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Tao Chen
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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
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Agent Framework Samples
The agent framework samples are designed to help you get started with building AI-powered agents from various providers.
The Agent Framework supports building agents using various infererence and inference-style services.
All these are supported using the single ChatClientAgent class.
The Agent Framework also supports creating proxy agents, that allow accessing remote agents as if they
were local agents. These are supported using various AIAgent subclasses.
Sample Categories
The samples are subdivided into the following categories:
- Getting Started - Agents: Basic steps to get started with the agent framework.
These samples demonstrate the fundamental concepts and functionalities of the agent framework when using the
AIAgentand can be used with any underlying service that provides anAIAgentimplementation. - Getting Started - Agent Providers: Shows how to create an AIAgent instance for a selection of providers.
- Getting Started - Agent Telemetry: Demo which showcases the integration of OpenTelemetry with the Microsoft Agent Framework using Azure OpenAI and .NET Aspire Dashboard for telemetry visualization.
- Semantic Kernel to Agent Framework Migration: For instructions and samples describing how to migrate from Semantic Kernel to Microsoft Agent Framework
- Durable Agents - Azure Functions: Samples for using the Microsoft Agent Framework with Azure Functions via the durable task extension.
- Durable Agents - Console Apps: Samples demonstrating durable agents in console applications.
Prerequisites
For prerequisites see each set of samples for their specific requirements.