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Python telemetry (#223)
* initial work on telemetry * moved tool operation const * missing quotes * working otel with samples * updated readme and other assets * added tests * added tests * small updates * updated genaiattributes docs * updated tests * additional warning * cleanup of tests
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Eduard van Valkenburg
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# Copyright (c) Microsoft. All rights reserved.
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# type: ignore
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import asyncio
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import logging
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from random import randint
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from typing import Annotated
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from agent_framework import ChatMessage, ChatResponse, ChatResponseUpdate
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from agent_framework.openai import OpenAIChatClient
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from azure.monitor.opentelemetry import configure_azure_monitor
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from opentelemetry import trace
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from opentelemetry._logs import set_logger_provider
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from opentelemetry.exporter.otlp.proto.grpc._log_exporter import OTLPLogExporter
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from opentelemetry.exporter.otlp.proto.grpc.metric_exporter import OTLPMetricExporter
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from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
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from opentelemetry.metrics import set_meter_provider
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from opentelemetry.sdk._logs import LoggerProvider, LoggingHandler
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from opentelemetry.sdk._logs.export import BatchLogRecordProcessor, ConsoleLogExporter
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from opentelemetry.sdk.metrics import MeterProvider
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from opentelemetry.sdk.metrics.export import ConsoleMetricExporter, PeriodicExportingMetricReader
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from opentelemetry.sdk.metrics.view import DropAggregation, View
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from opentelemetry.sdk.resources import Resource
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from opentelemetry.sdk.trace import TracerProvider
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from opentelemetry.sdk.trace.export import BatchSpanProcessor, ConsoleSpanExporter
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from opentelemetry.semconv.attributes import service_attributes
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from opentelemetry.trace import set_tracer_provider
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from pydantic import Field
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from pydantic_settings import BaseSettings
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class TelemetrySampleSettings(BaseSettings):
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"""Settings for the telemetry sample application.
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Optional settings are:
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- connection_string: str - The connection string for the Application Insights resource.
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This value can be found in the Overview section when examining
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your resource from the Azure portal.
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(Env var CONNECTION_STRING)
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- otlp_endpoint: str - The OTLP endpoint to send telemetry data to.
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Depending on the exporter used, you may find this value in different places.
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(Env var OTLP_ENDPOINT)
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If no connection string or OTLP endpoint is provided, the telemetry data will be
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exported to the console.
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"""
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connection_string: str | None = None
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otlp_endpoint: str | None = None
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# Load settings
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settings = TelemetrySampleSettings()
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# Create a resource to represent the service/sample
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resource = Resource.create({service_attributes.SERVICE_NAME: "TelemetryExample"})
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# Define the scenarios that can be run
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SCENARIOS = ["ai_service", "kernel_function", "auto_function_invocation", "all"]
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if settings.connection_string:
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configure_azure_monitor(
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connection_string=settings.connection_string, enable_live_metrics=True, logger_name="agent_framework"
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)
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def set_up_logging():
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class LogFilter(logging.Filter):
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"""A filter to not process records from several subpackages."""
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# These are the namespaces that we want to exclude from logging for the purposes of this demo.
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namespaces_to_exclude: list[str] = [
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"httpx",
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"openai",
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]
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def filter(self, record):
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return not any([record.name.startswith(namespace) for namespace in self.namespaces_to_exclude])
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exporters = []
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if settings.otlp_endpoint:
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exporters.append(OTLPLogExporter(endpoint=settings.otlp_endpoint))
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if not exporters:
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exporters.append(ConsoleLogExporter())
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# Create and set a global logger provider for the application.
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logger_provider = LoggerProvider(resource=resource)
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# Log processors are initialized with an exporter which is responsible
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# for sending the telemetry data to a particular backend.
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for log_exporter in exporters:
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logger_provider.add_log_record_processor(BatchLogRecordProcessor(log_exporter))
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# Sets the global default logger provider
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set_logger_provider(logger_provider)
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# Create a logging handler to write logging records, in OTLP format, to the exporter.
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handler = LoggingHandler()
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handler.addFilter(LogFilter())
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# Attach the handler to the root logger. `getLogger()` with no arguments returns the root logger.
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# Events from all child loggers will be processed by this handler.
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logger = logging.getLogger()
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logger.addHandler(handler)
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# Set the logging level to NOTSET to allow all records to be processed by the handler.
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logger.setLevel(logging.WARNING)
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def set_up_tracing():
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exporters = []
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if settings.otlp_endpoint:
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exporters.append(OTLPSpanExporter(endpoint=settings.otlp_endpoint))
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if not exporters:
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exporters.append(ConsoleSpanExporter())
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# Initialize a trace provider for the application. This is a factory for creating tracers.
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tracer_provider = TracerProvider(resource=resource)
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# Span processors are initialized with an exporter which is responsible
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# for sending the telemetry data to a particular backend.
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for exporter in exporters:
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tracer_provider.add_span_processor(BatchSpanProcessor(exporter))
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# Sets the global default tracer provider
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set_tracer_provider(tracer_provider)
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def set_up_metrics():
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exporters = []
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if settings.otlp_endpoint:
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exporters.append(OTLPMetricExporter(endpoint=settings.otlp_endpoint))
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if not exporters:
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exporters.append(ConsoleMetricExporter())
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# Initialize a metric provider for the application. This is a factory for creating meters.
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metric_readers = [
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PeriodicExportingMetricReader(metric_exporter, export_interval_millis=5000) for metric_exporter in exporters
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]
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meter_provider = MeterProvider(
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metric_readers=metric_readers,
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resource=resource,
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views=[
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# Dropping all instrument names except for those starting with "agent_framework"
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View(instrument_name="*", aggregation=DropAggregation()),
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View(instrument_name="agent_framework*"),
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],
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)
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# Sets the global default meter provider
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set_meter_provider(meter_provider)
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def get_weather(
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location: Annotated[str, Field(description="The location to get the weather for.")],
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) -> str:
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"""Get the weather for a given location."""
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conditions = ["sunny", "cloudy", "rainy", "stormy"]
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return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
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async def main():
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# Set up the providers
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# This must be done before any other telemetry calls
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set_up_logging()
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set_up_tracing()
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set_up_metrics()
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tracer = trace.get_tracer("agent_framework")
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with tracer.start_as_current_span("Scenario: Interactive Chat") as current_span:
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print("Running scenario: Interactive Chat")
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print("Welcome to the chat, type 'exit' to quit.")
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client = OpenAIChatClient()
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messages: list[ChatMessage] = []
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message = input("User: ")
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try:
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while message.lower() != "exit":
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messages.append(ChatMessage(role="user", text=message))
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print("Assistant: ", end="")
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updates: list[ChatResponseUpdate] = []
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async for update in client.get_streaming_response(messages, tools=get_weather):
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updates.append(update)
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if update.text:
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print(update.text, end="")
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print("")
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messages.extend(ChatResponse.from_chat_response_updates(updates).messages)
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message = input("User: ")
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except Exception as e:
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current_span.record_exception(e)
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print(f"\nError running interactive chat: {e}")
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if __name__ == "__main__":
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asyncio.run(main())
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