type and therefore can have typed settings.
|
||||
- E.g. today we have a strongly typed setting on ChatClientAgentOptions to configure a ChatMessageStore for the agent.
|
||||
- To avoid global statics for application level features, the user would need to pass in the application level feature collection to each artifact that they create.
|
||||
- This would be very odd if the user also already has to strongly typed settings for each feature that they want to set at the artifact level.
|
||||
|
||||
### Layering Options
|
||||
|
||||
1. No layering - only a single feature collection is supported per action (the caller can still create a layered collection if desired, but the callee does not do any layering automatically).
|
||||
1. Fallback is to any features configured on the artifact via strongly typed settings.
|
||||
1. Full layering - support layering at all levels (Application -> Artifact -> Action).
|
||||
1. Only apply applicable artifact level features when calling into that artifact.
|
||||
1. Apply upstream artifact features when calling into downstream artifacts, e.g. Feature hierarchy in ChatClientAgent would be `Application -> Agent -> Run` and in ChatClient would be `Application -> ChatClient -> Agent -> Run` or `Application -> Agent -> ChatClient -> Run`
|
||||
1. The user needs to provide the application level feature collection to each artifact that they create and artifact features are passed via strongly typed settings.
|
||||
|
||||
### Accessing application level features Options
|
||||
|
||||
We need to consider how application level features would be accessed if supported.
|
||||
|
||||
1. The user provides the application level feature collection to each artifact that the user constructs
|
||||
1. Passing the application level feature collection to each artifact is tedious for the user.
|
||||
1. There is a static application level feature collection that can be accessed globally.
|
||||
1. Statics create issues with testing and isolation.
|
||||
|
||||
## Decisions
|
||||
|
||||
- Feature Collections Container: Use AdditionalProperties
|
||||
- Feature Layering: No layering - only a single collection/dictionary is supported per action. Application layers can be added later if needed.
|
||||
@@ -33,18 +33,18 @@
|
||||
<!-- Newtonsoft.Json -->
|
||||
<PackageVersion Include="Newtonsoft.Json" Version="13.0.4" />
|
||||
<!-- System.* -->
|
||||
<PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.1" />
|
||||
<PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.2" />
|
||||
<PackageVersion Include="Microsoft.Bcl.HashCode" Version="6.0.0" />
|
||||
<PackageVersion Include="System.ClientModel" Version="1.8.1" />
|
||||
<PackageVersion Include="System.CodeDom" Version="10.0.0" />
|
||||
<PackageVersion Include="System.Collections.Immutable" Version="10.0.0" />
|
||||
<PackageVersion Include="System.CommandLine" Version="2.0.0-rc.2.25502.107" />
|
||||
<PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="10.0.1" />
|
||||
<PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="10.0.2" />
|
||||
<PackageVersion Include="System.Linq.AsyncEnumerable" Version="10.0.0" />
|
||||
<PackageVersion Include="System.Net.Http.Json" Version="10.0.0" />
|
||||
<PackageVersion Include="System.Net.ServerSentEvents" Version="10.0.0" />
|
||||
<PackageVersion Include="System.Text.Json" Version="10.0.1" />
|
||||
<PackageVersion Include="System.Threading.Channels" Version="10.0.1" />
|
||||
<PackageVersion Include="System.Text.Json" Version="10.0.2" />
|
||||
<PackageVersion Include="System.Threading.Channels" Version="10.0.2" />
|
||||
<PackageVersion Include="System.Threading.Tasks.Extensions" Version="4.6.3" />
|
||||
<PackageVersion Include="System.Net.Security" Version="4.3.2" />
|
||||
<!-- OpenTelemetry -->
|
||||
@@ -61,9 +61,9 @@
|
||||
<PackageVersion Include="Microsoft.AspNetCore.OpenApi" Version="10.0.0" />
|
||||
<PackageVersion Include="Swashbuckle.AspNetCore.SwaggerUI" Version="10.0.0" />
|
||||
<!-- Microsoft.Extensions.* -->
|
||||
<PackageVersion Include="Microsoft.Extensions.AI" Version="10.1.1" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.1.1" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.1.1-preview.1.25612.2" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI" Version="10.2.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.2.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.2.0-preview.1.26063.2" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Caching.Memory" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Configuration" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Configuration.Binder" Version="10.0.0" />
|
||||
@@ -71,11 +71,11 @@
|
||||
<PackageVersion Include="Microsoft.Extensions.Configuration.Json" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Configuration.UserSecrets" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.DependencyInjection" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="10.0.1" />
|
||||
<PackageVersion Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="10.0.2" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Hosting" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Http.Resilience" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Logging" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Logging.Abstractions" Version="10.0.1" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Logging.Abstractions" Version="10.0.2" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Logging.Console" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.ServiceDiscovery" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.VectorData.Abstractions" Version="9.7.0" />
|
||||
@@ -89,6 +89,7 @@
|
||||
<PackageVersion Include="Microsoft.SemanticKernel.Agents.AzureAI" Version="1.67.0-preview" />
|
||||
<PackageVersion Include="Microsoft.SemanticKernel.Plugins.OpenApi" Version="1.67.0" />
|
||||
<!-- Agent SDKs -->
|
||||
<PackageVersion Include="GitHub.Copilot.SDK" Version="0.1.18" />
|
||||
<PackageVersion Include="Microsoft.Agents.CopilotStudio.Client" Version="1.3.171-beta" />
|
||||
<!-- M365 Agents SDK -->
|
||||
<PackageVersion Include="AdaptiveCards" Version="3.1.0" />
|
||||
@@ -143,6 +144,7 @@
|
||||
<!-- Symbols -->
|
||||
<PackageVersion Include="Microsoft.SourceLink.GitHub" Version="8.0.0" />
|
||||
<!-- Toolset -->
|
||||
<PackageVersion Include="Microsoft.CodeAnalysis.Analyzers" Version="3.11.0" />
|
||||
<PackageVersion Include="Microsoft.CodeAnalysis.CSharp" Version="4.14.0" />
|
||||
<PackageVersion Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="10.0.100" />
|
||||
<PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers">
|
||||
|
||||
@@ -35,6 +35,18 @@
|
||||
<Project Path="samples/AzureFunctions/07_AgentAsMcpTool/07_AgentAsMcpTool.csproj" />
|
||||
<Project Path="samples/AzureFunctions/08_ReliableStreaming/08_ReliableStreaming.csproj" />
|
||||
</Folder>
|
||||
<Folder Name="/Samples/DurableAgents/">
|
||||
<File Path="samples/DurableAgents/ConsoleApps/README.md" />
|
||||
</Folder>
|
||||
<Folder Name="/Samples/DurableAgents/ConsoleApps/">
|
||||
<Project Path="samples/DurableAgents/ConsoleApps/01_SingleAgent/01_SingleAgent.csproj" />
|
||||
<Project Path="samples/DurableAgents/ConsoleApps/02_AgentOrchestration_Chaining/02_AgentOrchestration_Chaining.csproj" />
|
||||
<Project Path="samples/DurableAgents/ConsoleApps/03_AgentOrchestration_Concurrency/03_AgentOrchestration_Concurrency.csproj" />
|
||||
<Project Path="samples/DurableAgents/ConsoleApps/04_AgentOrchestration_Conditionals/04_AgentOrchestration_Conditionals.csproj" />
|
||||
<Project Path="samples/DurableAgents/ConsoleApps/05_AgentOrchestration_HITL/05_AgentOrchestration_HITL.csproj" />
|
||||
<Project Path="samples/DurableAgents/ConsoleApps/06_LongRunningTools/06_LongRunningTools.csproj" />
|
||||
<Project Path="samples/DurableAgents/ConsoleApps/07_ReliableStreaming/07_ReliableStreaming.csproj" />
|
||||
</Folder>
|
||||
<Folder Name="/Samples/GettingStarted/">
|
||||
<File Path="samples/GettingStarted/README.md" />
|
||||
</Folder>
|
||||
@@ -53,6 +65,7 @@
|
||||
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureOpenAIChatCompletion/Agent_With_AzureOpenAIChatCompletion.csproj" />
|
||||
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureOpenAIResponses/Agent_With_AzureOpenAIResponses.csproj" />
|
||||
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_CustomImplementation/Agent_With_CustomImplementation.csproj" />
|
||||
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_GithubCopilot/Agent_With_GithubCopilot.csproj" />
|
||||
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_GoogleGemini/Agent_With_GoogleGemini.csproj" />
|
||||
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_Ollama/Agent_With_Ollama.csproj" />
|
||||
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_ONNX/Agent_With_ONNX.csproj" />
|
||||
@@ -81,6 +94,7 @@
|
||||
<Project Path="samples/GettingStarted/Agents/Agent_Step17_BackgroundResponses/Agent_Step17_BackgroundResponses.csproj" />
|
||||
<Project Path="samples/GettingStarted/Agents/Agent_Step18_DeepResearch/Agent_Step18_DeepResearch.csproj" />
|
||||
<Project Path="samples/GettingStarted/Agents/Agent_Step19_Declarative/Agent_Step19_Declarative.csproj" />
|
||||
<Project Path="samples/GettingStarted/Agents/Agent_Step20_AdditionalAIContext/Agent_Step20_AdditionalAIContext.csproj" />
|
||||
</Folder>
|
||||
<Folder Name="/Samples/GettingStarted/DeclarativeAgents/">
|
||||
<Project Path="samples/GettingStarted/DeclarativeAgents/ChatClient/DeclarativeChatClientAgents.csproj" />
|
||||
@@ -216,6 +230,7 @@
|
||||
<Folder Name="/Samples/GettingStarted/Workflows/Agents/">
|
||||
<Project Path="samples/GettingStarted/Workflows/Agents/CustomAgentExecutors/CustomAgentExecutors.csproj" />
|
||||
<Project Path="samples/GettingStarted/Workflows/Agents/FoundryAgent/FoundryAgent.csproj" />
|
||||
<Project Path="samples/GettingStarted/Workflows/Agents/GroupChatToolApproval/GroupChatToolApproval.csproj" />
|
||||
<Project Path="samples/GettingStarted/Workflows/Agents/WorkflowAsAnAgent/WorkflowAsAnAgent.csproj" />
|
||||
</Folder>
|
||||
<Folder Name="/Samples/GettingStarted/Workflows/Checkpoint/">
|
||||
@@ -286,6 +301,11 @@
|
||||
<File Path="../docs/decisions/0007-agent-filtering-middleware.md" />
|
||||
<File Path="../docs/decisions/0008-python-subpackages.md" />
|
||||
<File Path="../docs/decisions/0009-support-long-running-operations.md" />
|
||||
<File Path="../docs/decisions/0010-ag-ui-support.md" />
|
||||
<File Path="../docs/decisions/0011-create-get-agent-api.md" />
|
||||
<File Path="../docs/decisions/0012-python-typeddict-options.md" />
|
||||
<File Path="../docs/decisions/0013-python-get-response-simplification.md" />
|
||||
<File Path="../docs/decisions/0014-feature-collections.md" />
|
||||
<File Path="../docs/decisions/adr-short-template.md" />
|
||||
<File Path="../docs/decisions/adr-template.md" />
|
||||
<File Path="../docs/decisions/README.md" />
|
||||
@@ -377,6 +397,7 @@
|
||||
<Project Path="src/Microsoft.Agents.AI.Abstractions/Microsoft.Agents.AI.Abstractions.csproj" />
|
||||
<Project Path="src/Microsoft.Agents.AI.AGUI/Microsoft.Agents.AI.AGUI.csproj" />
|
||||
<Project Path="src/Microsoft.Agents.AI.Anthropic/Microsoft.Agents.AI.Anthropic.csproj" />
|
||||
<Project Path="src/Microsoft.Agents.AI.GithubCopilot/Microsoft.Agents.AI.GithubCopilot.csproj" />
|
||||
<Project Path="src/Microsoft.Agents.AI.AzureAI.Persistent/Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
|
||||
<Project Path="src/Microsoft.Agents.AI.AzureAI/Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
<Project Path="src/Microsoft.Agents.AI.CopilotStudio/Microsoft.Agents.AI.CopilotStudio.csproj" />
|
||||
@@ -396,6 +417,7 @@
|
||||
<Project Path="src/Microsoft.Agents.AI.Workflows.Declarative.AzureAI/Microsoft.Agents.AI.Workflows.Declarative.AzureAI.csproj" />
|
||||
<Project Path="src/Microsoft.Agents.AI.Workflows.Declarative/Microsoft.Agents.AI.Workflows.Declarative.csproj" />
|
||||
<Project Path="src/Microsoft.Agents.AI.Workflows/Microsoft.Agents.AI.Workflows.csproj" />
|
||||
<Project Path="src/Microsoft.Agents.AI.Workflows.Generators/Microsoft.Agents.AI.Workflows.Generators.csproj" />
|
||||
<Project Path="src/Microsoft.Agents.AI/Microsoft.Agents.AI.csproj" />
|
||||
</Folder>
|
||||
<Folder Name="/Tests/" />
|
||||
@@ -405,6 +427,7 @@
|
||||
<Project Path="tests/AzureAI.IntegrationTests/AzureAI.IntegrationTests.csproj" />
|
||||
<Project Path="tests/AzureAIAgentsPersistent.IntegrationTests/AzureAIAgentsPersistent.IntegrationTests.csproj" />
|
||||
<Project Path="tests/CopilotStudio.IntegrationTests/CopilotStudio.IntegrationTests.csproj" />
|
||||
<Project Path="tests/Microsoft.Agents.AI.GithubCopilot.IntegrationTests/Microsoft.Agents.AI.GithubCopilot.IntegrationTests.csproj" />
|
||||
<Project Path="tests/Microsoft.Agents.AI.DurableTask.IntegrationTests/Microsoft.Agents.AI.DurableTask.IntegrationTests.csproj" />
|
||||
<Project Path="tests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.IntegrationTests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.IntegrationTests.csproj" />
|
||||
<Project Path="tests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests.csproj" />
|
||||
@@ -419,6 +442,7 @@
|
||||
<Project Path="tests/Microsoft.Agents.AI.Abstractions.UnitTests/Microsoft.Agents.AI.Abstractions.UnitTests.csproj" />
|
||||
<Project Path="tests/Microsoft.Agents.AI.AGUI.UnitTests/Microsoft.Agents.AI.AGUI.UnitTests.csproj" />
|
||||
<Project Path="tests/Microsoft.Agents.AI.Anthropic.UnitTests/Microsoft.Agents.AI.Anthropic.UnitTests.csproj" />
|
||||
<Project Path="tests/Microsoft.Agents.AI.GithubCopilot.UnitTests/Microsoft.Agents.AI.GithubCopilot.UnitTests.csproj" />
|
||||
<Project Path="tests/Microsoft.Agents.AI.AzureAI.Persistent.UnitTests/Microsoft.Agents.AI.AzureAI.Persistent.UnitTests.csproj" />
|
||||
<Project Path="tests/Microsoft.Agents.AI.AzureAI.UnitTests/Microsoft.Agents.AI.AzureAI.UnitTests.csproj" />
|
||||
<Project Path="tests/Microsoft.Agents.AI.CosmosNoSql.UnitTests/Microsoft.Agents.AI.CosmosNoSql.UnitTests.csproj" />
|
||||
@@ -435,6 +459,7 @@
|
||||
<Project Path="tests/Microsoft.Agents.AI.Purview.UnitTests/Microsoft.Agents.AI.Purview.UnitTests.csproj" />
|
||||
<Project Path="tests/Microsoft.Agents.AI.UnitTests/Microsoft.Agents.AI.UnitTests.csproj" />
|
||||
<Project Path="tests/Microsoft.Agents.AI.Workflows.Declarative.UnitTests/Microsoft.Agents.AI.Workflows.Declarative.UnitTests.csproj" />
|
||||
<Project Path="tests/Microsoft.Agents.AI.Workflows.Generators.UnitTests/Microsoft.Agents.AI.Workflows.Generators.UnitTests.csproj" />
|
||||
<Project Path="tests/Microsoft.Agents.AI.Workflows.UnitTests/Microsoft.Agents.AI.Workflows.UnitTests.csproj" />
|
||||
</Folder>
|
||||
</Solution>
|
||||
@@ -6,6 +6,7 @@
|
||||
"src\\Microsoft.Agents.AI.Abstractions\\Microsoft.Agents.AI.Abstractions.csproj",
|
||||
"src\\Microsoft.Agents.AI.AGUI\\Microsoft.Agents.AI.AGUI.csproj",
|
||||
"src\\Microsoft.Agents.AI.Anthropic\\Microsoft.Agents.AI.Anthropic.csproj",
|
||||
"src\\Microsoft.Agents.AI.GithubCopilot\\Microsoft.Agents.AI.GithubCopilot.csproj",
|
||||
"src\\Microsoft.Agents.AI.AzureAI.Persistent\\Microsoft.Agents.AI.AzureAI.Persistent.csproj",
|
||||
"src\\Microsoft.Agents.AI.AzureAI\\Microsoft.Agents.AI.AzureAI.csproj",
|
||||
"src\\Microsoft.Agents.AI.CopilotStudio\\Microsoft.Agents.AI.CopilotStudio.csproj",
|
||||
|
||||
@@ -2,9 +2,9 @@
|
||||
<PropertyGroup>
|
||||
<!-- Central version prefix - applies to all nuget packages. -->
|
||||
<VersionPrefix>1.0.0</VersionPrefix>
|
||||
<PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).260108.1</PackageVersion>
|
||||
<PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.260108.1</PackageVersion>
|
||||
<GitTag>1.0.0-preview.260108.1</GitTag>
|
||||
<PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).260127.1</PackageVersion>
|
||||
<PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.260127.1</PackageVersion>
|
||||
<GitTag>1.0.0-preview.260127.1</GitTag>
|
||||
|
||||
<Configurations>Debug;Release;Publish</Configurations>
|
||||
<IsPackable>true</IsPackable>
|
||||
|
||||
@@ -42,7 +42,7 @@ public static class Program
|
||||
// Create the Host agent
|
||||
var hostAgent = new HostClientAgent(loggerFactory);
|
||||
await hostAgent.InitializeAgentAsync(modelId, apiKey, agentUrls!.Split(";"));
|
||||
AgentThread thread = await hostAgent.Agent!.GetNewThreadAsync(cancellationToken);
|
||||
AgentSession session = await hostAgent.Agent!.GetNewSessionAsync(cancellationToken);
|
||||
try
|
||||
{
|
||||
while (true)
|
||||
@@ -61,7 +61,7 @@ public static class Program
|
||||
break;
|
||||
}
|
||||
|
||||
var agentResponse = await hostAgent.Agent!.RunAsync(message, thread, cancellationToken: cancellationToken);
|
||||
var agentResponse = await hostAgent.Agent!.RunAsync(message, session, cancellationToken: cancellationToken);
|
||||
foreach (var chatMessage in agentResponse.Messages)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Cyan;
|
||||
|
||||
@@ -88,7 +88,7 @@ public static class Program
|
||||
description: "AG-UI Client Agent",
|
||||
tools: [changeBackground, readClientClimateSensors]);
|
||||
|
||||
AgentThread thread = await agent.GetNewThreadAsync(cancellationToken);
|
||||
AgentSession session = await agent.GetNewSessionAsync(cancellationToken);
|
||||
List<ChatMessage> messages = [new(ChatRole.System, "You are a helpful assistant.")];
|
||||
try
|
||||
{
|
||||
@@ -112,23 +112,23 @@ public static class Program
|
||||
|
||||
// Call RunStreamingAsync to get streaming updates
|
||||
bool isFirstUpdate = true;
|
||||
string? threadId = null;
|
||||
string? sessionId = null;
|
||||
var updates = new List<ChatResponseUpdate>();
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread, cancellationToken: cancellationToken))
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, session, cancellationToken: cancellationToken))
|
||||
{
|
||||
// Use AsChatResponseUpdate to access ChatResponseUpdate properties
|
||||
ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();
|
||||
updates.Add(chatUpdate);
|
||||
if (chatUpdate.ConversationId != null)
|
||||
{
|
||||
threadId = chatUpdate.ConversationId;
|
||||
sessionId = chatUpdate.ConversationId;
|
||||
}
|
||||
|
||||
// Display run started information from the first update
|
||||
if (isFirstUpdate && threadId != null && update.ResponseId != null)
|
||||
if (isFirstUpdate && sessionId != null && update.ResponseId != null)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine($"\n[Run Started - Thread: {threadId}, Run: {update.ResponseId}]");
|
||||
Console.WriteLine($"\n[Run Started - Session: {sessionId}, Run: {update.ResponseId}]");
|
||||
Console.ResetColor();
|
||||
isFirstUpdate = false;
|
||||
}
|
||||
@@ -177,7 +177,7 @@ public static class Program
|
||||
var lastUpdate = updates[^1];
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine();
|
||||
Console.WriteLine($"[Run Ended - Thread: {threadId}, Run: {lastUpdate.ResponseId}]");
|
||||
Console.WriteLine($"[Run Ended - Session: {sessionId}, Run: {lastUpdate.ResponseId}]");
|
||||
Console.ResetColor();
|
||||
}
|
||||
messages.Clear();
|
||||
|
||||
@@ -19,21 +19,21 @@ internal sealed class AgenticUIAgent : DelegatingAIAgent
|
||||
this._jsonSerializerOptions = jsonSerializerOptions;
|
||||
}
|
||||
|
||||
protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
|
||||
protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentSession? session = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
|
||||
{
|
||||
return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
|
||||
return this.RunCoreStreamingAsync(messages, session, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
|
||||
}
|
||||
|
||||
protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
[EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
// Track function calls that should trigger state events
|
||||
var trackedFunctionCalls = new Dictionary<string, FunctionCallContent>();
|
||||
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, thread, options, cancellationToken).ConfigureAwait(false))
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, session, options, cancellationToken).ConfigureAwait(false))
|
||||
{
|
||||
// Process contents: track function calls and emit state events for results
|
||||
List<AIContent> stateEventsToEmit = new();
|
||||
|
||||
+4
-4
@@ -20,21 +20,21 @@ internal sealed class PredictiveStateUpdatesAgent : DelegatingAIAgent
|
||||
this._jsonSerializerOptions = jsonSerializerOptions;
|
||||
}
|
||||
|
||||
protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
|
||||
protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentSession? session = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
|
||||
{
|
||||
return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
|
||||
return this.RunCoreStreamingAsync(messages, session, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
|
||||
}
|
||||
|
||||
protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
[EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
// Track the last emitted document state to avoid duplicates
|
||||
string? lastEmittedDocument = null;
|
||||
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, thread, options, cancellationToken).ConfigureAwait(false))
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, session, options, cancellationToken).ConfigureAwait(false))
|
||||
{
|
||||
// Check if we're seeing a write_document tool call and emit predictive state
|
||||
bool hasToolCall = false;
|
||||
|
||||
@@ -19,21 +19,21 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
|
||||
this._jsonSerializerOptions = jsonSerializerOptions;
|
||||
}
|
||||
|
||||
protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
|
||||
protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentSession? session = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
|
||||
{
|
||||
return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
|
||||
return this.RunCoreStreamingAsync(messages, session, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
|
||||
}
|
||||
|
||||
protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
[EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
if (options is not ChatClientAgentRunOptions { ChatOptions.AdditionalProperties: { } properties } chatRunOptions ||
|
||||
!properties.TryGetValue("ag_ui_state", out JsonElement state))
|
||||
{
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, thread, options, cancellationToken).ConfigureAwait(false))
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, session, options, cancellationToken).ConfigureAwait(false))
|
||||
{
|
||||
yield return update;
|
||||
}
|
||||
@@ -64,7 +64,7 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
|
||||
var firstRunMessages = messages.Append(stateUpdateMessage);
|
||||
|
||||
var allUpdates = new List<AgentResponseUpdate>();
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(firstRunMessages, thread, firstRunOptions, cancellationToken).ConfigureAwait(false))
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(firstRunMessages, session, firstRunOptions, cancellationToken).ConfigureAwait(false))
|
||||
{
|
||||
allUpdates.Add(update);
|
||||
|
||||
@@ -98,7 +98,7 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
|
||||
ChatRole.System,
|
||||
[new TextContent("Please provide a concise summary of the state changes in at most two sentences.")]));
|
||||
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(secondRunMessages, thread, options, cancellationToken).ConfigureAwait(false))
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(secondRunMessages, session, options, cancellationToken).ConfigureAwait(false))
|
||||
{
|
||||
yield return update;
|
||||
}
|
||||
|
||||
@@ -36,7 +36,7 @@ var pirateAgentBuilder = builder.AddAIAgent(
|
||||
chatClientServiceKey: "chat-model")
|
||||
.WithAITool(new CustomAITool())
|
||||
.WithAITool(new CustomFunctionTool())
|
||||
.WithInMemoryThreadStore();
|
||||
.WithInMemorySessionStore();
|
||||
|
||||
var knightsKnavesAgentBuilder = builder.AddAIAgent("knights-and-knaves", (sp, key) =>
|
||||
{
|
||||
|
||||
@@ -28,13 +28,13 @@ internal sealed class A2AAgentClient : AgentClientBase
|
||||
public override async IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
|
||||
string agentName,
|
||||
IList<ChatMessage> messages,
|
||||
string? threadId = null,
|
||||
string? sessionId = null,
|
||||
[EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
this._logger.LogInformation("Running agent {AgentName} with {MessageCount} messages via A2A", agentName, messages.Count);
|
||||
|
||||
var (a2aClient, _) = this.ResolveClient(agentName);
|
||||
var contextId = threadId ?? Guid.NewGuid().ToString("N");
|
||||
var contextId = sessionId ?? Guid.NewGuid().ToString("N");
|
||||
|
||||
// Convert and send messages via A2A without try-catch in yield method
|
||||
var results = new List<AgentResponseUpdate>();
|
||||
|
||||
@@ -16,13 +16,13 @@ internal abstract class AgentClientBase
|
||||
/// </summary>
|
||||
/// <param name="agentName">The name of the agent to run.</param>
|
||||
/// <param name="messages">The messages to send to the agent.</param>
|
||||
/// <param name="threadId">Optional thread identifier for conversation continuity.</param>
|
||||
/// <param name="sessionId">Optional session identifier for conversation continuity.</param>
|
||||
/// <param name="cancellationToken">Cancellation token.</param>
|
||||
/// <returns>An asynchronous enumerable of agent response updates.</returns>
|
||||
public abstract IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
|
||||
string agentName,
|
||||
IList<ChatMessage> messages,
|
||||
string? threadId = null,
|
||||
string? sessionId = null,
|
||||
CancellationToken cancellationToken = default);
|
||||
|
||||
/// <summary>
|
||||
@@ -34,16 +34,3 @@ internal abstract class AgentClientBase
|
||||
public virtual Task<AgentCard?> GetAgentCardAsync(string agentName, CancellationToken cancellationToken = default)
|
||||
=> Task.FromResult<AgentCard?>(null);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Helper class to create a thread-like wrapper for agent clients.
|
||||
/// </summary>
|
||||
public class AgentClientThread
|
||||
{
|
||||
public string ThreadId { get; }
|
||||
|
||||
public AgentClientThread(string? threadId = null)
|
||||
{
|
||||
this.ThreadId = threadId ?? Guid.NewGuid().ToString("N");
|
||||
}
|
||||
}
|
||||
|
||||
@@ -19,7 +19,7 @@ internal sealed class OpenAIChatCompletionsAgentClient(HttpClient httpClient) :
|
||||
public override async IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
|
||||
string agentName,
|
||||
IList<ChatMessage> messages,
|
||||
string? threadId = null,
|
||||
string? sessionId = null,
|
||||
[EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
OpenAIClientOptions options = new()
|
||||
|
||||
@@ -18,7 +18,7 @@ internal sealed class OpenAIResponsesAgentClient(HttpClient httpClient) : AgentC
|
||||
public override async IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
|
||||
string agentName,
|
||||
IList<ChatMessage> messages,
|
||||
string? threadId = null,
|
||||
string? sessionId = null,
|
||||
[EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
OpenAIClientOptions options = new()
|
||||
@@ -30,7 +30,7 @@ internal sealed class OpenAIResponsesAgentClient(HttpClient httpClient) : AgentC
|
||||
var openAiClient = new ResponsesClient(model: agentName, credential: new ApiKeyCredential("dummy-key"), options: options).AsIChatClient();
|
||||
var chatOptions = new ChatOptions()
|
||||
{
|
||||
ConversationId = threadId
|
||||
ConversationId = sessionId
|
||||
};
|
||||
|
||||
await foreach (var update in openAiClient.GetStreamingResponseAsync(messages, chatOptions, cancellationToken: cancellationToken))
|
||||
|
||||
@@ -19,15 +19,15 @@ public static class FunctionTriggers
|
||||
public static async Task<string> RunOrchestrationAsync([OrchestrationTrigger] TaskOrchestrationContext context)
|
||||
{
|
||||
DurableAIAgent writer = context.GetAgent("WriterAgent");
|
||||
AgentThread writerThread = await writer.GetNewThreadAsync();
|
||||
AgentSession writerSession = await writer.GetNewSessionAsync();
|
||||
|
||||
AgentResponse<TextResponse> initial = await writer.RunAsync<TextResponse>(
|
||||
message: "Write a concise inspirational sentence about learning.",
|
||||
thread: writerThread);
|
||||
session: writerSession);
|
||||
|
||||
AgentResponse<TextResponse> refined = await writer.RunAsync<TextResponse>(
|
||||
message: $"Improve this further while keeping it under 25 words: {initial.Result.Text}",
|
||||
thread: writerThread);
|
||||
session: writerSession);
|
||||
|
||||
return refined.Result.Text;
|
||||
}
|
||||
|
||||
@@ -21,7 +21,7 @@ AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
|
||||
? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
|
||||
: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Single agent used by the orchestration to demonstrate sequential calls on the same thread.
|
||||
// Single agent used by the orchestration to demonstrate sequential calls on the same session.
|
||||
const string WriterName = "WriterAgent";
|
||||
const string WriterInstructions =
|
||||
"""
|
||||
|
||||
@@ -1,11 +1,11 @@
|
||||
# Single Agent Orchestration Sample
|
||||
|
||||
This sample demonstrates how to use the Durable Agent Framework (DAFx) to create a simple Azure Functions app that orchestrates sequential calls to a single AI agent using the same conversation thread for context continuity.
|
||||
This sample demonstrates how to use the Durable Agent Framework (DAFx) to create a simple Azure Functions app that orchestrates sequential calls to a single AI agent using the same session for context continuity.
