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The workflow event system provides observability into workflow execution. Events are emitted at key points during execution and can be consumed in real-time via streaming.
Built-in Event Types
// Workflow lifecycle events
WorkflowStartedEvent // Workflow execution begins
WorkflowOutputEvent // Workflow outputs data
WorkflowErrorEvent // Workflow encounters an error
WorkflowWarningEvent // Workflow encountered a warning
// Executor events
ExecutorInvokedEvent // Executor starts processing
ExecutorCompletedEvent // Executor finishes processing
ExecutorFailedEvent // Executor encounters an error
AgentResponseEvent // An agent run produces output
AgentResponseUpdateEvent // An agent run produces a streaming update
// Superstep events
SuperStepStartedEvent // Superstep begins
SuperStepCompletedEvent // Superstep completes
// Request events
RequestInfoEvent // A request is issued
# All events use the unified WorkflowEvent class with a type discriminator:
# Workflow lifecycle events
WorkflowEvent.type == "started" # Workflow execution begins
WorkflowEvent.type == "status" # Workflow state changed (use .state)
WorkflowEvent.type == "output" # Workflow produces an output
WorkflowEvent.type == "failed" # Workflow terminated with error (use .details)
WorkflowEvent.type == "error" # Non-fatal error from user code
WorkflowEvent.type == "warning" # Workflow encountered a warning
# Executor events
WorkflowEvent.type == "executor_invoked" # Executor starts processing
WorkflowEvent.type == "executor_completed" # Executor finishes processing
WorkflowEvent.type == "executor_failed" # Executor encounters an error
WorkflowEvent.type == "data" # Executor emitted data (e.g., AgentResponse)
# Superstep events
WorkflowEvent.type == "superstep_started" # Superstep begins
WorkflowEvent.type == "superstep_completed" # Superstep completes
# Request events
WorkflowEvent.type == "request_info" # A request is issued
Consuming Events
using Microsoft.Agents.AI.Workflows;
await foreach (WorkflowEvent evt in run.WatchStreamAsync())
{
switch (evt)
{
case ExecutorInvokedEvent invoke:
Console.WriteLine($"Starting {invoke.ExecutorId}");
break;
case ExecutorCompletedEvent complete:
Console.WriteLine($"Completed {complete.ExecutorId}: {complete.Data}");
break;
case WorkflowOutputEvent output:
Console.WriteLine($"Workflow output: {output.Data}");
return;
case WorkflowErrorEvent error:
Console.WriteLine($"Workflow error: {error.Exception}");
return;
}
}
from agent_framework import WorkflowEvent
async for event in workflow.run_stream(input_message):
if event.type == "executor_invoked":
print(f"Starting {event.executor_id}")
elif event.type == "executor_completed":
print(f"Completed {event.executor_id}: {event.data}")
elif event.type == "output":
print(f"Workflow produced output: {event.data}")
return
elif event.type == "error":
print(f"Workflow error: {event.data}")
return
Custom Events
Custom events let executors emit domain-specific signals during workflow execution tailored to your application's needs. Some example use cases include:
- Track progress — report intermediate steps so callers can show status updates.
- Emit diagnostics — surface warnings, metrics, or debug information without changing the workflow output.
- Relay domain data — push structured payloads (e.g., database writes, tool calls) to listeners in real time.
Defining Custom Events
Define a custom event by subclassing WorkflowEvent. The base constructor accepts an optional object? data payload that is exposed through the Data property.
using Microsoft.Agents.AI.Workflows;
// Simple event with a string payload
internal sealed class ProgressEvent(string step) : WorkflowEvent(step) { }
// Event with a structured payload
internal sealed class MetricsEvent(MetricsData metrics) : WorkflowEvent(metrics) { }
In Python, create custom events using the WorkflowEvent class directly with a custom type discriminator string. The type and data parameters carry all the information.
from agent_framework import WorkflowEvent
# Create a custom event with a custom type string and payload
event = WorkflowEvent(type="progress", data="Step 1 complete")
# Custom event with a structured payload
event = WorkflowEvent(type="metrics", data={"latency_ms": 42, "tokens": 128})
Note
The event types "started", "status", and "failed" are reserved for framework lifecycle notifications. If an executor attempts to emit one of these types, the event is ignored and a warning is logged.
Emitting Custom Events
Emit custom events from an executor's message handler by calling AddEventAsync on the IWorkflowContext:
using Microsoft.Agents.AI.Workflows;
internal sealed class ProgressEvent(string step) : WorkflowEvent(step) { }
internal sealed partial class CustomExecutor() : Executor("CustomExecutor")
{
[MessageHandler]
private async ValueTask HandleAsync(string message, IWorkflowContext context)
{
await context.AddEventAsync(new ProgressEvent("Validating input"));
// Executor logic...
await context.AddEventAsync(new ProgressEvent("Processing complete"));
}
}
Emit custom events from a handler by calling add_event on the WorkflowContext:
from agent_framework import (
handler,
Executor,
WorkflowContext,
WorkflowEvent,
)
class CustomExecutor(Executor):
@handler
async def handle(self, message: str, ctx: WorkflowContext[str]) -> None:
await ctx.add_event(WorkflowEvent(type="progress", data="Validating input"))
# Executor logic...
await ctx.add_event(WorkflowEvent(type="progress", data="Processing complete"))
Consuming Custom Events
Use pattern matching to filter for your custom event type in the event stream:
await foreach (WorkflowEvent evt in run.WatchStreamAsync())
{
switch (evt)
{
case ProgressEvent progress:
Console.WriteLine($"Progress: {progress.Data}");
break;
case WorkflowOutputEvent output:
Console.WriteLine($"Done: {output.Data}");
return;
}
}
Filter on the custom type discriminator string:
async for event in workflow.run(input_message, stream=True):
if event.type == "progress":
print(f"Progress: {event.data}")
elif event.type == "output":
print(f"Done: {event.data}")
return
Next steps
Related topics: