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* feat(workflows): Make telemetry opt-in via WithOpenTelemetry() - Add WorkflowTelemetryOptions class with EnableSensitiveData property - Add WorkflowTelemetryContext to manage ActivitySource lifecycle - Add WithOpenTelemetry() extension method on WorkflowBuilder - Update all workflow components to use telemetry context: - WorkflowBuilder, Workflow, Executor - InProcessRunnerContext, InProcessRunner - LockstepRunEventStream, StreamingRunEventStream - All edge runners (Direct, FanIn, FanOut, Response) - Telemetry is now disabled by default - Users must call WithOpenTelemetry() to enable spans/activities BREAKING CHANGE: Workflow telemetry is now opt-in. Users who relied on automatic telemetry must add .WithOpenTelemetry() to their workflow builder. * refactor: Pass telemetry context as parameter instead of via interface - Remove IWorkflowContextWithTelemetry interface - Add internal ExecuteAsync overload that accepts WorkflowTelemetryContext - Public ExecuteAsync delegates with WorkflowTelemetryContext.Disabled - InProcessRunner passes TelemetryContext when calling ExecuteAsync - BoundContext now implements IWorkflowContext (not the removed interface) * Add optional ActivitySource parameter to WithOpenTelemetry Allow users to provide their own ActivitySource when enabling telemetry, giving them better control over the ActivitySource lifecycle. When not provided, the framework creates one internally (existing behavior). Changes: - Add optional activitySource parameter to WithOpenTelemetry() extension - Update WorkflowTelemetryContext to accept external ActivitySource - Add unit test for user-provided ActivitySource scenario * Add component-level telemetry control with disable flags Allow users to selectively disable specific activity types via WorkflowTelemetryOptions. All activities are enabled by default. New disable flags: - DisableWorkflowBuild: Disables workflow.build activities - DisableWorkflowRun: Disables workflow_invoke activities - DisableExecutorProcess: Disables executor.process activities - DisableEdgeGroupProcess: Disables edge_group.process activities - DisableMessageSend: Disables message.send activities Added helper methods to WorkflowTelemetryContext for each activity type and updated all activity creation sites to use them. * Implement EnableSensitiveData to log executor input/output When EnableSensitiveData is true in WorkflowTelemetryOptions, executor input and output are logged as JSON-serialized attributes in the executor.process activity. New activity tags: - executor.input: JSON serialized input message - executor.output: JSON serialized output result (non-void only) Added suppression attributes for AOT/trimming warnings since this is an opt-in feature for debugging/diagnostics. * Refactor activity start methods to centralize tagging logic Move tagging logic into WorkflowTelemetryContext methods: - StartExecutorProcessActivity now accepts executorId, executorType, messageType, and message; sets all tags including executor.input when EnableSensitiveData is true - Added SetExecutorOutput method to set executor.output after execution - StartMessageSendActivity now accepts sourceId, targetId, and message; sets all tags including message.content when EnableSensitiveData is true Simplified Executor.cs and InProcessRunnerContext.cs by removing inline tagging code. Added message.content tag constant. * Revert Python changes * Update samples and code cleanup * Fix file formatting * Add comment * Add telemetry configuration to declarative workflow * Remove delays in tests * Address comments
Creating and Managing AI Agents with Versioning
This sample demonstrates how to create and manage AI agents with Azure Foundry Agents, including:
- Creating agents with different versions
- Retrieving agents by version or latest version
- Running multi-turn conversations with agents
- Managing agent lifecycle (creation and deletion)
Prerequisites
Before you begin, ensure you have the following prerequisites:
- .NET 10 SDK or later
- Azure Foundry service endpoint and deployment configured
- Azure CLI installed and authenticated (for Azure credential authentication)
Note: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with az login and have access to the Azure Foundry resource. For more information, see the Azure CLI documentation.
Set the following environment variables:
$env:AZURE_FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
$env:AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME="gpt-4o-mini" # Optional, defaults to gpt-4o-mini
Run the sample
Navigate to the FoundryAgents sample directory and run:
cd dotnet/samples/GettingStarted/FoundryAgents
dotnet run --project .\FoundryAgents_Step01.1_Basics
What this sample demonstrates
- Creating agents with versions: Shows how to create multiple versions of the same agent with different instructions
- Retrieving agents: Demonstrates retrieving agents by specific version or getting the latest version
- Multi-turn conversations: Shows how to use threads to maintain conversation context across multiple agent runs
- Agent cleanup: Demonstrates proper resource cleanup by deleting agents