|
||||
|
||||
## Key Concepts Demonstrated
|
||||
|
||||
- Orchestrating multiple interactions with the same agent in a deterministic order
|
||||
- Using the same `AgentThread` across multiple calls to maintain conversational context
|
||||
- Using the same `AgentSession` across multiple calls to maintain conversational context
|
||||
- Durable orchestration with automatic checkpointing and resumption from failures
|
||||
- HTTP API integration for starting and monitoring orchestrations
|
||||
|
||||
|
||||
+4
-4
@@ -21,7 +21,7 @@ public static class FunctionTriggers
|
||||
|
||||
// Get the spam detection agent
|
||||
DurableAIAgent spamDetectionAgent = context.GetAgent("SpamDetectionAgent");
|
||||
AgentThread spamThread = await spamDetectionAgent.GetNewThreadAsync();
|
||||
AgentSession spamSession = await spamDetectionAgent.GetNewSessionAsync();
|
||||
|
||||
// Step 1: Check if the email is spam
|
||||
AgentResponse<DetectionResult> spamDetectionResponse = await spamDetectionAgent.RunAsync<DetectionResult>(
|
||||
@@ -31,7 +31,7 @@ public static class FunctionTriggers
|
||||
Email ID: {email.EmailId}
|
||||
Content: {email.EmailContent}
|
||||
""",
|
||||
thread: spamThread);
|
||||
session: spamSession);
|
||||
DetectionResult result = spamDetectionResponse.Result;
|
||||
|
||||
// Step 2: Conditional logic based on spam detection result
|
||||
@@ -43,7 +43,7 @@ public static class FunctionTriggers
|
||||
|
||||
// Generate and send response for legitimate email
|
||||
DurableAIAgent emailAssistantAgent = context.GetAgent("EmailAssistantAgent");
|
||||
AgentThread emailThread = await emailAssistantAgent.GetNewThreadAsync();
|
||||
AgentSession emailSession = await emailAssistantAgent.GetNewSessionAsync();
|
||||
|
||||
AgentResponse<EmailResponse> emailAssistantResponse = await emailAssistantAgent.RunAsync<EmailResponse>(
|
||||
message:
|
||||
@@ -53,7 +53,7 @@ public static class FunctionTriggers
|
||||
Email ID: {email.EmailId}
|
||||
Content: {email.EmailContent}
|
||||
""",
|
||||
thread: emailThread);
|
||||
session: emailSession);
|
||||
|
||||
EmailResponse emailResponse = emailAssistantResponse.Result;
|
||||
|
||||
|
||||
@@ -24,7 +24,7 @@ public static class FunctionTriggers
|
||||
|
||||
// Get the writer agent
|
||||
DurableAIAgent writerAgent = context.GetAgent("WriterAgent");
|
||||
AgentThread writerThread = await writerAgent.GetNewThreadAsync();
|
||||
AgentSession writerSession = await writerAgent.GetNewSessionAsync();
|
||||
|
||||
// Set initial status
|
||||
context.SetCustomStatus($"Starting content generation for topic: {input.Topic}");
|
||||
@@ -32,7 +32,7 @@ public static class FunctionTriggers
|
||||
// Step 1: Generate initial content
|
||||
AgentResponse<GeneratedContent> writerResponse = await writerAgent.RunAsync<GeneratedContent>(
|
||||
message: $"Write a short article about '{input.Topic}'.",
|
||||
thread: writerThread);
|
||||
session: writerSession);
|
||||
GeneratedContent content = writerResponse.Result;
|
||||
|
||||
// Human-in-the-loop iteration - we set a maximum number of attempts to avoid infinite loops
|
||||
@@ -81,7 +81,7 @@ public static class FunctionTriggers
|
||||
|
||||
Human Feedback: {humanResponse.Feedback}
|
||||
""",
|
||||
thread: writerThread);
|
||||
session: writerSession);
|
||||
|
||||
content = writerResponse.Result;
|
||||
}
|
||||
|
||||
@@ -20,7 +20,7 @@ public static class FunctionTriggers
|
||||
|
||||
// Get the writer agent
|
||||
DurableAIAgent writerAgent = context.GetAgent("Writer");
|
||||
AgentThread writerThread = await writerAgent.GetNewThreadAsync();
|
||||
AgentSession writerSession = await writerAgent.GetNewSessionAsync();
|
||||
|
||||
// Set initial status
|
||||
context.SetCustomStatus($"Starting content generation for topic: {input.Topic}");
|
||||
@@ -28,7 +28,7 @@ public static class FunctionTriggers
|
||||
// Step 1: Generate initial content
|
||||
AgentResponse<GeneratedContent> writerResponse = await writerAgent.RunAsync<GeneratedContent>(
|
||||
message: $"Write a short article about '{input.Topic}'.",
|
||||
thread: writerThread);
|
||||
session: writerSession);
|
||||
GeneratedContent content = writerResponse.Result;
|
||||
|
||||
// Human-in-the-loop iteration - we set a maximum number of attempts to avoid infinite loops
|
||||
@@ -102,7 +102,7 @@ public static class FunctionTriggers
|
||||
|
||||
Human Feedback: {humanResponse.Feedback}
|
||||
""",
|
||||
thread: writerThread);
|
||||
session: writerSession);
|
||||
|
||||
content = writerResponse.Result;
|
||||
}
|
||||
|
||||
@@ -47,7 +47,7 @@ internal sealed class Tools(ILogger<Tools> logger)
|
||||
{
|
||||
this._logger.LogInformation("Getting status for workflow instance: {InstanceId}", instanceId);
|
||||
|
||||
// Get the current agent context using the thread-static property
|
||||
// Get the current agent context using the session-static property
|
||||
OrchestrationMetadata? status = await DurableAgentContext.Current.GetOrchestrationStatusAsync(
|
||||
instanceId,
|
||||
includeDetails);
|
||||
|
||||
@@ -94,15 +94,15 @@ public sealed class FunctionTriggers
|
||||
|
||||
AIAgent agentProxy = durableClient.AsDurableAgentProxy(context, "TravelPlanner");
|
||||
|
||||
// Create a new agent thread
|
||||
AgentThread thread = await agentProxy.GetNewThreadAsync(cancellationToken);
|
||||
string agentSessionId = thread.GetService<AgentSessionId>().ToString();
|
||||
// Create a new agent session
|
||||
AgentSession session = await agentProxy.GetNewSessionAsync(cancellationToken);
|
||||
string agentSessionId = session.GetService<AgentSessionId>().ToString();
|
||||
|
||||
this._logger.LogInformation("Creating new agent session: {AgentSessionId}", agentSessionId);
|
||||
|
||||
// Run the agent in the background (fire-and-forget)
|
||||
DurableAgentRunOptions options = new() { IsFireAndForget = true };
|
||||
await agentProxy.RunAsync(prompt, thread, options, cancellationToken);
|
||||
await agentProxy.RunAsync(prompt, session, options, cancellationToken);
|
||||
|
||||
this._logger.LogInformation("Agent run started for session: {AgentSessionId}", agentSessionId);
|
||||
|
||||
|
||||
@@ -65,9 +65,9 @@ public sealed class RedisStreamResponseHandler : IAgentResponseHandler
|
||||
"DurableAgentContext.Current is not set. This handler must be used within a durable agent context.");
|
||||
}
|
||||
|
||||
// Get session ID from the current thread context, which is only available in the context of
|
||||
// Get session ID from the current session context, which is only available in the context of
|
||||
// a durable agent execution.
|
||||
string agentSessionId = context.CurrentThread.GetService<AgentSessionId>().ToString();
|
||||
string agentSessionId = context.CurrentSession.GetService<AgentSessionId>().ToString();
|
||||
string streamKey = GetStreamKey(agentSessionId);
|
||||
|
||||
IDatabase db = this._redis.GetDatabase();
|
||||
|
||||
@@ -0,0 +1,30 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
<PropertyGroup>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
<OutputType>Exe</OutputType>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<Nullable>enable</Nullable>
|
||||
<AssemblyName>SingleAgent</AssemblyName>
|
||||
<RootNamespace>SingleAgent</RootNamespace>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.OpenAI" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="Microsoft.DurableTask.Client.AzureManaged" />
|
||||
<PackageReference Include="Microsoft.DurableTask.Worker.AzureManaged" />
|
||||
<PackageReference Include="Microsoft.Extensions.Hosting" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
|
||||
<!--
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.Agents.AI.DurableTask" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
|
||||
</ItemGroup>
|
||||
-->
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.DurableTask\Microsoft.Agents.AI.DurableTask.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
|
||||
</ItemGroup>
|
||||
</Project>
|
||||
@@ -0,0 +1,103 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using Azure;
|
||||
using Azure.AI.OpenAI;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Agents.AI.DurableTask;
|
||||
using Microsoft.DurableTask.Client.AzureManaged;
|
||||
using Microsoft.DurableTask.Worker.AzureManaged;
|
||||
using Microsoft.Extensions.AI;
|
||||
using Microsoft.Extensions.DependencyInjection;
|
||||
using Microsoft.Extensions.Hosting;
|
||||
using Microsoft.Extensions.Logging;
|
||||
using OpenAI.Chat;
|
||||
|
||||
// Get the Azure OpenAI endpoint and deployment name from environment variables.
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
|
||||
?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
|
||||
?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
|
||||
|
||||
// Get DTS connection string from environment variable
|
||||
string dtsConnectionString = Environment.GetEnvironmentVariable("DURABLE_TASK_SCHEDULER_CONNECTION_STRING")
|
||||
?? "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None";
|
||||
|
||||
// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
|
||||
string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
|
||||
AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
|
||||
? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
|
||||
: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Set up an AI agent following the standard Microsoft Agent Framework pattern.
|
||||
const string JokerName = "Joker";
|
||||
const string JokerInstructions = "You are good at telling jokes.";
|
||||
|
||||
AIAgent agent = client.GetChatClient(deploymentName).AsAIAgent(JokerInstructions, JokerName);
|
||||
|
||||
// Configure the console app to host the AI agent.
|
||||
IHost host = Host.CreateDefaultBuilder(args)
|
||||
.ConfigureLogging(logging => logging.SetMinimumLevel(LogLevel.Warning))
|
||||
.ConfigureServices(services =>
|
||||
{
|
||||
services.ConfigureDurableAgents(
|
||||
options => options.AddAIAgent(agent, timeToLive: TimeSpan.FromHours(1)),
|
||||
workerBuilder: builder => builder.UseDurableTaskScheduler(dtsConnectionString),
|
||||
clientBuilder: builder => builder.UseDurableTaskScheduler(dtsConnectionString));
|
||||
})
|
||||
.Build();
|
||||
|
||||
await host.StartAsync();
|
||||
|
||||
// Get the agent proxy from services
|
||||
IServiceProvider services = host.Services;
|
||||
AIAgent agentProxy = services.GetRequiredKeyedService<AIAgent>(JokerName);
|
||||
|
||||
// Console colors for better UX
|
||||
Console.ForegroundColor = ConsoleColor.Cyan;
|
||||
Console.WriteLine("=== Single Agent Console Sample ===");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine("Enter a message for the Joker agent (or 'exit' to quit):");
|
||||
Console.WriteLine();
|
||||
|
||||
// Create a session for the conversation
|
||||
AgentSession session = await agentProxy.GetNewSessionAsync();
|
||||
|
||||
while (true)
|
||||
{
|
||||
// Read input from stdin
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.Write("You: ");
|
||||
Console.ResetColor();
|
||||
|
||||
string? input = Console.ReadLine();
|
||||
if (string.IsNullOrWhiteSpace(input) || input.Equals("exit", StringComparison.OrdinalIgnoreCase))
|
||||
{
|
||||
break;
|
||||
}
|
||||
|
||||
// Run the agent
|
||||
Console.ForegroundColor = ConsoleColor.Green;
|
||||
Console.Write("Joker: ");
|
||||
Console.ResetColor();
|
||||
|
||||
try
|
||||
{
|
||||
AgentResponse agentResponse = await agentProxy.RunAsync(
|
||||
message: input,
|
||||
session: session,
|
||||
cancellationToken: CancellationToken.None);
|
||||
|
||||
Console.WriteLine(agentResponse.Text);
|
||||
Console.WriteLine();
|
||||
}
|
||||
catch (Exception ex)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.Error.WriteLine($"Error: {ex.Message}");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine();
|
||||
}
|
||||
}
|
||||
|
||||
await host.StopAsync();
|
||||
@@ -0,0 +1,56 @@
|
||||
# Single Agent Sample
|
||||
|
||||
This sample demonstrates how to use the durable agents extension to create a simple console app that hosts a single AI agent and provides interactive conversation via stdin/stdout.
|
||||
|
||||
## Key Concepts Demonstrated
|
||||
|
||||
- Using the Microsoft Agent Framework to define a simple AI agent with a name and instructions.
|
||||
- Registering durable agents with the console app and running them interactively.
|
||||
- Conversation management (via threads) for isolated interactions.
|
||||
|
||||
## Environment Setup
|
||||
|
||||
See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
|
||||
|
||||
## Running the Sample
|
||||
|
||||
With the environment setup, you can run the sample:
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/DurableAgents/ConsoleApps/01_SingleAgent
|
||||
dotnet run --framework net10.0
|
||||
```
|
||||
|
||||
The app will prompt you for input. You can interact with the Joker agent:
|
||||
|
||||
```text
|
||||
=== Single Agent Console Sample ===
|
||||
Enter a message for the Joker agent (or 'exit' to quit):
|
||||
|
||||
You: Tell me a joke about a pirate.
|
||||
Joker: Why don't pirates ever learn the alphabet? Because they always get stuck at "C"!
|
||||
|
||||
You: Now explain the joke.
|
||||
Joker: The joke plays on the word "sea" (C), which pirates are famously associated with...
|
||||
|
||||
You: exit
|
||||
```
|
||||
|
||||
## Scriptable Usage
|
||||
|
||||
You can also pipe input to the app for scriptable usage:
|
||||
|
||||
```bash
|
||||
echo "Tell me a joke about a pirate." | dotnet run
|
||||
```
|
||||
|
||||
The app will read from stdin, process the input, and write the response to stdout.
|
||||
|
||||
## Viewing Agent State
|
||||
|
||||
You can view the state of the agent in the Durable Task Scheduler dashboard:
|
||||
|
||||
1. Open your browser and navigate to `http://localhost:8082`
|
||||
2. In the dashboard, you can view the state of the Joker agent, including its conversation history and current state
|
||||
|
||||
The agent maintains conversation state across multiple interactions, and you can inspect this state in the dashboard to understand how the durable agents extension manages conversation context.
|
||||
+30
@@ -0,0 +1,30 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
<PropertyGroup>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
<OutputType>Exe</OutputType>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<Nullable>enable</Nullable>
|
||||
<AssemblyName>AgentOrchestration_Chaining</AssemblyName>
|
||||
<RootNamespace>AgentOrchestration_Chaining</RootNamespace>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.OpenAI" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="Microsoft.DurableTask.Client.AzureManaged" />
|
||||
<PackageReference Include="Microsoft.DurableTask.Worker.AzureManaged" />
|
||||
<PackageReference Include="Microsoft.Extensions.Hosting" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
|
||||
<!--
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.Agents.AI.DurableTask" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
|
||||
</ItemGroup>
|
||||
-->
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.DurableTask\Microsoft.Agents.AI.DurableTask.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
|
||||
</ItemGroup>
|
||||
</Project>
|
||||
@@ -0,0 +1,6 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
namespace AgentOrchestration_Chaining;
|
||||
|
||||
// Response model
|
||||
public sealed record TextResponse(string Text);
|
||||
@@ -0,0 +1,148 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using AgentOrchestration_Chaining;
|
||||
using Azure;
|
||||
using Azure.AI.OpenAI;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Agents.AI.DurableTask;
|
||||
using Microsoft.DurableTask;
|
||||
using Microsoft.DurableTask.Client;
|
||||
using Microsoft.DurableTask.Client.AzureManaged;
|
||||
using Microsoft.DurableTask.Worker;
|
||||
using Microsoft.DurableTask.Worker.AzureManaged;
|
||||
using Microsoft.Extensions.DependencyInjection;
|
||||
using Microsoft.Extensions.Hosting;
|
||||
using Microsoft.Extensions.Logging;
|
||||
using OpenAI.Chat;
|
||||
using Environment = System.Environment;
|
||||
|
||||
// Get the Azure OpenAI endpoint and deployment name from environment variables.
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
|
||||
?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
|
||||
?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
|
||||
|
||||
// Get DTS connection string from environment variable
|
||||
string dtsConnectionString = Environment.GetEnvironmentVariable("DURABLE_TASK_SCHEDULER_CONNECTION_STRING")
|
||||
?? "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None";
|
||||
|
||||
// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
|
||||
string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
|
||||
AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
|
||||
? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
|
||||
: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Single agent used by the orchestration to demonstrate sequential calls on the same session.
|
||||
const string WriterName = "WriterAgent";
|
||||
const string WriterInstructions =
|
||||
"""
|
||||
You refine short pieces of text. When given an initial sentence you enhance it;
|
||||
when given an improved sentence you polish it further.
|
||||
""";
|
||||
|
||||
AIAgent writerAgent = client.GetChatClient(deploymentName).AsAIAgent(WriterInstructions, WriterName);
|
||||
|
||||
// Orchestrator function
|
||||
static async Task<string> RunOrchestratorAsync(TaskOrchestrationContext context)
|
||||
{
|
||||
DurableAIAgent writer = context.GetAgent("WriterAgent");
|
||||
AgentSession writerSession = await writer.GetNewSessionAsync();
|
||||
|
||||
AgentResponse<TextResponse> initial = await writer.RunAsync<TextResponse>(
|
||||
message: "Write a concise inspirational sentence about learning.",
|
||||
session: writerSession);
|
||||
|
||||
AgentResponse<TextResponse> refined = await writer.RunAsync<TextResponse>(
|
||||
message: $"Improve this further while keeping it under 25 words: {initial.Result.Text}",
|
||||
session: writerSession);
|
||||
|
||||
return refined.Result.Text;
|
||||
}
|
||||
|
||||
// Configure the console app to host the AI agent.
|
||||
IHost host = Host.CreateDefaultBuilder(args)
|
||||
.ConfigureLogging(loggingBuilder => loggingBuilder.SetMinimumLevel(LogLevel.Warning))
|
||||
.ConfigureServices(services =>
|
||||
{
|
||||
services.ConfigureDurableAgents(
|
||||
options => options.AddAIAgent(writerAgent),
|
||||
workerBuilder: builder =>
|
||||
{
|
||||
builder.UseDurableTaskScheduler(dtsConnectionString);
|
||||
builder.AddTasks(registry => registry.AddOrchestratorFunc(nameof(RunOrchestratorAsync), RunOrchestratorAsync));
|
||||
},
|
||||
clientBuilder: builder => builder.UseDurableTaskScheduler(dtsConnectionString));
|
||||
})
|
||||
.Build();
|
||||
|
||||
await host.StartAsync();
|
||||
|
||||
DurableTaskClient durableClient = host.Services.GetRequiredService<DurableTaskClient>();
|
||||
|
||||
// Console colors for better UX
|
||||
Console.ForegroundColor = ConsoleColor.Cyan;
|
||||
Console.WriteLine("=== Single Agent Orchestration Chaining Sample ===");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine("Starting orchestration...");
|
||||
Console.WriteLine();
|
||||
|
||||
try
|
||||
{
|
||||
// Start the orchestration
|
||||
string instanceId = await durableClient.ScheduleNewOrchestrationInstanceAsync(
|
||||
orchestratorName: nameof(RunOrchestratorAsync));
|
||||
|
||||
Console.ForegroundColor = ConsoleColor.Gray;
|
||||
Console.WriteLine($"Orchestration started with instance ID: {instanceId}");
|
||||
Console.WriteLine("Waiting for completion...");
|
||||
Console.ResetColor();
|
||||
|
||||
// Wait for orchestration to complete
|
||||
OrchestrationMetadata status = await durableClient.WaitForInstanceCompletionAsync(
|
||||
instanceId,
|
||||
getInputsAndOutputs: true,
|
||||
CancellationToken.None);
|
||||
|
||||
Console.WriteLine();
|
||||
|
||||
if (status.RuntimeStatus == OrchestrationRuntimeStatus.Completed)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Green;
|
||||
Console.WriteLine("✓ Orchestration completed successfully!");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine();
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.Write("Result: ");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine(status.ReadOutputAs<string>());
|
||||
}
|
||||
else if (status.RuntimeStatus == OrchestrationRuntimeStatus.Failed)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.WriteLine("✗ Orchestration failed!");
|
||||
Console.ResetColor();
|
||||
if (status.FailureDetails != null)
|
||||
{
|
||||
Console.WriteLine($"Error: {status.FailureDetails.ErrorMessage}");
|
||||
}
|
||||
Environment.Exit(1);
|
||||
}
|
||||
else
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine($"Orchestration status: {status.RuntimeStatus}");
|
||||
Console.ResetColor();
|
||||
}
|
||||
}
|
||||
catch (Exception ex)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.Error.WriteLine($"Error: {ex.Message}");
|
||||
Console.ResetColor();
|
||||
Environment.Exit(1);
|
||||
}
|
||||
finally
|
||||
{
|
||||
await host.StopAsync();
|
||||
}
|
||||
@@ -0,0 +1,53 @@
|
||||
# Single Agent Orchestration Sample
|
||||
|
||||
This sample demonstrates how to use the durable agents extension to create a simple console app that orchestrates sequential calls to a single AI agent using the same session for context continuity.
|
||||
|
||||
## Key Concepts Demonstrated
|
||||
|
||||
- Orchestrating multiple interactions with the same agent in a deterministic order
|
||||
- Using the same `AgentSession` across multiple calls to maintain conversational context
|
||||
- Durable orchestration with automatic checkpointing and resumption from failures
|
||||
- Waiting for orchestration completion using `WaitForInstanceCompletionAsync`
|
||||
|
||||
## Environment Setup
|
||||
|
||||
See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
|
||||
|
||||
## Running the Sample
|
||||
|
||||
With the environment setup, you can run the sample:
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/DurableAgents/ConsoleApps/02_AgentOrchestration_Chaining
|
||||
dotnet run --framework net10.0
|
||||
```
|
||||
|
||||
The app will start the orchestration, wait for it to complete, and display the result:
|
||||
|
||||
```text
|
||||
=== Single Agent Orchestration Chaining Sample ===
|
||||
Starting orchestration...
|
||||
|
||||
Orchestration started with instance ID: 86313f1d45fb42eeb50b1852626bf3ff
|
||||
Waiting for completion...
|
||||
|
||||
✓ Orchestration completed successfully!
|
||||
|
||||
Result: Learning serves as the key, opening doors to boundless opportunities and a brighter future.
|
||||
```
|
||||
|
||||
The orchestration will proceed to run the WriterAgent twice in sequence:
|
||||
|
||||
1. First, it writes an inspirational sentence about learning
|
||||
2. Then, it refines the initial output using the same conversation thread
|
||||
|
||||
## Viewing Orchestration State
|
||||
|
||||
You can view the state of the orchestration in the Durable Task Scheduler dashboard:
|
||||
|
||||
1. Open your browser and navigate to `http://localhost:8082`
|
||||
2. In the dashboard, you can see:
|
||||
- **Orchestrations**: View the orchestration instance, including its runtime status, input, output, and execution history
|
||||
- **Agents**: View the state of the WriterAgent, including conversation history maintained across the orchestration steps
|
||||
|
||||
The orchestration instance ID is displayed in the console output. You can use this ID to find the specific orchestration in the dashboard and inspect its execution details, including the sequence of agent calls and their results.
|
||||
+30
@@ -0,0 +1,30 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
<PropertyGroup>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
<OutputType>Exe</OutputType>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<Nullable>enable</Nullable>
|
||||
<AssemblyName>AgentOrchestration_Concurrency</AssemblyName>
|
||||
<RootNamespace>AgentOrchestration_Concurrency</RootNamespace>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.OpenAI" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="Microsoft.DurableTask.Client.AzureManaged" />
|
||||
<PackageReference Include="Microsoft.DurableTask.Worker.AzureManaged" />
|
||||
<PackageReference Include="Microsoft.Extensions.Hosting" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
|
||||
<!--
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.Agents.AI.DurableTask" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
|
||||
</ItemGroup>
|
||||
-->
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.DurableTask\Microsoft.Agents.AI.DurableTask.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
|
||||
</ItemGroup>
|
||||
</Project>
|
||||
@@ -0,0 +1,6 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
namespace AgentOrchestration_Concurrency;
|
||||
|
||||
// Response model
|
||||
public sealed record TextResponse(string Text);
|
||||
+191
@@ -0,0 +1,191 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using System.Text.Json;
|
||||
using AgentOrchestration_Concurrency;
|
||||
using Azure;
|
||||
using Azure.AI.OpenAI;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Agents.AI.DurableTask;
|
||||
using Microsoft.DurableTask;
|
||||
using Microsoft.DurableTask.Client;
|
||||
using Microsoft.DurableTask.Client.AzureManaged;
|
||||
using Microsoft.DurableTask.Worker;
|
||||
using Microsoft.DurableTask.Worker.AzureManaged;
|
||||
using Microsoft.Extensions.DependencyInjection;
|
||||
using Microsoft.Extensions.Hosting;
|
||||
using Microsoft.Extensions.Logging;
|
||||
using OpenAI.Chat;
|
||||
|
||||
// Get the Azure OpenAI endpoint and deployment name from environment variables.
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
|
||||
?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
|
||||
?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
|
||||
|
||||
// Get DTS connection string from environment variable
|
||||
string dtsConnectionString = Environment.GetEnvironmentVariable("DURABLE_TASK_SCHEDULER_CONNECTION_STRING")
|
||||
?? "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None";
|
||||
|
||||
// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
|
||||
string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
|
||||
AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
|
||||
? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
|
||||
: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Two agents used by the orchestration to demonstrate concurrent execution.
|
||||
const string PhysicistName = "PhysicistAgent";
|
||||
const string PhysicistInstructions = "You are an expert in physics. You answer questions from a physics perspective.";
|
||||
|
||||
const string ChemistName = "ChemistAgent";
|
||||
const string ChemistInstructions = "You are a middle school chemistry teacher. You answer questions so that middle school students can understand.";
|
||||
|
||||
AIAgent physicistAgent = client.GetChatClient(deploymentName).AsAIAgent(PhysicistInstructions, PhysicistName);
|
||||
AIAgent chemistAgent = client.GetChatClient(deploymentName).AsAIAgent(ChemistInstructions, ChemistName);
|
||||
|
||||
// Orchestrator function
|
||||
static async Task<object> RunOrchestratorAsync(TaskOrchestrationContext context, string prompt)
|
||||
{
|
||||
// Get both agents
|
||||
DurableAIAgent physicist = context.GetAgent(PhysicistName);
|
||||
DurableAIAgent chemist = context.GetAgent(ChemistName);
|
||||
|
||||
// Start both agent runs concurrently
|
||||
Task<AgentResponse<TextResponse>> physicistTask = physicist.RunAsync<TextResponse>(prompt);
|
||||
Task<AgentResponse<TextResponse>> chemistTask = chemist.RunAsync<TextResponse>(prompt);
|
||||
|
||||
// Wait for both tasks to complete using Task.WhenAll
|
||||
await Task.WhenAll(physicistTask, chemistTask);
|
||||
|
||||
// Get the results
|
||||
TextResponse physicistResponse = (await physicistTask).Result;
|
||||
TextResponse chemistResponse = (await chemistTask).Result;
|
||||
|
||||
// Return the result as a structured, anonymous type
|
||||
return new
|
||||
{
|
||||
physicist = physicistResponse.Text,
|
||||
chemist = chemistResponse.Text,
|
||||
};
|
||||
}
|
||||
|
||||
// Configure the console app to host the AI agents.
|
||||
IHost host = Host.CreateDefaultBuilder(args)
|
||||
.ConfigureLogging(loggingBuilder => loggingBuilder.SetMinimumLevel(LogLevel.Warning))
|
||||
.ConfigureServices(services =>
|
||||
{
|
||||
services.ConfigureDurableAgents(
|
||||
options =>
|
||||
{
|
||||
options
|
||||
.AddAIAgent(physicistAgent)
|
||||
.AddAIAgent(chemistAgent);
|
||||
},
|
||||
workerBuilder: builder =>
|
||||
{
|
||||
builder.UseDurableTaskScheduler(dtsConnectionString);
|
||||
builder.AddTasks(
|
||||
registry => registry.AddOrchestratorFunc<string, object>(nameof(RunOrchestratorAsync), RunOrchestratorAsync));
|
||||
},
|
||||
clientBuilder: builder => builder.UseDurableTaskScheduler(dtsConnectionString));
|
||||
})
|
||||
.Build();
|
||||
|
||||
await host.StartAsync();
|
||||
|
||||
DurableTaskClient durableTaskClient = host.Services.GetRequiredService<DurableTaskClient>();
|
||||
|
||||
// Console colors for better UX
|
||||
Console.ForegroundColor = ConsoleColor.Cyan;
|
||||
Console.WriteLine("=== Multi-Agent Concurrent Orchestration Sample ===");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine("Enter a question for the agents:");
|
||||
Console.WriteLine();
|
||||
|
||||
// Read prompt from stdin
|
||||
string? prompt = Console.ReadLine();
|
||||
if (string.IsNullOrWhiteSpace(prompt))
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.Error.WriteLine("Error: Prompt is required.");
|
||||
Console.ResetColor();
|
||||
Environment.Exit(1);
|
||||
return;
|
||||
}
|
||||
|
||||
Console.WriteLine();
|
||||
Console.ForegroundColor = ConsoleColor.Gray;
|
||||
Console.WriteLine("Starting orchestration...");
|
||||
Console.ResetColor();
|
||||
|
||||
try
|
||||
{
|
||||
// Start the orchestration
|
||||
string instanceId = await durableTaskClient.ScheduleNewOrchestrationInstanceAsync(
|
||||
orchestratorName: nameof(RunOrchestratorAsync),
|
||||
input: prompt);
|
||||
|
||||
Console.ForegroundColor = ConsoleColor.Gray;
|
||||
Console.WriteLine($"Orchestration started with instance ID: {instanceId}");
|
||||
Console.WriteLine("Waiting for completion...");
|
||||
Console.ResetColor();
|
||||
|
||||
// Wait for orchestration to complete
|
||||
OrchestrationMetadata status = await durableTaskClient.WaitForInstanceCompletionAsync(
|
||||
instanceId,
|
||||
getInputsAndOutputs: true,
|
||||
CancellationToken.None);
|
||||
|
||||
Console.WriteLine();
|
||||
|
||||
if (status.RuntimeStatus == OrchestrationRuntimeStatus.Completed)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Green;
|
||||
Console.WriteLine("✓ Orchestration completed successfully!");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine();
|
||||
|
||||
// Parse the output
|
||||
using JsonDocument doc = JsonDocument.Parse(status.SerializedOutput!);
|
||||
JsonElement output = doc.RootElement;
|
||||
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine("Physicist's response:");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine(output.GetProperty("physicist").GetString());
|
||||
Console.WriteLine();
|
||||
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine("Chemist's response:");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine(output.GetProperty("chemist").GetString());
|
||||
}
|
||||
else if (status.RuntimeStatus == OrchestrationRuntimeStatus.Failed)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.WriteLine("✗ Orchestration failed!");
|
||||
Console.ResetColor();
|
||||
if (status.FailureDetails != null)
|
||||
{
|
||||
Console.WriteLine($"Error: {status.FailureDetails.ErrorMessage}");
|
||||
}
|
||||
Environment.Exit(1);
|
||||
}
|
||||
else
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine($"Orchestration status: {status.RuntimeStatus}");
|
||||
Console.ResetColor();
|
||||
}
|
||||
}
|
||||
catch (Exception ex)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.Error.WriteLine($"Error: {ex.Message}");
|
||||
Console.ResetColor();
|
||||
Environment.Exit(1);
|
||||
}
|
||||
finally
|
||||
{
|
||||
await host.StopAsync();
|
||||
}
|
||||
@@ -0,0 +1,68 @@
|
||||
# Multi-Agent Concurrent Orchestration Sample
|
||||
|
||||
This sample demonstrates how to use the durable agents extension to create a console app that orchestrates concurrent execution of multiple AI agents using durable orchestration.
