agent/agent-framework
2
0
Fork 0
mirror of https://github.com/microsoft/agent-framework.git synced 2026-06-16 21:04:09 +08:00
Code Issues Packages Projects Releases Wiki Activity

.NET: [BREAKING] Workflows API Review Naming Changes (Part 1?) (#4090)

Browse Source 
* refactor: Normalize Run/RunStreaming with AIAgent

* refactor: Clarify Session vs. Run -level concepts

* Rename RunId to SessionId to better match Run/Session terminology in AIAgent
* [BREAKING]: Will break existing checkpointed sessions in CosmosDb due to field rename

* refactor: Rename and simplify interface around getting typed data out of ExternalRequest/Response

* Also adds hints around using value types in PortableValue

* refactor: Rename AddFanInEdge to AddFanInBarrierEdge

This will prevent a breaking change later when we introduce a programmable FanIn edge, analogous to the FanOut edge's EdgeSelector.

The goal, in the long run is to support a number of different FanIn scenarios, with naive FanIn (no barrier) by default, similar to FanOut.

* refactor: AsAgent(this Workflow, ...) => AsAIAgent(...)

* misc - part1: SwitchBuilder internal

---------

Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com>
This commit is contained in:
Jacob Alber
2026-02-19 21:05:18 -05:00
committed by GitHub
Unverified
parent 5fd260e11d
commit 0086d38f58
93 changed files with 397 additions and 458 deletions
Download Patch File Download Diff File Expand all files Collapse all files
dotnet/samples/GettingStarted/Workflows/ConditionalEdges/01_EdgeCondition/Program.cs
+2 -5
View File
@@ -37,10 +37,7 @@ public static class Program
// Set up the Azure OpenAI client
var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
var chatClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential()).GetChatClient(deploymentName).AsIChatClient();
var chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential()).GetChatClient(deploymentName).AsIChatClient();
// Create agents
AIAgent spamDetectionAgent = GetSpamDetectionAgent(chatClient);
@@ -64,7 +61,7 @@ public static class Program
string email = Resources.Read("spam.txt");
// Execute the workflow
await using StreamingRun run = await InProcessExecution.StreamAsync(workflow, new ChatMessage(ChatRole.User, email));
await using StreamingRun run = await InProcessExecution.RunStreamingAsync(workflow, new ChatMessage(ChatRole.User, email));
await run.TrySendMessageAsync(new TurnToken(emitEvents: true));
await foreach (WorkflowEvent evt in run.WatchStreamAsync())
{
dotnet/samples/GettingStarted/Workflows/ConditionalEdges/02_SwitchCase/Program.cs
+2 -5
View File
@@ -38,10 +38,7 @@ public static class Program
// Set up the Azure OpenAI client
var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
var chatClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential()).GetChatClient(deploymentName).AsIChatClient();
var chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential()).GetChatClient(deploymentName).AsIChatClient();
// Create agents
AIAgent spamDetectionAgent = GetSpamDetectionAgent(chatClient);
@@ -80,7 +77,7 @@ public static class Program
string email = Resources.Read("ambiguous_email.txt");
// Execute the workflow
await using StreamingRun run = await InProcessExecution.StreamAsync(workflow, new ChatMessage(ChatRole.User, email));
await using StreamingRun run = await InProcessExecution.RunStreamingAsync(workflow, new ChatMessage(ChatRole.User, email));
await run.TrySendMessageAsync(new TurnToken(emitEvents: true));
await foreach (WorkflowEvent evt in run.WatchStreamAsync())
{
dotnet/samples/GettingStarted/Workflows/ConditionalEdges/03_MultiSelection/Program.cs
+2 -5
View File
@@ -40,10 +40,7 @@ public static class Program
// Set up the Azure OpenAI client
var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
var chatClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential()).GetChatClient(deploymentName).AsIChatClient();
var chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential()).GetChatClient(deploymentName).AsIChatClient();
// Create agents
AIAgent emailAnalysisAgent = GetEmailAnalysisAgent(chatClient);
@@ -88,7 +85,7 @@ public static class Program
string email = Resources.Read("email.txt");
// Execute the workflow
await using StreamingRun run = await InProcessExecution.StreamAsync(workflow, new ChatMessage(ChatRole.User, email));
await using StreamingRun run = await InProcessExecution.RunStreamingAsync(workflow, new ChatMessage(ChatRole.User, email));
await run.TrySendMessageAsync(new TurnToken(emitEvents: true));
await foreach (WorkflowEvent evt in run.WatchStreamAsync())
{