Files
agent-framework/python/samples/getting_started/observability/04-workflow.py
T
Eduard van Valkenburg 2576e7a091 Python: Telemetry and observability follow-up (#833)
* updated telemetry work

* updated telemetry

* slight improvement

* updated tests

* fixes for telemetry

* fixes for mypy

* added settings setup to runner to avoid error

* streamline usage

* updated tests

* updated tests

* further refinement

* fix dumped item for otel

* removed enable_workflow_otel

* final fixes

* final fixes

* updated samples

* removed exporters

* fix tests

* fixed last import'

* fixed devui
2025-09-23 06:21:56 +00:00

116 lines
4.2 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
# type: ignore
import asyncio
from typing import Any
from agent_framework import (
Executor,
WorkflowBuilder,
WorkflowCompletedEvent,
WorkflowContext,
handler,
)
from agent_framework.observability import get_tracer, setup_observability
from opentelemetry.trace import SpanKind
from opentelemetry.trace.span import format_trace_id
"""Telemetry sample demonstrating OpenTelemetry integration with Agent Framework workflows.
This sample runs a simple sequential workflow with telemetry collection,
showing telemetry collection for workflow execution, executor processing,
and message publishing between executors.
"""
tracer = get_tracer("agent_framework.workflow")
# Executors for sequential workflow
class UpperCaseExecutor(Executor):
"""An executor that converts text to uppercase."""
@handler
async def to_upper_case(self, text: str, ctx: WorkflowContext[str]) -> None:
"""Execute the task by converting the input string to uppercase."""
print(f"UpperCaseExecutor: Processing '{text}'")
result = text.upper()
print(f"UpperCaseExecutor: Result '{result}'")
# Send the result to the next executor in the workflow.
await ctx.send_message(result)
class ReverseTextExecutor(Executor):
"""An executor that reverses text."""
@handler
async def reverse_text(self, text: str, ctx: WorkflowContext[Any]) -> None:
"""Execute the task by reversing the input string."""
print(f"ReverseTextExecutor: Processing '{text}'")
result = text[::-1]
print(f"ReverseTextExecutor: Result '{result}'")
# Send the result with a workflow completion event.
await ctx.add_event(WorkflowCompletedEvent(result))
async def run_sequential_workflow() -> None:
"""Run a simple sequential workflow demonstrating telemetry collection.
This workflow processes a string through two executors in sequence:
1. UpperCaseExecutor converts the input to uppercase
2. ReverseTextExecutor reverses the string and completes the workflow
Telemetry data collected includes:
- Overall workflow execution spans
- Individual executor processing spans
- Message publishing between executors
- Workflow completion events
"""
with tracer.start_as_current_span("Scenario: Sequential Workflow", kind=SpanKind.CLIENT) as current_span:
print("Running scenario: Sequential Workflow")
try:
# Step 1: Create the executors.
upper_case_executor = UpperCaseExecutor(id="upper_case_executor")
reverse_text_executor = ReverseTextExecutor(id="reverse_text_executor")
# Step 2: Build the workflow with the defined edges.
workflow = (
WorkflowBuilder()
.add_edge(upper_case_executor, reverse_text_executor)
.set_start_executor(upper_case_executor)
.build()
)
# Step 3: Run the workflow with an initial message.
input_text = "hello world"
print(f"Starting workflow with input: '{input_text}'")
completion_event = None
async for event in workflow.run_stream(input_text):
print(f"Event: {event}")
if isinstance(event, WorkflowCompletedEvent):
# The WorkflowCompletedEvent contains the final result.
completion_event = event
if completion_event:
print(f"Workflow completed with result: '{completion_event.data}'")
else:
print("Workflow completed without a completion event")
except Exception as e:
current_span.record_exception(e)
print(f"Error running workflow: {e}")
async def main():
"""Run the telemetry sample with a simple sequential workflow."""
setup_observability()
with tracer.start_as_current_span("Sequential Workflow Scenario", kind=SpanKind.CLIENT) as current_span:
print(f"Trace ID: {format_trace_id(current_span.get_span_context().trace_id)}")
# Run the sequential workflow scenario
await run_sequential_workflow()
if __name__ == "__main__":
asyncio.run(main())