|
||||
|
||||
## Key Concepts Demonstrated
|
||||
|
||||
- Running multiple agents concurrently in a single orchestration
|
||||
- Using `Task.WhenAll` to wait for concurrent agent executions
|
||||
- Combining results from multiple agents into a single response
|
||||
- Waiting for orchestration completion using `WaitForInstanceCompletionAsync`
|
||||
|
||||
## Environment Setup
|
||||
|
||||
See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
|
||||
|
||||
## Running the Sample
|
||||
|
||||
With the environment setup, you can run the sample:
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/DurableAgents/ConsoleApps/03_AgentOrchestration_Concurrency
|
||||
dotnet run --framework net10.0
|
||||
```
|
||||
|
||||
The app will prompt you for a question:
|
||||
|
||||
```text
|
||||
=== Multi-Agent Concurrent Orchestration Sample ===
|
||||
Enter a question for the agents:
|
||||
|
||||
What is temperature?
|
||||
```
|
||||
|
||||
The orchestration will run both agents concurrently and display their responses:
|
||||
|
||||
```text
|
||||
Orchestration started with instance ID: 86313f1d45fb42eeb50b1852626bf3ff
|
||||
Waiting for completion...
|
||||
|
||||
✓ Orchestration completed successfully!
|
||||
|
||||
Physicist's response:
|
||||
Temperature is a measure of the average kinetic energy of particles in a system...
|
||||
|
||||
Chemist's response:
|
||||
From a chemistry perspective, temperature is crucial for chemical reactions...
|
||||
```
|
||||
|
||||
Both agents run in parallel, and the orchestration waits for both to complete before returning the combined results.
|
||||
|
||||
## Viewing Orchestration State
|
||||
|
||||
You can view the state of the orchestration in the Durable Task Scheduler dashboard:
|
||||
|
||||
1. Open your browser and navigate to `http://localhost:8082`
|
||||
2. In the dashboard, you can see:
|
||||
- **Orchestrations**: View the orchestration instance, including its runtime status, input, output, and execution history
|
||||
- **Agents**: View the state of both the PhysicistAgent and ChemistAgent, including their individual conversation histories
|
||||
|
||||
The orchestration instance ID is displayed in the console output. You can use this ID to find the specific orchestration in the dashboard and inspect how the concurrent agent executions were coordinated, including the timing of when each agent started and completed.
|
||||
|
||||
## Scriptable Usage
|
||||
|
||||
You can also pipe input to the app:
|
||||
|
||||
```bash
|
||||
echo "What is temperature?" | dotnet run
|
||||
```
|
||||
+30
@@ -0,0 +1,30 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
<PropertyGroup>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
<OutputType>Exe</OutputType>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<Nullable>enable</Nullable>
|
||||
<AssemblyName>AgentOrchestration_Conditionals</AssemblyName>
|
||||
<RootNamespace>AgentOrchestration_Conditionals</RootNamespace>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.OpenAI" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="Microsoft.DurableTask.Client.AzureManaged" />
|
||||
<PackageReference Include="Microsoft.DurableTask.Worker.AzureManaged" />
|
||||
<PackageReference Include="Microsoft.Extensions.Hosting" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
|
||||
<!--
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.Agents.AI.DurableTask" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
|
||||
</ItemGroup>
|
||||
-->
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.DurableTask\Microsoft.Agents.AI.DurableTask.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
|
||||
</ItemGroup>
|
||||
</Project>
|
||||
@@ -0,0 +1,38 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using System.Text.Json.Serialization;
|
||||
|
||||
namespace AgentOrchestration_Conditionals;
|
||||
|
||||
/// <summary>
|
||||
/// Represents an email input for spam detection and response generation.
|
||||
/// </summary>
|
||||
public sealed class Email
|
||||
{
|
||||
[JsonPropertyName("email_id")]
|
||||
public string EmailId { get; set; } = string.Empty;
|
||||
|
||||
[JsonPropertyName("email_content")]
|
||||
public string EmailContent { get; set; } = string.Empty;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Represents the result of spam detection analysis.
|
||||
/// </summary>
|
||||
public sealed class DetectionResult
|
||||
{
|
||||
[JsonPropertyName("is_spam")]
|
||||
public bool IsSpam { get; set; }
|
||||
|
||||
[JsonPropertyName("reason")]
|
||||
public string Reason { get; set; } = string.Empty;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Represents a generated email response.
|
||||
/// </summary>
|
||||
public sealed class EmailResponse
|
||||
{
|
||||
[JsonPropertyName("response")]
|
||||
public string Response { get; set; } = string.Empty;
|
||||
}
|
||||
+228
@@ -0,0 +1,228 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using AgentOrchestration_Conditionals;
|
||||
using Azure;
|
||||
using Azure.AI.OpenAI;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Agents.AI.DurableTask;
|
||||
using Microsoft.DurableTask;
|
||||
using Microsoft.DurableTask.Client;
|
||||
using Microsoft.DurableTask.Client.AzureManaged;
|
||||
using Microsoft.DurableTask.Worker;
|
||||
using Microsoft.DurableTask.Worker.AzureManaged;
|
||||
using Microsoft.Extensions.DependencyInjection;
|
||||
using Microsoft.Extensions.Hosting;
|
||||
using Microsoft.Extensions.Logging;
|
||||
using OpenAI.Chat;
|
||||
|
||||
// Get the Azure OpenAI endpoint and deployment name from environment variables.
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
|
||||
?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
|
||||
?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
|
||||
|
||||
// Get DTS connection string from environment variable
|
||||
string dtsConnectionString = Environment.GetEnvironmentVariable("DURABLE_TASK_SCHEDULER_CONNECTION_STRING")
|
||||
?? "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None";
|
||||
|
||||
// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
|
||||
string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
|
||||
AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
|
||||
? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
|
||||
: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Spam detection agent
|
||||
const string SpamDetectionAgentName = "SpamDetectionAgent";
|
||||
const string SpamDetectionAgentInstructions =
|
||||
"""
|
||||
You are an expert email spam detection system. Analyze emails and determine if they are spam.
|
||||
Return your analysis as JSON with 'is_spam' (boolean) and 'reason' (string) fields.
|
||||
""";
|
||||
|
||||
// Email assistant agent
|
||||
const string EmailAssistantAgentName = "EmailAssistantAgent";
|
||||
const string EmailAssistantAgentInstructions =
|
||||
"""
|
||||
You are a professional email assistant. Draft professional, courteous, and helpful email responses.
|
||||
Return your response as JSON with a 'response' field containing the reply.
|
||||
""";
|
||||
|
||||
AIAgent spamDetectionAgent = client.GetChatClient(deploymentName).AsAIAgent(SpamDetectionAgentInstructions, SpamDetectionAgentName);
|
||||
AIAgent emailAssistantAgent = client.GetChatClient(deploymentName).AsAIAgent(EmailAssistantAgentInstructions, EmailAssistantAgentName);
|
||||
|
||||
// Orchestrator function
|
||||
static async Task<string> RunOrchestratorAsync(TaskOrchestrationContext context, Email email)
|
||||
{
|
||||
// Get the spam detection agent
|
||||
DurableAIAgent spamDetectionAgent = context.GetAgent(SpamDetectionAgentName);
|
||||
AgentSession spamSession = await spamDetectionAgent.GetNewSessionAsync();
|
||||
|
||||
// Step 1: Check if the email is spam
|
||||
AgentResponse<DetectionResult> spamDetectionResponse = await spamDetectionAgent.RunAsync<DetectionResult>(
|
||||
message:
|
||||
$"""
|
||||
Analyze this email for spam content and return a JSON response with 'is_spam' (boolean) and 'reason' (string) fields:
|
||||
Email ID: {email.EmailId}
|
||||
Content: {email.EmailContent}
|
||||
""",
|
||||
session: spamSession);
|
||||
DetectionResult result = spamDetectionResponse.Result;
|
||||
|
||||
// Step 2: Conditional logic based on spam detection result
|
||||
if (result.IsSpam)
|
||||
{
|
||||
// Handle spam email
|
||||
return await context.CallActivityAsync<string>(nameof(HandleSpamEmail), result.Reason);
|
||||
}
|
||||
|
||||
// Generate and send response for legitimate email
|
||||
DurableAIAgent emailAssistantAgent = context.GetAgent(EmailAssistantAgentName);
|
||||
AgentSession emailSession = await emailAssistantAgent.GetNewSessionAsync();
|
||||
|
||||
AgentResponse<EmailResponse> emailAssistantResponse = await emailAssistantAgent.RunAsync<EmailResponse>(
|
||||
message:
|
||||
$"""
|
||||
Draft a professional response to this email. Return a JSON response with a 'response' field containing the reply:
|
||||
|
||||
Email ID: {email.EmailId}
|
||||
Content: {email.EmailContent}
|
||||
""",
|
||||
session: emailSession);
|
||||
|
||||
EmailResponse emailResponse = emailAssistantResponse.Result;
|
||||
|
||||
return await context.CallActivityAsync<string>(nameof(SendEmail), emailResponse.Response);
|
||||
}
|
||||
|
||||
// Activity functions
|
||||
static void HandleSpamEmail(TaskActivityContext context, string reason)
|
||||
{
|
||||
Console.WriteLine($"Email marked as spam: {reason}");
|
||||
}
|
||||
|
||||
static void SendEmail(TaskActivityContext context, string message)
|
||||
{
|
||||
Console.WriteLine($"Email sent: {message}");
|
||||
}
|
||||
|
||||
// Configure the console app to host the AI agents.
|
||||
IHost host = Host.CreateDefaultBuilder(args)
|
||||
.ConfigureLogging(loggingBuilder => loggingBuilder.SetMinimumLevel(LogLevel.Warning))
|
||||
.ConfigureServices(services =>
|
||||
{
|
||||
services.ConfigureDurableAgents(
|
||||
options =>
|
||||
{
|
||||
options
|
||||
.AddAIAgent(spamDetectionAgent)
|
||||
.AddAIAgent(emailAssistantAgent);
|
||||
},
|
||||
workerBuilder: builder =>
|
||||
{
|
||||
builder.UseDurableTaskScheduler(dtsConnectionString);
|
||||
builder.AddTasks(registry =>
|
||||
{
|
||||
registry.AddOrchestratorFunc<Email>(nameof(RunOrchestratorAsync), RunOrchestratorAsync);
|
||||
registry.AddActivityFunc<string>(nameof(HandleSpamEmail), HandleSpamEmail);
|
||||
registry.AddActivityFunc<string>(nameof(SendEmail), SendEmail);
|
||||
});
|
||||
},
|
||||
clientBuilder: builder => builder.UseDurableTaskScheduler(dtsConnectionString));
|
||||
})
|
||||
.Build();
|
||||
|
||||
await host.StartAsync();
|
||||
|
||||
DurableTaskClient durableTaskClient = host.Services.GetRequiredService<DurableTaskClient>();
|
||||
|
||||
// Console colors for better UX
|
||||
Console.ForegroundColor = ConsoleColor.Cyan;
|
||||
Console.WriteLine("=== Multi-Agent Conditional Orchestration Sample ===");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine("Enter email content:");
|
||||
Console.WriteLine();
|
||||
|
||||
// Read email content from stdin
|
||||
string? emailContent = Console.ReadLine();
|
||||
if (string.IsNullOrWhiteSpace(emailContent))
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.Error.WriteLine("Error: Email content is required.");
|
||||
Console.ResetColor();
|
||||
Environment.Exit(1);
|
||||
return;
|
||||
}
|
||||
|
||||
// Generate email ID automatically
|
||||
Email email = new()
|
||||
{
|
||||
EmailId = $"email-{Guid.NewGuid():N}",
|
||||
EmailContent = emailContent
|
||||
};
|
||||
|
||||
Console.WriteLine();
|
||||
Console.ForegroundColor = ConsoleColor.Gray;
|
||||
Console.WriteLine("Starting orchestration...");
|
||||
Console.ResetColor();
|
||||
|
||||
try
|
||||
{
|
||||
// Start the orchestration
|
||||
string instanceId = await durableTaskClient.ScheduleNewOrchestrationInstanceAsync(
|
||||
orchestratorName: nameof(RunOrchestratorAsync),
|
||||
input: email);
|
||||
|
||||
Console.ForegroundColor = ConsoleColor.Gray;
|
||||
Console.WriteLine($"Orchestration started with instance ID: {instanceId}");
|
||||
Console.WriteLine("Waiting for completion...");
|
||||
Console.ResetColor();
|
||||
|
||||
// Wait for orchestration to complete
|
||||
OrchestrationMetadata status = await durableTaskClient.WaitForInstanceCompletionAsync(
|
||||
instanceId,
|
||||
getInputsAndOutputs: true,
|
||||
CancellationToken.None);
|
||||
|
||||
Console.WriteLine();
|
||||
|
||||
if (status.RuntimeStatus == OrchestrationRuntimeStatus.Completed)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Green;
|
||||
Console.WriteLine("✓ Orchestration completed successfully!");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine();
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.Write("Result: ");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine(status.ReadOutputAs<string>());
|
||||
}
|
||||
else if (status.RuntimeStatus == OrchestrationRuntimeStatus.Failed)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.WriteLine("✗ Orchestration failed!");
|
||||
Console.ResetColor();
|
||||
if (status.FailureDetails != null)
|
||||
{
|
||||
Console.WriteLine($"Error: {status.FailureDetails.ErrorMessage}");
|
||||
}
|
||||
Environment.Exit(1);
|
||||
}
|
||||
else
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine($"Orchestration status: {status.RuntimeStatus}");
|
||||
Console.ResetColor();
|
||||
}
|
||||
}
|
||||
catch (Exception ex)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.Error.WriteLine($"Error: {ex.Message}");
|
||||
Console.ResetColor();
|
||||
Environment.Exit(1);
|
||||
}
|
||||
finally
|
||||
{
|
||||
await host.StopAsync();
|
||||
}
|
||||
@@ -0,0 +1,95 @@
|
||||
# Multi-Agent Conditional Orchestration Sample
|
||||
|
||||
This sample demonstrates how to use the durable agents extension to create a console app that orchestrates multiple AI agents with conditional logic based on the results of previous agent interactions.
|
||||
|
||||
## Key Concepts Demonstrated
|
||||
|
||||
- Multi-agent orchestration with conditional branching
|
||||
- Using agent responses to determine workflow paths
|
||||
- Activity functions for non-agent operations
|
||||
- Waiting for orchestration completion using `WaitForInstanceCompletionAsync`
|
||||
|
||||
## Environment Setup
|
||||
|
||||
See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
|
||||
|
||||
## Running the Sample
|
||||
|
||||
With the environment setup, you can run the sample:
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/DurableAgents/ConsoleApps/04_AgentOrchestration_Conditionals
|
||||
dotnet run --framework net10.0
|
||||
```
|
||||
|
||||
The app will prompt you for email content. You can test both legitimate emails and spam emails:
|
||||
|
||||
### Testing with a Legitimate Email
|
||||
|
||||
```text
|
||||
=== Multi-Agent Conditional Orchestration Sample ===
|
||||
Enter email content:
|
||||
|
||||
Hi John, I hope you're doing well. I wanted to follow up on our meeting yesterday about the quarterly report. Could you please send me the updated figures by Friday? Thanks!
|
||||
```
|
||||
|
||||
The orchestration will analyze the email and display the result:
|
||||
|
||||
```text
|
||||
Orchestration started with instance ID: 86313f1d45fb42eeb50b1852626bf3ff
|
||||
Waiting for completion...
|
||||
|
||||
✓ Orchestration completed successfully!
|
||||
|
||||
Result: Email sent: Thank you for your email. I'll prepare the updated figures...
|
||||
```
|
||||
|
||||
### Testing with a Spam Email
|
||||
|
||||
```text
|
||||
=== Multi-Agent Conditional Orchestration Sample ===
|
||||
Enter email content:
|
||||
|
||||
URGENT! You've won $1,000,000! Click here now to claim your prize! Limited time offer! Don't miss out!
|
||||
```
|
||||
|
||||
The orchestration will detect it as spam and display:
|
||||
|
||||
```text
|
||||
Orchestration started with instance ID: 86313f1d45fb42eeb50b1852626bf3ff
|
||||
Waiting for completion...
|
||||
|
||||
✓ Orchestration completed successfully!
|
||||
|
||||
Result: Email marked as spam: Contains suspicious claims about winning money and urgent action requests...
|
||||
```
|
||||
|
||||
## Scriptable Usage
|
||||
|
||||
You can also pipe email content to the app:
|
||||
|
||||
```bash
|
||||
# Test with a legitimate email
|
||||
echo "Hi John, I hope you're doing well..." | dotnet run
|
||||
|
||||
# Test with a spam email
|
||||
echo "URGENT! You've won $1,000,000! Click here now!" | dotnet run
|
||||
```
|
||||
|
||||
The orchestration will proceed as follows:
|
||||
|
||||
1. The SpamDetectionAgent analyzes the email to determine if it's spam
|
||||
2. Based on the result:
|
||||
- If spam: The orchestration calls the `HandleSpamEmail` activity function
|
||||
- If not spam: The EmailAssistantAgent drafts a response, then the `SendEmail` activity function is called
|
||||
|
||||
## Viewing Orchestration State
|
||||
|
||||
You can view the state of the orchestration in the Durable Task Scheduler dashboard:
|
||||
|
||||
1. Open your browser and navigate to `http://localhost:8082`
|
||||
2. In the dashboard, you can see:
|
||||
- **Orchestrations**: View the orchestration instance, including its runtime status, input, output, and execution history
|
||||
- **Agents**: View the state of both the SpamDetectionAgent and EmailAssistantAgent
|
||||
|
||||
The orchestration instance ID is displayed in the console output. You can use this ID to find the specific orchestration in the dashboard and inspect the conditional branching logic, including which path was taken based on the spam detection result.
|
||||
+30
@@ -0,0 +1,30 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
<PropertyGroup>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
<OutputType>Exe</OutputType>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<Nullable>enable</Nullable>
|
||||
<AssemblyName>AgentOrchestration_HITL</AssemblyName>
|
||||
<RootNamespace>AgentOrchestration_HITL</RootNamespace>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.OpenAI" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="Microsoft.DurableTask.Client.AzureManaged" />
|
||||
<PackageReference Include="Microsoft.DurableTask.Worker.AzureManaged" />
|
||||
<PackageReference Include="Microsoft.Extensions.Hosting" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
|
||||
<!--
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.Agents.AI.DurableTask" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
|
||||
</ItemGroup>
|
||||
-->
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.DurableTask\Microsoft.Agents.AI.DurableTask.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
|
||||
</ItemGroup>
|
||||
</Project>
|
||||
@@ -0,0 +1,44 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using System.Text.Json.Serialization;
|
||||
|
||||
namespace AgentOrchestration_HITL;
|
||||
|
||||
/// <summary>
|
||||
/// Represents the input for the Human-in-the-Loop content generation workflow.
|
||||
/// </summary>
|
||||
public sealed class ContentGenerationInput
|
||||
{
|
||||
[JsonPropertyName("topic")]
|
||||
public string Topic { get; set; } = string.Empty;
|
||||
|
||||
[JsonPropertyName("max_review_attempts")]
|
||||
public int MaxReviewAttempts { get; set; } = 3;
|
||||
|
||||
[JsonPropertyName("approval_timeout_hours")]
|
||||
public float ApprovalTimeoutHours { get; set; } = 72;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Represents the content generated by the writer agent.
|
||||
/// </summary>
|
||||
public sealed class GeneratedContent
|
||||
{
|
||||
[JsonPropertyName("title")]
|
||||
public string Title { get; set; } = string.Empty;
|
||||
|
||||
[JsonPropertyName("content")]
|
||||
public string Content { get; set; } = string.Empty;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Represents the human approval response.
|
||||
/// </summary>
|
||||
public sealed class HumanApprovalResponse
|
||||
{
|
||||
[JsonPropertyName("approved")]
|
||||
public bool Approved { get; set; }
|
||||
|
||||
[JsonPropertyName("feedback")]
|
||||
public string Feedback { get; set; } = string.Empty;
|
||||
}
|
||||
@@ -0,0 +1,333 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using System.Text.Json;
|
||||
using AgentOrchestration_HITL;
|
||||
using Azure;
|
||||
using Azure.AI.OpenAI;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Agents.AI.DurableTask;
|
||||
using Microsoft.DurableTask;
|
||||
using Microsoft.DurableTask.Client;
|
||||
using Microsoft.DurableTask.Client.AzureManaged;
|
||||
using Microsoft.DurableTask.Worker;
|
||||
using Microsoft.DurableTask.Worker.AzureManaged;
|
||||
using Microsoft.Extensions.DependencyInjection;
|
||||
using Microsoft.Extensions.Hosting;
|
||||
using Microsoft.Extensions.Logging;
|
||||
using OpenAI.Chat;
|
||||
|
||||
// Get the Azure OpenAI endpoint and deployment name from environment variables.
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
|
||||
?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
|
||||
?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
|
||||
|
||||
// Get DTS connection string from environment variable
|
||||
string dtsConnectionString = Environment.GetEnvironmentVariable("DURABLE_TASK_SCHEDULER_CONNECTION_STRING")
|
||||
?? "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None";
|
||||
|
||||
// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
|
||||
string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
|
||||
AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
|
||||
? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
|
||||
: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Single agent used by the orchestration to demonstrate human-in-the-loop workflow.
|
||||
const string WriterName = "WriterAgent";
|
||||
const string WriterInstructions =
|
||||
"""
|
||||
You are a professional content writer who creates high-quality articles on various topics.
|
||||
You write engaging, informative, and well-structured content that follows best practices for readability and accuracy.
|
||||
""";
|
||||
|
||||
AIAgent writerAgent = client.GetChatClient(deploymentName).AsAIAgent(WriterInstructions, WriterName);
|
||||
|
||||
// Orchestrator function
|
||||
static async Task<object> RunOrchestratorAsync(TaskOrchestrationContext context, ContentGenerationInput input)
|
||||
{
|
||||
// Get the writer agent
|
||||
DurableAIAgent writerAgent = context.GetAgent("WriterAgent");
|
||||
AgentSession writerSession = await writerAgent.GetNewSessionAsync();
|
||||
|
||||
// Set initial status
|
||||
context.SetCustomStatus($"Starting content generation for topic: {input.Topic}");
|
||||
|
||||
// Step 1: Generate initial content
|
||||
AgentResponse<GeneratedContent> writerResponse = await writerAgent.RunAsync<GeneratedContent>(
|
||||
message: $"Write a short article about '{input.Topic}' in less than 300 words.",
|
||||
session: writerSession);
|
||||
GeneratedContent content = writerResponse.Result;
|
||||
|
||||
// Human-in-the-loop iteration - we set a maximum number of attempts to avoid infinite loops
|
||||
int iterationCount = 0;
|
||||
while (iterationCount++ < input.MaxReviewAttempts)
|
||||
{
|
||||
context.SetCustomStatus(
|
||||
$"Requesting human feedback. Iteration #{iterationCount}. Timeout: {input.ApprovalTimeoutHours} hour(s).");
|
||||
|
||||
// Step 2: Notify user to review the content
|
||||
await context.CallActivityAsync(nameof(NotifyUserForApproval), content);
|
||||
|
||||
// Step 3: Wait for human feedback with configurable timeout
|
||||
HumanApprovalResponse humanResponse;
|
||||
try
|
||||
{
|
||||
humanResponse = await context.WaitForExternalEvent<HumanApprovalResponse>(
|
||||
eventName: "HumanApproval",
|
||||
timeout: TimeSpan.FromHours(input.ApprovalTimeoutHours));
|
||||
}
|
||||
catch (OperationCanceledException)
|
||||
{
|
||||
// Timeout occurred - treat as rejection
|
||||
context.SetCustomStatus(
|
||||
$"Human approval timed out after {input.ApprovalTimeoutHours} hour(s). Treating as rejection.");
|
||||
throw new TimeoutException($"Human approval timed out after {input.ApprovalTimeoutHours} hour(s).");
|
||||
}
|
||||
|
||||
if (humanResponse.Approved)
|
||||
{
|
||||
context.SetCustomStatus("Content approved by human reviewer. Publishing content...");
|
||||
|
||||
// Step 4: Publish the approved content
|
||||
await context.CallActivityAsync(nameof(PublishContent), content);
|
||||
|
||||
context.SetCustomStatus($"Content published successfully at {context.CurrentUtcDateTime:s}");
|
||||
return new { content = content.Content };
|
||||
}
|
||||
|
||||
context.SetCustomStatus("Content rejected by human reviewer. Incorporating feedback and regenerating...");
|
||||
|
||||
// Incorporate human feedback and regenerate
|
||||
writerResponse = await writerAgent.RunAsync<GeneratedContent>(
|
||||
message: $"""
|
||||
The content was rejected by a human reviewer. Please rewrite the article incorporating their feedback.
|
||||
|
||||
Human Feedback: {humanResponse.Feedback}
|
||||
""",
|
||||
session: writerSession);
|
||||
|
||||
content = writerResponse.Result;
|
||||
}
|
||||
|
||||
// If we reach here, it means we exhausted the maximum number of iterations
|
||||
throw new InvalidOperationException(
|
||||
$"Content could not be approved after {input.MaxReviewAttempts} iterations.");
|
||||
}
|
||||
|
||||
// Activity functions
|
||||
static void NotifyUserForApproval(TaskActivityContext context, GeneratedContent content)
|
||||
{
|
||||
// In a real implementation, this would send notifications via email, SMS, etc.
|
||||
Console.WriteLine(
|
||||
$"""
|
||||
NOTIFICATION: Please review the following content for approval:
|
||||
Title: {content.Title}
|
||||
Content: {content.Content}
|
||||
Use the approval endpoint to approve or reject this content.
|
||||
""");
|
||||
}
|
||||
|
||||
static void PublishContent(TaskActivityContext context, GeneratedContent content)
|
||||
{
|
||||
// In a real implementation, this would publish to a CMS, website, etc.
|
||||
Console.WriteLine(
|
||||
$"""
|
||||
PUBLISHING: Content has been published successfully.
|
||||
Title: {content.Title}
|
||||
Content: {content.Content}
|
||||
""");
|
||||
}
|
||||
|
||||
// Configure the console app to host the AI agent.
