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Overview

This example demonstrates how to instrument your Agno agent with OpenInference and send traces to Langfuse.

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Code

import base64
import os

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.duckduckgo import DuckDuckGoTools
from openinference.instrumentation.agno import AgnoInstrumentor
from opentelemetry import trace as trace_api
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import SimpleSpanProcessor

LANGFUSE_AUTH = base64.b64encode(
    f"{os.getenv('LANGFUSE_PUBLIC_KEY')}:{os.getenv('LANGFUSE_SECRET_KEY')}".encode()
).decode()
os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = (
    "https://us.cloud.langfuse.com/api/public/otel"  # 🇺🇸 US data region
)
# os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"]="https://cloud.langfuse.com/api/public/otel" # 🇪🇺 EU data region
# os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"]="http://localhost:3000/api/public/otel" # 🏠 Local deployment (>= v3.22.0)

os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = f"Authorization=Basic {LANGFUSE_AUTH}"

tracer_provider = TracerProvider()
tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter()))
trace_api.set_tracer_provider(tracer_provider=tracer_provider)

# Start instrumenting agno
AgnoInstrumentor().instrument()

agent = Agent(
    name="Stock Price Agent",
    model=OpenAIChat(id="gpt-4o-mini"),
    tools=[DuckDuckGoTools(search=True, news=True)],
    instructions="You are a stock price agent. Answer questions in the style of a stock analyst.",
    debug_mode=True,
)

agent.print_response("What is the current price of Tesla?")

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Usage

1

Install Dependencies

pip install agno openai opentelemetry-sdk opentelemetry-exporter-otlp openinference-instrumentation-agno arize-otel
2

Set Environment Variables

export LANGFUSE_PUBLIC_KEY=<your-public-key>
export LANGFUSE_SECRET_KEY=<your-secret-key>
3

Run the Agent

python cookbook/observability/langfuse_via_openinference.py

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Notes

  • Data Regions: Adjust the OTEL_EXPORTER_OTLP_ENDPOINT for your data region or local deployment as needed:
    • https://us.cloud.langfuse.com/api/public/otel for the US region
    • https://cloud.langfuse.com/api/public/otel for the EU region
    • http://localhost:3000/api/public/otel for local deployment