Python: Improved telemetry setup (#421)

* test with stack and simplified names * quick demo of agent decorator * moved builder to protocol to enhance functionality * undid chatclientAgent -> agent rename * one more * reverted AIAgent rename * final reverts * fixed foundry import * revert changes * streamlined otel and fcc decorators * cleanup of telemetry * further refinement * lots of updates * fixed typing * fix for mypy * added input and output atttributes * fix import * initial work on baking in otel * major update to telemetry * final fixes after rename * fix * fix test * updated tests * fix for tests * fixes for tests * updated based on comments * removed agent decorator * fix for Python: ServiceResponseException when using multiple tools Fixes #649 * addressed comments * fix tests * fix tests * fix tools tests * fix for conversation_id in assistants client * fix responses test * fix tests and mypy * updated test * foundry fix --------- Co-authored-by: Chris <66376200+crickman@users.noreply.github.com>
2026-06-16 21:04:09 +08:00 · 2025-09-10 16:52:42 +02:00
parent 6aa746d891
commit 82ca4065cb
45 changed files with 3246 additions and 2984 deletions
@@ -0,0 +1,120 @@
+# Copyright (c) Microsoft. All rights reserved.
+# type: ignore
+import asyncio
+from typing import Any
+
+from agent_framework.telemetry import setup_telemetry
+from agent_framework.workflow import (
+    Executor,
+    WorkflowBuilder,
+    WorkflowCompletedEvent,
+    WorkflowContext,
+    handler,
+)
+from opentelemetry import trace
+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.
+"""
+
+
+# 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
+    """
+
+    tracer = trace.get_tracer(__name__)
+    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_telemetry()
+
+    tracer = trace.get_tracer("agent_framework")
+    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())