|
||||
IHost host = Host.CreateDefaultBuilder(args)
|
||||
.ConfigureLogging(loggingBuilder => loggingBuilder.SetMinimumLevel(LogLevel.Warning))
|
||||
.ConfigureServices(services =>
|
||||
{
|
||||
services.ConfigureDurableAgents(
|
||||
options => options.AddAIAgent(writerAgent),
|
||||
workerBuilder: builder =>
|
||||
{
|
||||
builder.UseDurableTaskScheduler(dtsConnectionString);
|
||||
builder.AddTasks(registry =>
|
||||
{
|
||||
registry.AddOrchestratorFunc<ContentGenerationInput>(nameof(RunOrchestratorAsync), RunOrchestratorAsync);
|
||||
registry.AddActivityFunc<GeneratedContent>(nameof(NotifyUserForApproval), NotifyUserForApproval);
|
||||
registry.AddActivityFunc<GeneratedContent>(nameof(PublishContent), PublishContent);
|
||||
});
|
||||
},
|
||||
clientBuilder: builder => builder.UseDurableTaskScheduler(dtsConnectionString));
|
||||
})
|
||||
.Build();
|
||||
|
||||
await host.StartAsync();
|
||||
|
||||
DurableTaskClient durableTaskClient = host.Services.GetRequiredService<DurableTaskClient>();
|
||||
|
||||
// Console colors for better UX
|
||||
Console.ForegroundColor = ConsoleColor.Cyan;
|
||||
Console.WriteLine("=== Human-in-the-Loop Orchestration Sample ===");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine("Enter topic for content generation:");
|
||||
Console.WriteLine();
|
||||
|
||||
// Read topic from stdin
|
||||
string? topic = Console.ReadLine();
|
||||
if (string.IsNullOrWhiteSpace(topic))
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.Error.WriteLine("Error: Topic is required.");
|
||||
Console.ResetColor();
|
||||
Environment.Exit(1);
|
||||
return;
|
||||
}
|
||||
|
||||
// Prompt for optional parameters with defaults
|
||||
Console.WriteLine();
|
||||
Console.WriteLine("Max review attempts (default: 3):");
|
||||
string? maxAttemptsInput = Console.ReadLine();
|
||||
int maxReviewAttempts = int.TryParse(maxAttemptsInput, out int maxAttempts) && maxAttempts > 0
|
||||
? maxAttempts
|
||||
: 3;
|
||||
|
||||
Console.WriteLine("Approval timeout in hours (default: 72):");
|
||||
string? timeoutInput = Console.ReadLine();
|
||||
float approvalTimeoutHours = float.TryParse(timeoutInput, out float timeout) && timeout > 0
|
||||
? timeout
|
||||
: 72;
|
||||
|
||||
ContentGenerationInput input = new()
|
||||
{
|
||||
Topic = topic,
|
||||
MaxReviewAttempts = maxReviewAttempts,
|
||||
ApprovalTimeoutHours = approvalTimeoutHours
|
||||
};
|
||||
|
||||
Console.WriteLine();
|
||||
Console.ForegroundColor = ConsoleColor.Gray;
|
||||
Console.WriteLine("Starting orchestration...");
|
||||
Console.ResetColor();
|
||||
|
||||
try
|
||||
{
|
||||
// Start the orchestration
|
||||
string instanceId = await durableTaskClient.ScheduleNewOrchestrationInstanceAsync(
|
||||
orchestratorName: nameof(RunOrchestratorAsync),
|
||||
input: input);
|
||||
|
||||
Console.ForegroundColor = ConsoleColor.Gray;
|
||||
Console.WriteLine($"Orchestration started with instance ID: {instanceId}");
|
||||
Console.WriteLine("Waiting for human approval...");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine();
|
||||
|
||||
// Monitor orchestration status and handle approval prompts
|
||||
using CancellationTokenSource cts = new();
|
||||
Task orchestrationTask = Task.Run(async () =>
|
||||
{
|
||||
while (!cts.Token.IsCancellationRequested)
|
||||
{
|
||||
OrchestrationMetadata? status = await durableTaskClient.GetInstanceAsync(
|
||||
instanceId,
|
||||
getInputsAndOutputs: true,
|
||||
cts.Token);
|
||||
|
||||
if (status == null)
|
||||
{
|
||||
await Task.Delay(TimeSpan.FromSeconds(1), cts.Token);
|
||||
continue;
|
||||
}
|
||||
|
||||
// Check if we're waiting for approval
|
||||
if (status.SerializedCustomStatus != null)
|
||||
{
|
||||
string? customStatus = status.ReadCustomStatusAs<string>();
|
||||
if (customStatus?.StartsWith("Requesting human feedback", StringComparison.OrdinalIgnoreCase) == true)
|
||||
{
|
||||
// Prompt user for approval
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine("Content is ready for review. Check the logs above for details.");
|
||||
Console.Write("Approve? (y/n): ");
|
||||
Console.ResetColor();
|
||||
|
||||
string? approvalInput = Console.ReadLine();
|
||||
bool approved = approvalInput?.Trim().Equals("y", StringComparison.OrdinalIgnoreCase) == true;
|
||||
|
||||
Console.Write("Feedback (optional): ");
|
||||
string? feedback = Console.ReadLine() ?? "";
|
||||
|
||||
HumanApprovalResponse approvalResponse = new()
|
||||
{
|
||||
Approved = approved,
|
||||
Feedback = feedback
|
||||
};
|
||||
|
||||
await durableTaskClient.RaiseEventAsync(instanceId, "HumanApproval", approvalResponse);
|
||||
}
|
||||
}
|
||||
|
||||
if (status.RuntimeStatus is OrchestrationRuntimeStatus.Completed or OrchestrationRuntimeStatus.Failed or OrchestrationRuntimeStatus.Terminated)
|
||||
{
|
||||
break;
|
||||
}
|
||||
|
||||
await Task.Delay(TimeSpan.FromSeconds(1), cts.Token);
|
||||
}
|
||||
}, cts.Token);
|
||||
|
||||
// Wait for orchestration to complete
|
||||
OrchestrationMetadata finalStatus = await durableTaskClient.WaitForInstanceCompletionAsync(
|
||||
instanceId,
|
||||
getInputsAndOutputs: true,
|
||||
CancellationToken.None);
|
||||
|
||||
cts.Cancel();
|
||||
await orchestrationTask;
|
||||
|
||||
Console.WriteLine();
|
||||
|
||||
if (finalStatus.RuntimeStatus == OrchestrationRuntimeStatus.Completed)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Green;
|
||||
Console.WriteLine("✓ Orchestration completed successfully!");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine();
|
||||
|
||||
JsonElement output = finalStatus.ReadOutputAs<JsonElement>();
|
||||
if (output.TryGetProperty("content", out JsonElement contentElement))
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine("Published content:");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine(contentElement.GetString());
|
||||
}
|
||||
}
|
||||
else if (finalStatus.RuntimeStatus == OrchestrationRuntimeStatus.Failed)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.WriteLine("✗ Orchestration failed!");
|
||||
Console.ResetColor();
|
||||
if (finalStatus.FailureDetails != null)
|
||||
{
|
||||
Console.WriteLine($"Error: {finalStatus.FailureDetails.ErrorMessage}");
|
||||
}
|
||||
Environment.Exit(1);
|
||||
}
|
||||
else
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine($"Orchestration status: {finalStatus.RuntimeStatus}");
|
||||
Console.ResetColor();
|
||||
}
|
||||
}
|
||||
catch (Exception ex)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.Error.WriteLine($"Error: {ex.Message}");
|
||||
Console.ResetColor();
|
||||
Environment.Exit(1);
|
||||
}
|
||||
finally
|
||||
{
|
||||
await host.StopAsync();
|
||||
}
|
||||
@@ -0,0 +1,73 @@
|
||||
# Human-in-the-Loop Orchestration Sample
|
||||
|
||||
This sample demonstrates how to use the durable agents extension to create a console app that implements a human-in-the-loop workflow using durable orchestration, including interactive approval prompts.
|
||||
|
||||
## Key Concepts Demonstrated
|
||||
|
||||
- Human-in-the-loop workflows with durable orchestration
|
||||
- External event handling for human approval/rejection
|
||||
- Timeout handling for approval requests
|
||||
- Iterative content refinement based on human feedback
|
||||
|
||||
## Environment Setup
|
||||
|
||||
See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
|
||||
|
||||
## Running the Sample
|
||||
|
||||
With the environment setup, you can run the sample:
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/DurableAgents/ConsoleApps/05_AgentOrchestration_HITL
|
||||
dotnet run --framework net10.0
|
||||
```
|
||||
|
||||
The app will prompt you for input:
|
||||
|
||||
```text
|
||||
=== Human-in-the-Loop Orchestration Sample ===
|
||||
Enter topic for content generation:
|
||||
|
||||
The Future of Artificial Intelligence
|
||||
|
||||
Max review attempts (default: 3):
|
||||
3
|
||||
Approval timeout in hours (default: 72):
|
||||
72
|
||||
```
|
||||
|
||||
The orchestration will generate content and prompt you for approval:
|
||||
|
||||
```text
|
||||
Orchestration started with instance ID: 86313f1d45fb42eeb50b1852626bf3ff
|
||||
|
||||
=== NOTIFICATION: Content Ready for Review ===
|
||||
Title: The Future of Artificial Intelligence
|
||||
|
||||
Content:
|
||||
[Generated content appears here]
|
||||
|
||||
Please review the content above and provide your approval.
|
||||
|
||||
Content is ready for review. Check the logs above for details.
|
||||
Approve? (y/n): n
|
||||
Feedback (optional): Please add more details about the ethical implications.
|
||||
```
|
||||
|
||||
The orchestration will incorporate your feedback and regenerate the content. Once approved, it will publish and complete.
|
||||
|
||||
## Viewing Orchestration State
|
||||
|
||||
You can view the state of the orchestration in the Durable Task Scheduler dashboard:
|
||||
|
||||
1. Open your browser and navigate to `http://localhost:8082`
|
||||
2. In the dashboard, you can see:
|
||||
- **Orchestrations**: View the orchestration instance, including its runtime status, custom status (which shows approval state), input, output, and execution history
|
||||
- **Agents**: View the state of the WriterAgent, including conversation history
|
||||
|
||||
The orchestration instance ID is displayed in the console output. You can use this ID to find the specific orchestration in the dashboard and inspect:
|
||||
|
||||
- The custom status field, which shows the current state of the approval workflow
|
||||
- When the orchestration is waiting for external events
|
||||
- The iteration count and feedback history
|
||||
- The final published content
|
||||
+30
@@ -0,0 +1,30 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
<PropertyGroup>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
<OutputType>Exe</OutputType>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<Nullable>enable</Nullable>
|
||||
<AssemblyName>LongRunningTools</AssemblyName>
|
||||
<RootNamespace>LongRunningTools</RootNamespace>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.OpenAI" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="Microsoft.DurableTask.Client.AzureManaged" />
|
||||
<PackageReference Include="Microsoft.DurableTask.Worker.AzureManaged" />
|
||||
<PackageReference Include="Microsoft.Extensions.Hosting" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
|
||||
<!--
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.Agents.AI.DurableTask" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
|
||||
</ItemGroup>
|
||||
-->
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.DurableTask\Microsoft.Agents.AI.DurableTask.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
|
||||
</ItemGroup>
|
||||
</Project>
|
||||
@@ -0,0 +1,44 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using System.Text.Json.Serialization;
|
||||
|
||||
namespace LongRunningTools;
|
||||
|
||||
/// <summary>
|
||||
/// Represents the input for the content generation workflow.
|
||||
/// </summary>
|
||||
public sealed class ContentGenerationInput
|
||||
{
|
||||
[JsonPropertyName("topic")]
|
||||
public string Topic { get; set; } = string.Empty;
|
||||
|
||||
[JsonPropertyName("max_review_attempts")]
|
||||
public int MaxReviewAttempts { get; set; } = 3;
|
||||
|
||||
[JsonPropertyName("approval_timeout_hours")]
|
||||
public float ApprovalTimeoutHours { get; set; } = 72;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Represents the content generated by the writer agent.
|
||||
/// </summary>
|
||||
public sealed class GeneratedContent
|
||||
{
|
||||
[JsonPropertyName("title")]
|
||||
public string Title { get; set; } = string.Empty;
|
||||
|
||||
[JsonPropertyName("content")]
|
||||
public string Content { get; set; } = string.Empty;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Represents the human feedback response.
|
||||
/// </summary>
|
||||
public sealed class HumanFeedbackResponse
|
||||
{
|
||||
[JsonPropertyName("approved")]
|
||||
public bool Approved { get; set; }
|
||||
|
||||
[JsonPropertyName("feedback")]
|
||||
public string Feedback { get; set; } = string.Empty;
|
||||
}
|
||||
@@ -0,0 +1,351 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using System.ComponentModel;
|
||||
using Azure;
|
||||
using Azure.AI.OpenAI;
|
||||
using Azure.Identity;
|
||||
using LongRunningTools;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Agents.AI.DurableTask;
|
||||
using Microsoft.DurableTask;
|
||||
using Microsoft.DurableTask.Client;
|
||||
using Microsoft.DurableTask.Client.AzureManaged;
|
||||
using Microsoft.DurableTask.Worker;
|
||||
using Microsoft.DurableTask.Worker.AzureManaged;
|
||||
using Microsoft.Extensions.AI;
|
||||
using Microsoft.Extensions.DependencyInjection;
|
||||
using Microsoft.Extensions.Hosting;
|
||||
using Microsoft.Extensions.Logging;
|
||||
using OpenAI.Chat;
|
||||
|
||||
// Get the Azure OpenAI endpoint and deployment name from environment variables.
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
|
||||
?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
|
||||
?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
|
||||
|
||||
// Get DTS connection string from environment variable
|
||||
string dtsConnectionString = Environment.GetEnvironmentVariable("DURABLE_TASK_SCHEDULER_CONNECTION_STRING")
|
||||
?? "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None";
|
||||
|
||||
// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
|
||||
string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
|
||||
AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
|
||||
? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
|
||||
: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Agent used by the orchestration to write content.
|
||||
const string WriterAgentName = "Writer";
|
||||
const string WriterAgentInstructions =
|
||||
"""
|
||||
You are a professional content writer who creates high-quality articles on various topics.
|
||||
You write engaging, informative, and well-structured content that follows best practices for readability and accuracy.
|
||||
""";
|
||||
|
||||
AIAgent writerAgent = client.GetChatClient(deploymentName).AsAIAgent(WriterAgentInstructions, WriterAgentName);
|
||||
|
||||
// Agent that can start content generation workflows using tools
|
||||
const string PublisherAgentName = "Publisher";
|
||||
const string PublisherAgentInstructions =
|
||||
"""
|
||||
You are a publishing agent that can manage content generation workflows.
|
||||
You have access to tools to start, monitor, and raise events for content generation workflows.
|
||||
""";
|
||||
|
||||
const string HumanFeedbackEventName = "HumanFeedback";
|
||||
|
||||
// Orchestrator function
|
||||
static async Task<object> RunOrchestratorAsync(TaskOrchestrationContext context, ContentGenerationInput input)
|
||||
{
|
||||
// Get the writer agent
|
||||
DurableAIAgent writerAgent = context.GetAgent(WriterAgentName);
|
||||
AgentSession writerSession = await writerAgent.GetNewSessionAsync();
|
||||
|
||||
// Set initial status
|
||||
context.SetCustomStatus($"Starting content generation for topic: {input.Topic}");
|
||||
|
||||
// Step 1: Generate initial content
|
||||
AgentResponse<GeneratedContent> writerResponse = await writerAgent.RunAsync<GeneratedContent>(
|
||||
message: $"Write a short article about '{input.Topic}'.",
|
||||
session: writerSession);
|
||||
GeneratedContent content = writerResponse.Result;
|
||||
|
||||
// Human-in-the-loop iteration - we set a maximum number of attempts to avoid infinite loops
|
||||
int iterationCount = 0;
|
||||
while (iterationCount++ < input.MaxReviewAttempts)
|
||||
{
|
||||
context.SetCustomStatus(
|
||||
new
|
||||
{
|
||||
message = "Requesting human feedback.",
|
||||
approvalTimeoutHours = input.ApprovalTimeoutHours,
|
||||
iterationCount,
|
||||
content
|
||||
});
|
||||
|
||||
// Step 2: Notify user to review the content
|
||||
await context.CallActivityAsync(nameof(NotifyUserForApproval), content);
|
||||
|
||||
// Step 3: Wait for human feedback with configurable timeout
|
||||
HumanFeedbackResponse humanResponse;
|
||||
try
|
||||
{
|
||||
humanResponse = await context.WaitForExternalEvent<HumanFeedbackResponse>(
|
||||
eventName: HumanFeedbackEventName,
|
||||
timeout: TimeSpan.FromHours(input.ApprovalTimeoutHours));
|
||||
}
|
||||
catch (OperationCanceledException)
|
||||
{
|
||||
// Timeout occurred - treat as rejection
|
||||
context.SetCustomStatus(
|
||||
new
|
||||
{
|
||||
message = $"Human approval timed out after {input.ApprovalTimeoutHours} hour(s). Treating as rejection.",
|
||||
iterationCount,
|
||||
content
|
||||
});
|
||||
throw new TimeoutException($"Human approval timed out after {input.ApprovalTimeoutHours} hour(s).");
|
||||
}
|
||||
|
||||
if (humanResponse.Approved)
|
||||
{
|
||||
context.SetCustomStatus(new
|
||||
{
|
||||
message = "Content approved by human reviewer. Publishing content...",
|
||||
content
|
||||
});
|
||||
|
||||
// Step 4: Publish the approved content
|
||||
await context.CallActivityAsync(nameof(PublishContent), content);
|
||||
|
||||
context.SetCustomStatus(new
|
||||
{
|
||||
message = $"Content published successfully at {context.CurrentUtcDateTime:s}",
|
||||
humanFeedback = humanResponse,
|
||||
content
|
||||
});
|
||||
return new { content = content.Content };
|
||||
}
|
||||
|
||||
context.SetCustomStatus(new
|
||||
{
|
||||
message = "Content rejected by human reviewer. Incorporating feedback and regenerating...",
|
||||
humanFeedback = humanResponse,
|
||||
content
|
||||
});
|
||||
|
||||
// Incorporate human feedback and regenerate
|
||||
writerResponse = await writerAgent.RunAsync<GeneratedContent>(
|
||||
message: $"""
|
||||
The content was rejected by a human reviewer. Please rewrite the article incorporating their feedback.
|
||||
|
||||
Human Feedback: {humanResponse.Feedback}
|
||||
""",
|
||||
session: writerSession);
|
||||
|
||||
content = writerResponse.Result;
|
||||
}
|
||||
|
||||
// If we reach here, it means we exhausted the maximum number of iterations
|
||||
throw new InvalidOperationException(
|
||||
$"Content could not be approved after {input.MaxReviewAttempts} iterations.");
|
||||
}
|
||||
|
||||
// Activity functions
|
||||
static void NotifyUserForApproval(TaskActivityContext context, GeneratedContent content)
|
||||
{
|
||||
// In a real implementation, this would send notifications via email, SMS, etc.
|
||||
Console.ForegroundColor = ConsoleColor.DarkMagenta;
|
||||
Console.WriteLine(
|
||||
$"""
|
||||
NOTIFICATION: Please review the following content for approval:
|
||||
Title: {content.Title}
|
||||
Content: {content.Content}
|
||||
""");
|
||||
Console.ResetColor();
|
||||
}
|
||||
|
||||
static void PublishContent(TaskActivityContext context, GeneratedContent content)
|
||||
{
|
||||
// In a real implementation, this would publish to a CMS, website, etc.
|
||||
Console.ForegroundColor = ConsoleColor.DarkMagenta;
|
||||
Console.WriteLine(
|
||||
$"""
|
||||
PUBLISHING: Content has been published successfully.
|
||||
Title: {content.Title}
|
||||
Content: {content.Content}
|
||||
""");
|
||||
Console.ResetColor();
|
||||
}
|
||||
|
||||
// Tools that demonstrate starting orchestrations from agent tool calls.
|
||||
[Description("Starts a content generation workflow and returns the instance ID for tracking.")]
|
||||
static string StartContentGenerationWorkflow([Description("The topic for content generation")] string topic)
|
||||
{
|
||||
const int MaxReviewAttempts = 3;
|
||||
const float ApprovalTimeoutHours = 72;
|
||||
|
||||
// Schedule the orchestration, which will start running after the tool call completes.
|
||||
string instanceId = DurableAgentContext.Current.ScheduleNewOrchestration(
|
||||
name: nameof(RunOrchestratorAsync),
|
||||
input: new ContentGenerationInput
|
||||
{
|
||||
Topic = topic,
|
||||
MaxReviewAttempts = MaxReviewAttempts,
|
||||
ApprovalTimeoutHours = ApprovalTimeoutHours
|
||||
});
|
||||
|
||||
return $"Workflow started with instance ID: {instanceId}";
|
||||
}
|
||||
|
||||
[Description("Gets the status of a workflow orchestration and returns a summary of the workflow's current status.")]
|
||||
static async Task<object> GetWorkflowStatusAsync(
|
||||
[Description("The instance ID of the workflow to check")] string instanceId,
|
||||
[Description("Whether to include detailed information")] bool includeDetails = true)
|
||||
{
|
||||
// Get the current agent context using the session-static property
|
||||
OrchestrationMetadata? status = await DurableAgentContext.Current.GetOrchestrationStatusAsync(
|
||||
instanceId,
|
||||
includeDetails);
|
||||
|
||||
if (status is null)
|
||||
{
|
||||
return new
|
||||
{
|
||||
instanceId,
|
||||
error = $"Workflow instance '{instanceId}' not found.",
|
||||
};
|
||||
}
|
||||
|
||||
return new
|
||||
{
|
||||
instanceId = status.InstanceId,
|
||||
createdAt = status.CreatedAt,
|
||||
executionStatus = status.RuntimeStatus,
|
||||
workflowStatus = status.SerializedCustomStatus,
|
||||
lastUpdatedAt = status.LastUpdatedAt,
|
||||
failureDetails = status.FailureDetails
|
||||
};
|
||||
}
|
||||
|
||||
[Description(
|
||||
"Raises a feedback event for the content generation workflow. If approved, the workflow will be published. " +
|
||||
"If rejected, the workflow will generate new content.")]
|
||||
static async Task SubmitHumanFeedbackAsync(
|
||||
[Description("The instance ID of the workflow to submit feedback for")] string instanceId,
|
||||
[Description("Feedback to submit")] HumanFeedbackResponse feedback)
|
||||
{
|
||||
await DurableAgentContext.Current.RaiseOrchestrationEventAsync(instanceId, HumanFeedbackEventName, feedback);
|
||||
}
|
||||
|
||||
// Configure the console app to host the AI agents.
|
||||
IHost host = Host.CreateDefaultBuilder(args)
|
||||
.ConfigureLogging(loggingBuilder => loggingBuilder.SetMinimumLevel(LogLevel.Warning))
|
||||
.ConfigureServices(services =>
|
||||
{
|
||||
services.ConfigureDurableAgents(
|
||||
options =>
|
||||
{
|
||||
// Add the writer agent used by the orchestration
|
||||
options.AddAIAgent(writerAgent);
|
||||
|
||||
// Define the agent that can start orchestrations from tool calls
|
||||
options.AddAIAgentFactory(PublisherAgentName, sp =>
|
||||
{
|
||||
return client.GetChatClient(deploymentName).AsAIAgent(
|
||||
instructions: PublisherAgentInstructions,
|
||||
name: PublisherAgentName,
|
||||
services: sp,
|
||||
tools: [
|
||||
AIFunctionFactory.Create(StartContentGenerationWorkflow),
|
||||
AIFunctionFactory.Create(GetWorkflowStatusAsync),
|
||||
AIFunctionFactory.Create(SubmitHumanFeedbackAsync),
|
||||
]);
|
||||
});
|
||||
},
|
||||
workerBuilder: builder =>
|
||||
{
|
||||
builder.UseDurableTaskScheduler(dtsConnectionString);
|
||||
builder.AddTasks(registry =>
|
||||
{
|
||||
registry.AddOrchestratorFunc<ContentGenerationInput>(nameof(RunOrchestratorAsync), RunOrchestratorAsync);
|
||||
registry.AddActivityFunc<GeneratedContent>(nameof(NotifyUserForApproval), NotifyUserForApproval);
|
||||
registry.AddActivityFunc<GeneratedContent>(nameof(PublishContent), PublishContent);
|
||||
});
|
||||
},
|
||||
clientBuilder: builder => builder.UseDurableTaskScheduler(dtsConnectionString));
|
||||
})
|
||||
.Build();
|
||||
|
||||
await host.StartAsync();
|
||||
|
||||
// Get the agent proxy from services
|
||||
IServiceProvider services = host.Services;
|
||||
AIAgent? agentProxy = services.GetKeyedService<AIAgent>(PublisherAgentName);
|
||||
if (agentProxy == null)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.Error.WriteLine("Agent 'Publisher' not found.");
|
||||
Console.ResetColor();
|
||||
Environment.Exit(1);
|
||||
return;
|
||||
}
|
||||
|
||||
// Console colors for better UX
|
||||
Console.ForegroundColor = ConsoleColor.Cyan;
|
||||
Console.WriteLine("=== Long Running Tools Sample ===");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine("Enter a topic for the Publisher agent to write about (or 'exit' to quit):");
|
||||
Console.WriteLine();
|
||||
|
||||
// Create a session for the conversation
|
||||
AgentSession session = await agentProxy.GetNewSessionAsync();
|
||||
|
||||
using CancellationTokenSource cts = new();
|
||||
Console.CancelKeyPress += (sender, e) =>
|
||||
{
|
||||
e.Cancel = true;
|
||||
cts.Cancel();
|
||||
};
|
||||
|
||||
while (!cts.Token.IsCancellationRequested)
|
||||
{
|
||||
// Read input from stdin
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.Write("You: ");
|
||||
Console.ResetColor();
|
||||
|
||||
string? input = Console.ReadLine();
|
||||
if (string.IsNullOrWhiteSpace(input) || input.Equals("exit", StringComparison.OrdinalIgnoreCase))
|
||||
{
|
||||
break;
|
||||
}
|
||||
|
||||
// Run the agent
|
||||
Console.ForegroundColor = ConsoleColor.Green;
|
||||
Console.Write("Publisher: ");
|
||||
Console.ResetColor();
|
||||
|
||||
try
|
||||
{
|
||||
AgentResponse agentResponse = await agentProxy.RunAsync(
|
||||
message: input,
|
||||
session: session,
|
||||
cancellationToken: cts.Token);
|
||||
|
||||
Console.WriteLine(agentResponse.Text);
|
||||
Console.WriteLine();
|
||||
}
|
||||
catch (Exception ex)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.Error.WriteLine($"Error: {ex.Message}");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine();
|
||||
}
|
||||
|
||||
Console.WriteLine("(Press Enter to prompt the Publisher agent again)");
|
||||
_ = Console.ReadLine();
|
||||
}
|
||||
|
||||
await host.StopAsync();
|
||||
@@ -0,0 +1,90 @@
|
||||
# Long Running Tools Sample
|
||||
|
||||
This sample demonstrates how to use the durable agents extension to create a console app with agents that have long running tools. This sample builds on the [05_AgentOrchestration_HITL](../05_AgentOrchestration_HITL) sample by adding a publisher agent that can start and manage content generation workflows. A key difference is that the publisher agent knows the IDs of the workflows it starts, so it can check the status of the workflows and approve or reject them without being explicitly given the context (instance IDs, etc).
|
||||
|
||||
## Key Concepts Demonstrated
|
||||
|
||||
The same key concepts as the [05_AgentOrchestration_HITL](../05_AgentOrchestration_HITL) sample are demonstrated, but with the following additional concepts:
|
||||
|
||||
- **Long running tools**: Using `DurableAgentContext.Current` to start orchestrations from tool calls
|
||||
- **Multi-agent orchestration**: Agents can start and manage workflows that orchestrate other agents
|
||||
- **Human-in-the-loop (with delegation)**: The agent acts as an intermediary between the human and the workflow. The human remains in the loop, but delegates to the agent to start the workflow and approve or reject the content.
|
||||
|
||||
## Environment Setup
|
||||
|
||||
See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
|
||||
|
||||
## Running the Sample
|
||||
|
||||
With the environment setup, you can run the sample:
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/DurableAgents/ConsoleApps/06_LongRunningTools
|
||||
dotnet run --framework net10.0
|
||||
```
|
||||
|
||||
The app will prompt you for input. You can interact with the Publisher agent:
|
||||
|
||||
```text
|
||||
=== Long Running Tools Sample ===
|
||||
Enter a topic for the Publisher agent to write about (or 'exit' to quit):
|
||||
|
||||
You: Start a content generation workflow for the topic 'The Future of Artificial Intelligence'
|
||||
Publisher: The content generation workflow for the topic "The Future of Artificial Intelligence" has been successfully started, and the instance ID is **6a04276e8d824d8d941e1dc4142cc254**. If you need any further assistance or updates on the workflow, feel free to ask!
|
||||
```
|
||||
|
||||
Behind the scenes, the publisher agent will:
|
||||
|
||||
1. Start the content generation workflow via a tool call
|
||||
2. The workflow will generate initial content using the Writer agent and wait for human approval, which will be visible in the terminal
|
||||
|
||||
Once the workflow is waiting for human approval, you can send approval or rejection by prompting the publisher agent accordingly.
|
||||
|
||||
> [!NOTE]
|
||||
> You must press Enter after each message to continue the conversation. The sample is set up this way because the workflow is running in the background and may write to the console asynchronously.
|
||||
|
||||
To tell the agent to rewrite the content with feedback, you can prompt it to reject the content with feedback.
|
||||
|
||||
```text
|
||||
You: Reject the content with feedback: The article needs more technical depth and better examples.
|
||||
Publisher: The content has been successfully rejected with the feedback: "The article needs more technical depth and better examples." The workflow will now generate new content based on this feedback.
|
||||
```
|
||||
|
||||
Once you're satisfied with the content, you can approve it for publishing.
|
||||
|
||||
```text
|
||||
You: Approve the content
|
||||
Publisher: The content has been successfully approved for publishing. If you need any more assistance or have further requests, feel free to let me know!
|
||||
```
|
||||
|
||||
Once the workflow has completed, you can get the status by prompting the publisher agent to give you the status.
|
||||
|
||||
```text
|
||||
You: Get the status of the workflow you previously started
|
||||
Publisher: The status of the workflow with instance ID **6a04276e8d824d8d941e1dc4142cc254** is as follows:
|
||||
|
||||
- **Execution Status:** Completed
|
||||
- **Created At:** December 22, 2025, 23:08:13 UTC
|
||||
- **Last Updated At:** December 22, 2025, 23:09:59 UTC
|
||||
- **Workflow Status:**
|
||||
- Message: Content published successfully at December 22, 2025, 23:09:59 UTC
|
||||
- Human Feedback: Approved
|
||||
```
|
||||
|
||||
## Viewing Agent and Orchestration State
|
||||
|
||||
You can view the state of both the agent and the orchestrations it starts in the Durable Task Scheduler dashboard:
|
||||
|
||||
1. Open your browser and navigate to `http://localhost:8082`
|
||||
2. In the dashboard, you can see:
|
||||
- **Agents**: View the state of the Publisher agent, including its conversation history and tool call history
|
||||
- **Orchestrations**: View the content generation orchestration instances that were started by the agent via tool calls, including their runtime status, custom status, input, output, and execution history
|
||||
|
||||
When the publisher agent starts a workflow, the orchestration instance ID is included in the agent's response. You can use this ID to find the specific orchestration in the dashboard and inspect:
|
||||
|
||||
- The orchestration's execution progress
|
||||
- When it's waiting for human approval (visible in custom status)
|
||||
- The content generation workflow state
|
||||
- The WriterAgent state within the orchestration
|
||||
|
||||
This demonstrates how agents can manage long-running workflows and how you can monitor both the agent's state and the workflows it orchestrates.
|
||||
+31
@@ -0,0 +1,31 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
<PropertyGroup>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
<OutputType>Exe</OutputType>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<Nullable>enable</Nullable>
|
||||
<AssemblyName>ReliableStreaming</AssemblyName>
|
||||
<RootNamespace>ReliableStreaming</RootNamespace>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.OpenAI" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="Microsoft.DurableTask.Client.AzureManaged" />
|
||||
<PackageReference Include="Microsoft.DurableTask.Worker.AzureManaged" />
|
||||
<PackageReference Include="Microsoft.Extensions.Hosting" />
|
||||
<PackageReference Include="StackExchange.Redis" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
|
||||
<!--
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.Agents.AI.DurableTask" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
|
||||
</ItemGroup>
|
||||
-->
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.DurableTask\Microsoft.Agents.AI.DurableTask.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
|
||||
</ItemGroup>
|
||||
</Project>
|
||||
@@ -0,0 +1,363 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample demonstrates how to implement reliable streaming for durable agents using Redis Streams.
|
||||
// It reads prompts from stdin and streams agent responses to stdout in real-time.
|
||||
|
||||
using System.ComponentModel;
|
||||
using Azure;
|
||||
using Azure.AI.OpenAI;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Agents.AI.DurableTask;
|
||||
using Microsoft.DurableTask.Client.AzureManaged;
|
||||
using Microsoft.DurableTask.Worker.AzureManaged;
|
||||
using Microsoft.Extensions.AI;
|
||||
using Microsoft.Extensions.DependencyInjection;
|
||||
using Microsoft.Extensions.Hosting;
|
||||
using Microsoft.Extensions.Logging;
|
||||
using OpenAI.Chat;
|
||||
using ReliableStreaming;
|
||||
using StackExchange.Redis;
|
||||
|
||||
// Get the Azure OpenAI endpoint and deployment name from environment variables.
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
|
||||
?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
|
||||
?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
|
||||
|
||||
// Get Redis connection string from environment variable.
|
||||
string redisConnectionString = Environment.GetEnvironmentVariable("REDIS_CONNECTION_STRING")
|
||||
?? "localhost:6379";
|
||||
|
||||
// Get the Redis stream TTL from environment variable (default: 10 minutes).
|
||||
int redisStreamTtlMinutes = int.Parse(Environment.GetEnvironmentVariable("REDIS_STREAM_TTL_MINUTES") ?? "10");
|
||||
|
||||
// Get DTS connection string from environment variable
|
||||
string dtsConnectionString = Environment.GetEnvironmentVariable("DURABLE_TASK_SCHEDULER_CONNECTION_STRING")
|
||||
?? "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None";
|
||||
|
||||
// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
|
||||
string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
|
||||
AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
|
||||
? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
|
||||
: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Travel Planner agent instructions - designed to produce longer responses for demonstrating streaming.
|
||||
const string TravelPlannerName = "TravelPlanner";
|
||||
const string TravelPlannerInstructions =
|
||||
"""
|
||||
You are an expert travel planner who creates detailed, personalized travel itineraries.
|
||||
When asked to plan a trip, you should:
|
||||
1. Create a comprehensive day-by-day itinerary
|
||||
2. Include specific recommendations for activities, restaurants, and attractions
|
||||
3. Provide practical tips for each destination
|
||||
4. Consider weather and local events when making recommendations
|
||||
5. Include estimated times and logistics between activities
|
||||
|
||||
Always use the available tools to get current weather forecasts and local events
|
||||
for the destination to make your recommendations more relevant and timely.
|
||||
|
||||
Format your response with clear headings for each day and include emoji icons
|
||||
to make the itinerary easy to scan and visually appealing.
|
||||
""";
|
||||
|
||||
// Mock travel tools that return hardcoded data for demonstration purposes.
|
||||
[Description("Gets the weather forecast for a destination on a specific date. Use this to provide weather-aware recommendations in the itinerary.")]
|
||||
static string GetWeatherForecast(string destination, string date)
|
||||
{
|
||||
Dictionary<string, (string condition, int highF, int lowF)> weatherByRegion = new(StringComparer.OrdinalIgnoreCase)
|
||||
{
|
||||
["Tokyo"] = ("Partly cloudy with a chance of light rain", 58, 45),
|
||||
["Paris"] = ("Overcast with occasional drizzle", 52, 41),
|
||||
["New York"] = ("Clear and cold", 42, 28),
|
||||
["London"] = ("Foggy morning, clearing in afternoon", 48, 38),
|
||||
["Sydney"] = ("Sunny and warm", 82, 68),
|
||||
["Rome"] = ("Sunny with light breeze", 62, 48),
|
||||
["Barcelona"] = ("Partly sunny", 59, 47),
|
||||
["Amsterdam"] = ("Cloudy with light rain", 46, 38),
|
||||
["Dubai"] = ("Sunny and hot", 85, 72),
|
||||
["Singapore"] = ("Tropical thunderstorms in afternoon", 88, 77),
|
||||
["Bangkok"] = ("Hot and humid, afternoon showers", 91, 78),
|
||||
["Los Angeles"] = ("Sunny and pleasant", 72, 55),
|
||||
["San Francisco"] = ("Morning fog, afternoon sun", 62, 52),
|
||||
["Seattle"] = ("Rainy with breaks", 48, 40),
|
||||
["Miami"] = ("Warm and sunny", 78, 65),
|
||||
["Honolulu"] = ("Tropical paradise weather", 82, 72),
|
||||
};
|
||||
|
||||
(string condition, int highF, int lowF) forecast = ("Partly cloudy", 65, 50);
|
||||
foreach (KeyValuePair<string, (string, int, int)> entry in weatherByRegion)
|
||||
{
|
||||
if (destination.Contains(entry.Key, StringComparison.OrdinalIgnoreCase))
|
||||
{
|
||||
forecast = entry.Value;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
return $"""
|
||||
Weather forecast for {destination} on {date}:
|
||||
Conditions: {forecast.condition}
|
||||
High: {forecast.highF}°F ({(forecast.highF - 32) * 5 / 9}°C)
|
||||
Low: {forecast.lowF}°F ({(forecast.lowF - 32) * 5 / 9}°C)
|
||||
|
||||
Recommendation: {GetWeatherRecommendation(forecast.condition)}
|
||||
""";
|
||||
}
|
||||
|
||||
[Description("Gets local events and activities happening at a destination around a specific date. Use this to suggest timely activities and experiences.")]
|
||||
static string GetLocalEvents(string destination, string date)
|
||||
{
|
||||
Dictionary<string, string[]> eventsByCity = new(StringComparer.OrdinalIgnoreCase)
|
||||
{
|
||||
["Tokyo"] = [
|
||||
"🎭 Kabuki Theater Performance at Kabukiza Theatre - Traditional Japanese drama",
|
||||
"🌸 Winter Illuminations at Yoyogi Park - Spectacular light displays",
|
||||
"🍜 Ramen Festival at Tokyo Station - Sample ramen from across Japan",
|
||||
"🎮 Gaming Expo at Tokyo Big Sight - Latest video games and technology",
|
||||
],
|
||||
["Paris"] = [
|
||||
"🎨 Impressionist Exhibition at Musée d'Orsay - Extended evening hours",
|
||||
"🍷 Wine Tasting Tour in Le Marais - Local sommelier guided",
|
||||
"🎵 Jazz Night at Le Caveau de la Huchette - Historic jazz club",
|
||||
"🥐 French Pastry Workshop - Learn from master pâtissiers",
|
||||
],
|
||||
["New York"] = [
|
||||
"🎭 Broadway Show: Hamilton - Limited engagement performances",
|
||||
"🏀 Knicks vs Lakers at Madison Square Garden",
|
||||
"🎨 Modern Art Exhibit at MoMA - New installations",
|
||||
"🍕 Pizza Walking Tour of Brooklyn - Artisan pizzerias",
|
||||
],
|
||||
["London"] = [
|
||||
"👑 Royal Collection Exhibition at Buckingham Palace",
|
||||
"🎭 West End Musical: The Phantom of the Opera",
|
||||
"🍺 Craft Beer Festival at Brick Lane",
|
||||
"🎪 Winter Wonderland at Hyde Park - Rides and markets",
|
||||
],
|
||||
["Sydney"] = [
|
||||
"🏄 Pro Surfing Competition at Bondi Beach",
|
||||
"🎵 Opera at Sydney Opera House - La Bohème",
|
||||
"🦘 Wildlife Night Safari at Taronga Zoo",
|
||||
"🍽️ Harbor Dinner Cruise with fireworks",
|
||||
],
|
||||
["Rome"] = [
|
||||
"🏛️ After-Hours Vatican Tour - Skip the crowds",
|
||||
"🍝 Pasta Making Class in Trastevere",
|
||||
"🎵 Classical Concert at Borghese Gallery",
|
||||
"🍷 Wine Tasting in Roman Cellars",
|
||||
],
|
||||
};
|
||||
|
||||
string[] events = [
|
||||
"🎭 Local theater performance",
|
||||
"🍽️ Food and wine festival",
|
||||
"🎨 Art gallery opening",
|
||||
"🎵 Live music at local venues",
|
||||
];
|
||||
|
||||
foreach (KeyValuePair<string, string[]> entry in eventsByCity)
|
||||
{
|
||||
if (destination.Contains(entry.Key, StringComparison.OrdinalIgnoreCase))
|
||||
{
|
||||
events = entry.Value;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
string eventList = string.Join("\n• ", events);
|
||||
return $"""
|
||||
Local events in {destination} around {date}:
|
||||
|
||||
• {eventList}
|
||||
|
||||
💡 Tip: Book popular events in advance as they may sell out quickly!
|
||||
""";
|
||||
}
|
||||
|
||||
static string GetWeatherRecommendation(string condition)
|
||||
{
|
||||
return condition switch
|
||||
{
|
||||
string c when c.Contains("rain", StringComparison.OrdinalIgnoreCase) || c.Contains("drizzle", StringComparison.OrdinalIgnoreCase) =>
|
||||
"Bring an umbrella and waterproof jacket. Consider indoor activities for backup.",
|
||||
string c when c.Contains("fog", StringComparison.OrdinalIgnoreCase) =>
|
||||
"Morning visibility may be limited. Plan outdoor sightseeing for afternoon.",
|
||||
string c when c.Contains("cold", StringComparison.OrdinalIgnoreCase) =>
|
||||
"Layer up with warm clothing. Hot drinks and cozy cafés recommended.",
|
||||
string c when c.Contains("hot", StringComparison.OrdinalIgnoreCase) || c.Contains("warm", StringComparison.OrdinalIgnoreCase) =>
|
||||
"Stay hydrated and use sunscreen. Plan strenuous activities for cooler morning hours.",
|
||||
string c when c.Contains("thunder", StringComparison.OrdinalIgnoreCase) || c.Contains("storm", StringComparison.OrdinalIgnoreCase) =>
|
||||
"Keep an eye on weather updates. Have indoor alternatives ready.",
|
||||
_ => "Pleasant conditions expected. Great day for outdoor exploration!"
|
||||
};
|
||||
}
|
||||
|
||||
// Configure the console app to host the AI agent.
|
||||
IHost host = Host.CreateDefaultBuilder(args)
|
||||
.ConfigureLogging(loggingBuilder => loggingBuilder.SetMinimumLevel(LogLevel.Warning))
|
||||
.ConfigureServices(services =>
|
||||
{
|
||||
services.ConfigureDurableAgents(
|
||||
options =>
|
||||
{
|
||||
// Define the Travel Planner agent with tools for weather and events
|
||||
options.AddAIAgentFactory(TravelPlannerName, sp =>
|
||||
{
|
||||
return client.GetChatClient(deploymentName).AsAIAgent(
|
||||
instructions: TravelPlannerInstructions,
|
||||
name: TravelPlannerName,
|
||||
services: sp,
|
||||
tools: [
|
||||
AIFunctionFactory.Create(GetWeatherForecast),
|
||||
AIFunctionFactory.Create(GetLocalEvents),
|
||||
]);
|
||||
});
|
||||
},
|
||||
workerBuilder: builder => builder.UseDurableTaskScheduler(dtsConnectionString),
|
||||
clientBuilder: builder => builder.UseDurableTaskScheduler(dtsConnectionString));
|
||||
|
||||
// Register Redis connection as a singleton
|
||||
services.AddSingleton<IConnectionMultiplexer>(_ =>
|
||||
ConnectionMultiplexer.Connect(redisConnectionString));
|
||||
|
||||
// Register the Redis stream response handler - this captures agent responses
|
||||
// and publishes them to Redis Streams for reliable delivery.
|
||||
services.AddSingleton(sp =>
|
||||
new RedisStreamResponseHandler(
|
||||
sp.GetRequiredService<IConnectionMultiplexer>(),
|
||||
TimeSpan.FromMinutes(redisStreamTtlMinutes)));
|
||||
services.AddSingleton<IAgentResponseHandler>(sp =>
|
||||
sp.GetRequiredService<RedisStreamResponseHandler>());
|
||||
})
|
||||
.Build();
|
||||
|
||||
await host.StartAsync();
|
||||
|
||||
// Get the agent proxy from services
|
||||
IServiceProvider services = host.Services;
|
||||
AIAgent? agentProxy = services.GetKeyedService<AIAgent>(TravelPlannerName);
|
||||
RedisStreamResponseHandler streamHandler = services.GetRequiredService<RedisStreamResponseHandler>();
|
||||
|
||||
if (agentProxy == null)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.Error.WriteLine($"Agent '{TravelPlannerName}' not found.");
|
||||
Console.ResetColor();
|
||||
Environment.Exit(1);
|
||||
return;
|
||||
}
|
||||
|
||||
// Console colors for better UX
|
||||
Console.ForegroundColor = ConsoleColor.Cyan;
|
||||
Console.WriteLine("=== Reliable Streaming Sample ===");
|
||||
Console.ResetColor();
|
||||
Console.WriteLine("Enter a travel planning request (or 'exit' to quit):");
|
||||
Console.WriteLine();
|
||||
|
||||
string? lastCursor = null;
|
||||
|
||||
async Task ReadStreamTask(string conversationId, string? cursor, CancellationToken cancellationToken)
|
||||
{
|
||||
// Initialize lastCursor to the starting cursor position
|
||||
// This ensures we have a valid cursor even if cancellation happens before any chunks are processed
|
||||
lastCursor = cursor;
|
||||
|
||||
await foreach (StreamChunk chunk in streamHandler.ReadStreamAsync(conversationId, cursor, cancellationToken))
|
||||
{
|
||||
if (chunk.Error != null)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Red;
|
||||
Console.Error.WriteLine($"\n[Error: {chunk.Error}]");
|
||||
Console.ResetColor();
|
||||
break;
|
||||
}
|
||||
|
||||
if (chunk.IsDone)
|
||||
{
|
||||
Console.WriteLine();
|
||||
Console.WriteLine();
|
||||
break;
|
||||
}
|
||||
|
||||
if (chunk.Text != null)
|
||||
{
|
||||
Console.Write(chunk.Text);
|
||||
}
|
||||
|
||||
// Always update lastCursor to track the latest entry ID, even if text is null
|
||||
// This ensures we can resume from the correct position after interruption
|
||||
if (!string.IsNullOrEmpty(chunk.EntryId))
|
||||
{
|
||||
lastCursor = chunk.EntryId;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// New conversation: prompt from stdin
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.Write("You: ");
|
||||
Console.ResetColor();
|
||||
|
||||
string? prompt = Console.ReadLine();
|
||||
if (string.IsNullOrWhiteSpace(prompt) || prompt.Equals("exit", StringComparison.OrdinalIgnoreCase))
|
||||
{
|
||||
return;
|
||||
}
|
||||
|
||||
// Create a new agent session
|
||||
AgentSession session = await agentProxy.GetNewSessionAsync();
|
||||
AgentSessionId sessionId = session.GetService<AgentSessionId>();
|
||||
string conversationId = sessionId.ToString();
|
||||
|
||||
Console.ForegroundColor = ConsoleColor.Green;
|
||||
Console.WriteLine($"Conversation ID: {conversationId}");
|
||||
Console.WriteLine("Press [Enter] to interrupt the stream.");
|
||||
Console.ResetColor();
|
||||
|
||||
// Run the agent in the background
|
||||
DurableAgentRunOptions options = new() { IsFireAndForget = true };
|
||||
await agentProxy.RunAsync(prompt, session, options, CancellationToken.None);
|
||||
|
||||
bool streamCompleted = false;
|
||||
while (!streamCompleted)
|
||||
{
|
||||
// On a key press, cancel the cancellation token to stop the stream
|
||||
using CancellationTokenSource userCancellationSource = new();
|
||||
_ = Task.Run(() =>
|
||||
{
|
||||
_ = Console.ReadLine();
|
||||
userCancellationSource.Cancel();
|
||||
});
|
||||
|
||||
try
|
||||
{
|
||||
// Start reading the stream and wait for it to complete
|
||||
await ReadStreamTask(conversationId, lastCursor, userCancellationSource.Token);
|
||||
streamCompleted = true;
|
||||
}
|
||||
catch (OperationCanceledException)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine("Stream cancelled. Press [Enter] to reconnect and resume the stream from the last cursor.");
|
||||
// Ensure lastCursor is set - if it's still null, we at least have the starting cursor
|
||||
string cursorValue = lastCursor ?? "(n/a)";
|
||||
Console.WriteLine($"Last cursor: {cursorValue}");
|
||||
Console.ResetColor();
|
||||
// Explicitly flush to ensure the message is written immediately
|
||||
Console.Out.Flush();
|
||||
}
|
||||
|
||||
if (!streamCompleted)
|
||||
{
|
||||
Console.ReadLine();
|
||||
Console.ForegroundColor = ConsoleColor.Green;
|
||||
Console.WriteLine($"Resuming conversation: {conversationId} from cursor: {lastCursor ?? "(beginning)"}");
|
||||
Console.ResetColor();
|
||||
}
|
||||
}
|
||||
|
||||
Console.ForegroundColor = ConsoleColor.Green;
|
||||
Console.WriteLine("Conversation completed.");
|
||||
Console.ResetColor();
|
||||
|
||||
await host.StopAsync();
|
||||
@@ -0,0 +1,181 @@
|
||||
# Reliable Streaming with Redis
|
||||
|
||||
This sample demonstrates how to implement reliable streaming for durable agents using Redis Streams as a message broker. It enables clients to disconnect and reconnect to ongoing agent responses without losing messages, inspired by [OpenAI's background mode](https://platform.openai.com/docs/guides/background) for the Responses API.
|
||||
|
||||
## Key Concepts Demonstrated
|
||||
|
||||
- **Reliable message delivery**: Agent responses are persisted to Redis Streams, allowing clients to resume from any point
|
||||
- **Real-time streaming**: Chunks are printed to stdout as they arrive (like `tail -f`)
|
||||
- **Cursor-based resumption**: Each chunk includes an entry ID that can be used to resume the stream
|
||||
- **Fire-and-forget agent invocation**: The agent runs in the background while the client streams from Redis
|
||||
|
||||
## Environment Setup
|
||||
|
||||
See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
|
||||
|
||||
### Additional Requirements: Redis
|
||||
|
||||
This sample requires a Redis instance. Start a local Redis instance using Docker:
|
||||
|
||||
```bash
|
||||
docker run -d --name redis -p 6379:6379 redis:latest
|
||||
```
|
||||
|
||||
To verify Redis is running:
|
||||
|
||||
```bash
|
||||
docker ps | grep redis
|
||||
```
|
||||
|
||||
## Running the Sample
|
||||
|
||||
With the environment setup, you can run the sample:
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/DurableAgents/ConsoleApps/07_ReliableStreaming
|
||||
dotnet run --framework net10.0
|
||||
```
|
||||
|
||||
The app will prompt you for a travel planning request:
|
||||
|
||||
```text
|
||||
=== Reliable Streaming Sample ===
|
||||
Enter a travel planning request (or 'exit' to quit):
|
||||
|
||||
You: Plan a 7-day trip to Tokyo, Japan for next month. Include daily activities, restaurant recommendations, and tips for getting around.
|
||||
```
|
||||
|
||||
The agent's response will stream to your console in real-time as chunks arrive from Redis:
|
||||
|
||||
```text
|
||||
Starting new conversation: @dafx-travelplanner@a1b2c3d4e5f67890abcdef1234567890
|
||||
Press [Enter] to interrupt the stream.
|
||||
|
||||
TravelPlanner: # 7-Day Tokyo Adventure
|
||||
|
||||
## Day 1: Arrival and Exploration
|
||||
...
|
||||
```
|
||||
|
||||
### Demonstrating Stream Interruption and Resumption
|
||||
|
||||
This is the key feature of reliable streaming. Follow these steps to see it in action:
|
||||
|
||||
1. **Start a stream**: Run the app and enter a travel planning request
|
||||
2. **Note the conversation ID**: The conversation ID is displayed at the start of the stream (e.g., `Starting new conversation: @dafx-travelplanner@a1b2c3d4e5f67890abcdef1234567890`)
|
||||
3. **Interrupt the stream**: While the agent is still generating text, press **`Enter`** to interrupt. The agent continues running in the background - your messages are being saved to Redis.
|
||||
4. **Resume the stream**: Press **`Enter`** again to reconnect and resume the stream from the last cursor position. The app will automatically resume from where it left off.
|
||||
|
||||
```text
|
||||
Starting new conversation: @dafx-travelplanner@a1b2c3d4e5f67890abcdef1234567890
|
||||
Press [Enter] to interrupt the stream.
|
||||
|
||||
TravelPlanner: # 7-Day Tokyo Adventure
|
||||
|
||||
## Day 1: Arrival and Exploration
|
||||
[Streaming content...]
|
||||
|
||||
[Press Enter to interrupt]
|
||||
Stream cancelled. Press [Enter] to reconnect and resume the stream from the last cursor.
|
||||
Last cursor: 1734567890123-0
|
||||
|
||||
[Press Enter to resume]
|
||||
Resuming conversation: @dafx-travelplanner@a1b2c3d4e5f67890abcdef1234567890 from cursor: 1734567890123-0
|
||||
|
||||
[Stream continues from where it left off...]
|
||||
```
|
||||
|
||||
## Viewing Agent State
|
||||
|
||||
You can view the state of the agent in the Durable Task Scheduler dashboard:
|
||||
|
||||
1. Open your browser and navigate to `http://localhost:8082`
|
||||
2. In the dashboard, you can see:
|
||||
- **Agents**: View the state of the TravelPlanner agent, including conversation history and current state
|
||||
- **Orchestrations**: View any orchestrations that may have been triggered by the agent
|
||||
|
||||
The conversation ID displayed in the console output (shown as "Starting new conversation: {conversationId}") corresponds to the agent's conversation thread. You can use this to identify the agent in the dashboard and inspect:
|
||||
|
||||
- The agent's conversation state
|
||||
- Tool calls made by the agent (weather and events lookups)
|
||||
- The streaming response state
|
||||
|
||||
Note that while the console app streams responses from Redis, the agent state in DTS shows the underlying durable agent execution, including all tool calls and conversation context.
|
||||
|
||||
## Architecture Overview
|
||||
|
||||
```text
|
||||
┌─────────────┐ stdin (prompt) ┌─────────────────────┐
|
||||
│ Client │ ─────────────────────► │ Console App │
|
||||
│ (stdin) │ │ (Program.cs) │
|
||||
└─────────────┘ └──────────────┬──────┘
|
||||
▲ │
|
||||
│ stdout (chunks) Signal Entity
|
||||
│ │
|
||||
│ ▼
|
||||
│ ┌─────────────────────┐
|
||||
│ │ AgentEntity │
|
||||
│ │ (Durable Entity) │
|
||||
│ └──────────┬──────────┘
|
||||
│ │
|
||||
│ IAgentResponseHandler
|
||||
│ │
|
||||
│ ▼
|
||||
│ ┌─────────────────────┐
|
||||
│ │ RedisStreamResponse │
|
||||
│ │ Handler │
|
||||
│ └──────────┬──────────┘
|
||||
│ │
|
||||
│ XADD (write)
|
||||
│ │
|
||||
│ ▼
|
||||
│ ┌─────────────────────┐
|
||||
└─────────── XREAD (poll) ────────── │ Redis Streams │
|
||||
│ (Durable Log) │
|
||||
└─────────────────────┘
|
||||
```
|
||||
|
||||
### Data Flow
|
||||
|
||||
1. **Client sends prompt**: The console app reads the prompt from stdin and generates a new agent thread.
|
||||
|
||||
2. **Agent invoked**: The durable agent is signaled to run the travel planner agent. This is fire-and-forget from the console app's perspective.
|
||||
|
||||
3. **Responses captured**: As the agent generates responses, the `RedisStreamResponseHandler` (implementing `IAgentResponseHandler`) extracts the text from each `AgentRunResponseUpdate` and publishes it to a Redis Stream keyed by the agent session's conversation ID.
|
||||
|
||||
4. **Client polls Redis**: The console app streams events by polling the Redis Stream and printing chunks to stdout as they arrive.
|
||||
|
||||
5. **Resumption**: If the client interrupts the stream (e.g., by pressing Enter in the sample), it can resume from the last cursor position by providing the conversation ID and cursor to the call to resume the stream.
|
||||
|
||||
## Message Delivery Guarantees
|
||||
|
||||
This sample provides **at-least-once delivery** with the following characteristics:
|
||||
|
||||
- **Durability**: Messages are persisted to Redis Streams with configurable TTL (default: 10 minutes).
|
||||
- **Ordering**: Messages are delivered in order within a session.
|
||||
- **Real-time**: Chunks are printed as soon as they arrive from Redis.
|
||||
|
||||
### Important Considerations
|
||||
|
||||
- **No exactly-once delivery**: If a client disconnects exactly when receiving a message, it may receive that message again upon resumption. Clients should handle duplicate messages idempotently.
|
||||
- **TTL expiration**: Streams expire after the configured TTL. Clients cannot resume streams that have expired.
|
||||
- **Redis guarantees**: Redis streams are backed by Redis persistence mechanisms (RDB/AOF). Ensure your Redis instance is configured for durability as needed.
|
||||
|
||||
## Configuration
|
||||
|
||||
| Environment Variable | Description | Default |
|
||||
|---------------------|-------------|---------|
|
||||
| `REDIS_CONNECTION_STRING` | Redis connection string | `localhost:6379` |
|
||||
| `REDIS_STREAM_TTL_MINUTES` | How long streams are retained after last write | `10` |
|
||||
| `AZURE_OPENAI_ENDPOINT` | Azure OpenAI endpoint URL | (required) |
|
||||
| `AZURE_OPENAI_DEPLOYMENT` | Azure OpenAI deployment name | (required) |
|
||||
| `AZURE_OPENAI_KEY` | API key (optional, uses Azure CLI auth if not set) | (optional) |
|
||||
|
||||
## Cleanup
|
||||
|
||||
To stop and remove the Redis Docker containers:
|
||||
|
||||
```bash
|
||||
docker stop redis
|
||||
docker rm redis
|
||||
```
|
||||
+216
@@ -0,0 +1,216 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using System.Runtime.CompilerServices;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Agents.AI.DurableTask;
|
||||
using StackExchange.Redis;
|
||||
|
||||
namespace ReliableStreaming;
|
||||
|
||||
/// <summary>
|
||||
/// Represents a chunk of data read from a Redis stream.
|
||||
/// </summary>
|
||||
/// <param name="EntryId">The Redis stream entry ID (can be used as a cursor for resumption).</param>
|
||||
/// <param name="Text">The text content of the chunk, or null if this is a completion/error marker.</param>
|
||||
/// <param name="IsDone">True if this chunk marks the end of the stream.</param>
|
||||
/// <param name="Error">An error message if something went wrong, or null otherwise.</param>
|
||||
public readonly record struct StreamChunk(string EntryId, string? Text, bool IsDone, string? Error);
|
||||
|
||||
/// <summary>
|
||||
/// An implementation of <see cref="IAgentResponseHandler"/> that publishes agent response updates
|
||||
/// to Redis Streams for reliable delivery. This enables clients to disconnect and reconnect
|
||||
/// to ongoing agent responses without losing messages.
|
||||
/// </summary>
|
||||
/// <remarks>
|
||||
/// <para>
|
||||
/// Redis Streams provide a durable, append-only log that supports consumer groups and message
|
||||
/// acknowledgment. This implementation uses auto-generated IDs (which are timestamp-based)
|
||||
/// as sequence numbers, allowing clients to resume from any point in the stream.
|
||||
/// </para>
|
||||
/// <para>
|
||||
/// Each agent session gets its own Redis Stream, keyed by session ID. The stream entries
|
||||
/// contain text chunks extracted from <see cref="AgentResponseUpdate"/> objects.
|
||||
/// </para>
|
||||
/// </remarks>
|
||||
public sealed class RedisStreamResponseHandler : IAgentResponseHandler
|
||||
{
|
||||
private const int MaxEmptyReads = 300; // 5 minutes at 1 second intervals
|
||||
private const int PollIntervalMs = 1000;
|
||||
|
||||
private readonly IConnectionMultiplexer _redis;
|
||||
private readonly TimeSpan _streamTtl;
|
||||
|
||||
/// <summary>
|
||||
/// Initializes a new instance of the <see cref="RedisStreamResponseHandler" /> class.
|
||||
/// </summary>
|
||||
/// <param name="redis">The Redis connection multiplexer.</param>
|
||||
/// <param name="streamTtl">The time-to-live for stream entries. Streams will expire after this duration of inactivity.</param>
|
||||
public RedisStreamResponseHandler(IConnectionMultiplexer redis, TimeSpan streamTtl)
|
||||
{
|
||||
this._redis = redis;
|
||||
this._streamTtl = streamTtl;
|
||||
}
|
||||
|
||||
/// <inheritdoc/>
|
||||
public async ValueTask OnStreamingResponseUpdateAsync(
|
||||
IAsyncEnumerable<AgentResponseUpdate> messageStream,
|
||||
CancellationToken cancellationToken)
|
||||
{
|
||||
// Get the current session ID from the DurableAgentContext
|
||||
// This is set by the AgentEntity before invoking the response handler
|
||||
DurableAgentContext context = DurableAgentContext.Current
|
||||
?? throw new InvalidOperationException("DurableAgentContext.Current is not set. This handler must be used within a durable agent context.");
|
||||
|
||||
// Get conversation ID from the current session context, which is only available in the context of
|
||||
// a durable agent execution.
|
||||
string conversationId = context.CurrentSession.GetService<AgentSessionId>().ToString();
|
||||
if (string.IsNullOrEmpty(conversationId))
|
||||
{
|
||||
throw new InvalidOperationException("Unable to determine conversation ID from the current session.");
|
||||
}
|
||||
|
||||
string streamKey = GetStreamKey(conversationId);
|
||||
|
||||
IDatabase db = this._redis.GetDatabase();
|
||||
int sequenceNumber = 0;
|
||||
|
||||
await foreach (AgentResponseUpdate update in messageStream.WithCancellation(cancellationToken))
|
||||
{
|
||||
// Extract just the text content - this avoids serialization round-trip issues
|
||||
string text = update.Text;
|
||||
|
||||
// Only publish non-empty text chunks
|
||||
if (!string.IsNullOrEmpty(text))
|
||||
{
|
||||
// Create the stream entry with the text and metadata
|
||||
NameValueEntry[] entries =
|
||||
[
|
||||
new NameValueEntry("text", text),
|
||||
new NameValueEntry("sequence", sequenceNumber++),
|
||||
new NameValueEntry("timestamp", DateTimeOffset.UtcNow.ToUnixTimeMilliseconds()),
|
||||
];
|
||||
|
||||
// Add to the Redis Stream with auto-generated ID (timestamp-based)
|
||||
await db.StreamAddAsync(streamKey, entries);
|
||||
|
||||
// Refresh the TTL on each write to keep the stream alive during active streaming
|
||||
await db.KeyExpireAsync(streamKey, this._streamTtl);
|
||||
}
|
||||
}
|
||||
|
||||
// Add a sentinel entry to mark the end of the stream
|
||||
NameValueEntry[] endEntries =
|
||||
[
|
||||
new NameValueEntry("text", ""),
|
||||
new NameValueEntry("sequence", sequenceNumber),
|
||||
new NameValueEntry("timestamp", DateTimeOffset.UtcNow.ToUnixTimeMilliseconds()),
|
||||
new NameValueEntry("done", "true"),
|
||||
];
|
||||
await db.StreamAddAsync(streamKey, endEntries);
|
||||
|
||||
// Set final TTL - the stream will be cleaned up after this duration
|
||||
await db.KeyExpireAsync(streamKey, this._streamTtl);
|
||||
}
|
||||
|
||||
/// <inheritdoc/>
|
||||
public ValueTask OnAgentResponseAsync(AgentResponse message, CancellationToken cancellationToken)
|
||||
{
|
||||
// This handler is optimized for streaming responses.
|
||||
// For non-streaming responses, we don't need to store in Redis since
|
||||
// the response is returned directly to the caller.
|
||||
return ValueTask.CompletedTask;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Reads chunks from a Redis stream for the given session, yielding them as they become available.
|
||||
/// </summary>
|
||||
/// <param name="conversationId">The conversation ID to read from.</param>
|
||||
/// <param name="cursor">Optional cursor to resume from. If null, reads from the beginning.</param>
|
||||
/// <param name="cancellationToken">Cancellation token.</param>
|
||||
/// <returns>An async enumerable of stream chunks.</returns>
|
||||
public async IAsyncEnumerable<StreamChunk> ReadStreamAsync(
|
||||
string conversationId,
|
||||
string? cursor,
|
||||
[EnumeratorCancellation] CancellationToken cancellationToken)
|
||||
{
|
||||
string streamKey = GetStreamKey(conversationId);
|
||||
|
||||
IDatabase db = this._redis.GetDatabase();
|
||||
string startId = string.IsNullOrEmpty(cursor) ? "0-0" : cursor;
|
||||
|
||||
int emptyReadCount = 0;
|
||||
bool hasSeenData = false;
|
||||
|
||||
while (!cancellationToken.IsCancellationRequested)
|
||||
{
|
||||
StreamEntry[]? entries = null;
|
||||
string? errorMessage = null;
|
||||
|
||||
try
|
||||
{
|
||||
entries = await db.StreamReadAsync(streamKey, startId, count: 100);
|
||||
}
|
||||
catch (Exception ex)
|
||||
{
|
||||
errorMessage = ex.Message;
|
||||
}
|
||||
|
||||
if (errorMessage != null)
|
||||
{
|
||||
yield return new StreamChunk(startId, null, false, errorMessage);
|
||||
yield break;
|
||||
}
|
||||
|
||||
// entries is guaranteed to be non-null if errorMessage is null
|
||||
if (entries!.Length == 0)
|
||||
{
|
||||
if (!hasSeenData)
|
||||
{
|
||||
emptyReadCount++;
|
||||
if (emptyReadCount >= MaxEmptyReads)
|
||||
{
|
||||
yield return new StreamChunk(
|
||||
startId,
|
||||
null,
|
||||
false,
|
||||
$"Stream not found or timed out after {MaxEmptyReads * PollIntervalMs / 1000} seconds");
|
||||
yield break;
|
||||
}
|
||||
}
|
||||
|
||||
await Task.Delay(PollIntervalMs, cancellationToken);
|
||||
continue;
|
||||
}
|
||||
|
||||
hasSeenData = true;
|
||||
|
||||
foreach (StreamEntry entry in entries)
|
||||
{
|
||||
startId = entry.Id.ToString();
|
||||
string? text = entry["text"];
|
||||
string? done = entry["done"];
|
||||
|
||||
if (done == "true")
|
||||
{
|
||||
yield return new StreamChunk(startId, null, true, null);
|
||||
yield break;
|
||||
}
|
||||
|
||||
if (!string.IsNullOrEmpty(text))
|
||||
{
|
||||
yield return new StreamChunk(startId, text, false, null);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// If we exited the loop due to cancellation, throw to signal the caller
|
||||
cancellationToken.ThrowIfCancellationRequested();
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Gets the Redis Stream key for a given conversation ID.
|
||||
/// </summary>
|
||||
/// <param name="conversationId">The conversation ID.</param>
|
||||
/// <returns>The Redis Stream key.</returns>
|
||||
internal static string GetStreamKey(string conversationId) => $"agent-stream:{conversationId}";
|
||||
}
|
||||
@@ -0,0 +1,109 @@
|
||||
# Console App Samples
|
||||
|
||||
This directory contains samples for console app hosting of durable agents. These samples use standard I/O (stdin/stdout) for interaction, making them both interactive and scriptable.
|
||||
|
||||
- **[01_SingleAgent](01_SingleAgent)**: A sample that demonstrates how to host a single conversational agent in a console app and interact with it via stdin/stdout.
|
||||
- **[02_AgentOrchestration_Chaining](02_AgentOrchestration_Chaining)**: A sample that demonstrates how to host a single conversational agent in a console app and invoke it using a durable orchestration.
|
||||
- **[03_AgentOrchestration_Concurrency](03_AgentOrchestration_Concurrency)**: A sample that demonstrates how to host multiple agents in a console app and run them concurrently using a durable orchestration.
|
||||
- **[04_AgentOrchestration_Conditionals](04_AgentOrchestration_Conditionals)**: A sample that demonstrates how to host multiple agents in a console app and run them sequentially using a durable orchestration with conditionals.
|
||||
- **[05_AgentOrchestration_HITL](05_AgentOrchestration_HITL)**: A sample that demonstrates how to implement a human-in-the-loop workflow using durable orchestration, including interactive approval prompts.
|
||||
- **[06_LongRunningTools](06_LongRunningTools)**: A sample that demonstrates how agents can start and interact with durable orchestrations from tool calls to enable long-running tool scenarios.
|
||||
- **[07_ReliableStreaming](07_ReliableStreaming)**: A sample that demonstrates how to implement reliable streaming for durable agents using Redis Streams, enabling clients to disconnect and reconnect without losing messages.
|
||||
|
||||
## Running the Samples
|
||||
|
||||
These samples are designed to be run locally in a cloned repository.
|
||||
|
||||
### Prerequisites
|
||||
|
||||
The following prerequisites are required to run the samples:
|
||||
|
||||
- [.NET 10.0 SDK or later](https://dotnet.microsoft.com/download/dotnet)
|
||||
- [Azure CLI](https://learn.microsoft.com/cli/azure/install-azure-cli) installed and authenticated (`az login`) or an API key for the Azure OpenAI service
|
||||
- [Azure OpenAI Service](https://learn.microsoft.com/azure/ai-services/openai/how-to/create-resource) with a deployed model (gpt-4o-mini or better is recommended)
|
||||
- [Durable Task Scheduler](https://learn.microsoft.com/azure/azure-functions/durable/durable-task-scheduler/develop-with-durable-task-scheduler) (local emulator or Azure-hosted)
|
||||
- [Docker](https://docs.docker.com/get-docker/) installed if running the Durable Task Scheduler emulator locally
|
||||
- [Redis](https://redis.io/) (for sample 07 only) - can be run locally using Docker
|
||||
|
||||
### Configuring RBAC Permissions for Azure OpenAI
|
||||
|
||||
These samples are configured to use the Azure OpenAI service with RBAC permissions to access the model. You'll need to configure the RBAC permissions for the Azure OpenAI service to allow the console app to access the model.
|
||||
|
||||
Below is an example of how to configure the RBAC permissions for the Azure OpenAI service to allow the current user to access the model.
|
||||
|
||||
Bash (Linux/macOS/WSL):
|
||||
|
||||
```bash
|
||||
az role assignment create \
|
||||
--assignee "yourname@contoso.com" \
|
||||
--role "Cognitive Services OpenAI User" \
|
||||
--scope /subscriptions/<your-subscription-id>/resourceGroups/<your-resource-group-name>/providers/Microsoft.CognitiveServices/accounts/<your-openai-resource-name>
|
||||
```
|
||||
|
||||
PowerShell:
|
||||
|
||||
```powershell
|
||||
az role assignment create `
|
||||
--assignee "yourname@contoso.com" `
|
||||
--role "Cognitive Services OpenAI User" `
|
||||
--scope /subscriptions/<your-subscription-id>/resourceGroups/<your-resource-group-name>/providers/Microsoft.CognitiveServices/accounts/<your-openai-resource-name>
|
||||
```
|
||||
|
||||
More information on how to configure RBAC permissions for Azure OpenAI can be found in the [Azure OpenAI documentation](https://learn.microsoft.com/azure/ai-services/openai/how-to/create-resource?pivots=cli).
|
||||
|
||||
### Setting an API key for the Azure OpenAI service
|
||||
|
||||
As an alternative to configuring Azure RBAC permissions, you can set an API key for the Azure OpenAI service by setting the `AZURE_OPENAI_KEY` environment variable.
|
||||
|
||||
Bash (Linux/macOS/WSL):
|
||||
|
||||
```bash
|
||||
export AZURE_OPENAI_KEY="your-api-key"
|
||||
```
|
||||
|
||||
PowerShell:
|
||||
|
||||
```powershell
|
||||
$env:AZURE_OPENAI_KEY="your-api-key"
|
||||
```
|
||||
|
||||
### Start Durable Task Scheduler
|
||||
|
||||
Most samples use the Durable Task Scheduler (DTS) to support hosted agents and durable orchestrations. DTS also allows you to view the status of orchestrations and their inputs and outputs from a web UI.
|
||||
|
||||
To run the Durable Task Scheduler locally, you can use the following `docker` command:
|
||||
|
||||
```bash
|
||||
docker run -d --name dts-emulator -p 8080:8080 -p 8082:8082 mcr.microsoft.com/dts/dts-emulator:latest
|
||||
```
|
||||
|
||||
The DTS dashboard will be available at `http://localhost:8080`.
|
||||
|
||||
### Environment Configuration
|
||||
|
||||
Each sample reads configuration from environment variables. You'll need to set the following environment variables:
|
||||
|
||||
```bash
|
||||
export AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"
|
||||
export AZURE_OPENAI_DEPLOYMENT="your-deployment-name"
|
||||
```
|
||||
|
||||
### Running the Console Apps
|
||||
|
||||
Navigate to the sample directory and run the console app:
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/DurableAgents/ConsoleApps/01_SingleAgent
|
||||
dotnet run --framework net10.0
|
||||
```
|
||||
|
||||
> [!NOTE]
|
||||
> The `--framework` option is required to specify the target framework for the console app because the samples are designed to support multiple target frameworks. If you are using a different target framework, you can specify it with the `--framework` option.
|
||||
|
||||
The app will prompt you for input via stdin.
|
||||
|
||||
### Viewing the sample output
|
||||
|
||||
The console app output is displayed directly in the terminal where you ran `dotnet run`. Agent responses are printed to stdout with subtle color coding for better readability.
|
||||
|
||||
You can also see the state of agents and orchestrations in the Durable Task Scheduler dashboard at `http://localhost:8082`.
|
||||
@@ -0,0 +1,9 @@
|
||||
<Project>
|
||||
|
||||
<Import Project="../Directory.Build.props" />
|
||||
|
||||
<!-- Remove the Environment alias from parent Directory.Build.props to allow System.Environment usage -->
|
||||
<ItemGroup>
|
||||
<Using Remove="SampleHelpers.SampleEnvironment" />
|
||||
</ItemGroup>
|
||||
</Project>
|
||||
@@ -16,10 +16,10 @@ AgentCard agentCard = await agentCardResolver.GetAgentCardAsync();
|
||||
// Create an instance of the AIAgent for an existing A2A agent specified by the agent card.
|
||||
AIAgent agent = agentCard.AsAIAgent();
|
||||
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
|
||||
// Start the initial run with a long-running task.
|
||||
AgentResponse response = await agent.RunAsync("Conduct a comprehensive analysis of quantum computing applications in cryptography, including recent breakthroughs, implementation challenges, and future roadmap. Please include diagrams and visual representations to illustrate complex concepts.", thread);
|
||||
AgentResponse response = await agent.RunAsync("Conduct a comprehensive analysis of quantum computing applications in cryptography, including recent breakthroughs, implementation challenges, and future roadmap. Please include diagrams and visual representations to illustrate complex concepts.", session);
|
||||
|
||||
// Poll until the response is complete.
|
||||
while (response.ContinuationToken is { } token)
|
||||
@@ -28,7 +28,7 @@ while (response.ContinuationToken is { } token)
|
||||
await Task.Delay(TimeSpan.FromSeconds(2));
|
||||
|
||||
// Continue with the token.
|
||||
response = await agent.RunAsync(thread, options: new AgentRunOptions { ContinuationToken = token });
|
||||
response = await agent.RunAsync(session, options: new AgentRunOptions { ContinuationToken = token });
|
||||
}
|
||||
|
||||
// Display the result
|
||||
|
||||
@@ -20,7 +20,7 @@ AIAgent agent = chatClient.AsAIAgent(
|
||||
name: "agui-client",
|
||||
description: "AG-UI Client Agent");
|
||||
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
List<ChatMessage> messages =
|
||||
[
|
||||
new(ChatRole.System, "You are a helpful assistant.")
|
||||
@@ -49,18 +49,18 @@ try
|
||||
|
||||
// Stream the response
|
||||
bool isFirstUpdate = true;
|
||||
string? threadId = null;
|
||||
string? sessionId = null;
|
||||
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread))
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, session))
|
||||
{
|
||||
ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();
|
||||
|
||||
// First update indicates run started
|
||||
if (isFirstUpdate)
|
||||
{
|
||||
threadId = chatUpdate.ConversationId;
|
||||
sessionId = chatUpdate.ConversationId;
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine($"\n[Run Started - Thread: {chatUpdate.ConversationId}, Run: {chatUpdate.ResponseId}]");
|
||||
Console.WriteLine($"\n[Run Started - Session: {chatUpdate.ConversationId}, Run: {chatUpdate.ResponseId}]");
|
||||
Console.ResetColor();
|
||||
isFirstUpdate = false;
|
||||
}
|
||||
@@ -84,7 +84,7 @@ try
|
||||
}
|
||||
|
||||
Console.ForegroundColor = ConsoleColor.Green;
|
||||
Console.WriteLine($"\n[Run Finished - Thread: {threadId}]");
|
||||
Console.WriteLine($"\n[Run Finished - Session: {sessionId}]");
|
||||
Console.ResetColor();
|
||||
}
|
||||
}
|
||||
|
||||
@@ -20,7 +20,7 @@ AIAgent agent = chatClient.AsAIAgent(
|
||||
name: "agui-client",
|
||||
description: "AG-UI Client Agent");
|
||||
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
List<ChatMessage> messages =
|
||||
[
|
||||
new(ChatRole.System, "You are a helpful assistant.")
|
||||
@@ -49,18 +49,18 @@ try
|
||||
|
||||
// Stream the response
|
||||
bool isFirstUpdate = true;
|
||||
string? threadId = null;
|
||||
string? sessionId = null;
|
||||
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread))
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, session))
|
||||
{
|
||||
ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();
|
||||
|
||||
// First update indicates run started
|
||||
if (isFirstUpdate)
|
||||
{
|
||||
threadId = chatUpdate.ConversationId;
|
||||
sessionId = chatUpdate.ConversationId;
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine($"\n[Run Started - Thread: {chatUpdate.ConversationId}, Run: {chatUpdate.ResponseId}]");
|
||||
Console.WriteLine($"\n[Run Started - Session: {chatUpdate.ConversationId}, Run: {chatUpdate.ResponseId}]");
|
||||
Console.ResetColor();
|
||||
isFirstUpdate = false;
|
||||
}
|
||||
@@ -116,7 +116,7 @@ try
|
||||
}
|
||||
|
||||
Console.ForegroundColor = ConsoleColor.Green;
|
||||
Console.WriteLine($"\n[Run Finished - Thread: {threadId}]");
|
||||
Console.WriteLine($"\n[Run Finished - Session: {sessionId}]");
|
||||
Console.ResetColor();
|
||||
}
|
||||
}
|
||||
|
||||
@@ -33,7 +33,7 @@ AIAgent agent = chatClient.AsAIAgent(
|
||||
description: "AG-UI Client Agent",
|
||||
tools: frontendTools);
|
||||
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
List<ChatMessage> messages =
|
||||
[
|
||||
new(ChatRole.System, "You are a helpful assistant.")
|
||||
@@ -62,18 +62,18 @@ try
|
||||
|
||||
// Stream the response
|
||||
bool isFirstUpdate = true;
|
||||
string? threadId = null;
|
||||
string? sessionId = null;
|
||||
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread))
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, session))
|
||||
{
|
||||
ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();
|
||||
|
||||
// First update indicates run started
|
||||
if (isFirstUpdate)
|
||||
{
|
||||
threadId = chatUpdate.ConversationId;
|
||||
sessionId = chatUpdate.ConversationId;
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine($"\n[Run Started - Thread: {chatUpdate.ConversationId}, Run: {chatUpdate.ResponseId}]");
|
||||
Console.WriteLine($"\n[Run Started - Session: {chatUpdate.ConversationId}, Run: {chatUpdate.ResponseId}]");
|
||||
Console.ResetColor();
|
||||
isFirstUpdate = false;
|
||||
}
|
||||
@@ -109,7 +109,7 @@ try
|
||||
}
|
||||
|
||||
Console.ForegroundColor = ConsoleColor.Green;
|
||||
Console.WriteLine($"\n[Run Finished - Thread: {threadId}]");
|
||||
Console.WriteLine($"\n[Run Finished - Session: {sessionId}]");
|
||||
Console.ResetColor();
|
||||
}
|
||||
}
|
||||
|
||||
@@ -27,7 +27,7 @@ JsonSerializerOptions jsonSerializerOptions = JsonSerializerOptions.Default;
|
||||
ServerFunctionApprovalClientAgent agent = new(baseAgent, jsonSerializerOptions);
|
||||
|
||||
List<ChatMessage> messages = [];
|
||||
AgentThread? thread = null;
|
||||
AgentSession? session = null;
|
||||
|
||||
Console.ForegroundColor = ConsoleColor.White;
|
||||
Console.WriteLine("Ask a question (or type 'exit' to quit):");
|
||||
@@ -52,7 +52,7 @@ while ((input = Console.ReadLine()) != null && !input.Equals("exit", StringCompa
|
||||
approvalResponses.Clear();
|
||||
|
||||
List<AgentResponseUpdate> chatResponseUpdates = [];
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread, cancellationToken: default))
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, session, cancellationToken: default))
|
||||
{
|
||||
chatResponseUpdates.Add(update);
|
||||
foreach (AIContent content in update.Contents)
|
||||
|
||||
+4
-4
@@ -24,17 +24,17 @@ internal sealed class ServerFunctionApprovalClientAgent : DelegatingAIAgent
|
||||
|
||||
protected override Task<AgentResponse> RunCoreAsync(
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
CancellationToken cancellationToken = default)
|
||||
{
|
||||
return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken)
|
||||
return this.RunCoreStreamingAsync(messages, session, options, cancellationToken)
|
||||
.ToAgentResponseAsync(cancellationToken);
|
||||
}
|
||||
|
||||
protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
[EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
@@ -43,7 +43,7 @@ internal sealed class ServerFunctionApprovalClientAgent : DelegatingAIAgent
|
||||
|
||||
// Run the inner agent and intercept any approval requests
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(
|
||||
processedMessages, thread, options, cancellationToken).ConfigureAwait(false))
|
||||
processedMessages, session, options, cancellationToken).ConfigureAwait(false))
|
||||
{
|
||||
yield return ProcessIncomingServerApprovalRequests(update, this._jsonSerializerOptions);
|
||||
}
|
||||
|
||||
+4
-4
@@ -24,17 +24,17 @@ internal sealed class ServerFunctionApprovalAgent : DelegatingAIAgent
|
||||
|
||||
protected override Task<AgentResponse> RunCoreAsync(
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
CancellationToken cancellationToken = default)
|
||||
{
|
||||
return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken)
|
||||
return this.RunCoreStreamingAsync(messages, session, options, cancellationToken)
|
||||
.ToAgentResponseAsync(cancellationToken);
|
||||
}
|
||||
|
||||
protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
[EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
@@ -43,7 +43,7 @@ internal sealed class ServerFunctionApprovalAgent : DelegatingAIAgent
|
||||
|
||||
// Run the inner agent and intercept any approval requests
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(
|
||||
processedMessages, thread, options, cancellationToken).ConfigureAwait(false))
|
||||
processedMessages, session, options, cancellationToken).ConfigureAwait(false))
|
||||
{
|
||||
yield return ProcessOutgoingApprovalRequests(update, this._jsonSerializerOptions);
|
||||
}
|
||||
|
||||
@@ -30,7 +30,7 @@ JsonSerializerOptions jsonOptions = new(JsonSerializerDefaults.Web)
|
||||
};
|
||||
StatefulAgent<AgentState> agent = new(baseAgent, jsonOptions, new AgentState());
|
||||
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
List<ChatMessage> messages =
|
||||
[
|
||||
new(ChatRole.System, "You are a helpful recipe assistant.")
|
||||
@@ -65,21 +65,21 @@ try
|
||||
|
||||
// Stream the response
|
||||
bool isFirstUpdate = true;
|
||||
string? threadId = null;
|
||||
string? sessionId = null;
|
||||
bool stateReceived = false;
|
||||
|
||||
Console.WriteLine();
|
||||
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread))
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, session))
|
||||
{
|
||||
ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();
|
||||
|
||||
// First update indicates run started
|
||||
if (isFirstUpdate)
|
||||
{
|
||||
threadId = chatUpdate.ConversationId;
|
||||
sessionId = chatUpdate.ConversationId;
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine($"[Run Started - Thread: {chatUpdate.ConversationId}, Run: {chatUpdate.ResponseId}]");
|
||||
Console.WriteLine($"[Run Started - Session: {chatUpdate.ConversationId}, Run: {chatUpdate.ResponseId}]");
|
||||
Console.ResetColor();
|
||||
isFirstUpdate = false;
|
||||
}
|
||||
@@ -113,7 +113,7 @@ try
|
||||
}
|
||||
|
||||
Console.ForegroundColor = ConsoleColor.Green;
|
||||
Console.WriteLine($"\n[Run Finished - Thread: {threadId}]");
|
||||
Console.WriteLine($"\n[Run Finished - Session: {sessionId}]");
|
||||
Console.ResetColor();
|
||||
|
||||
// Display final state if received
|
||||
|
||||
@@ -37,18 +37,18 @@ internal sealed class StatefulAgent<TState> : DelegatingAIAgent
|
||||
/// <inheritdoc />
|
||||
protected override Task<AgentResponse> RunCoreAsync(
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
CancellationToken cancellationToken = default)
|
||||
{
|
||||
return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken)
|
||||
return this.RunCoreStreamingAsync(messages, session, options, cancellationToken)
|
||||
.ToAgentResponseAsync(cancellationToken);
|
||||
}
|
||||
|
||||
/// <inheritdoc />
|
||||
protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
[EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
@@ -64,7 +64,7 @@ internal sealed class StatefulAgent<TState> : DelegatingAIAgent
|
||||
messagesWithState.Add(stateMessage);
|
||||
|
||||
// Stream the response and update state when received
|
||||
await foreach (AgentResponseUpdate update in this.InnerAgent.RunStreamingAsync(messagesWithState, thread, options, cancellationToken))
|
||||
await foreach (AgentResponseUpdate update in this.InnerAgent.RunStreamingAsync(messagesWithState, session, options, cancellationToken))
|
||||
{
|
||||
// Check if this update contains a state snapshot
|
||||
foreach (AIContent content in update.Contents)
|
||||
|
||||
+7
-7
@@ -19,17 +19,17 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
|
||||
|
||||
protected override Task<AgentResponse> RunCoreAsync(
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
CancellationToken cancellationToken = default)
|
||||
{
|
||||
return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken)
|
||||
return this.RunCoreStreamingAsync(messages, session, options, cancellationToken)
|
||||
.ToAgentResponseAsync(cancellationToken);
|
||||
}
|
||||
|
||||
protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
[EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
@@ -40,7 +40,7 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
|
||||
state.ValueKind != JsonValueKind.Object)
|
||||
{
|
||||
// No state management requested, pass through to inner agent
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, thread, options, cancellationToken).ConfigureAwait(false))
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, session, options, cancellationToken).ConfigureAwait(false))
|
||||
{
|
||||
yield return update;
|
||||
}
|
||||
@@ -58,7 +58,7 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
|
||||
if (!hasProperties)
|
||||
{
|
||||
// Empty state - treat as no state
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, thread, options, cancellationToken).ConfigureAwait(false))
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, session, options, cancellationToken).ConfigureAwait(false))
|
||||
{
|
||||
yield return update;
|
||||
}
|
||||
@@ -92,7 +92,7 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
|
||||
|
||||
// Collect all updates from first run
|
||||
var allUpdates = new List<AgentResponseUpdate>();
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(firstRunMessages, thread, firstRunOptions, cancellationToken).ConfigureAwait(false))
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(firstRunMessages, session, firstRunOptions, cancellationToken).ConfigureAwait(false))
|
||||
{
|
||||
allUpdates.Add(update);
|
||||
|
||||
@@ -129,7 +129,7 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
|
||||
ChatRole.System,
|
||||
[new TextContent("Please provide a concise summary of the state changes in at most two sentences.")]));
|
||||
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(secondRunMessages, thread, options, cancellationToken).ConfigureAwait(false))
|
||||
await foreach (var update in this.InnerAgent.RunStreamingAsync(secondRunMessages, session, options, cancellationToken).ConfigureAwait(false))
|
||||
{
|
||||
yield return update;
|
||||
}
|
||||
|
||||
@@ -128,7 +128,7 @@ var agent = new ChatClientAgent(instrumentedChatClient,
|
||||
.UseOpenTelemetry(SourceName, configure: (cfg) => cfg.EnableSensitiveData = true) // enable telemetry at the agent level
|
||||
.Build();
|
||||
|
||||
var thread = await agent.GetNewThreadAsync();
|
||||
var session = await agent.GetNewSessionAsync();
|
||||
|
||||
appLogger.LogInformation("Agent created successfully with ID: {AgentId}", agent.Id);
|
||||
|
||||
@@ -176,7 +176,7 @@ using (appLogger.BeginScope(new Dictionary<string, object> { ["SessionId"] = ses
|
||||
Console.Write("Agent: ");
|
||||
|
||||
// Run the agent (this will create its own internal telemetry spans)
|
||||
await foreach (var update in agent.RunStreamingAsync(userInput, thread))
|
||||
await foreach (var update in agent.RunStreamingAsync(userInput, session))
|
||||
{
|
||||
Console.Write(update.Text);
|
||||
}
|
||||
|
||||
+2
-2
@@ -31,8 +31,8 @@ AIAgent agent2 = await persistentAgentsClient.CreateAIAgentAsync(
|
||||
instructions: JokerInstructions);
|
||||
|
||||
// You can then invoke the agent like any other AIAgent.
|
||||
AgentThread thread = await agent1.GetNewThreadAsync();
|
||||
Console.WriteLine(await agent1.RunAsync("Tell me a joke about a pirate.", thread));
|
||||
AgentSession session = await agent1.GetNewSessionAsync();
|
||||
Console.WriteLine(await agent1.RunAsync("Tell me a joke about a pirate.", session));
|
||||
|
||||
// Cleanup for sample purposes.
|
||||
await persistentAgentsClient.Administration.DeleteAgentAsync(agent1.Id);
|
||||
|
||||
@@ -26,25 +26,25 @@ var createdAgentVersion = aiProjectClient.Agents.CreateAgentVersion(agentName: J
|
||||
// agentVersion.Version = <versionNumber>,
|
||||
// agentVersion.Name = <agentName>
|
||||
|
||||
// You can retrieve an AIAgent for an already created server side agent version.
|
||||
// You can use an AIAgent with an already created server side agent version.
|
||||
AIAgent existingJokerAgent = aiProjectClient.AsAIAgent(createdAgentVersion);
|
||||
|
||||
// You can also create another AIAgent version by providing the same name with a different definition.
|
||||
AIAgent newJokerAgent = aiProjectClient.CreateAIAgent(name: JokerName, model: deploymentName, instructions: "You are extremely hilarious at telling jokes.");
|
||||
AIAgent newJokerAgent = await aiProjectClient.CreateAIAgentAsync(name: JokerName, model: deploymentName, instructions: "You are extremely hilarious at telling jokes.");
|
||||
|
||||
// You can also get the AIAgent latest version just providing its name.
|
||||
AIAgent jokerAgentLatest = aiProjectClient.GetAIAgent(name: JokerName);
|
||||
AIAgent jokerAgentLatest = await aiProjectClient.GetAIAgentAsync(name: JokerName);
|
||||
var latestAgentVersion = jokerAgentLatest.GetService<AgentVersion>()!;
|
||||
|
||||
// The AIAgent version can be accessed via the GetService method.
|
||||
Console.WriteLine($"Latest agent version id: {latestAgentVersion.Id}");
|
||||
|
||||
// Once you have the AIAgent, you can invoke it like any other AIAgent.
|
||||
AgentThread thread = await jokerAgentLatest.GetNewThreadAsync();
|
||||
Console.WriteLine(await jokerAgentLatest.RunAsync("Tell me a joke about a pirate.", thread));
|
||||
AgentSession session = await jokerAgentLatest.GetNewSessionAsync();
|
||||
Console.WriteLine(await jokerAgentLatest.RunAsync("Tell me a joke about a pirate.", session));
|
||||
|
||||
// This will use the same thread to continue the conversation.
|
||||
Console.WriteLine(await jokerAgentLatest.RunAsync("Now tell me a joke about a cat and a dog using last joke as the anchor.", thread));
|
||||
// This will use the same session to continue the conversation.
|
||||
Console.WriteLine(await jokerAgentLatest.RunAsync("Now tell me a joke about a cat and a dog using last joke as the anchor.", session));
|
||||
|
||||
// Cleanup by agent name removes both agent versions created.
|
||||
aiProjectClient.Agents.DeleteAgent(existingJokerAgent.Name);
|
||||
|
||||
+29
-29
@@ -28,35 +28,35 @@ namespace SampleApp
|
||||
{
|
||||
public override string? Name => "UpperCaseParrotAgent";
|
||||
|
||||
public override ValueTask<AgentThread> GetNewThreadAsync(CancellationToken cancellationToken = default)
|
||||
=> new(new CustomAgentThread());
|
||||
public override ValueTask<AgentSession> GetNewSessionAsync(CancellationToken cancellationToken = default)
|
||||
=> new(new CustomAgentSession());
|
||||
|
||||
public override ValueTask<AgentThread> DeserializeThreadAsync(JsonElement serializedThread, JsonSerializerOptions? jsonSerializerOptions = null, CancellationToken cancellationToken = default)
|
||||
=> new(new CustomAgentThread(serializedThread, jsonSerializerOptions));
|
||||
public override ValueTask<AgentSession> DeserializeSessionAsync(JsonElement serializedSession, JsonSerializerOptions? jsonSerializerOptions = null, CancellationToken cancellationToken = default)
|
||||
=> new(new CustomAgentSession(serializedSession, jsonSerializerOptions));
|
||||
|
||||
protected override async Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
|
||||
protected override async Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentSession? session = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
|
||||
{
|
||||
// Create a thread if the user didn't supply one.
|
||||
thread ??= await this.GetNewThreadAsync(cancellationToken);
|
||||
// Create a session if the user didn't supply one.
|
||||
session ??= await this.GetNewSessionAsync(cancellationToken);
|
||||
|
||||
if (thread is not CustomAgentThread typedThread)
|
||||
if (session is not CustomAgentSession typedSession)
|
||||
{
|
||||
throw new ArgumentException($"The provided thread is not of type {nameof(CustomAgentThread)}.", nameof(thread));
|
||||
throw new ArgumentException($"The provided session is not of type {nameof(CustomAgentSession)}.", nameof(session));
|
||||
}
|
||||
|
||||
// Get existing messages from the store
|
||||
var invokingContext = new ChatMessageStore.InvokingContext(messages);
|
||||
var storeMessages = await typedThread.MessageStore.InvokingAsync(invokingContext, cancellationToken);
|
||||
var invokingContext = new ChatHistoryProvider.InvokingContext(messages);
|
||||
var storeMessages = await typedSession.ChatHistoryProvider.InvokingAsync(invokingContext, cancellationToken);
|
||||
|
||||
// Clone the input messages and turn them into response messages with upper case text.
|
||||
List<ChatMessage> responseMessages = CloneAndToUpperCase(messages, this.Name).ToList();
|
||||
|
||||
// Notify the thread of the input and output messages.
|
||||
var invokedContext = new ChatMessageStore.InvokedContext(messages, storeMessages)
|
||||
// Notify the session of the input and output messages.
|
||||
var invokedContext = new ChatHistoryProvider.InvokedContext(messages, storeMessages)
|
||||
{
|
||||
ResponseMessages = responseMessages
|
||||
};
|
||||
await typedThread.MessageStore.InvokedAsync(invokedContext, cancellationToken);
|
||||
await typedSession.ChatHistoryProvider.InvokedAsync(invokedContext, cancellationToken);
|
||||
|
||||
return new AgentResponse
|
||||
{
|
||||
@@ -66,29 +66,29 @@ namespace SampleApp
|
||||
};
|
||||
}
|
||||
|
||||
protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(IEnumerable<ChatMessage> messages, AgentSession? session = null, AgentRunOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
// Create a thread if the user didn't supply one.
|
||||
thread ??= await this.GetNewThreadAsync(cancellationToken);
|
||||
// Create a session if the user didn't supply one.
|
||||
session ??= await this.GetNewSessionAsync(cancellationToken);
|
||||
|
||||
if (thread is not CustomAgentThread typedThread)
|
||||
if (session is not CustomAgentSession typedSession)
|
||||
{
|
||||
throw new ArgumentException($"The provided thread is not of type {nameof(CustomAgentThread)}.", nameof(thread));
|
||||
throw new ArgumentException($"The provided session is not of type {nameof(CustomAgentSession)}.", nameof(session));
|
||||
}
|
||||
|
||||
// Get existing messages from the store
|
||||
var invokingContext = new ChatMessageStore.InvokingContext(messages);
|
||||
var storeMessages = await typedThread.MessageStore.InvokingAsync(invokingContext, cancellationToken);
|
||||
var invokingContext = new ChatHistoryProvider.InvokingContext(messages);
|
||||
var storeMessages = await typedSession.ChatHistoryProvider.InvokingAsync(invokingContext, cancellationToken);
|
||||
|
||||
// Clone the input messages and turn them into response messages with upper case text.
|
||||
List<ChatMessage> responseMessages = CloneAndToUpperCase(messages, this.Name).ToList();
|
||||
|
||||
// Notify the thread of the input and output messages.
|
||||
var invokedContext = new ChatMessageStore.InvokedContext(messages, storeMessages)
|
||||
// Notify the session of the input and output messages.
|
||||
var invokedContext = new ChatHistoryProvider.InvokedContext(messages, storeMessages)
|
||||
{
|
||||
ResponseMessages = responseMessages
|
||||
};
|
||||
await typedThread.MessageStore.InvokedAsync(invokedContext, cancellationToken);
|
||||
await typedSession.ChatHistoryProvider.InvokedAsync(invokedContext, cancellationToken);
|
||||
|
||||
foreach (var message in responseMessages)
|
||||
{
|
||||
@@ -128,14 +128,14 @@ namespace SampleApp
|
||||
});
|
||||
|
||||
/// <summary>
|
||||
/// A thread type for our custom agent that only supports in memory storage of messages.
|
||||
/// A session type for our custom agent that only supports in memory storage of messages.
|
||||
/// </summary>
|
||||
internal sealed class CustomAgentThread : InMemoryAgentThread
|
||||
internal sealed class CustomAgentSession : InMemoryAgentSession
|
||||
{
|
||||
internal CustomAgentThread() { }
|
||||
internal CustomAgentSession() { }
|
||||
|
||||
internal CustomAgentThread(JsonElement serializedThreadState, JsonSerializerOptions? jsonSerializerOptions = null)
|
||||
: base(serializedThreadState, jsonSerializerOptions) { }
|
||||
internal CustomAgentSession(JsonElement serializedSessionState, JsonSerializerOptions? jsonSerializerOptions = null)
|
||||
: base(serializedSessionState, jsonSerializerOptions) { }
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
+19
@@ -0,0 +1,19 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="GitHub.Copilot.SDK" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.GithubCopilot\Microsoft.Agents.AI.GithubCopilot.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
@@ -0,0 +1,51 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample shows how to create a GitHub Copilot agent with shell command permissions.
|
||||
|
||||
using GitHub.Copilot.SDK;
|
||||
using Microsoft.Agents.AI;
|
||||
|
||||
// Permission handler that prompts the user for approval
|
||||
static Task<PermissionRequestResult> PromptPermission(PermissionRequest request, PermissionInvocation invocation)
|
||||
{
|
||||
Console.WriteLine($"\n[Permission Request: {request.Kind}]");
|
||||
Console.Write("Approve? (y/n): ");
|
||||
|
||||
string? input = Console.ReadLine()?.Trim().ToUpperInvariant();
|
||||
string kind = input is "Y" or "YES" ? "approved" : "denied-interactively-by-user";
|
||||
|
||||
return Task.FromResult(new PermissionRequestResult { Kind = kind });
|
||||
}
|
||||
|
||||
// Create and start a Copilot client
|
||||
await using CopilotClient copilotClient = new();
|
||||
await copilotClient.StartAsync();
|
||||
|
||||
// Create an agent with a session config that enables permission handling
|
||||
SessionConfig sessionConfig = new()
|
||||
{
|
||||
OnPermissionRequest = PromptPermission,
|
||||
};
|
||||
|
||||
AIAgent agent = copilotClient.AsAIAgent(sessionConfig, ownsClient: true);
|
||||
|
||||
// Toggle between streaming and non-streaming modes
|
||||
bool useStreaming = true;
|
||||
|
||||
string prompt = "List all files in the current directory";
|
||||
Console.WriteLine($"User: {prompt}\n");
|
||||
|
||||
if (useStreaming)
|
||||
{
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(prompt))
|
||||
{
|
||||
Console.Write(update);
|
||||
}
|
||||
|
||||
Console.WriteLine();
|
||||
}
|
||||
else
|
||||
{
|
||||
AgentResponse response = await agent.RunAsync(prompt);
|
||||
Console.WriteLine(response);
|
||||
}
|
||||
@@ -0,0 +1,76 @@
|
||||
# Prerequisites
|
||||
|
||||
> **⚠️ WARNING: Container Recommendation**
|
||||
>
|
||||
> GitHub Copilot can execute tools and commands that may interact with your system. For safety, it is strongly recommended to run this sample in a containerized environment (e.g., Docker, Dev Container) to avoid unintended consequences to your machine.
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 10 SDK or later
|
||||
- GitHub Copilot CLI installed and available in your PATH (or provide a custom path)
|
||||
|
||||
## Setting up GitHub Copilot CLI
|
||||
|
||||
To use this sample, you need to have the GitHub Copilot CLI installed. You can install it by following the instructions at:
|
||||
https://github.com/github/copilot-sdk
|
||||
|
||||
Once installed, ensure the `copilot` command is available in your PATH, or configure a custom path using `CopilotClientOptions`.
|
||||
|
||||
## Running the Sample
|
||||
|
||||
No additional environment variables are required if using default configuration. The sample will:
|
||||
|
||||
1. Create a GitHub Copilot client with default options
|
||||
2. Create an AI agent using the Copilot SDK
|
||||
3. Send a message to the agent
|
||||
4. Display the response
|
||||
|
||||
Run the sample:
|
||||
|
||||
```powershell
|
||||
dotnet run
|
||||
```
|
||||
|
||||
## Advanced Usage
|
||||
|
||||
You can customize the agent by providing additional configuration:
|
||||
|
||||
```csharp
|
||||
using GitHub.Copilot.SDK;
|
||||
using Microsoft.Agents.AI;
|
||||
|
||||
// Create and start a Copilot client
|
||||
await using CopilotClient copilotClient = new();
|
||||
await copilotClient.StartAsync();
|
||||
|
||||
// Create session configuration with specific model
|
||||
SessionConfig sessionConfig = new()
|
||||
{
|
||||
Model = "claude-opus-4.5",
|
||||
Streaming = false
|
||||
};
|
||||
|
||||
// Create an agent with custom configuration using the extension method
|
||||
AIAgent agent = copilotClient.AsAIAgent(
|
||||
sessionConfig,
|
||||
ownsClient: true,
|
||||
id: "my-copilot-agent",
|
||||
name: "My Copilot Assistant",
|
||||
description: "A helpful AI assistant powered by GitHub Copilot"
|
||||
);
|
||||
|
||||
// Use the agent - ask it to write code for us
|
||||
AgentResponse response = await agent.RunAsync("Write a small .NET 10 C# hello world single file application");
|
||||
Console.WriteLine(response);
|
||||
```
|
||||
|
||||
## Streaming Responses
|
||||
|
||||
To get streaming responses:
|
||||
|
||||
```csharp
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync("Write a C# function to calculate Fibonacci numbers"))
|
||||
{
|
||||
Console.Write(update.Text);
|
||||
}
|
||||
```
|
||||
@@ -33,8 +33,8 @@ AIAgent agent2 = await assistantClient.CreateAIAgentAsync(
|
||||
instructions: JokerInstructions);
|
||||
|
||||
// You can invoke the agent like any other AIAgent.
|
||||
AgentThread thread = await agent1.GetNewThreadAsync();
|
||||
Console.WriteLine(await agent1.RunAsync("Tell me a joke about a pirate.", thread));
|
||||
AgentSession session = await agent1.GetNewSessionAsync();
|
||||
Console.WriteLine(await agent1.RunAsync("Tell me a joke about a pirate.", session));
|
||||
|
||||
// Cleanup for sample purposes.
|
||||
await assistantClient.DeleteAssistantAsync(agent1.Id);
|
||||
|
||||
@@ -22,6 +22,7 @@ See the README.md for each sample for the prerequisites for that sample.
|
||||
|[Creating an AIAgent with Azure OpenAI ChatCompletion](./Agent_With_AzureOpenAIChatCompletion/)|This sample demonstrates how to create an AIAgent using Azure OpenAI ChatCompletion as the underlying inference service|
|
||||
|[Creating an AIAgent with Azure OpenAI Responses](./Agent_With_AzureOpenAIResponses/)|This sample demonstrates how to create an AIAgent using Azure OpenAI Responses as the underlying inference service|
|
||||
|[Creating an AIAgent with a custom implementation](./Agent_With_CustomImplementation/)|This sample demonstrates how to create an AIAgent with a custom implementation|
|
||||
|[Creating an AIAgent with GitHub Copilot](./Agent_With_GithubCopilot/)|This sample demonstrates how to create an AIAgent using GitHub Copilot SDK as the underlying inference service|
|
||||
|[Creating an AIAgent with Ollama](./Agent_With_Ollama/)|This sample demonstrates how to create an AIAgent using Ollama as the underlying inference service|
|
||||
|[Creating an AIAgent with ONNX](./Agent_With_ONNX/)|This sample demonstrates how to create an AIAgent using ONNX as the underlying inference service|
|
||||
|[Creating an AIAgent with OpenAI Assistants](./Agent_With_OpenAIAssistants/)|This sample demonstrates how to create an AIAgent using OpenAI Assistants as the underlying inference service.</br>WARNING: The Assistants API is deprecated and will be shut down. For more information see the OpenAI documentation: https://platform.openai.com/docs/assistants/migration|
|
||||
|
||||
+4
-4
@@ -26,12 +26,12 @@ AIAgent agent = new AnthropicClient { APIKey = apiKey }
|
||||
.AsAIAgent(model: model, instructions: AssistantInstructions, name: AssistantName, tools: [tool]);
|
||||
|
||||
// Non-streaming agent interaction with function tools.
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
Console.WriteLine(await agent.RunAsync("What is the weather like in Amsterdam?", thread));
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
Console.WriteLine(await agent.RunAsync("What is the weather like in Amsterdam?", session));
|
||||
|
||||
// Streaming agent interaction with function tools.
|
||||
thread = await agent.GetNewThreadAsync();
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync("What is the weather like in Amsterdam?", thread))
|
||||
session = await agent.GetNewSessionAsync();
|
||||
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync("What is the weather like in Amsterdam?", session))
|
||||
{
|
||||
Console.WriteLine(update);
|
||||
}
|
||||
|
||||
+11
-11
@@ -39,22 +39,22 @@ AIAgent agent = new AzureOpenAIClient(
|
||||
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() },
|
||||
// In this case, we are using a fixed user ID and a unique session ID for each new session.
|
||||
storageScope: new() { UserId = "UID1", SessionId = Guid.NewGuid().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.
|
||||
// In this case, we are searching for any messages for the user across all sessions.
|
||||
searchScope: new() { UserId = "UID1" }))
|
||||
});
|
||||
|
||||
// Start a new thread for the agent conversation.
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
// Start a new session for the agent conversation.
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
|
||||
// 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));
|
||||
// Run the agent with the session 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.", session));
|
||||
|
||||
// Start a second thread. Since we configured the search scope to be across all threads for the user,
|
||||
// Start a second session. Since we configured the search scope to be across all sessions for the user,
|
||||
// the agent should remember that the user likes pirate jokes.
|
||||
AgentThread thread2 = await agent.GetNewThreadAsync();
|
||||
AgentSession? session2 = await agent.GetNewSessionAsync();
|
||||
|
||||
// Run the agent with the second thread.
|
||||
Console.WriteLine(await agent.RunAsync("Tell me a joke that I might like.", thread2));
|
||||
// Run the agent with the second session.
|
||||
Console.WriteLine(await agent.RunAsync("Tell me a joke that I might like.", session2));
|
||||
|
||||
+14
-14
@@ -2,7 +2,7 @@
|
||||
|
||||
// This sample shows how to use the Mem0Provider to persist and recall memories for an agent.
|
||||
// The sample stores conversation messages in a Mem0 service and retrieves relevant memories
|
||||
// for subsequent invocations, even across new threads.
|
||||
// for subsequent invocations, even across new sessions.
|
||||
|
||||
using System.Net.Http.Headers;
|
||||
using System.Text.Json;
|
||||
@@ -32,7 +32,7 @@ AIAgent agent = new AzureOpenAIClient(
|
||||
{
|
||||
ChatOptions = new() { Instructions = "You are a friendly travel assistant. Use known memories about the user when responding, and do not invent details." },
|
||||
AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(ctx.SerializedState.ValueKind is not JsonValueKind.Null and not JsonValueKind.Undefined
|
||||
// If each thread should have its own Mem0 scope, you can create a new id per thread here:
|
||||
// If each session should have its own Mem0 scope, you can create a new id per session here:
|
||||
// ? new Mem0Provider(mem0HttpClient, new Mem0ProviderScope() { ThreadId = Guid.NewGuid().ToString() })
|
||||
// In this case we are storing memories scoped by application and user instead so that memories are retained across threads.
|
||||
? new Mem0Provider(mem0HttpClient, new Mem0ProviderScope() { ApplicationId = "getting-started-agents", UserId = "sample-user" })
|
||||
@@ -40,25 +40,25 @@ AIAgent agent = new AzureOpenAIClient(
|
||||
: new Mem0Provider(mem0HttpClient, ctx.SerializedState, ctx.JsonSerializerOptions))
|
||||
});
|
||||
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
|
||||
// Clear any existing memories for this scope to demonstrate fresh behavior.
|
||||
Mem0Provider mem0Provider = thread.GetService<Mem0Provider>()!;
|
||||
Mem0Provider mem0Provider = session.GetService<Mem0Provider>()!;
|
||||
await mem0Provider.ClearStoredMemoriesAsync();
|
||||
|
||||
Console.WriteLine(await agent.RunAsync("Hi there! My name is Taylor and I'm planning a hiking trip to Patagonia in November.", thread));
|
||||
Console.WriteLine(await agent.RunAsync("I'm travelling with my sister and we love finding scenic viewpoints.", thread));
|
||||
Console.WriteLine(await agent.RunAsync("Hi there! My name is Taylor and I'm planning a hiking trip to Patagonia in November.", session));
|
||||
Console.WriteLine(await agent.RunAsync("I'm travelling with my sister and we love finding scenic viewpoints.", session));
|
||||
|
||||
Console.WriteLine("\nWaiting briefly for Mem0 to index the new memories...\n");
|
||||
await Task.Delay(TimeSpan.FromSeconds(2));
|
||||
|
||||
Console.WriteLine(await agent.RunAsync("What do you already know about my upcoming trip?", thread));
|
||||
Console.WriteLine(await agent.RunAsync("What do you already know about my upcoming trip?", session));
|
||||
|
||||
Console.WriteLine("\n>> Serialize and deserialize the thread to demonstrate persisted state\n");
|
||||
JsonElement serializedThread = thread.Serialize();
|
||||
AgentThread restoredThread = await agent.DeserializeThreadAsync(serializedThread);
|
||||
Console.WriteLine(await agent.RunAsync("Can you recap the personal details you remember?", restoredThread));
|
||||
Console.WriteLine("\n>> Serialize and deserialize the session to demonstrate persisted state\n");
|
||||
JsonElement serializedSession = session.Serialize();
|
||||
AgentSession restoredSession = await agent.DeserializeSessionAsync(serializedSession);
|
||||
Console.WriteLine(await agent.RunAsync("Can you recap the personal details you remember?", restoredSession));
|
||||
|
||||
Console.WriteLine("\n>> Start a new thread that shares the same Mem0 scope\n");
|
||||
AgentThread newThread = await agent.GetNewThreadAsync();
|
||||
Console.WriteLine(await agent.RunAsync("Summarize what you already know about me.", newThread));
|
||||
Console.WriteLine("\n>> Start a new session that shares the same Mem0 scope\n");
|
||||
AgentSession newSession = await agent.GetNewSessionAsync();
|
||||
Console.WriteLine(await agent.RunAsync("Summarize what you already know about me.", newSession));
|
||||
|
||||
+24
-24
@@ -24,10 +24,10 @@ ChatClient chatClient = new AzureOpenAIClient(
|
||||
.GetChatClient(deploymentName);
|
||||
|
||||
// Create the agent and provide a factory to add our custom memory component to
|
||||
// all threads created by the agent. Here each new memory component will have its own
|
||||
// user info object, so each thread will have its own memory.
|
||||
// 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 threads used by the same user, ensure that the
|
||||
// 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()
|
||||
@@ -36,47 +36,47 @@ AIAgent agent = chatClient.AsAIAgent(new ChatClientAgentOptions()
|
||||
AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(new UserInfoMemory(chatClient.AsIChatClient(), ctx.SerializedState, ctx.JsonSerializerOptions))
|
||||
});
|
||||
|
||||
// Create a new thread for the conversation.
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
// Create a new session for the conversation.
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
|
||||
Console.WriteLine(">> Use thread with blank memory\n");
|
||||
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?", thread));
|
||||
Console.WriteLine(await agent.RunAsync("My name is Ruaidhrí", thread));
|
||||
Console.WriteLine(await agent.RunAsync("I am 20 years old", thread));
|
||||
Console.WriteLine(await agent.RunAsync("Hello, what is the square root of 9?", session));
|
||||
Console.WriteLine(await agent.RunAsync("My name is Ruaidhrí", session));
|
||||
Console.WriteLine(await agent.RunAsync("I am 20 years old", session));
|
||||
|
||||
// We can serialize the thread. The serialized state will include the state of the memory component.
|
||||
var threadElement = thread.Serialize();
|
||||
// We can serialize the session. The serialized state will include the state of the memory component.
|
||||
var sesionElement = session.Serialize();
|
||||
|
||||
Console.WriteLine("\n>> Use deserialized thread with previously created memories\n");
|
||||
Console.WriteLine("\n>> Use deserialized session with previously created memories\n");
|
||||
|
||||
// Later we can deserialize the thread and continue the conversation with the previous memory component state.
|
||||
var deserializedThread = await agent.DeserializeThreadAsync(threadElement);
|
||||
Console.WriteLine(await agent.RunAsync("What is my name and age?", deserializedThread));
|
||||
// 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 from memory component\n");
|
||||
|
||||
// It's possible to access the memory component via the thread's GetService method.
|
||||
var userInfo = deserializedThread.GetService<UserInfoMemory>()?.UserInfo;
|
||||
// It's possible to access the memory component via the session's GetService method.
|
||||
var userInfo = deserializedSession.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");
|
||||
Console.WriteLine("\n>> Use new session 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 = await agent.GetNewThreadAsync();
|
||||
if (userInfo is not null && newThread.GetService<UserInfoMemory>() is UserInfoMemory newThreadMemory)
|
||||
// It is also possible to set the memories in 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.GetNewSessionAsync();
|
||||
if (userInfo is not null && newSession.GetService<UserInfoMemory>() is UserInfoMemory newSessionMemory)
|
||||
{
|
||||
newThreadMemory.UserInfo = userInfo;
|
||||
newSessionMemory.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));
|
||||
Console.WriteLine(await agent.RunAsync("What is my name and age?", newSession));
|
||||
|
||||
namespace SampleApp
|
||||
{
|
||||
|
||||
+10
-10
@@ -52,17 +52,17 @@ public class OpenAIChatClientAgent : DelegatingAIAgent
|
||||
/// Run the agent with the provided message and arguments.
|
||||
/// </summary>
|
||||
/// <param name="messages">The messages to pass to the agent.</param>
|
||||
/// <param name="thread">The conversation thread to continue with this invocation. If not provided, creates a new thread. The thread will be mutated with the provided messages and agent response.</param>
|
||||
/// <param name="session">The conversation session to continue with this invocation. If not provided, creates a new session. The session will be mutated with the provided messages and agent response.</param>
|
||||
/// <param name="options">Optional parameters for agent invocation.</param>
|
||||
/// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
|
||||
/// <returns>A <see cref="ChatCompletion"/> containing the list of <see cref="ChatMessage"/> items.</returns>
|
||||
public virtual async Task<ChatCompletion> RunAsync(
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
CancellationToken cancellationToken = default)
|
||||
{
|
||||
var response = await this.RunAsync(messages.AsChatMessages(), thread, options, cancellationToken).ConfigureAwait(false);
|
||||
var response = await this.RunAsync(messages.AsChatMessages(), session, options, cancellationToken).ConfigureAwait(false);
|
||||
|
||||
return response.AsOpenAIChatCompletion();
|
||||
}
|
||||
@@ -71,26 +71,26 @@ public class OpenAIChatClientAgent : DelegatingAIAgent
|
||||
/// Run the agent streaming with the provided message and arguments.
|
||||
/// </summary>
|
||||
/// <param name="messages">The messages to pass to the agent.</param>
|
||||
/// <param name="thread">The conversation thread to continue with this invocation. If not provided, creates a new thread. The thread will be mutated with the provided messages and agent response.</param>
|
||||
/// <param name="session">The conversation session to continue with this invocation. If not provided, creates a new session. The session will be mutated with the provided messages and agent response.</param>
|
||||
/// <param name="options">Optional parameters for agent invocation.</param>
|
||||
/// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
|
||||
/// <returns>A <see cref="ChatCompletion"/> containing the list of <see cref="ChatMessage"/> items.</returns>
|
||||
public virtual IAsyncEnumerable<StreamingChatCompletionUpdate> RunStreamingAsync(
|
||||
IEnumerable<ChatMessage> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
CancellationToken cancellationToken = default)
|
||||
{
|
||||
var response = this.RunStreamingAsync(messages.AsChatMessages(), thread, options, cancellationToken);
|
||||
var response = this.RunStreamingAsync(messages.AsChatMessages(), session, options, cancellationToken);
|
||||
|
||||
return response.AsChatResponseUpdatesAsync().AsOpenAIStreamingChatCompletionUpdatesAsync(cancellationToken);
|
||||
}
|
||||
|
||||
/// <inheritdoc/>
|
||||
protected sealed override Task<AgentResponse> RunCoreAsync(IEnumerable<Microsoft.Extensions.AI.ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
|
||||
base.RunCoreAsync(messages, thread, options, cancellationToken);
|
||||
protected sealed override Task<AgentResponse> RunCoreAsync(IEnumerable<Microsoft.Extensions.AI.ChatMessage> messages, AgentSession? session = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
|
||||
base.RunCoreAsync(messages, session, options, cancellationToken);
|
||||
|
||||
/// <inheritdoc/>
|
||||
protected override IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(IEnumerable<Microsoft.Extensions.AI.ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
|
||||
base.RunCoreStreamingAsync(messages, thread, options, cancellationToken);
|
||||
protected override IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(IEnumerable<Microsoft.Extensions.AI.ChatMessage> messages, AgentSession? session = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
|
||||
base.RunCoreStreamingAsync(messages, session, options, cancellationToken);
|
||||
}
|
||||
|
||||
+10
-10
@@ -52,17 +52,17 @@ public class OpenAIResponseClientAgent : DelegatingAIAgent
|
||||
/// Run the agent with the provided message and arguments.
|
||||
/// </summary>
|
||||
/// <param name="messages">The messages to pass to the agent.</param>
|
||||
/// <param name="thread">The conversation thread to continue with this invocation. If not provided, creates a new thread. The thread will be mutated with the provided messages and agent response.</param>
|
||||
/// <param name="session">The conversation session to continue with this invocation. If not provided, creates a new session. The session will be mutated with the provided messages and agent response.</param>
|
||||
/// <param name="options">Optional parameters for agent invocation.</param>
|
||||
/// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
|
||||
/// <returns>A <see cref="ResponseResult"/> containing the list of <see cref="ChatMessage"/> items.</returns>
|
||||
public virtual async Task<ResponseResult> RunAsync(
|
||||
IEnumerable<ResponseItem> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
CancellationToken cancellationToken = default)
|
||||
{
|
||||
var response = await this.RunAsync(messages.AsChatMessages(), thread, options, cancellationToken).ConfigureAwait(false);
|
||||
var response = await this.RunAsync(messages.AsChatMessages(), session, options, cancellationToken).ConfigureAwait(false);
|
||||
|
||||
return response.AsOpenAIResponse();
|
||||
}
|
||||
@@ -71,17 +71,17 @@ public class OpenAIResponseClientAgent : DelegatingAIAgent
|
||||
/// Run the agent streaming with the provided message and arguments.
|
||||
/// </summary>
|
||||
/// <param name="messages">The messages to pass to the agent.</param>
|
||||
/// <param name="thread">The conversation thread to continue with this invocation. If not provided, creates a new thread. The thread will be mutated with the provided messages and agent response.</param>
|
||||
/// <param name="session">The conversation session to continue with this invocation. If not provided, creates a new session. The session will be mutated with the provided messages and agent response.</param>
|
||||
/// <param name="options">Optional parameters for agent invocation.</param>
|
||||
/// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
|
||||
/// <returns>A <see cref="ResponseResult"/> containing the list of <see cref="ChatMessage"/> items.</returns>
|
||||
public virtual async IAsyncEnumerable<StreamingResponseUpdate> RunStreamingAsync(
|
||||
IEnumerable<ResponseItem> messages,
|
||||
AgentThread? thread = null,
|
||||
AgentSession? session = null,
|
||||
AgentRunOptions? options = null,
|
||||
[EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
var response = this.RunStreamingAsync(messages.AsChatMessages(), thread, options, cancellationToken);
|
||||
var response = this.RunStreamingAsync(messages.AsChatMessages(), session, options, cancellationToken);
|
||||
|
||||
await foreach (var update in response.ConfigureAwait(false))
|
||||
{
|
||||
@@ -105,10 +105,10 @@ public class OpenAIResponseClientAgent : DelegatingAIAgent
|
||||
}
|
||||
|
||||
/// <inheritdoc/>
|
||||
protected sealed override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
|
||||
base.RunCoreAsync(messages, thread, options, cancellationToken);
|
||||
protected sealed override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentSession? session = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
|
||||
base.RunCoreAsync(messages, session, options, cancellationToken);
|
||||
|
||||
/// <inheritdoc/>
|
||||
protected sealed override IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
|
||||
base.RunCoreStreamingAsync(messages, thread, options, cancellationToken);
|
||||
protected sealed override IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(IEnumerable<ChatMessage> messages, AgentSession? session = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
|
||||
base.RunCoreStreamingAsync(messages, session, options, cancellationToken);
|
||||
}
|
||||
|
||||
+7
-7
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample demonstrates how to maintain conversation state using the OpenAIResponseClientAgent
|
||||
// and AgentThread. By passing the same thread to multiple agent invocations, the agent
|
||||
// and AgentSession. By passing the same session to multiple agent invocations, the agent
|
||||
// automatically maintains the conversation history, allowing the AI model to understand
|
||||
// context from previous exchanges.
|
||||
|
||||
@@ -29,8 +29,8 @@ ClientResult createConversationResult = await conversationClient.CreateConversat
|
||||
using JsonDocument createConversationResultAsJson = JsonDocument.Parse(createConversationResult.GetRawResponse().Content.ToString());
|
||||
string conversationId = createConversationResultAsJson.RootElement.GetProperty("id"u8)!.GetString()!;
|
||||
|
||||
// Create a thread for the conversation - this enables conversation state management for subsequent turns
|
||||
AgentThread thread = await agent.GetNewThreadAsync(conversationId);
|
||||
// Create a session for the conversation - this enables conversation state management for subsequent turns
|
||||
AgentSession session = await agent.GetNewSessionAsync(conversationId);
|
||||
|
||||
Console.WriteLine("=== Multi-turn Conversation Demo ===\n");
|
||||
|
||||
@@ -38,22 +38,22 @@ Console.WriteLine("=== Multi-turn Conversation Demo ===\n");
|
||||
Console.WriteLine("User: What is the capital of France?");
|
||||
UserChatMessage firstMessage = new("What is the capital of France?");
|
||||
|
||||
// After this call, the conversation state associated in the options is stored in 'thread' and used in subsequent calls
|
||||
ChatCompletion firstResponse = await agent.RunAsync([firstMessage], thread);
|
||||
// After this call, the conversation state associated in the options is stored in 'session' and used in subsequent calls
|
||||
ChatCompletion firstResponse = await agent.RunAsync([firstMessage], session);
|
||||
Console.WriteLine($"Assistant: {firstResponse.Content.Last().Text}\n");
|
||||
|
||||
// Second turn: Follow-up question that relies on conversation context
|
||||
Console.WriteLine("User: What famous landmarks are located there?");
|
||||
UserChatMessage secondMessage = new("What famous landmarks are located there?");
|
||||
|
||||
ChatCompletion secondResponse = await agent.RunAsync([secondMessage], thread);
|
||||
ChatCompletion secondResponse = await agent.RunAsync([secondMessage], session);
|
||||
Console.WriteLine($"Assistant: {secondResponse.Content.Last().Text}\n");
|
||||
|
||||
// Third turn: Another follow-up that demonstrates context continuity
|
||||
Console.WriteLine("User: How tall is the most famous one?");
|
||||
UserChatMessage thirdMessage = new("How tall is the most famous one?");
|
||||
|
||||
ChatCompletion thirdResponse = await agent.RunAsync([thirdMessage], thread);
|
||||
ChatCompletion thirdResponse = await agent.RunAsync([thirdMessage], session);
|
||||
Console.WriteLine($"Assistant: {thirdResponse.Content.Last().Text}\n");
|
||||
|
||||
Console.WriteLine("=== End of Conversation ===");
|
||||
|
||||
+12
-12
@@ -4,7 +4,7 @@ This sample demonstrates how to maintain conversation state across multiple turn
|
||||
|
||||
## What This Sample Shows
|
||||
|
||||
- **Conversation State Management**: Shows how to use `ConversationClient` and `AgentThread` to maintain conversation context across multiple agent invocations
|
||||
- **Conversation State Management**: Shows how to use `ConversationClient` and `AgentSession` to maintain conversation context across multiple agent invocations
|
||||
- **Multi-turn Conversations**: Demonstrates follow-up questions that rely on context from previous messages in the conversation
|
||||
- **Server-Side Storage**: Uses OpenAI's Conversation API to manage conversation history server-side, allowing the model to access previous messages without resending them
|
||||
- **Conversation Lifecycle**: Demonstrates creating, retrieving, and deleting conversations
|
||||
@@ -24,22 +24,22 @@ ConversationClient conversationClient = openAIClient.GetConversationClient();
|
||||
ClientResult createConversationResult = await conversationClient.CreateConversationAsync(BinaryContent.Create(BinaryData.FromString("{}")));
|
||||
```
|
||||
|
||||
### AgentThread for Conversation State
|
||||
### AgentSession for Conversation State
|
||||
|
||||
The `AgentThread` works with `ChatClientAgentRunOptions` to link the agent to a server-side conversation:
|
||||
The `AgentSession` works with `ChatClientAgentRunOptions` to link the agent to a server-side conversation:
|
||||
|
||||
```csharp
|
||||
// Set up agent run options with the conversation ID
|
||||
ChatClientAgentRunOptions agentRunOptions = new() { ChatOptions = new ChatOptions() { ConversationId = conversationId } };
|
||||
|
||||
// Create a thread for the conversation
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
// Create a session for the conversation
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
|
||||
// First call links the thread to the conversation
|
||||
ChatCompletion firstResponse = await agent.RunAsync([firstMessage], thread, agentRunOptions);
|
||||
// First call links the session to the conversation
|
||||
ChatCompletion firstResponse = await agent.RunAsync([firstMessage], session, agentRunOptions);
|
||||
|
||||
// Subsequent calls use the thread without needing to pass options again
|
||||
ChatCompletion secondResponse = await agent.RunAsync([secondMessage], thread);
|
||||
// Subsequent calls use the session without needing to pass options again
|
||||
ChatCompletion secondResponse = await agent.RunAsync([secondMessage], session);
|
||||
```
|
||||
|
||||
### Retrieving Conversation History
|
||||
@@ -59,9 +59,9 @@ foreach (ClientResult result in getConversationItemsResults.GetRawPages())
|
||||
1. **Create an OpenAI Client**: Initialize an `OpenAIClient` with your API key
|
||||
2. **Create a Conversation**: Use `ConversationClient` to create a server-side conversation
|
||||
3. **Create an Agent**: Initialize an `OpenAIResponseClientAgent` with the desired model and instructions
|
||||
4. **Create a Thread**: Call `agent.GetNewThreadAsync()` to create a new conversation thread
|
||||
5. **Link Thread to Conversation**: Pass `ChatClientAgentRunOptions` with the `ConversationId` on the first call
|
||||
6. **Send Messages**: Subsequent calls to `agent.RunAsync()` only need the thread - context is maintained
|
||||
4. **Create a Session**: Call `agent.GetNewSessionAsync()` to create a new conversation session
|
||||
5. **Link Session to Conversation**: Pass `ChatClientAgentRunOptions` with the `ConversationId` on the first call
|
||||
6. **Send Messages**: Subsequent calls to `agent.RunAsync()` only need the session - context is maintained
|
||||
7. **Cleanup**: Delete the conversation when done using `conversationClient.DeleteConversation()`
|
||||
|
||||
## Running the Sample
|
||||
|
||||
@@ -14,4 +14,4 @@ Agent Framework provides additional support to allow OpenAI developers to use th
|
||||
|[Using Reasoning Capabilities](./Agent_OpenAI_Step02_Reasoning/)|This sample demonstrates how to create an AI agent with reasoning capabilities using OpenAI's reasoning models and response types.|
|
||||
|[Creating an Agent from a ChatClient](./Agent_OpenAI_Step03_CreateFromChatClient/)|This sample demonstrates how to create an AI agent directly from an OpenAI.Chat.ChatClient instance using OpenAIChatClientAgent.|
|
||||
|[Creating an Agent from an OpenAIResponseClient](./Agent_OpenAI_Step04_CreateFromOpenAIResponseClient/)|This sample demonstrates how to create an AI agent directly from an OpenAI.Responses.OpenAIResponseClient instance using OpenAIResponseClientAgent.|
|
||||
|[Managing Conversation State](./Agent_OpenAI_Step05_Conversation/)|This sample demonstrates how to maintain conversation state across multiple turns using the AgentThread for context continuity.|
|
||||
|[Managing Conversation State](./Agent_OpenAI_Step05_Conversation/)|This sample demonstrates how to maintain conversation state across multiple turns using the AgentSession for context continuity.|
|
||||
+5
-5
@@ -66,20 +66,20 @@ AIAgent agent = azureOpenAIClient
|
||||
// Since we are using ChatCompletion which stores chat history locally, we can also add a message removal policy
|
||||
// that removes messages produced by the TextSearchProvider before they are added to the chat history, so that
|
||||
// we don't bloat chat history with all the search result messages.
|
||||
ChatMessageStoreFactory = (ctx, ct) => new ValueTask<ChatMessageStore>(new InMemoryChatMessageStore(ctx.SerializedState, ctx.JsonSerializerOptions)
|
||||
ChatHistoryProviderFactory = (ctx, ct) => new ValueTask<ChatHistoryProvider>(new InMemoryChatHistoryProvider(ctx.SerializedState, ctx.JsonSerializerOptions)
|
||||
.WithAIContextProviderMessageRemoval()),
|
||||
});
|
||||
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
|
||||
Console.WriteLine(">> Asking about returns\n");
|
||||
Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", thread));
|
||||
Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", session));
|
||||
|
||||
Console.WriteLine("\n>> Asking about shipping\n");
|
||||
Console.WriteLine(await agent.RunAsync("How long does standard shipping usually take?", thread));
|
||||
Console.WriteLine(await agent.RunAsync("How long does standard shipping usually take?", session));
|
||||
|
||||
Console.WriteLine("\n>> Asking about product care\n");
|
||||
Console.WriteLine(await agent.RunAsync("What is the best way to maintain the TrailRunner tent fabric?", thread));
|
||||
Console.WriteLine(await agent.RunAsync("What is the best way to maintain the TrailRunner tent fabric?", session));
|
||||
|
||||
// Produces some sample search documents.
|
||||
// Each one contains a source name and link, which the agent can use to cite sources in its responses.
|
||||
|
||||
+7
-7
@@ -74,22 +74,22 @@ AIAgent agent = azureOpenAIClient
|
||||
AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(new TextSearchProvider(SearchAdapter, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions))
|
||||
});
|
||||
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
|
||||
Console.WriteLine(">> Asking about SK threads\n");
|
||||
Console.WriteLine(await agent.RunAsync("Hi! How do I create a thread in Semantic Kernel?", thread));
|
||||
Console.WriteLine(">> Asking about SK sessions\n");
|
||||
Console.WriteLine(await agent.RunAsync("Hi! How do I create a thread/session in Semantic Kernel?", session));
|
||||
|
||||
// Here we are asking a very vague question when taken out of context,
|
||||
// but since we are including previous messages in our search using RecentMessageMemoryLimit
|
||||
// the RAG search should still produce useful results.
|
||||
Console.WriteLine("\n>> Asking about AF threads\n");
|
||||
Console.WriteLine(await agent.RunAsync("and in Agent Framework?", thread));
|
||||
Console.WriteLine("\n>> Asking about AF sessions\n");
|
||||
Console.WriteLine(await agent.RunAsync("and in Agent Framework?", session));
|
||||
|
||||
Console.WriteLine("\n>> Contrasting Approaches\n");
|
||||
Console.WriteLine(await agent.RunAsync("Please contrast the two approaches", thread));
|
||||
Console.WriteLine(await agent.RunAsync("Please contrast the two approaches", session));
|
||||
|
||||
Console.WriteLine("\n>> Asking about ancestry\n");
|
||||
Console.WriteLine(await agent.RunAsync("What are the predecessors to the Agent Framework?", thread));
|
||||
Console.WriteLine(await agent.RunAsync("What are the predecessors to the Agent Framework?", session));
|
||||
|
||||
static async Task UploadDataFromMarkdown(string markdownUrl, string sourceName, VectorStoreCollection<Guid, DocumentationChunk> vectorStoreCollection, int chunkSize, int overlap)
|
||||
{
|
||||
|
||||
+4
-4
@@ -32,16 +32,16 @@ AIAgent agent = new AzureOpenAIClient(
|
||||
AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(new TextSearchProvider(MockSearchAsync, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions))
|
||||
});
|
||||
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
|
||||
Console.WriteLine(">> Asking about returns\n");
|
||||
Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", thread));
|
||||
Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", session));
|
||||
|
||||
Console.WriteLine("\n>> Asking about shipping\n");
|
||||
Console.WriteLine(await agent.RunAsync("How long does standard shipping usually take?", thread));
|
||||
Console.WriteLine(await agent.RunAsync("How long does standard shipping usually take?", session));
|
||||
|
||||
Console.WriteLine("\n>> Asking about product care\n");
|
||||
Console.WriteLine(await agent.RunAsync("What is the best way to maintain the TrailRunner tent fabric?", thread));
|
||||
Console.WriteLine(await agent.RunAsync("What is the best way to maintain the TrailRunner tent fabric?", session));
|
||||
|
||||
static Task<IEnumerable<TextSearchProvider.TextSearchResult>> MockSearchAsync(string query, CancellationToken cancellationToken)
|
||||
{
|
||||
|
||||
+4
-4
@@ -43,16 +43,16 @@ AIAgent agent = await aiProjectClient
|
||||
instructions: "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available.",
|
||||
tools: [fileSearchTool]);
|
||||
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
|
||||
Console.WriteLine(">> Asking about returns\n");
|
||||
Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", thread));
|
||||
Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", session));
|
||||
|
||||
Console.WriteLine("\n>> Asking about shipping\n");
|
||||
Console.WriteLine(await agent.RunAsync("How long does standard shipping usually take?", thread));
|
||||
Console.WriteLine(await agent.RunAsync("How long does standard shipping usually take?", session));
|
||||
|
||||
Console.WriteLine("\n>> Asking about product care\n");
|
||||
Console.WriteLine(await agent.RunAsync("What is the best way to maintain the TrailRunner tent fabric?", thread));
|
||||
Console.WriteLine(await agent.RunAsync("What is the best way to maintain the TrailRunner tent fabric?", session));
|
||||
|
||||
// Cleanup
|
||||
await fileClient.DeleteFileAsync(uploadResult.Value.Id);
|
||||
|
||||
@@ -16,18 +16,18 @@ AIAgent agent = new AzureOpenAIClient(
|
||||
.GetChatClient(deploymentName)
|
||||
.AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
|
||||
|
||||
// Invoke the agent with a multi-turn conversation, where the context is preserved in the thread object.
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", thread));
|
||||
Console.WriteLine(await agent.RunAsync("Now add some emojis to the joke and tell it in the voice of a pirate's parrot.", thread));
|
||||
// Invoke the agent with a multi-turn conversation, where the context is preserved in the session object.
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", session));
|
||||
Console.WriteLine(await agent.RunAsync("Now add some emojis to the joke and tell it in the voice of a pirate's parrot.", session));
|
||||
|
||||
// Invoke the agent with a multi-turn conversation and streaming, where the context is preserved in the thread object.
|
||||
thread = await agent.GetNewThreadAsync();
|
||||
await foreach (var update in agent.RunStreamingAsync("Tell me a joke about a pirate.", thread))
|
||||
// Invoke the agent with a multi-turn conversation and streaming, where the context is preserved in the session object.
|
||||
session = await agent.GetNewSessionAsync();
|
||||
await foreach (var update in agent.RunStreamingAsync("Tell me a joke about a pirate.", session))
|
||||
{
|
||||
Console.WriteLine(update);
|
||||
}
|
||||
await foreach (var update in agent.RunStreamingAsync("Now add some emojis to the joke and tell it in the voice of a pirate's parrot.", thread))
|
||||
await foreach (var update in agent.RunStreamingAsync("Now add some emojis to the joke and tell it in the voice of a pirate's parrot.", session))
|
||||
{
|
||||
Console.WriteLine(update);
|
||||
}
|
||||
|
||||
+5
-5
@@ -30,12 +30,12 @@ AIAgent agent = new AzureOpenAIClient(
|
||||
.AsAIAgent(instructions: "You are a helpful assistant", tools: [new ApprovalRequiredAIFunction(AIFunctionFactory.Create(GetWeather))]);
|
||||
|
||||
// Call the agent and check if there are any user input requests to handle.
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
var response = await agent.RunAsync("What is the weather like in Amsterdam?", thread);
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
var response = await agent.RunAsync("What is the weather like in Amsterdam?", session);
|
||||
var userInputRequests = response.UserInputRequests.ToList();
|
||||
|
||||
// For streaming use:
|
||||
// var updates = await agent.RunStreamingAsync("What is the weather like in Amsterdam?", thread).ToListAsync();
|
||||
// var updates = await agent.RunStreamingAsync("What is the weather like in Amsterdam?", session).ToListAsync();
|
||||
// userInputRequests = updates.SelectMany(x => x.UserInputRequests).ToList();
|
||||
|
||||
while (userInputRequests.Count > 0)
|
||||
@@ -52,12 +52,12 @@ while (userInputRequests.Count > 0)
|
||||
.ToList();
|
||||
|
||||
// Pass the user input responses back to the agent for further processing.
|
||||
response = await agent.RunAsync(userInputResponses, thread);
|
||||
response = await agent.RunAsync(userInputResponses, session);
|
||||
|
||||
userInputRequests = response.UserInputRequests.ToList();
|
||||
|
||||
// For streaming use:
|
||||
// updates = await agent.RunStreamingAsync(userInputResponses, thread).ToListAsync();
|
||||
// updates = await agent.RunStreamingAsync(userInputResponses, session).ToListAsync();
|
||||
// userInputRequests = updates.SelectMany(x => x.UserInputRequests).ToList();
|
||||
}
|
||||
|
||||
|
||||
+14
-14
@@ -18,24 +18,24 @@ AIAgent agent = new AzureOpenAIClient(
|
||||
.GetChatClient(deploymentName)
|
||||
.AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
|
||||
|
||||
// Start a new thread for the agent conversation.
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
// Start a new session for the agent conversation.
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
|
||||
// Run the agent with a new thread.
|
||||
Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", thread));
|
||||
// Run the agent with a new session.
|
||||
Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", session));
|
||||
|
||||
// Serialize the thread state to a JsonElement, so it can be stored for later use.
|
||||
JsonElement serializedThread = thread.Serialize();
|
||||
// Serialize the session state to a JsonElement, so it can be stored for later use.
|
||||
JsonElement serializedSession = session.Serialize();
|
||||
|
||||
// Save the serialized thread to a temporary file (for demonstration purposes).
|
||||
// Save the serialized session to a temporary file (for demonstration purposes).
|
||||
string tempFilePath = Path.GetTempFileName();
|
||||
await File.WriteAllTextAsync(tempFilePath, JsonSerializer.Serialize(serializedThread));
|
||||
await File.WriteAllTextAsync(tempFilePath, JsonSerializer.Serialize(serializedSession));
|
||||
|
||||
// Load the serialized thread from the temporary file (for demonstration purposes).
|
||||
JsonElement reloadedSerializedThread = JsonElement.Parse(await File.ReadAllTextAsync(tempFilePath));
|
||||
// Load the serialized session from the temporary file (for demonstration purposes).
|
||||
JsonElement reloadedSerializedSession = JsonElement.Parse(await File.ReadAllTextAsync(tempFilePath));
|
||||
|
||||
// Deserialize the thread state after loading from storage.
|
||||
AgentThread resumedThread = await agent.DeserializeThreadAsync(reloadedSerializedThread);
|
||||
// Deserialize the session state after loading from storage.
|
||||
AgentSession resumedSession = await agent.DeserializeSessionAsync(reloadedSerializedSession);
|
||||
|
||||
// Run the agent again with the resumed thread.
|
||||
Console.WriteLine(await agent.RunAsync("Now tell the same joke in the voice of a pirate, and add some emojis to the joke.", resumedThread));
|
||||
// Run the agent again with the resumed session.
|
||||
Console.WriteLine(await agent.RunAsync("Now tell the same joke in the voice of a pirate, and add some emojis to the joke.", resumedSession));
|
||||
|
||||
+36
-36
@@ -31,61 +31,61 @@ AIAgent agent = new AzureOpenAIClient(
|
||||
{
|
||||
ChatOptions = new() { Instructions = "You are good at telling jokes." },
|
||||
Name = "Joker",
|
||||
ChatMessageStoreFactory = (ctx, ct) => new ValueTask<ChatMessageStore>(
|
||||
// Create a new chat message store for this agent that stores the messages in a vector store.
|
||||
// Each thread must get its own copy of the VectorChatMessageStore, since the store
|
||||
// also contains the id that the thread is stored under.
|
||||
new VectorChatMessageStore(vectorStore, ctx.SerializedState, ctx.JsonSerializerOptions))
|
||||
ChatHistoryProviderFactory = (ctx, ct) => new ValueTask<ChatHistoryProvider>(
|
||||
// Create a new ChatHistoryProvider for this agent that stores chat history in a vector store.
|
||||
// Each session must get its own copy of the VectorChatHistoryProvider, since the provider
|
||||
// also contains the id that the chat history is stored under.
|
||||
new VectorChatHistoryProvider(vectorStore, ctx.SerializedState, ctx.JsonSerializerOptions))
|
||||
});
|
||||
|
||||
// Start a new thread for the agent conversation.
|
||||
AgentThread thread = await agent.GetNewThreadAsync();
|
||||
// Start a new session for the agent conversation.
|
||||
AgentSession session = await agent.GetNewSessionAsync();
|
||||
|
||||
// Run the agent with the thread that stores conversation history in the vector store.
|
||||
Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", thread));
|
||||
// Run the agent with the session that stores chat history in the vector store.
|
||||
Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", session));
|
||||
|
||||
// Serialize the thread state, so it can be stored for later use.
|
||||
// Since the chat history is stored in the vector store, the serialized thread
|
||||
// Serialize the session state, so it can be stored for later use.
|
||||
// Since the chat history is stored in the vector store, the serialized session
|
||||
// only contains the guid that the messages are stored under in the vector store.
|
||||
JsonElement serializedThread = thread.Serialize();
|
||||
JsonElement serializedSession = session.Serialize();
|
||||
|
||||
Console.WriteLine("\n--- Serialized thread ---\n");
|
||||
Console.WriteLine(JsonSerializer.Serialize(serializedThread, new JsonSerializerOptions { WriteIndented = true }));
|
||||
Console.WriteLine("\n--- Serialized session ---\n");
|
||||
Console.WriteLine(JsonSerializer.Serialize(serializedSession, new JsonSerializerOptions { WriteIndented = true }));
|
||||
|
||||
// The serialized thread can now be saved to a database, file, or any other storage mechanism
|
||||
// The serialized session can now be saved to a database, file, or any other storage mechanism
|
||||
// and loaded again later.
|
||||
|
||||
// Deserialize the thread state after loading from storage.
|
||||
AgentThread resumedThread = await agent.DeserializeThreadAsync(serializedThread);
|
||||
// Deserialize the session state after loading from storage.
|
||||
AgentSession resumedSession = await agent.DeserializeSessionAsync(serializedSession);
|
||||
|
||||
// Run the agent with the thread that stores conversation history in the vector store a second time.
|
||||
Console.WriteLine(await agent.RunAsync("Now tell the same joke in the voice of a pirate, and add some emojis to the joke.", resumedThread));
|
||||
// Run the agent with the session that stores chat history in the vector store a second time.
|
||||
Console.WriteLine(await agent.RunAsync("Now tell the same joke in the voice of a pirate, and add some emojis to the joke.", resumedSession));
|
||||
|
||||
// We can access the VectorChatMessageStore via the thread's GetService method if we need to read the key under which threads are stored.
|
||||
var messageStore = resumedThread.GetService<VectorChatMessageStore>()!;
|
||||
Console.WriteLine($"\nThread is stored in vector store under key: {messageStore.ThreadDbKey}");
|
||||
// We can access the VectorChatHistoryProvider via the session's GetService method if we need to read the key under which chat history is stored.
|
||||
var chatHistoryProvider = resumedSession.GetService<VectorChatHistoryProvider>()!;
|
||||
Console.WriteLine($"\nSession is stored in vector store under key: {chatHistoryProvider.SessionDbKey}");
|
||||
|
||||
namespace SampleApp
|
||||
{
|
||||
/// <summary>
|
||||
/// A sample implementation of <see cref="ChatMessageStore"/> that stores chat messages in a vector store.
|
||||
/// A sample implementation of <see cref="ChatHistoryProvider"/> that stores chat history in a vector store.
|
||||
/// </summary>
|
||||
internal sealed class VectorChatMessageStore : ChatMessageStore
|
||||
internal sealed class VectorChatHistoryProvider : ChatHistoryProvider
|
||||
{
|
||||
private readonly VectorStore _vectorStore;
|
||||
|
||||
public VectorChatMessageStore(VectorStore vectorStore, JsonElement serializedStoreState, JsonSerializerOptions? jsonSerializerOptions = null)
|
||||
public VectorChatHistoryProvider(VectorStore vectorStore, JsonElement serializedState, JsonSerializerOptions? jsonSerializerOptions = null)
|
||||
{
|
||||
this._vectorStore = vectorStore ?? throw new ArgumentNullException(nameof(vectorStore));
|
||||
|
||||
if (serializedStoreState.ValueKind is JsonValueKind.String)
|
||||
if (serializedState.ValueKind is JsonValueKind.String)
|
||||
{
|
||||
// Here we can deserialize the thread id so that we can access the same messages as before the suspension.
|
||||
this.ThreadDbKey = serializedStoreState.Deserialize<string>();
|
||||
// Here we can deserialize the session id so that we can access the same messages as before the suspension.
|
||||
this.SessionDbKey = serializedState.Deserialize<string>();
|
||||
}
|
||||
}
|
||||
|
||||
public string? ThreadDbKey { get; private set; }
|
||||
public string? SessionDbKey { get; private set; }
|
||||
|
||||
public override async ValueTask<IEnumerable<ChatMessage>> InvokingAsync(InvokingContext context, CancellationToken cancellationToken = default)
|
||||
{
|
||||
@@ -94,7 +94,7 @@ namespace SampleApp
|
||||
|
||||
var records = await collection
|
||||
.GetAsync(
|
||||
x => x.ThreadId == this.ThreadDbKey, 10,
|
||||
x => x.SessionId == this.SessionDbKey, 10,
|
||||
new() { OrderBy = x => x.Descending(y => y.Timestamp) },
|
||||
cancellationToken)
|
||||
.ToListAsync(cancellationToken);
|
||||
@@ -113,7 +113,7 @@ namespace SampleApp
|
||||
return;
|
||||
}
|
||||
|
||||
this.ThreadDbKey ??= Guid.NewGuid().ToString("N");
|
||||
this.SessionDbKey ??= Guid.NewGuid().ToString("N");
|
||||
|
||||
var collection = this._vectorStore.GetCollection<string, ChatHistoryItem>("ChatHistory");
|
||||
await collection.EnsureCollectionExistsAsync(cancellationToken);
|
||||
@@ -124,17 +124,17 @@ namespace SampleApp
|
||||
|
||||
await collection.UpsertAsync(allNewMessages.Select(x => new ChatHistoryItem()
|
||||
{
|
||||
Key = this.ThreadDbKey + x.MessageId,
|
||||
Key = this.SessionDbKey + x.MessageId,
|
||||
Timestamp = DateTimeOffset.UtcNow,
|
||||
ThreadId = this.ThreadDbKey,
|
||||
SessionId = this.SessionDbKey,
|
||||
SerializedMessage = JsonSerializer.Serialize(x),
|
||||
MessageText = x.Text
|
||||
}), cancellationToken);
|
||||
}
|
||||
|
||||
public override JsonElement Serialize(JsonSerializerOptions? jsonSerializerOptions = null) =>
|
||||
// We have to serialize the thread id, so that on deserialization we can retrieve the messages using the same thread id.
|
||||
JsonSerializer.SerializeToElement(this.ThreadDbKey);
|
||||
// We have to serialize the session id, so that on deserialization we can retrieve the messages using the same session id.
|
||||
JsonSerializer.SerializeToElement(this.SessionDbKey);
|
||||
|
||||
/// <summary>
|
||||
/// The data structure used to store chat history items in the vector store.
|
||||
@@ -145,7 +145,7 @@ namespace SampleApp
|
||||
public string? Key { get; set; }
|
||||
|
||||
[VectorStoreData]
|
||||
public string? ThreadId { get; set; }
|
||||
public string? SessionId { get; set; }
|
||||
|
||||
[VectorStoreData]
|
||||
public DateTimeOffset? Timestamp { get; set; }
|
||||
|
||||
@@ -44,12 +44,12 @@ await host.RunAsync().ConfigureAwait(false);
|
||||
/// </summary>
|
||||
internal sealed class SampleService(AIAgent agent, IHostApplicationLifetime appLifetime) : IHostedService
|
||||
{
|
||||
private AgentThread? _thread;
|
||||
private AgentSession? _session;
|
||||
|
||||
public async Task StartAsync(CancellationToken cancellationToken)
|
||||
{
|
||||
// Create a thread that will be used for the entirety of the service lifetime so that the user can ask follow up questions.
|
||||
this._thread = await agent.GetNewThreadAsync(cancellationToken);
|
||||
// Create a session that will be used for the entirety of the service lifetime so that the user can ask follow up questions.
|
||||
this._session = await agent.GetNewSessionAsync(cancellationToken);
|
||||
_ = this.RunAsync(appLifetime.ApplicationStopping);
|
||||
}
|
||||
|
||||
@@ -72,7 +72,7 @@ internal sealed class SampleService(AIAgent agent, IHostApplicationLifetime appL
|
||||
}
|
||||
|
||||
// Stream the output to the console as it is generated.
|
||||
await foreach (var update in agent.RunStreamingAsync(input, this._thread, cancellationToken: cancellationToken))
|
||||
await foreach (var update in agent.RunStreamingAsync(input, this._session, cancellationToken: cancellationToken))
|
||||
{
|
||||
Console.Write(update);
|
||||
}
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user